Modeling, Analysis, and Prediction (MAP) Program

ROSES 12 NASA/MAP Funded Investigations

Research Opportunities in Space and Earth Sciences, 2012 - A.13 Modeling, Analysis, and Prediction  (NNH12ZDA001N-MAP)

NASA's Science Mission Directorate, NASA Headquarters, Washington, DC, has selected proposals, for the Modeling, Analysis, and Prediction program in support of the Earth Science Division (ESD). The Modeling, Analysis, and Prediction (MAP) program seeks an understanding of the Earth as a complete, dynamic system, with particular emphasis on climate and weather. The MAP program supports observation driven modeling that integrates the research activities in NASA’s Earth Science Program. The research is distinguished by rigorous examination and incorporation of satellite-based observations, using models to bridge the spatial and temporal scales between satellite observations and observations from ground and air based campaigns. This contributes to the validation of the satellite observations and to observationally based improvements of Earth system model components. MAP strives to generate models and model components that are documented and validated.

The research themes specific to this solicitation included investigations to understand the role of processes in the context of the Earth system, improvement of their representation in Earth system models or development of new parameterizations, studies to understand regional and local climate change in the context of global climate change, investigations using or evaluating NASA MERRA reanalysis data, reducing uncertainties in Earth system predictions, and the role of constituents in the climate system.

The ESD has selected 36 out of a total of 161 proposals received in response to this solicitation. The total first-year funding for these investigations is approximately eight million dollars.

We propose to develop testing protocols for cloud microphysics and atmospheric boundary-layer dynamics in the GISS GCM that can be used as part of its regular testing cycle in the future. The protocols will focus on shallow, marine convection, and will include warm and mixed-phase clouds. The testing environment will leverage upgrades to the stratiform cloud microphysics and boundary-layer dynamics parameterizations in the GISS GCM.

The first mode of the testing protocol bypasses the complexities of the coupled climate system by evaluating the performance of the new model components in a standalone mode, using a library of established case studies. The large-eddy simulation (LES) results will be used to test and tune the newly upgraded GCM parameterizations. The second mode of the testing protocol is to identify aspects of the present-day GCM climatology that are deficient with respect to observations and using that identification to target further standalone work, possibly requiring expansion of the case-study library.

The two workhorses of the standalone work are the LES code DHARMA and the single column model (SCM) version of the GISS Model E2. A library of case studies is already in hand from previous work with the LES code. The LES-SCM library comparisons will take place in two stages, in parallel with the upgrades of the GCM components in sequence: first stratiform cloud microphysics, then boundary-layer dynamics. In both stages of the standalone work, single-layer, low-lying warm marine clouds will be targeted first, followed by mixed-phase Arctic clouds. Because cloud microphysical processes such as drizzle production depend sensitively upon not only aerosol populations but also cloud depth and thus boundary-layer dynamics, for the first stage of the work the aerosol population other environmental profiles will be nudged toward their initial conditions. Using suitably strong nudging will ensure matching cloud macrophysical conditions and and bypass problems with the existing boundary-layer scheme in Model E2. For the second stage of the work, the updated boundary-layer scheme will be allowed to operate. In this phase of the work, the testing protocol will be used as an opportunity to adjust tunable constants in the GCM microphysics and turbulence parameterizations. The SCM will be evaluated first on a refined vertical grid and subsequently tested and tuned on the operational vertical grid.

Following the testing and SCM-mode tuning of the microphysics, multi-year present-day GCM simulations with prescribed sea-surface temperatures will be compared with satellite observations using the CFMIP Observation Simulator Package to document the effects of the microphysics upgrade on the GCM cloud climatology. For the GCM simulations, greater effort in terms of the work proposed here will follow the testing and SCM-mode tuning of the upgraded boundary-layer parameterization. This stage of the work will include compositing satellite observations with large-scale conditions from the MERRA reanalysis products. The general approach will be to use compositing to filter for low-level maritime clouds, with the aim of detecting robust features in their observed climatology that stand out as deficient in the GCM simulations. For regimes in which the corresponding large-scale conditions are represented in the GCM climatology but the overlap between the distributions of simulated and observed cloud properties are problematic, the testing will turn back to the standalone LES-SCM approach. For problematic large-scale conditions will either correspond to cases within the testing library or will fall outside those limited conditions, which will require devising new case study specifications. In either case, the idea is to use glaring discrepancies in the global simulations as a means of targeting parameterization issues in the more controlled testing environment of LES-SCM comparisons.

The prospect of breakthroughs in understanding Greenland ice sheet dynamics in the next years is substantial. Key variables for the ice sheet are becoming clearer through sustained observation campaigns, specifically ICESat and more recent IceBridge measurements of surface and bed elevations and also time series of maps of ice flow velocity. With the GRACE gravity observations it has become possible to examine time-dependent mass changes both regionally and for the whole ice sheet. We propose to identify measurements which expose the physical mechanisms behind the variability already seen for Greenland. We will add new physical modeling techniques to the Parallel Ice Sheet Model (PISM), including improved coupling to Earth System models (ESMs), to understand this variability. Specifically we will revise PISM to allow user-verifiable conservation of mass and energy, despite the existence of many moving boundaries, and verifying conservation over all implemented possibilities for fluxes through ESM coupling. New transport schemes will be identified by validation using dated isochronal surfaces from ice-penetrating radar data. We will explain differences between outlet glaciers through use of continuously improving bed elevation maps, the construction of new subglacial hydrology models, and the evaluation of different parameterizations for the complex ocean-ice interaction occurring in fjords in Greenland. We will separate the part of observed mass loss which is surface balance from that which is ice dynamics. Evolving the Parallel Ice Sheet Model as in this proposal will most effectively make NASA cryosphere observations relevant to Earth System models.

In order to understand how the climate responds to variations in forcing, one necessary component is to understand the full distribution of variability of exchanges of heat and moisture between the atmosphere and ocean. A number of studies recognize the important role of surface heat and moisture fluxes in the generation and decay of important coupled air-sea phenomena. These mechanisms operate across a number of scales and contain significant contributions from interactions between the anomalous (i.e. non-mean), often extreme-valued, flux components. It is important to have a characterization and understanding of these processes for the development of accurate modeling efforts.

We propose a unified approach to evaluate the representation of the turbulent fluxes at the air-sea interface in the current and evolving Goddard Earth Observing System (GEOS) model. One aspect of this proposal will be the evaluation of the extent to which the distributions of the fluxes in the observational data and the NASA GEOS 5 and when available GEOS 6 models differ with differing weather and climate states, and explore the driving oceanic and atmospheric factors producing the distributions. We will evaluate how the distributions of the fluxes vary in space and time between these datasets, their representation in different weather-regimes, and how these variations affect the climatology. Particular emphasis is placed on understanding the distribution of the fluxes including extremes, and the representation of near-surface forcing variables directly related to their estimation. The extent to which the model simulations of the surface fluxes rectify onto sea surface temperature on seasonal to interannual time scales will be quantified. The proposed inclusion of diurnal sea surface temperature warming, wave effects, and surface roughness changes in GEOS-6 establishes a need to characterize their impacts to the representation of turbulent surface heat and moisture fluxes.

Primarily, this work addresses the Mapping, Analysis, and Prediction (MAP) programmatic priority of characterizing the limits of validity of models and model components and identifying the sources of uncertainties. Turbulent latent and sensible heat fluxes are key variables in the estimation of Earth s energy and water cycles. In GEOS-6 the air-sea interface will be the focus of much of the ocean work, and our analysis of the current and evolving GEOS models will provide context for the extent to which new model parameterizations are improving the physical representation of this crucial boundary. This research addresses the task of using observations to identify and characterize model uncertainties in key aspects of the air-sea coupling on synoptic to interannual time scales. The anticipated results of this research will be three-fold: better understanding of the distribution of surface fluxes across the global oceans, key feedbacks and regimes that need further improvements in the models, and traceability of improved air-sea flux parameterizations and boundary models and their effects in GEOS 5 and 6 models.

Suboptimal weighting of the information provided by models and measurements poses a fundamental limitation on the performance of atmospheric data assimilation systems (DAS).

This project aims to optimize the information content of observations in the NASA Goddard Earth Observing System (GEOS) DAS by completing the following research objectives: a posteriori statistical analysis of data assimilation products and diagnosis of the observational error correlation structures; identification of those state and observing system components whose improved estimates of the error statistics will contribute most to reducing the analysis and forecast uncertainties; a priori quantification of the gain in forecast skill that may achieved from adjustments in the error covariance models; error covariance parameter tuning and validation using observing system experiments (OSEs).

This research will establish a synergistic link between various methodologies to analyze the DAS performance: adjoint-DAS observation sensitivity and impact assessment, error covariance sensitivity, and a posteriori consistency diagnosis. Emphasis will be placed on the diagnosis and forecast impact estimation of the observation error covariances for the remote sensing instruments and on the optimal weighting in the DAS between the information provided by the prior state estimate (background) and the information provided by the observing system. Advanced mathematical tools will be used to develop novel error covariance models that incorporate both spatial and instrument interchannel error correlations.

The research objectives are directly related to the programmatic priority of the NASA MAP Program to characterize and reduce uncertainties in the models and data assimilation products. This project will develop the tools that are necessary to optimize the GEOS DAS capabilities to assimilate high-resolution time-distributed data and to maximize the satellite data utility. The project will leverage current research at NASA Global Modeling and Assimilation Office (GMAO) on observation impact assessment and observing system simulation experiments (OSSEs) and will contribute to the NASA/GMAO efforts to achieve an optimal use of satellite and in situ observations in the GEOS DAS.

Problem statement: Feedbacks from land to atmosphere primarily originate from anomalies in soil moisture, which must be conveyed to the atmosphere in a two-segment path in order to affect weather and climate. The first segment is the terrestrial one from soil moisture to surface fluxes (latent and sensible heat). A positive correlation between soil moisture and latent heat flux has been found to be a necessary condition for the existence of a feedback pathway in the water cycle. Recent work has improved upon these simple correlations to focus on regions with important variability. The second segment is from surface fluxes to relevant manifestations in the properties of the atmosphere. Precipitation and temperature have typically been the focus, most clearly revealed in ensemble modeling studies. A means to quantify the impact of surface heat and moisture fluxes on the PBL in energy space, and their strength relative to atmospheric components, such as advection and boundary layer entrainment has been developed recently. This provides the connection missing in previous studies. Thus, we now have the ability to quantify simultaneously both segments of the feedback branch from land to atmosphere, and furthermore, to diagnose them in a way applicable to observations and conventional model output, advancing model improvement.

Methodology: We propose to investigate the land-atmosphere coupling in GEOS-5 and CFSv2 using the new techniques described above. In the first phase, the terrestrial and PBL segments of coupling will be quantified in terms of spatial, seasonal and interannual variability in the MERRA and CFS reanalyses. This will be compared with previous analyses based on other global datasets, and more importantly, to in situ estimates based on observational data and, in the case of the PBL mixing diagrams, pointwise NU-WRF model-based analyses. In the second phase, available CFS Reforecasts and additional seasonal hindcasts with GEOS-5 and CFSv2 will be examined to diagnose the land-atmosphere feedback mechanisms in the model. Ensembles will be constructed where only the initial land surface state is perturbed; the divergence among the ensemble members in the first hours and days of the simulation clearly reveals the propagation of the land surface signal into the atmosphere, furthering the diagnostic potential. Specific processes and parameterizations in the coupled land-atmosphere system will be scrutinized for their impact on the errors diagnosed from the coupling metrics.

