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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS1995

Low-frequency variability and wavenumber selection in models with zonally symmetric forcing

The authors consider a two-layer quasigeostrophic model with linear surface drag and forcing that relaxes to a zonal baroclinically unstable equilibrium state consisting of a meridionally confined temperature gradient. It is observed that the most energetic wave in the time-mean climate has near zero frequency and is not driven by upscale nonlinear energy transfers. This wave has a zonal scale near the long-wave cutoff of the equilibrium state, and its energy balance is mainly between baroclinic generation and dissipation. This maintenance mechanism is different from that suggested by beta-plane, two-dimensional, and quasigeostrophic turbulence arguments and may be relevant to the dynamics of zonally asymmetric low-frequency variability in the atmosphere, particularly in the Southern Hemisphere.

Whitaker, Jeffrey S.↗
NASA NTRSDate not supplied

Evaluation of Spectral Band Adjustment Factors for Cross-Calibration of Visible Imagers

The CERES EBAF dataset provides TOA SW and LW fluxes for long-term monitoring of the Earth’s energy balance and to validate climate models. The EBAF products, based on the Terra and Aqua CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS imagers to determine cloud properties that are used in the angular distribution model scene selection required to convert the CERES observed radiances into flux values. Once the Terra and Aqua orbits start drifting outside of their 15-minute window, the CERES project will rely solely on the NOAA-20 CERES observations. A seamless transition of fluxes and clouds can only occur if the analogous MODIS and VIIRS channels are properly inter-calibrated. The visible band (0.65 µm) in MODIS (band 1) and VIIRS (M5 or I1) is critical for retrieving the cloud mask and optical depth. The spectral response functions (SRF) of these bands differ noticeably and will require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Fortunately, the VIIRS I1 and M5 bands are calibrated using the same solar diffuser as a reference, which implies that band reflectance differences must be due to the spectral disparity. The coincident I1 and M5 TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, Hyperion, and radiative transfer model-based scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study will evaluate the SCIAMACHY, GOME-2, Hyperion, and RTM based SBAFs over tropical ocean targets used in SNO inter-calibration of MODIS and VIIRS, including clear-sky ocean, deep convective clouds (DCC), and liquid cloud targets in terms of their applicability to absolute intercomparison of visible imagers. The large SCIAMACHY and GOME-2 footprints and the lack of Hyperion cloudy scenes will impact the resulting SBAFs and necessitates the need for future CLARREO hyper-spectral reflectances to decrease SBAF uncertainties Preliminary results indicate that the SCIAMACHY and GOME-2 based SBAFs for the VIIRS I1 