Significance and relevance to NASA/MAP: The project will lead to improvement of weather and climate model fidelity over land through the diagnosis and improved simulation of coupled land-atmosphere processes that have not been previously examined. Such improvements are key to the goals of the GMAO. The project also draws upon the NU-WRF core activities as an essential means to bridge the scales involved in land-atmosphere feedbacks. The project is multi-model, drawing upon collaborations between NCEP and NASA/GSFC.

We primarily address the MAP theme of examination of the role of coupled land-atmosphere processes within the Earth system and improvement of their representation in global models. This includes representation of the weather-to-climate continuum of high impact events such as tropical systems, floods, droughts, heat waves, and extreme storms. This work necessarily bridges the weather-climate continuum, and will contribute to better understanding of the feedback processes that exacerbate extremes like drought and flood with potential to improve prediction. The research draws heavily on MERRA and the GEOS5 modeling system, and compares/contrasts to the corresponding NOAA reanalysis and models.

We propose a computationally-efficient forward modeling study, using the NASA Goddard Earth Observing System version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM), which has the primary goal to understand the causes of variability in observed methane (CH4; 1980-2010), so as to lend confidence to our projections (2010-2050) of future methane abundances.

We will use the carbon monoxide-hydroxyl radical (CO-OH) and CH4-CO-OH options of the AGCM. These options are being developed and implemented under current MAP funding by the PI (Duncan) and offer a unique (as far as we are aware) method for calculating OH as a function of meteorological, solar irradiance, and chemical variables, including methane and CO. This approach allows our simulations to capture the nonlinear feedbacks of the CH4-CO-OH cycle in a computationally-efficient way. As a consequence, we will be able to study the CH4-CO-OH cycle with many sensitivity simulations for a long period of time, 1980-2050, which is important for understanding perturbations to relatively long-lived methane. These options will allow us to do many more sensitivity simulations than we could with the computationally-expensive option of the model that carries a full representation of atmospheric chemistry (i.e., nitrogen oxides, volatile organic compounds, ozone, etc.).

First, we propose a retrospective model study (1980-2010) in which we deconvolve the CO response to changes in emissions and in the individual drivers that can change OH, using sensitivity simulations following the method of Duncan and Logan (2008). Understaning trends and variability in CO is important as reaction with CO is the primary sink for OH, which controls the lifetimes of some Greenhouse Gases (GHG), including methane, and indirectly affects tropospheric ozone, another important GHG. We will use the CO-OH option of the AGCM to interpret observed distributions, following evaluation of our simulations with CO data from in situ and remote sensing instruments, including those on board NASA Earth Observing System (EOS) satellites.

Second, we propose a model study (1980-2050) to deconvolve the influence of changes in emissions and in the individual factors influencing OH on atmospheric methane and CO, using the CH4-CO-OH option of the AGCM. Our goal is not to assess the impact of all possible factors on global mean methane, but instead to constrain, where possible, important causal factors with observations so as to clearly demonstrate variations and trends in methane and CO that are associated with these factors. The results of our computationally-efficient sensitivity simulations will help us to decide which model simulations are appropriate for further analysis using the option of the AGCM with a full representation of atmospheric chemistry. These simulations, combined with companion simulations at Lamont-Doherty Earth Observatory (LDEO) with the Geophysical Fluid Dynamics Laboratory (GFDL) AM3 chemistry-climate model, will allow us to examine a broad suite of possible future methane evolution scenarios. Examination of observational constraints on the causal factors influencing OH, and thereby CO and methane, will allow for new insights into observed trends and variability in recent decades, as well as the potential for revising projected future abundances following correction for model biases.

One pronounced feature in GCM (general circulation model)-predicted climate change in the 21st century is the much enhanced maximum warming in tropical upper troposphere near ~200-150 hPa (IPCC2007). This feature has important implications for GCM climate sensitivity because of its impact on water vapor, lapse rate, and cloud feedbacks and for the changes of atmospheric circulations. It is evident from satellite observations that GCMs may exaggerate the increase in tropical upper tropospheric temperature relative to that in tropical middle troposphere during last three decades (Fu et al. 2011). Temperature in tropical troposphere largely follows the moist adiabatic lapse rate, but deviates from it in tropical upper troposphere. The relative role of various physical processes in controlling the thermal structure in tropical upper troposphere, however, remains unclear. It is thus critically important to understand these processes and their exact balance and potential feedbacks in climate system, which is a necessary step for improving GCM prediction of tropical upper tropospheric warming in changing climate.

The overall objective of this proposed project is to improve our understanding of the physical processes responsible for the temperature and lapse rate changes in tropical upper troposphere, to be able to reliably predict its future evolution. The key science questions that we will address include (1) what is the heat balance in tropical upper troposphere which determines its thermal structure, and (2) how would the thermal structure in tropical upper troposphere change in response to changes in the heat balance associated with the climate change. We will achieve our goals by using a cloud resolving model (CRM) along with analyses of satellite cloud observations. In particular, we will examine the roles of (1) cloud radiative effects, especially those associated with tropical thin cirrus clouds; (2) interactive ozone profiles; and (3) the Brewer-Dobson circulations in the simulated tropical upper-tropospheric temperature and the responses to changing climate. The cloud radiative effects based on observations will be derived by integrated analyses of the Aqua MODIS, CALIPSO lidar and CloudSat radar observations. Our novel approach combining CRM radiative-convective equilibrium simulations with observationally derived cloud radiative effects will, for the first time, help quantify the impact on the simulated temperature profiles using cloud radiative effects (including those of tropical thin cirrus) based on the observations.

The proposed work will be part of the MAP research efforts in terms of Investigations utilizing observations which are aimed at identifying, characterizing, and reducing uncertainties in model predictions of climate change on seasonal to multi-decadal time scales, which will directly contribute to addressing the key questions of the Earth Science Division within the NASA SMD such as How is the Earth system changing? and how will the Earth system change in the future?

This project is to quantify variations/changes in the global hydrological cycle on the seasonal-to-interannual-to-interdecadal time scales and further examine the relationships among various hydrological-cycle components including precipitation, tropospheric water vapor, and surface and tropospheric temperature using the MERRA products and the AMIP5/CMIP5 runs of the GISS Model E in addition to a variety of satellite-/station-based observations. The objectives are (1) to assess the skills of the MERRA reanalysis product and the GISS model runs in reproducing changes and relationships discovered in satellite-/station-based observations; (2) to improve understanding of global precipitation changes during the past three decades (1979-the present) that may be related to both the global mean surface warming and the large-scale climate modes such as the Pacific Decadal Variability (PDV); (3) to improve knowledge of how precipitation (both mean and intensity/frequency distributions) and water vapor respond to surface temperature changes on interannual-to-long-term time scales. The primary observations include the monthly and daily GPCP datasets and daily TRMM precipitation products, the GISS surface temperature analysis data, and the SSM/I-SSMIS oceanic water vapor content.

The study will first do a quick examination of the precipitation climatologies and seasonal-to-interannual variations described by the MERRA reanalysis product and the CMIP5/AMIP5 runs of the GISS Model E for the post-1979 period. The first major task for this project is to examine the change rates (or sensitivities) of global and tropical mean precipitation (P) and water vapor (CWV) with surface temperature (Ts), respectively, on interannual and decadal/trend time scales. In particular, for MERRA, the examination will be focused on the interannual time scale and be done within three specific time periods (01 / 1979-06 / 1987, 07 / 1987-10 / 1998, 01 / 2001-02 / 2008) in which the hydrological cycle components are temporally homogeneous, given the in-homogeneity issue already found in the data set. The results from the MERRA withholding experiments will be made comparing to those from the original MERRA product and to observations. For CMIP5/AMIP5 outputs, the focus will be on both the interannual and interdecadal time scales. Using the CMIP5 / AMIP5 outputs, we will compare the simulated spatial structures of long-term precipitation changes during the past three decades against observations. Recent observational studies already indicate that precipitation changes during 1979-2010 might be related to both global mean surface warming and PDV.

Examining changes in precipitation intensity and frequency distributions is another concentration. We will focus on the post-1998 period in which the in-homogeneity issue is minor in the MERRA product especially after the year of 2001 and the high-quality daily rain rate (including TRMM 3B42 or TMPA) products are available. Responses of precipitation intensity distribution to surface temperature will be estimated for this period and for the tropical ocean, land, and land+ocean averages, providing a further assessment of the skills of the MERRA product and the AMIP5 runs. Furthermore, these responses will be stratified based on various climate regimes and tropospheric thermodynamic states by using both the MERRA data/the AMIP5 outputs and the AIRS/AMSU vertical profiles of temperature and water vapor.

Recent studies have highlighted the large spread among climate model simulations of cloud and water vapor that were submitted to the CMIP5 [e.g. Jiang et al., 2012]. The model spread in the upper troposphere is much greater than that in the middle and lower troposphere. It was demonstrated that improvements to GISS Model-E2 are sorely needed. This proposal aims to improve GISS Model-E2 cloud and water vapor simulations with the guidance of process-oriented model diagnostics using NASA A-Train satellite observations as references. Our model diagnosis will address dynamical, thermodynamic and microphysical aspects of model physics for simulations of clouds and water vapor to identify the dominant sources of model errors. The diagnosis will be followed by targeted model improvements in the identified areas. We particularly focus on ice clouds in the upper troposphere.

The objective of this proposed project will be achieved through the following steps:

1. Revealing the status of clouds and water vapor simulations in the post-CMIP5 version of the GISS model using the bi-variate metrics (clouds and water vapor together) as in Jiang et. al. [2012].

2. Examining the large-scale regime dependency of clouds and water vapor simulations using the "conditional sampled" clouds and water vapor distributions by large-scale dynamic and thermodynamic indices such as mid-tropospheric vertical velocity, lower-level divergence, sea surface temperature, water vapor path and lower troposphere stability [e.g., Su et al., 2008].

While the first two steps provide a general view of model performance, specific model physics that contribute to the model-observation discrepancies will be explored through the following in-depth investigations.

3. Separating convective and non-convective sources of ice clouds by satellite-based approaches [e.g. Comstock and Jacob 2004; Wang and Sassen, 2007].

3a. For convective clouds, we will analyze convective vertical velocity distribution; test the sensitivity of ice cloud amount to upper-level entrainment and to ice particle size distribution using satellite and field campaign measurements.

3b. For non-convective in-situ formed clouds, we focus on the sensitivity of ice cloud amount to the threshold relative humidity for ice formation.

4. Evaluating model simulations after each attempt of model parameter adjustment using the observational references in Steps 1 and 2 and evaluating the impacts of such changes of clouds and water vapor on model simulated cloud radiative forcing, precipitation and climate sensitivity.

This proposed work builds upon combined capabilities of the proposal team in model-observation comparisons and model developments [e.g. Jiang et al. 2010; 2012; Su et al. 2006; 2008; 2011; Del Genio et al., 2002, 2005, 2012]. It extends our ongoing multi-model evaluation work to specific GISS Model-E2 diagnosis and improvements. It is highly relevant to the MAP objectives. This proposed project is extremely critical to prepare GISS Model-E for the next phase of CMIP, and thus the IPCC AR6 (Intergovernmental Panel on Climate Change, the sixth Assessment Report).

We propose to develop a diagnostic (i.e., constrained by observations) carbon dioxide (CO2) surface flux capability for the NU-WRF model and to exercise this new facility to address carbon cycle science issues manifest at the relatively small scales accessible to the model. At the same time we will continue and extend ongoing CO2 work in the GMAO GEOS-5 modeling framework that has been developed in previous collaborations. This parallel approach will allow us to connect regional findings to the global scale. The initial NU-WRF development will comprise terrestrial vegetation physiological fluxes, biomass burning, and fossil fuel combustion of CO2. Relatively high-resolution (10-25 km) vegetation fluxes from the CASA model will be constrained by satellite vegetation indices and driven by NU-WRF meteorology and ground hydrology. The resulting transported CO2 fields and fluxes will be used to address a set of science issues related to the impact of small-scale variability in global analyses. Boundary conditions would be derived from concurrent development driven by the global GMAO MERRA analysis. The objective of the project is to improve CO2 flux and transport model representation by resolving processes at smaller scales, and thereby to reduce and quantify uncertainties in flux inferences for assessing the global carbon cycle.

The expected impact includes new modeling tools, improved regional-to-global bottom-up vegetation flux estimates, better understanding of how CO2 flux and transport processes at sub-grid scales can be aggregated up to global model scales, and advanced knowledge of how to use local flux and CO2 observations (including those from satellite) to infer representative fluxes on regional to global bases. These developments will ultimately contribute to an overall goal of validated Earth system models for confidently projecting future climate-carbon interactions.

Dynamic global vegetation models (DGVMs) vary widely in their simulation of the terrestrial carbon balance, and this poor performance is the major stumbling block in our ability to predict the global carbon balance under climate change. Model intercomparison studies have pointed out the common weaknesses or process differences among models, but there has been little systematic effort to improve model parameterizations or account for their uncertainty for global scale simulations. There is high natural variability in as well as different approaches to deriving the parameters that are used to define a very simplified set of plant functional types (PFTs). Because of computational constraints, global vegetation models cannot simulate individuals or all species diversity when coupled to climate models, and must capture at best the statistics of geographic variability in plant diversity and behavior. Thus far, the mean, let alone the variability, in biophysical, biochemical, and behavioral characteristics for a so-called plant functional type has not been well-defined.

We have been developing a dynamic global vegetation model, the Ent Terrestrial Biosphere Model (Ent TBM) (Kiang et al. 2006), which is the first to represent vegetation heterogeneity with the statistical-mechanical approach of the Ecosystem Demography (ED) model (Moorcroft et al., 2001) specifically for coupling with general circulation models (GCMs). Ent augments ED by quantifying foliage clumping for better accuracy in canopy radiative transfer and the surface energy balance. Ent s biophysics and seasonal growth dynamics have been well-tested for several PFTs at Fluxnet sites. Ent is coupled to the NASA Goddard Institute for Space Studies GCM (GISS GCM) ModelE2, capable of both off-line experiments with only land surface hydrology, or fully coupled with the GCM and carbon tracers. We would like now rigorously to determine parameter sets that are appropriate for global scale simulations. Because the ED approach statistically describes vegetation structure, it is appropriate that parameter sets should also define limited plant functional types according to their statistics across a global scale.

This proposal is to do a systematic mining of several large, recently compiled, globally ranging databases of plant traits and phenological timings to generate parameter fits and their variances for relations used in Ent. These include relations between leaf traits that affect photosynthesis and conductance, spectral albedoes of leaf and stem, geometric allometry, biomass allometry, plant tissue quality, specific respiration, turnover, and ecophysiology. We will use the technique of linear manifold clustering also to identify alternative sets of PFTs. We expect to develop parameter sets that distinguish the Ent PFTs, as well as identify global and climate relations that may help reduce parameter sets or the number of PFTs. Propagation of variances in these parameter sets will be approached through Latin hypercube sampling methods in simulations using observed climate drivers (e.g. 50-year dataset of Sheffield et al. 2006). GCM coupled simulations will be conducted to identify how GCM biases alter the carbon balance, how uncertainties propagate through future climate change scenarios, and how natural vegetation cover change may have different trajectories given parameter variance.

A community version of Ent will be released for use in global scale experiments, with technical reports and publications providing quantification of model performance and estimation of uncertainty in the terrestrial carbon balance given observed climate. This proposal is responsive to the program call for investigations utilizing the NASA GISS GCM and observations aimed at identifying, characterizing, and reducing uncertainties in DGVM predictions of climate change on seasonal time scales.

The Madden-Julian Oscillation (MJO) is a prominent mode of intraseasonal variability in the tropics. Recent studies have increasingly viewed the MJO as a moisture mode, where column-integrated moisture is the central prognostic variable. This places sources and sinks of column moisture front and center in understanding MJO dynamics. At the same time, isotopic compositions of water have long been used as tracers of moisture sources. Current observations from the Tropospheric Emission Spectrometer (TES) instrument aboard NASA's Aura satellite have indeed shown that the MJO significantly modulates the isotopic composition of water vapor, thus providing additional constraints on the water budget. In this proposal, we will add the representation of the physics of water isotopes (which are affected by microphysical transformations involving transitions between water vapor and liquid or ice hydrometeors, such as rain or snow) to two modeling frameworks: a flexible regional nonhydrostatic model (NU-WRF) and a state-of-the-art GCM (the SPCAM), which will share the same isotope microphysics module that will be based on one developed during a previous NASA project. The ability of the different modeling frameworks to reproduce the observed properties of the MJO will be evaluated using satellite observations of water vapor isotopic composition from TES, latent heating and precipitation intensity profiles from TRMM and cloud properties from CloudSat and ISCCP. The isotope-enabled models will allow us to better interpret the observed MJO modulations of isotopic composition of water vapor, as well as to explore how current (and future) isotopic observations can constrain the moisture sources and sinks associated with the MJO and their representations in the models. As the SPCAM is among the few GCMs that can simulate the MJO realistically, the isotope-enabled SPCAM will provide a benchmark for the NU-WRF. A modular simulator that approximates the isotopic composition that would be observed by TES given the model profiles of water vapor and its isotopologues under different cloud conditions will be developed as part of the project.

This proposal seeks to understand the relationship between regional climate change and the occurrence of extreme climate-related events. Using a case study approach, we will examine the physical processes associated with a rash of extreme events that occurred over the United States during 2011, including unprecedented heat and drought over the Southern Plains, and heavy rains leading to flooding over the Upper Missouri and Ohio River basins. High resolution large ensemble global climate model simulations will be used to understand both the physical processes associated with these events, and to determine their relationship to secular changes in the region s climate associated with anthropogenic forcings. The role of various physical factors will be assessed, including remote effect of ocean temperatures and sea ice, changes in greenhouse gas and aerosol concentrations, and the role of land surface changes and feedbacks. An intercomparison of several models, and comparison of each with observational data, will be used to assess robustness in the model representations of key physical processes associated with both the extremes and the regional trends. The validation of the NASA GEOS5 model, and its capacity to simulate both regional climate change and the statistics of extremes will be a further focus, with a related goal to characterize regional climate predictability.

Determining how global temperature changes translate into increased sea level rise (SLR) is one of the most fundamental questions addressed by climate projections. As demonstrated by the last Inter Governmental Panel on Climate Change (IPCC) Assessment Report AR4 (IPCC-AR4 2007), ice sheets are amongst the main contributors to SLR and their response to climate change has been identified as one of the key uncertainties in current climate model runs.

Ice sheets also play a significant role in the increase of global mean temperature, by providing several feedback mechanisms whereby: (1) ice sheet retreat reduces surface albedo in polar regions, which decreases the amount of heat radiated back to space and increases the amount of heat trapped in the Earth System, (2) ice flow dynamics modifies local surface slope (over time scales spanning from several decades to centuries), which in turn modifies atmospheric circulation and local wind-snow transport, therefore impacting surface mass balance (SMB), a key component of the mass balance of an ice sheet.

At present, state-of-the-art climate models account for changes in ice sheet SMB but fail to account for rapid changes in ice flow dynamics near outlet glaciers in Greenland and Antarctica, which can only be captured by ice flow models that include higher-order representations of stresses (Larour et al. 2012; Bueler and Brown 2009; Favier et al. 2012; Rutt et al. 2009). Similarly, most ice sheet models rely on reanalysis data for their SMB forcing that do not capture surface-slope feedback or albedo feedback modeled in atmospheric general circulation model AGCMs.

We propose here to develop a common general interface for coupling Ice Sheet Models (ISMs) and Atmospheric General Circulation Models (AGCMs), based on the existing GLINT (GLimmer INTerface) coupler from the Community Ice Sheet Model (CISM) (Rutt et al. 2009) and to explore the feedback mechanisms between polar ice sheet and atmosphere circulation using a coupled Ice Sheet System Model (ISSM) (Larour et al. 2012) and ModelE (Schmidt et al. 2006) model that relies on such interface. The goal is to run CMIP5 climate runs and to quantify critical feedback that need to be captured over century time scales to correctly account for the presence of ice sheets.

Aerosol is one of the largest sources of uncertainties in future climate projection by models. Improving representation of aerosol physics is important in development of Earth System Model. Aerosol can affect the climate system through the direct (radiation) and indirect (microphysics) effects. This proposal is focused on direct effect only. Aerosol direct effects can alter climate in three fundamental ways. First, aerosols attenuate solar radiation reaching the earth s surface, leading to a negative radiative surface forcing (cooling), i.e. the dimming effect. Second, heating of the atmosphere by absorbing aerosols (black carbon and dust) induces atmospheric feedbacks, modifying the regional and global l hydrologic cycles, i.e., the atmospheric heating effect. Third, deposition of absorbing aerosols on snow surfaces reduce snow-albedo, absorbs more sunlight, accelerate the rate of snow melt, and produce surface warming i.e., the darkening effect. These direct effects in combination could induce complex dynamical feedback processes in the climate system, leading to large departure from the climate norm.

In monsoon regions, the Elevated Heat Pump (EHP) hypothesis has been proposed positing that atmospheric heating by absorbing aerosols may induce atmospheric water-cycle feedback processes manifested in an advance of monsoon rainfall seasonal in northern Indian, and accelerated melting of the Himalaya snowpack in late spring and early summer (Lau et al. 2006, 2010). In Eurasia, where significant depositions by dust from the North Africa deserts, BC from biomass burning and from long range transport from Asia occur, the efficacy the snow-darkening was found to be much stronger than the dimming effect, possible amplify the warming due to greenhouse gases. IPCC AR4 models, which did not include snow darkening effect by aerosols, significantly under-predicted the observed trend of surface temperature warming (0.6°C/decade) in boreal spring (Flanner et al. 2009).

In addition, aerosol deposition may advance the timing and rate of spring snow melt, which may affect the long-term statistics of frequency and intensity of heat waves and associated atmospheric blocking events in the subsequent summer over Eurasia. Up to now, the interactions of the aforementioned triad of aerosol direct effects with land surface processes and atmospheric dynamics in affecting summertime heat waves are largely unknown. Here, we propose to carry out a modeling and analysis study using the GEOS-5 model and NASA satellite data, to address the overarching science question: How do radiative forcing by absorbing aerosols in the atmosphere, and at snow surface affect warm season climate variability and change over Eurasia? We propose three research tasks:

  1. Carry out diagnostic analyses to unravel the relationships among Eurasian snow amount, atmospheric loading of aerosols and surface deposition rates in boreal spring and early summer, and statistics of heat waves and blocking events in boreal summer over continental Europe and Asia, using MERRA, MODIS, AIRS and TRMM data, and GEOS-5/GOCART model outputs.
  2. Improve, implement, and test a radiative transfer model of dust and black carbon in snow in the current GEOS-5 land surface and snow cover model; validate model results with available satellite and in situ observations.
  3. Design, and conduct long-term (multi-decadal) integrations of GEOS-5/GOCART model to evaluate the relative roles of aerosol dimming, atmospheric heating, and snow-darkening on boreal spring time melting of Eurasian snow cover, and subsequent influence on boreal summer continental scale heat waves and drought over Eurasia.

Climate in the Southern Hemisphere (SH) stratosphere, troposphere, surface, and Southern Ocean has undergone significant changes in recent decades. These changes are closely linked to the trend of the Southern Annular Mode toward its high index polarity, which is driven primarily by Antarctic ozone depletion. We propose a 4-year project to investigate the influences of Antarctic ozone depletion and recovery on climate change in the SH troposphere and Southern Ocean. Our proposal will address the following questions:

  1. What is the role of Antarctic ozone depletion in recent SH climate change?
  2. How the ocean feedback affects climate change in the SH atmosphere?
  3. What are the impacts of Antarctic ozone recovery on SH climate change in the future?

We will use Goddard Earth Observing System Coupled Atmosphere-Ocean-Chemistry Climate Model (GEOS-AOCCM) as the main tool. The AOCCM integrates together the successful GEOS-Chemistry Climate Model (without interactive ocean) and the GEOS-5 Coupled Atmosphere-Ocean GCM (without interactive chemistry). We will conduct multiple centennial-scale ensemble simulations using the GEOS-AOGCM and combine model simulations with MERRA, NASA satellite and other observations to address the above key SH climate change questions. The proposed research include five tasks: 1) Development of the GEOS-AOCCM; 2) Preindustrial and present-day baseline assessment; 3) Quantify the effects of Antarctic ozone depletion on climate change in the Southern Hemisphere troposphere and Southern Ocean in recent decades; 4) Determine the effects of ocean feedback on Southern Hemisphere climate change; and 5) Investigate the effects of Antarctic ozone recovery on Southern Hemisphere climate change in the 21st century.

The proposed research will quantify the relative importance of Antarctic ozone change and greenhouse gas increase in causing the recent and future SH climate change. The results from the proposed work will improve the understanding of changes in the Southern Ocean overturning circulation and ventilation. The results will advance the understanding of the interactions among Antarctic ozone, SH atmospheric physical and dynamical processes, and Southern Ocean circulation.

Our proposed work is directly relevant to the Modeling, Analysis, and Prediction research themes in understanding regional and local scale climate change in the context of global climate change and identifying, characterizing, and reducing uncertainties in model predictions of climate change on seasonal to multidecadal time scales. The results of our proposed research may provide predictive capability, for instance ocean circulations and Southern Annular Mode. Our proposal fits the MAP theme of constituents in the climate system because it aims to understand the influence of constituent change on climate.

Atmospheric aerosols play a critical role in the climate system and yet aerosol radiative forcing is still one of the largest uncertainties in climate change projections. At the core of this problem are uncertainties in representing aerosol properties and processes in global climate models (GCMs). This proposal aims at significantly enhancing the aerosol modeling capabilities in NASA's Goddard Earth Observing System Model, Version 5 (GEOS-5) by the introduction of aerosol microphysics, a key feature for realistic representations of aerosol-cloud interactions and aerosol mixing state. The Modal Aerosol Module (MAM) that has been implemented at the NCAR Community Atmospheric Model version 5 (CAM5) is currently being adopted for GEOS-5. The first objective of this proposal is to extensively evaluate the MAM performance in GEOS-5 by confronting aerosol model simulations and data assimilation products with a wealth of satellite, aircraft and ground-based observations. As a second objective, we will make improvements to the aerosol representation in GEOS-5/MAM with the inclusion of nitrate and the revision of treatment of secondary organic aerosol (SOA) formation. Finally, the resulting GEOS-5 model with the new aerosol capabilities will be used to study aerosol direct and indirect effects on climate, and to produce an aerosol re-analysis for the NASA s Earth Observing System (EOS) period (2000-present). We will examine the uncertainties in aerosol forcing of climate by contrasting GEOS-5 and CAM5 simulations, both having similar treatments of aerosol and cloud microphysics but differing in other physical processes.

This project is a close collaboration between the Pacific Northwest National Laboratory (PNNL) and the NASA Goddard Space Flight Center (GSFC) Global Modeling and Assimilation Office (GMAO). The PNNL group is the lead developer of MAM and responsible for its implementation in NCAR's CAM5. This project complements another ongoing GMAO-NCAR collaboration on the implementation of the Morrison-Gettelman two-moment cloud microphysics; the aerosol microphysics being proposed here is an indispensable element for properly implementing cloud-aerosol interactions in GEOS-5. With its implementation in GEOS-5, MAM will be used for the first time in the context of aerosol assimilation.

This proposal directly supports the NASA's Modeling, Analysis, and Prediction research themes. Specifically, it provides investigations designed to examine the role of aerosols within the Earth system and improve their representation in global models. This proposal utilizes observations from space-borne, airborne and ground platforms that are aimed at identifying, characterizing and reducing uncertainties in model predictions, from days to seasonal to multi-decadal time scales.

Tropospheric ozone and aerosols affect climate on both regional and hemispheric scales. Climate change, in turn, influences the distribution and lifetimes of these species, with consequences for human health and ecosystems. Understanding the coupling between short-lived chemical species and climate change is a major challenge, given the uncertainties in chemical mechanisms and climate processes. To improve our knowledge of the links between chemistry and climate, we propose to mine the suite of multi-decadal climate and chemistry hindcasts currently underway at Goddard Space Flight Center.

These hindcasts include simulations from (1) the Global Modeling Initiative (GMI) chemical transport model (CTM), which is driven by assimilated meteorology, and (2) the Chemistry Climate Model (CCM), which is forced by observed trends in sea surface temperatures, sea ice cover, and greenhouse gases, as well as calculated ozone and aerosols. With a series of sensitivity studies, we will investigate: (1) variability in the oxidation capacity of the troposphere over recent decades, (2) trends in the cross-tropopause flux of ozone, (3) trends in the frequency or location of mid-latitude cyclones and the impacts of these trends on ozone, (4) effects of North Atlantic sea surface temperatures on regional climate and associated emissions, and (5) impacts of changing aerosol sources on regional climate. We plan to provide GMI with updated chemical schemes and emission inventories, thereby extending the long-term partnership between the Harvard Chemical Modeling Group and NASA Goddard. This project promises to increase scientific understanding of chemistry-climate interactions in the recent past, thereby enhancing confidence in future projections of climate change.

Calculations of radiative forcing since the pre-industrial generally include the effect of anthropogenic aerosols except for the contribution by dust aerosols. This omission is partly because the changing dust burden due to anthropogenic trends in the circulation is estimated to be small, but also because little is known about historical changes in dust sources due to human activities like cultivation and grazing as well as natural source changes due to drought. We propose to use a recent attribution of anthropogenic dust sources based upon high-resolution satellite retrievals during the past decade to calculate their contribution to the dust cycle and the effect of the corresponding dust radiative forcing upon the atmospheric circulation and regional precipitation. This calculation will be carried out using the NASA Goddard Institute for Space Studies general circulation modelE. Cultivated regions have been shown to exhibit high concentrations of atmospheric ammonia, a precursor to ammonium salt aerosols that coat dust particles. This coating increases the conversion of insoluble iron within the dust minerals to more soluble iron species whose deposition increases the rate of ocean productivity and the uptake of CO2 during photosynthesis. Anthropogenic dust sources also tend to coincide with high soil concentrations of iron-bearing minerals. To calculate perturbations to the climate by anthropogenic dust sources, we propose to calculate separate prognostic budgets for each mineral comprising dust. This will allow us to test whether anthropogenic sources preferentially increase the aerosol burden of hematite and goethite, iron-bearing minerals that dominate dust shortwave absorption. (Calculating shortwave absorption as a function of mineral content will also allow us to use AERONET retrievals to provide an additional constraint on the model's distribution of hematite and goethite.) In addition, the prognostic mineral scheme will allow us to test whether the enhanced ammonia emitted by anthropogenic sources leads to a greater conversion of insoluble to soluble iron.

We propose to calculate the resulting climate anomalies corresponding to anthropogenic dust sources for the present-day as well as anomalies compared to the pre-industrial and late 21st century along with their uncertainties. Present-day anomalies relative to the past can be compared to 20th century deposition measurements from the ice cores and coral records. Future anomalies will show the effect of projected land use and ammonia emission that will change in response to the greater demand for food associated with growing population. We are especially interested in rainfall anomalies in regions with extensive anthropogenic sources (like the Asian monsoon region or Australia) or societally important regions like the Sahel. Anthropogenic sources and enhanced ammonia emission in Australia are particularly important for the deposition of soluble iron in the Southern Ocean, a region where ocean productivity is limited by nutrient supply. We note that much of the model functionality needed to address the science questions addressed in this proposal already exists within the GISS modelE or is being added as part of a separately funded project.

Building on research under our expiring proposal, we will continue toward our goal of assimilating, in near-real time (NRT), cloud and surface properties derived from satellite data into the Global Modeling and Assimilation Office (GMAO) GEOS-5 assimilation system. We propose to use cloud property, surface skin temperature (Tskin), spectral albedo, and aerosol retrievals from operational geostationary-orbit (GEO) and NASA low-Earth-orbit (LEO) satellites to:

  1. validate and improve output parameters from GEOS-5 to improve weather and climate forecasts,
  2. serve as input to the GEOS-5 Data Assimilation System (DAS), and
  3. examine the impacts of hourly/3-hourly aerosol information on air-quality forecasts.

Under our expiring MAP funding, we performed cloud validation studies to assess uncertainties in the satellite-derived cloud parameters for a few specific cloud types, viz. marine stratus, mid-continental stratus, and midlatitude cirrus clouds. We established a NRT, 3-hourly, 8-km global GEO cloud and surface property retrieval system and transferred the data to the GMAO. Validation of Tskin retrievals in select locations showed they are equivalent to MODIS LST retrievals.

Our global comparisons of GEO Tskin with GEOS-5 revealed that there are some satellite viewing angle biases relative to the model and that the model is biased with respect to the satellite data as a function of time-of-day and location. The module to assimilate the global GEO Tskin data into the DAS is being completed this year. Comparisons of cloud amount and optical depth show reasonable agreement in certain areas, such as the USA, but are strongly biased in others, including parts of South America. Assimilation of GEO cloud data is underway and improvements are expected in cloud and surface properties and precipitation. However, studies using MODIS data indicate that cloud assimilation is most effective using high-resolution data because variability at small scales is needed for the assimilation.

In this proposal, we will continue the validation of the GEO cloud and surface retrievals over other sites to provide the DAS with improved uncertainty bounds. We will expand the retrievals to hourly, full (~4-km) resolution GEO data providing a complete diurnal cycle. In addition to improvements in our current cloud retrievals, we add a new multilayer cloud product, visible-channel surface albedo, and aerosol optical depths (AOD) to the data stream for GEOS-5. AOD will be retrieved using 1-wavelength variants of current methods applied to GOES and Meteosat data, but using an optimal estimation algorithm constrained by MODIS-assimilated GEOS-5 aerosols. This will provide a global, algorithmically consistent, hourly aerosol product that will be validated/tuned to AOD values from the MODIS products at the Terra/Aqua overpass times and from AERONET and ICESat GLAS data at other local times. The analyses will be performed on the Discover supercomputer for rapid delivery to GEOS-5. On the modeling/assimilation side, we will complete the integration of the Tskin analysis into the GEOS-5 NRT system using the higher resolution retrievals. Quality control routines will be refined based results from our expiring project. We will also investigate the potential of using the GEO albedo retrievals in the GEOS-5 analysis. The current NRT GEOS-5 products include an analysis and forecast of aerosol distributions using MODIS biomass emissions and AOD. Under this proposal we will improve the temporal and spatial representation of aerosols using the higher frequency GEO input. We have previously developed an assimilation of MODIS-derived cloud properties. Here, we will continue to refine that system to test the impact of the high resolution GEO data on the representation and forecast of moisture with GEOS-5. Finally, we will undertake a short reanalysis of the EOS period and evaluate the impact of the GEO data on estimated global energy and moisture budgets.

Atmospheric radiative processes are key drivers of the Earth s climate and must be accurately represented in global circulations models (GCMs) to allow faithful simulations of the planet s past, present, and future. In addition, the spectral signature of radiation exiting the atmosphere contains detailed information about atmospheric properties and composition, information of critical importance to our understanding of numerous geophysical processes and cycles. These two aspects of radiation are both essential to the objectives of the Goddard Earth Observation System (GEOS), which includes both a coupled atmosphere-ocean GCM that requires an accurate parameterization of radiative fluxes and heating rates, and a data assimilation system that can utilize spectrally resolved radiation measurements from a diverse set of satellite-based instruments. This proposal supports both of these GEOS-5 objectives by developing an enhanced radiation package for GEOS-5 that will provide accurate and efficient calculations of radiative fluxes, heating rates, and satellite radiances.

A key element of this radiation package will be an improved version of AER s RRTMG radiation code, recently implemented in GEOS-5, which will be updated to be consistent with current spectroscopic knowledge. In addition, deficiencies identified in RRTMG will be resolved and longwave scattering capability will be added. The enhanced radiation package will also include the capability to compute satellite radiances from instruments identified as priorities by our GMAO colleagues; this code will be developed using AER s Optimal Spectra Sampling (OSS) approach, the foundation for a new version of the Community Radiative Transfer Model (CRTM), used for data assimilation at the Joint Center for Satellite Data Assimilation (JCSDA). Although the relationship between this proposed radiation package and CRTM/OSS will provide consistency and synergy between GMAO and JCSDA efforts, a key priority of the proposed work will be the development of OSS-built satellite simulation code for instruments relevant to scientific applications other than weather. Our focus in this effort will be satellite channels that provide information on atmospheric composition, thereby supporting GEOS-5 data assimilation of greenhouse gases (GHG), atmospheric chemistry and aerosols. The development of accurate and efficient satellite radiance simulation capabilities for GEOS-5 will provide a key mechanism to expand our ability to understand the properties and evolution of the Earth system.

The enhanced radiation package will be extremely flexible, allowing users to choose the desired mixture of available flux and satellite radiance calculations for their particular application, thereby minimizing the computational cost. In this project, code will be developed not only for standard CPU processors but a version will also be developed that is consistent with GPU technology, work synergistic with our current effort (funded by NASA) to built a GPU-compatible version of RRTMG.

This development will significantly enhance the GEOS-5 representation of radiative processes, of critical importance across a wide range of spatial and temporal scales. This work would thereby support the MAP program objective of attaining a complete understanding the Earth system, as well as enhance the quality of GEOS-5 simulations and reanalysis products produced by the model. The enhanced radiation package would also benefit other MAP projects related to GEOS-5, such as the Global Modeling Initiative and the NASA Unified Weather Research Forecast Model, other modeling centers (such as NCAR, NCEP, ECMWF) that use RRTMG or may elect to implement the satellite radiance simulation capability (GISS), as well as providing infrastructure to assess future satellite instruments.

The principle objective of the proposal is to enhance GEOS-5 AGCM cloud prediction capabilities, especially the links of aerosols with cloud formation and microphysics. The proposed avenue for accomplishing this is by further development and validation of the McRAS-AC cloud scheme implemented in GEOS-5 under support from the previous MAP funding cycle. In addition to standard cloud macrophysical variables such as cloud fraction and condensate, McRAS-AC in GEOS-5 predicts profiles of mean cloud particle size and particle number density for liquid, ice and mixed phase clouds. Particle number prediction is achieved through implementation of aerosol activation and ice nucleation routines applied to both stratiform and convective clouds. The GEOS-5 AGCM has therefore the required framework for studying aerosol-cloud interactions and providing quantitative assessments of the aerosol indirect effect. Despite the many successful features of GEOS-5 AGCM simulations with McRAS-AC, areas of improvement still remain. Parallel microphysical parameterization improvements as part of core GEOS-5 AGCM development efforts pave the way for ultimately synthesizing the best features of the two cloud schemes.

The central task of the proposal is to enhance the capabilities of McRAS-AC. Plans to accomplish this include integration with a new aerosol microphysical scheme, addressing the absence of marine boundary layer clouds in tropical / subtropical regions, making the precipitation parameterization prognostic, adding the effects of ice crystal multiplication and aerosol-induced convective invigoration, and accounting for cloud horizontal heterogeneity and overlap effects in radiative transfer calculations.

A natural follow-up to the above task is in-depth validation of the cloud scheme taking into account measurements and retrievals provided by modern observational platforms and using recently developed tools that allow observation vs. model comparisons to be made in a way that addresses to the best extent possible the differences between model and satellite perspectives. This validation protocol will be extended with sophisticated higher-order diagnostics to test the ability of the model to reproduce observed cloud regimes, cloud albedo responses to droplet number perturbations (cloud susceptibility) and band-by-band longwave cloud radiative effects.

Lastly, a final group of subtasks within our third task encompasses side-by-side comparisons of McRAS-AC microphysics with those of a variant of the Morrison-Gettelman microphysical scheme enhanced with aerosol-cloud interactions, also being implemented in GEOS-5. The comparisons will take advantage of the common GEOS-5 AGCM platform and the constraints it provides. Such studies will enable isolation of weaknesses due to model deficiencies beyond moist processes. Regional sensitivity studies with both schemes to validate hypothesized aerosol-cloud interaction mechanisms will also offer illuminating clues on the model s microphysical performance.

Implementation of adjoint versions of aerosol activation and ice nucleation parameterizations will support these targeted regional studies by facilitating a closer examination of the physical processes responsible for specific cloud responses to aerosol amount and other parameters that control cloud microphysics.

The goal of this project is to investigate ozone-climate interactions in the Northern Hemisphere (NH) using the Goddard Earth Observing System (GEOS) chemistry-climate model (CCM). This project is motivated on the one hand by the 2011 severe Artic ozone hole which potentially contributed to the observed extreme NH climate anomalies in spring and on the other hand by the fact that the role of ozone climate interactions in future NH climate change is not understood.

The GEOS CCM configuration includes the GEOS-5 atmosphere-ocean GCM coupled to the GMI COMBO chemistry mechanism. In this project, the GEOS CCM will be used mainly in coupled atmosphere-ocean mode (GEOS AO-CCM). Based on a set of numerical experiments, accompanied by analysis of MERRA data and satellite observations, we will address the following research questions:

  1. How sensitive is ozone change to a range of factors in the model?
  2. How have ozone changes impacted surface climate in the early 21st century?
  3. How will ozone and climate interact in the late 21st century?

The project will begin with a characterization of tropospheric and stratospheric climate and troposphere-stratosphere interactions in the NH based on existing simulations of the atmospheric CCM and the AO-GCM. The MERRA reanalysis will be used to evaluate these models. This analysis will characterize the realism of GEOS-5, as well as the different impacts of ozone-circulation feedbacks and air-sea interactions. The evaluation also includes parameter-space experiments with the CCM for the first decade of the 21st century to test the sensitivity of simulated chemistry-circulation to changes in model parameter with EOS-Aura and other satellite observations used for comparison. The bulk of the new work for this project will be to conduct two unique sets of multi-decadal simulations, carried out in a large ensemble mode of the GEOS AO-CCM and AO-GCM. These two sets of experiments will be used to study the impacts of ozone (and other chemical changes) on recent and future changes in NH climate. The ensembles will cover uncertainty in initial conditions and also span a range of values of model parameters, allowing for (i) a robust assessment of the interactions and (ii) examination of their dependence on model formulation as well as (iii) the sensitivity to Representative Concentration Pathway (RCP) for future changes.

An important contribution of this project is to assess the role of ozone changes in the occurrence of extreme tropospheric climate events by conducting large ensembles that allow studying the properties of probability distribution functions (PDFs) of tropospheric climate parameters including the behavior of these PDFs in their tails, which represent the occurrence of extreme events.

By utilizing the GEOS CCM the project will link directly to GMAO s activities and use the chemistry modules developed by GMI, including studies that relate uncertainty in modeling atmospheric composition to the parameter sensitivity of the underlying GCM. The proposed work directly addresses several research themes identified in the MAP solicitation and its overall Earth System goal: This project will enhance our understanding about the role of ozone-climate feedbacks in hemispheric and regional climate change in the context of global climate change. Furthermore, it will assess the importance of representing feedbacks related to air-sea interaction and chemistry climate interactions for simulating future evolution of the ozone layer.

Overview: This project builds on the successful development and application of the NASA Unified Weather Research and Forecasting (NU-WRF) modeling system, with the goal of integrating and enhancing existing land and atmospheric data assimilation capabilities to advance regional-scale coupled land-atmosphere modeling for process studies. The NU-WRF currently combines the capabilities of the WRF with the Land Information System (LIS), the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model, advanced microphysics and coupling between clouds and aerosols to better represent cloud-aerosol-precipitation-land surface processes. Outputs can be directly compared with satellite L1B data via the Goddard Satellite Data Simulator Unit (G-SDSU). Further, the NU-WRF connects with global-scale modeling efforts, including the GEOS-5 and the MERRA, which can be used as atmospheric boundary and initial conditions. This project will focus on advanced component couplings and integration of existing land (LIS-DA) and atmospheric (WRF-EDA) data assimilation in NU-WRF.

Relevance: This proposal represents a continuation of the core development for NU-WRF, as described in the call. Specifically, we will (1) Characterize and/or reduce uncertainties in models and products (by evaluating the case studies with and without data assimilation, as well as after physics and chemistry refinements); (2) Extend the range of model or product validity by using new components (by incorporating and generalizing the LIS-DA and the WRF-EDA); and (3) Enable independent community validation and characterization (by distributing the NU WRF code to partners). The proposed data assimilation and physics enhancements to NU-WRF further the core MAP program interests in regional observation-driven modeling and data assimilation.

Approach: Recent results have indicated the critical role that incorporating land surface and atmospheric observations can play in helping further advance our ability to represent coupled land-atmosphere processes. As part of this work, we will first enhance the couplings between key NU-WRF components, such as wet deposition, dust and biogenic emissions, aerosol-cloud-precipitation interactions, and mesoscale circulations. Next, we will fully incorporate and advance LIS-DA in the NU-WRF to assimilate satellite-based land surface products such as soil moisture, snow cover and depth, and skin temperature, while also updating land parameters such as real-time green vegetation fraction, albedo, and irrigated area. We will also fully incorporate and advance the WRF-EDA in the NU-WRF to assimilate cloud-precipitation-affected microwave radiances to advance the representation of clouds and precipitation in the NU-WRF. Finally, we will conduct case studies demonstrating the impact of the LIS-DA and the WRF-EDA on land-atmosphere processes for high-impact weather-to-climate scenarios such as tropical cyclones, droughts, floods, heat waves and extreme storms; as well as impacts on atmospheric chemical constituents including severe air quality degrading events.

This research will focus on several key uncertainties in our assessments and modeling of the reactive greenhouse gases and aerosols. It places emphasis on the development of methods for calculating photochemistry with clouds, scavenging, and convection that are independent of the scale of the model, and thus do not need to be adjusted as the resolution increases. Accurate representation of these processes in GMAO / GMI components is a core element of projecting future air quality (surface ozone and particulate matter) and climate forcing (e.g., methane, nitrous oxide, tropospheric ozone and aerosols). This effort will train doctoral students and post-doctoral researchers, building a scientific workforce with an understanding of Earth system science in accord with NASA s mission.

In Task 1 the UCI CTM will use the T319L60 (0.5°) meteorology from ECMWF via U. Oslo as a test bed for developing (a) a fast-JX photolysis module linked more efficiently and accurately to fractional cloud cover, (b) an aerosol-gas scavenging module similarly linked, (c) a new lightning-NOx module tied to the statistics of convection and cloud-top heights, and (d) STE flux diagnostics using a synthetic tropopause tracer. All of these modules will be developed from lessons learned as we scale between T319 and T42 (2.8°, our low-resolution CTM) and then transferred to the GMI code. Processes that depend on clouds and convection profiles tend to look different when averaged over time and space, and this effort will develop modules that take account of the higher-resolution patterns that may or may not be resolved in GMAO/GMI (e.g., super-parameterizations).

In Task 2, UCI will maintain and further develop the fast-JX photolysis module now part of GMI to reflect current uncertainties so that these may be propagated through the GMI model, including fractional clouds noted above. There are few alternatives to fast-JX for cloud-aerosol-chemistry coupling, and it is important to maintain and update the module and spectral data. Specifically, the VOC J-values have pressure-dependent quantum yields that require a new approach to implement in GMI accurately. In this case the models need to be constrained by laboratory measurements. Task 3 will provide a unique direct comparison of the GMAO MERRA reanalysis with that of the ECMWF over the past decade in terms of tracer transport and photolysis fields. It is difficult to run the same full chemistry CTM with both MERRA and ECMWF fields as we have tried in past GMI work. Instead, simple-chemistry tracers and tropospheric photolysis budgets from fast-JX run with the GMI CTM (MERRA) and UCI CTM (ECMWF) will allow characterization of differences in met fields for the same period/synoptic events, thus giving us some independent measure of uncertainty in the hindcast fields.

Task 4 addresses uncertainties in large-scale integrated quantities, such as lifetimes, that can be attributed to possible errors in chemical data or processes. UCI recently made a systematic investigation of the uncertainties and their propagation in terms of future greenhouse gas abundances, identifying the key processes that drive the overall uncertainty. Under this analysis, atmospheric chemistry models must play a critical role in mapping uncertainties in chemical data (reactions, rates, cross sections) and process models (cloud cover, convection) onto the integrated quantities, such as current and future atmospheric lifetimes. We have also come to appreciate that observed interannual variability, such as the methyl-chloroform decay rate, provides a unique and integrative test for hindcast CTMs like GMI. For this task we will pursue sensitivity studies constrained by both atmospheric and laboratory measurements, with both UCI and GMAO/GMI CTMs, to identify major uncertainties.

Observations of tropical deep convection have long documented that there is more than one type of convective system, that convection exhibits differing styles of mesoscale organization that produce different effects on the atmosphere s energy, moisture and momentum. Recent analyses of satellite observations further suggest that changes in the large-scale tropical circulation during notable events, such as the Madden-Julian Oscillations or monsoons or African Easterly Waves, produce systematic changes in mesoscale convective organization that enhance the coupling of tropical deep convection to the larger-scale circulation. This particular switching behavior cannot be represented in current-day GCMs because they all parameterize deep convection as a single type of phenomena that most closely resembles cumulonimbus ordinary convection that is local and short-lived. This is a particularly opportune time to investigate what are the consequences of this limitation of GCM representations of deep convection because of the availability of: a rich variety of satellite observations, sufficient computer resources to conduct extensive experiments with convection-resolving models on the very large spatial domains characteristic of large-scale tropical waves, special purpose, very high resolution (25 km) weather-analyses of the atmospheric circulation for the Year of Tropical Convection (YOTC) from ECMWF and a longer-period analysis MERRA, and climate-style GCMs now running experimentally at 100 km scale.

Our proposed study exploits this set of resources by tightly coupling the analysis of satellite observations and the outputs from model experiments using the same advanced analysis methods, including classification, tracking and conditional sorting of multiple data products. These methods will be applied to the YOTC-ECMWF database (reanalysis merged with A-train observations) and the GEOS5 reanalysis (MERRA), the output of a large-domain cloud-system-resolving model (NCAR CRM), and to the output of two GCMs, NCARs CAM and NASA GISS ModelE. These comparisons will pose questions to be investigated by further CRM and GCM experiments. Modifications to the GCM parameterizations suggested by these results will be implemented to test how they change the GCMs representations of specific tropical phenomena. At every stage of the model experiments, satellite observations will be used to discriminate among the possible explanations of convective behavior. Our investigation addresses many of the fundamental questions posed in the YOTC Science Plan and connects to many of the MAP research themes, particularly concerning satellite-observation-guided model experiments to explain key tropical events involving the interaction of deep convective organization changes and the large-scale circulation disseminating our analysis methodologies for diagnosing convection-related behavior in satellite observations and in models.

Hydroxyl radical (OH) is the most important oxidizing agent in the troposphere, providing the main sinks of CO and CH4 as well as other species of interest to the air quality, climate, and stratospheric ozone communities. The chemistry of tropospheric OH (OHTROP) is complex and will respond to various factors such as future levels of CO and CH4, changes in atmospheric transport driven by greenhouse gases, as well as increasing anthropogenic emissions of short-lived species in some geographic regions and declining emissions of these species in other regions. One response of future OHTROP, posited by IPCC (2001) and now represented in numerous textbooks, is that increases in atmospheric CH4 will lead to future declines in OHTROP. The analyses that led to this conclusion, though, do not account for many factors that will affect OHTROP. One such factor is the expansion of the Hadley cell, suggested by a variety of recent observations. This widening of the tropical belt will likely cause a poleward expansion of the regions of low tropical O3 column and high relative humidity, driving up future OHTROP. Additionally, OH chemistry depends on concentrations of nitrogen oxide radicals, volatile organic compounds, and other hydrocarbons. Emissions of these species are expected to change, throughout this century, in ways that do not unequivocally indicate decreasing OHTROP. Finally, future abundances of CH4 are quite uncertain and at the time IPCC (2001) was written, dCH4/dt was much larger than during the past decade.

Increases in upper tropospheric O3 (O3UT) from 1750 to 2005 have contributed significantly to the radiative forcing of climate (RFCLIMATE). A recent international report drew attention to the societal benefit that could be attained by reducing future O3UT by focusing on CH4 (UNEP, 2011). Most public policy effort is focused on reducing future concentrations of surface O3. While a cursory examination of the relevant chemistry might suggest that future efforts to limit surface O3 should also reduce O3UT, there are important differences between the chemistry of ground-level and UT O3, such as lightning NOx and supply of HO2 to the UT from non-methane hydrocarbons, that could be relevant to any future policy.

We propose to work with output generated by Chemistry Climate Models, as part of the IGAC/SPARC Global Chemistry-Climate Modeling and Evaluation Initiative, to address how OHTROP and O3UT will respond to climate change. We propose to conduct analysis of model runs, being archived for this initiative, using an existing tropospheric/stratospheric chemistry photochemical box model, together with metrics we are helping to develop for this initiative (similar to those used successfully in the past for SPARC 2010 Report on the Evaluation of Chemistry-Climate Models), to address:

a) Might the continued widening of the tropical belt, the predicted permanent depletion of stratospheric ozone column in the tropics due to increased strength of the Brewer Dobson Circulation, and increased humidity due to rising temperature conspire to increase future OHTROP? If so, what are the implications for the lifetime of CH4 and other gases lost by reaction with OH?

b) Will measures designed to limit surface O3 and CH4 affect levels of O3 in the upper troposphere and, if not, what other policy options might be available to limit future growth of O3UT?

Despite major advances in our understanding and ability to simulate tropical storms and tropical storm activity, predicting the societally most important aspects of the storms such as intensities and tracks on sub-seasonal, seasonal and longer time scales remains a challenge. A key recent example is the 2010 hurricane season, characterized by hyper-activity (ACE › 175%; generally well-predicted) but marked at the same time by the absence of US land-falling hurricanes (not predicted). In this proposal we focus on improving our understanding and prediction of those aspects of North Atlantic tropical storm activity (in particular the all-important tracks) that are controlled by large-scale atmospheric dynamics, including the role of such phenomena as the Madden Julian Oscillation (MJO), El Nino Southern Oscillation (ENSO), and the Atlantic Meridional Mode (AMM).

Our approach takes advantage of on-going developments in the GMAO to improve the representation of hurricanes in high-resolution versions of the GEOS-5 global model together with a replay technology that allows us to constrain various components of the model s large-scale atmosphere to remain close to the observed (MERRA) fields.

Experiments will be conducted that constrain limited spatial domains (e.g., the large-scale atmosphere over selected ocean basins,) selected scales of motion (e.g. retaining only the largest planetary waves), and selected quantities (e.g., winds, humidity). In these experiments, the model-generated synoptic and smaller scale variability over the regions of interest will have no direct constraints, allowing us to make quantitative assessments of the controls on tropical storm activity imparted by the large-scale fields. By carrying out ensembles of runs, we will also be able to make an assessment of the potential predictability provided by such constraints.

The work should lead to improved understanding of the physical / dynamical processes that control changes in tropical North Atlantic storm tracks on subseasonal to interannual time scales. The proposal is directly relevant to the MAP research theme to examine the role of processes within the Earth system and improve their representation in global models, including the representation of the weather-to-climate continuum of high impact events such as tropical systems, floods, droughts, heat waves, and extreme storms.

We propose a successor project, continuing our current MAP project, which is focused on the simulation of the Madden-Julian oscillation (MJO) and tropical cyclones (TCs) in the NASA Goddard Institute for Space Studies (GISS) climate model. The objectives of the new project will be as follows:

  1. Continue to evaluate the simulations of the MJO and TCs in the latest versions of the model as they develop, including the most high-resolution versions (which we expect to have the best simulations of TCs);
  2. Evaluate the biases in the mean tropical climate together with those in the MJO and TCs in different model variants (esp. with differences in the convective and cloud parameterizations), including in coupled ocean-atmosphere simulations, and attempt to find convective and cloud schemes which retain good MJO and TC simulations without degrading the mean climate;
  3. Understand in greater depth the dynamics of the simulated MJO and TCs, including focusing on specific observed events;
  4. Assess the impacts of the MJO on extratropical circulation and weather in the model, including precipitation extremes;
  5. Analyze the changes in the MJO, TCs, and related precipitation extremes in a climate which is changing due to greenhouse gas increases as well as associated aerosol and cloud feedbacks.

This project involves simulation with both atmospheric and coupled versions of the model, at a range of horizontal resolutions, with the highest being 0.5x0.5 degrees. The TC work will use primarily the higher resolution models (1x1 and 0.5x0.5 degrees), while the MJO work will focus on lower-resolution models with convection schemes modified to produce the MJO.

For the first time, in recent years GISS models have been developed which can simulate the MJO and TCs with some fidelity. The improvement in TC simulation resulted from resolution increases, the improvement in MJO simulation from convective parameterization changes made by us in our current project. The focus of our model development effort in the proposed project will be to improve on the remaining weaknesses in the simulations (particularly with respect to the MJO and mean climate biases which result when the convective scheme is altered to improve it) while retaining the strengths as much as possible. At the same time, we will use the existing models, or any superior ones which may be developed in the course of the project, to address key science questions about the MJO, TCs, and the relation of both to a changing climate.

A component of the work involves continued participation in intercomparison projects, including those carried out for the US CLIVAR Working Group on Hurricanes and Climate, Year of Tropical Convection (YOTC), and Dynamics of the Madden Julian Oscillation (DYNAMO) field program.

This project addresses the focus in the solicitation on improving "representation of the weather-to-climate continuum of high impact events such as tropical systems, floods, droughts, heat waves, and extreme storms". More broadly, it addresses NASA s strategic objective to advance Earth System Science to meet the challenges of climate and environmental change; and the Earth Science Research Program s goal to distinguish natural from human-induced causes of change and to understand and predict the consequences of change. The GISS model is one of NASA s primary tools for meeting these objectives, and one of the two foci of the MAP program. The MJO and TCs are key phenomena which may change in a warmer climate, in ways which remain poorly constrained. By analyzing the model's performance in simulating these phenomena at present, understanding the mechanisms operating in the models, studying the changes in future climate change simulations, and using this knowledge to improve the simulations via parameterization development, our proposed project will bring NASA closer to achieving these goals.

We propose to use NASA satellite measurements and retrieved products as well as field campaign observations in conjunction with Goddard Multi-scale Modeling Systems with unified physics to extend our understanding of cloud-precipitation processes and their impact on short-term climate and weather. Combining observations with modeling will enable us to statistically quantify our ability to simulate the atmospheric response to clouds, precipitation, radiation, surface processes, aerosols and their interactive feedbacks. The cloud-scale GCE model and global-scale MMF will provide information on cloud and precipitation microphysical and dynamical processes and their interaction with radiation, aerosols, and the surface. These atmospheric models have been linked to multi-satellite, multi-sensor, and multi-spectrum satellite simulators to compute satellite-observable radiance (brightness temperature) and backscatter (e.g., radar reflectivity and lidar backscatter) signals for direct comparison with satellite-observed signals from passive microwave radiometer, visible-IR imagers, lidar, and/or radar sensors. The proposed modeling effort will improve our understanding of cloud and precipitation processes and their interactions with aerosols over many scales of motion, from cloud microphysical to regional to the large-scale circulations that organize the growth and decay of precipitation systems.

The major objectives of this proposal are:

  1. Compare and improve model-simulated precipitation processes associated with different types of clouds/cloud systems in different geographic locations/climate regimes utilizing the Goddard Satellite Data Simulator Unit (G-SDSU) and NASA satellite and ground-based observations,
  2. Continue improving the Goddard MMF s performance by evaluating a variety of coupling methodologies [e.g., using improved one and two moment cloud microphysics, enhancing model resolution, and replacing the Goddard Earth Observing System Data Assimilation System Version 4 (GEOS-4) with Version 5 (GEOS-5)] for studying aerosol-cloud-precipitation processes,
  3. Conduct multi-year model simulations and analyze and compare simulations for important regional weather/climate features, such as high-impact events (i.e., tropical systems and extreme storms), from the MMF and GEOS-5 with Modern ERA Retrospective Analyses for Research and Applications (MERRA) and NASA Earth Observing System (EOS) satellite products. In addition, current and future climates simulations (2001-2010 and 2026-2035) will be conducted using the improved MMF,
  4. Make the simulated and observed data available to the public via the Goddard Cloud Library

Relevance: Our proposed research will also address the programmatic priorities as stated in MAP12 in the following areas:

  1. Characterize and/or reduce uncertainties in models and products (by evaluating the quality of the GCE-, NU-WRF-and MMF-simulated data with associated observations and MERRA),
  2. Extend the range of model or product validity by using new components (i.e., the Goddard MMF and NU-WRF),
  3. GEOS-5 and NU-WRF are in alignment with the goals and objectives of the core MAP elements, and
  4. Enable independent community validation and characterization of the core MAP elements leading to improvement of the model and products (which we can accomplish via the Goddard Cloud Library).

Objective: The objectives of this project are: i) to develop an integrated approach for the parameterization of clouds and convection in the Planetary Boundary Layer (PBL) and ii) to implement and evaluate these parameterizations in the GMAO GEOS model. This integrated approach for boundary layer parameterization will be based on two main components: (i) the Eddy-Diffusivity Mass-Flux (EDMF) parameterization of boundary layer mixing; and (ii) the Probability Density Function (PDF) cloud parameterization.

Motivation and Technical Approach: A realistic representation of the cloudy boundary layer is essential for accurate weather, seasonal, decadal and climate predictions. Tropical and sub-tropical boundary layer clouds are essential to the surface energy balance and Sea Surface Temperature (SST) distribution and are key elements in biases in seasonal coupled model forecasts. It is well established that clouds remain the largest source of uncertainty in climate projections. Unfortunately, current climate and weather models are still far from realistically representing the cloudy PBL.

During the last few years two promising approaches to represent key components of the cloudy PBL have been developed and tested in some models: i) the Eddy-diffusivity/Mass-flux (EDMF) approach for PBL flux parameterization and ii) the PDF-based approach for cloud parameterization.

Eddy-Diffusivity/Mass-Flux (EDMF): the EDMF approach is based on the unification of concepts generally used for the parameterization of turbulence in the boundary layer (ED) and of moist convection (MF). The EDMF approach was first proposed about 10 years ago and subsequently tested and implemented operationally in the ECMWF model. Recent studies have shown the potential of the EDMF approach to represent the dry convective boundary layer and the shallow convection boundary layer. A dry version of the EDMF approach (with an MF model that does not allow for condensation) has been implemented and tested in the GEOS-5 model by this team, and has been shown to produce significant improvements.

PDF-based cloud parameterizations: PDF cloud parameterizations are based on the assumption that it is possible to estimate the probability density functions (PDFs) of moist conserved thermodynamic variables for each model grid point, and that from these PDFs, parameters such as cloud cover and mean liquid water content can be computed. The PDF cloud parameterization methods have been advocated for some time, but only relatively simplified versions have been implemented in weather and climate models.

We will evaluate the new EDMF and PDF-based parameterizations utilizing a variety of NASA satellite observations of cloud and PBL properties, including data from ISCCP, CERES, MODIS, MISR, AIRS, CloudSat, CALIPSO and GPS RO. We anticipate using satellite observational simulators for several of the evaluation investigations. Part of this evaluation will be carried out in the context of the GCSS Pacific Cross-section Intercomparison (GPCI) framework. The NASA MAP Program supported the development and establishment of the GPCI framework and working group.

Rationale and Objectives: Cloud feedbacks remain the primary source for the inter-model climate sensitivity spread. The majority of the studies examining this spread have focused on attributing the model differences to particular cloud types. Constraining against the observations is done by comparing the modeled and observed cloud type frequency of occurrence in current climate conditions. This is a good starting point but does not provide information on the processes responsible for the model sensitivity spread. The challenge is to identify those processes that play a major role in determining the properties of the cloud field that most strongly affect climate sensitivity. Recent studies have shown very strong correlations between model climate sensitivity and the poleward shift of cloud amount and cloud water path. This poleward shift is common in almost all climate warming simulations due to the poleward shift of the midlatitude storm track, and the degree of model warming is strongly related to the magnitude of the shift. Our recent work shows that a similar cloud shift can be found when satellite cloud-type retrievals of the last 25 years are analyzed. It also shows that poleward storm shifts produce strong signatures not only on midlatitude clouds but also on the subtropical cloud field, potentially related to changes in the zonal extent of the Hadley circulation. Given that for this 25 year period we have available retrievals of all the components of the cloud and radiation fields as well as reconstructions of the atmospheric circulation that assimilate those retrievals, it is now possible to both resolve at different time and space scales the relationships between storm shifts and the resulting cloud and radiation changes and to produce well defined observational constrains that will address directly the uncertainty of model climate sensitivity.

Approach: We have developed a clustering methodology that allows classification of clouds in regimes that have been shown to represent mesoscale weather states in all climate regimes. We also developed a new storminess tracking algorithm that, in addition to tracking a storm's central pressure, delineates the area of influence of the storm. The focus of the proposed work will be to utilize those techniques in order to map the relationships between storm properties and the structure of the cloud and radiation fields. The analysis will utilize cloud clusters as the determinants of cloud type and will examine the variability of the types and their radiative signatures with changing dynamic conditions. This analysis will be applied to both observations and current-climate runs of the GISS and GMAO climate models in order to evaluate model skill in simulating the observed relationships. The evaluation results will address quantitatively model sensitivity uncertainties as they relate to the variability of the midlatitude storm track and of the zonal extent of the Hadley circulation. Our work will produce observational constrains related initially to the distribution of the observed cloud clusters and then to the relation of the cluster distribution to the atmospheric dynamics. Those observational constrains will take the form of quantitative metrics as well as graphical representations and will be made available to all MAP researchers through the efficient structures of the GMAO evaluation portal.

ORepresenting cloud-radiation-dynamical interactions in GCMs remains a pressing challenge to producing high-fidelity global Earth System models, including accurate representations of weather, climate variability, and climate and Earth System changes. Addressing this challenge requires a number of key ingredients: 1) the availability of a wide-range of observations that constrain critical processes and that sample the relevant range of environmental conditions and variability, 2) the development of physically-based model components and sub-grid scale parameterizations associated with clouds, convection and radiation, and many other processes, and 3) a framework for the judicious application of observations to model/parameterization development and evaluation. The latter provides the pathways to not only improve the models but also inform the development and selections of the next generation of high-priority observations needed as the models are refined and gain new complexity. Our proposal addresses these ingredients via three related objectives, with each one successively expanding the scope for building and exploiting bridges between models and observations, and contributing to improved global models.

The first objective continues our present line of advancement on the judicious application of satellite observations for characterizing, understanding and improving cloud-radiation-dynamic interactions and their representation in global models. Specifically, we will continue to characterize systematic model biases in the 3D structure of atmospheric liquid and ice, including their partition into cloud vs precipitating and convective-cloud hydrometeors, and the exploration and application of diagnostics for evaluating cloud microphysical schemes. We will expand our efforts to diagnose the systematic biases we have identified in model radiation budgets, with the aim of understanding the role that precipitating hydrometeors play in these biases. Finally, we will build on this line of research by exploring whether/how these systematic biases in radiation impact atmospheric dynamics. Specifically, we will characterize the systematic biases in the large-scale atmospheric circulation, and use sensitivity/idealized experiments to determine their attribution to the biases in radiative heating. As in the past, within the context of these research questions, we will be pay close attention to, and provide feedback on, the development and evaluation of GEOS, GISS and GSFC-MMF, with CMIP5 and other models/experiments providing a broader backdrop.

The second objective expands the scope of the above research by putting it in the context of a broad community effort associated with a multi-institute and multi-model physics and prediction experiment sponsored by the WCRP-WWRP/THORPEX MJO Task Force and the GEWEX Atmospheric System Study that the PI is helping organize. This will leverage the scientific effort of a broad range of scientists, model developers and model physics studies related to cloud-radiation-dynamical interactions. The detailed experimental task plan allows for a robust examination of the vertical profiles of cloud structure, thermodynamics, radiation and dynamics via detailed process-level model output (i.e. all tendency terms) for climatological simulations and initialized hindcast experiments performed during the Year of Tropical Convection (YOTC) activity.

The third objective builds on the above sorts of activities as well as leverages a number of key international efforts and climate modeling programmatic activities such as "obs4MIPs", the Working Group on Numerical Experimentation (WGNE) and Working Group on Coupled Modeling (WGCM) to help foster the means for the modeling community, particularly NASA’s MAP Science Team, to provide explicit input to the 2017 NRC Decadal Survey on high priority needs for new satellite measurements to improve model representation of cloud-radiation-dynamical interactions.

Climate models and reanalyses have not yet successfully reproduced cloud, precipitation, and associated heating processes. This raises the question of how well the cloud microphysics and cumulus parameterizations in climate models represent clouds and moist thermodynamics in the real world. We propose to quantify the relationships among cloud properties, atmospheric water and energy budgets, and large-scale atmospheric conditions from satellite-based retrievals/estimates, and use the observed relationships to diagnose the origins of biases of the Modern Era Retrospective analysis for Research and Applications (MERRA) and the Goddard Institute for Space Studies General Circulation Model E2 (GISS Model E2) in simulating moist thermodynamic processes.

Cloud microphysics and cumulus convection modules parameterize sub-grid scale processes and simplify detailed relationships between these processes and the large-scale atmospheric conditions. Traditional methods of model evaluation use gridded climate variables averaged on monthly timescale. This can mask detailed information about the relationships between the sub-grid scale processes, which occur at timescale shorter than a month, and the large-scale atmospheric conditions. Important information about such relationships can be accurately extracted from regionally and temporally dependent multi-dimensional probability distribution functions that are constructed by simultaneously sampling relevant cloud and thermodynamic variables. Recently developed satellite-based retrievals of clouds and estimates of precipitation and heating rate profiles provide an ideal resource for model evaluation over a wide range of environmental conditions.

We will perform the following tasks:

  • Quantify and summarize the relationships between cloud states, atmospheric water and energy budgets, and large-scale atmospheric conditions using NASA satellite-based measurements
  • Identify the origins of biases in cloud and moist thermodynamic processes in MERRA and the GISS Model E2
  • Investigate the transition from shallow to deep convection and the climate regime of light precipitation in MERRA and the GISS Model E2
  • Provide observational constraints for the development of cloud microphysics and cumulus parameterization in the GISS Model E2
  • Process-oriented evaluation of the cloud-dependent atmospheric water and energy budgets associated with climate variations from intraseasonal to interannual timescales in MERRA

The proposed analyses move beyond the current state of evaluation that uses simple correlations with monthly mean averaged data. The results will be a significant stepping stone towards the goals of the MAP priorities: (1) characterize uncertainties in the models and products, (2) address the ESD research questions of how the earth system is changing and what the sources of change are in the Earth system and their magnitudes and trends, (3) reach the goals and objectives of the core MAP elements by maximizing satellite data utility and serving as a centralized resource for testing and validating as wide a range of modeling and observational efforts as possible. Finally, the multi-dimensional joint PDFs and the cloud-dependent atmospheric water and energy budgets will be available for public access to enable independent community validation and characterization of the core MAP elements leading to improvement of the models or products.

Large uncertainty of aerosol indirect forcing translates into uncertainty in projections of future climate change as shown by theoretical and modeling studies. As the model physics becoming more advanced and sophisticated the need of observationally constraining and evaluating model parameterization emerges and becomes increasingly acute. Progress in constraining model aerosol indirect effect has been slow due to a combination of difficulties, including the lack of observed aerosol-cloud interactions at large-scale and long-temporal scale; the challenge of separating meteorological and aerosol impacts from observations; and the cloud regime dependence of aerosol effects.

Recently, a long-term Hawaiian volcanic degassing event offers an ideal natural experiment to overcome these difficulties in a trade cumulus cloud regime, one of the most prevalent cloud types, whose properties are highly sensitive to aerosols. Customized physics packages for aerosol-cloud interactions have also been successfully developed for NASA models, NU-WRF and GEOS-5. Taking advantage of these developments, we propose to critically evaluate and constrain modeled aerosol indirect effects using models with different complexities and extensive NASA data sets. The novelty of our work includes:

  1. Fully characterize the gas, aerosol, cloud, precipitation and radiation fields observationally with NASA satellites and complementary in-situ aircraft data sets and prepare them for regional (NU-WRF) and global (GEOS-5) model to use.
  2. Derive a suite of metrics and key parameters based on observations for model evaluation and constraining purposes.
  3. Characterize sensitivity of models results to resolution, parameterization scheme, model complexity and key parameters for both NU-WRF and GEOS-5. Take full advantage of the contrasting model complexity and use NU-WRF with similar physics package to inform and improve GEOS-5 simulations.
  4. Evaluate and constrain modeled aerosol-cloud interactions with observational metrics and key parameters (e.g. regarding entrainment and autoconversion). Iterate the process to improve model performance with single column GEOS-5, regional (NU-WRF) and full GCM models.
  5. Determine the regional impact and global magnitude of aerosol indirect forcing within the trade cumulus regime with the observationally calibrated GEOS-5. Assess the potential of a geoengineering strategy within trade cumulus clouds.

Our investigation targets a specific cloud regime to constrain aerosol indirect effects modeling in GEOS-5 as well as NU-WRF with extensive observational anchor. This activity will improve aerosol indirect effect parameterization and put GEOS-5 and NU-WRF among the best evaluated and constrained models. Applications of the improved models will provide a fresh look at the historical impact and possible mitigating effect of aerosol indirect forcing within the trade cumulus regime. We also expect that the broader modeling community will greatly benefit from the outcome of these studies.

Modern Era Retrospective-analysis for Research and Applications (MERRA) is a NASA reanalysis developed under the MAP Program, and it represents an important GSFC/GMAO contribution towards the international reanalysis efforts. MERRA offers both hourly two-dimensional fields and 3-hourly three-dimensional atmospheric variables and their tendencies. It also includes the Incremental Analysis Update, the 'replay' capability, the observations assimilated and the associated forecast error and analysis error.

Our current MAP project has yielded 11 peer-reviewed publications, 3 submitted manuscripts, several manuscripts in preparation, 8 invited and 13 contributed presentations (from July 2009 to May 2012). Building on these accomplishments and using the unique capabilities of MERRA (including its land-only reprocessing and updated short-term reanalysis), our overall goal is to improve the understanding and parameterization of land-atmosphere-ocean interface processes by integrating the MERRA reanalysis with satellite, surface, and aircraft data. Four research questions will be addressed: (a) how realistic is the terrestrial energy and hydrological cycle of the MERRA? (b) how do the near-surface atmospheric fields affect global energy and water cycle, dynamic vegetation and carbon cycle? (c) what is the diurnal cycle of summertime land-atmospheric boundary layer-convection coupling? and (d) what are the diurnal and seasonal cycles of the ocean surface-stratocumulus interactions?

Six specific tasks will be carried out: (1) measurements of near-surface atmospheric fields and land surface fluxes will be combined with soil moisture, stremflow, and snow measurements to evaluate various reanalysis products; (2) MERRA and GEOS5 land surface skin temperature will be evaluated and improved; (3) global hourly near-surface atmospheric fields will be developed by adjusting reanalysis products with in situ and satellite measurements; (4) their impact on land surface energy, water, and carbon cycle and dynamic vegetation will be assessed; (5) land-atmospheric boundary layer-convection interaction over the U.S. Great Plains in summer will be evaluated; and (6) marine stratocumulus-aerosols-radiation-precipitation interaction will also be studied. For the last two tasks, detailed budget analysis will be emphasized.

The proposed work will directly address two NASA Earth Science Key Questions: How is the Earth system changing? and What are the sources of change in the Earth system and their magnitudes and trends? Our investigations using MERRA data represent one of the specific themes of the MAP solicitation. Our evaluation and improvement of the GEOS5 model (as used in MERRA) will directly contribute to the mission of GMAO - a core MAP project. Our use of satellite, surface, and aircraft data is also emphasized by the MAP program. The planned GMAO visit of the PI and students will accelerate the transition of our research results (including model improvements) to MERRA and GEOS5.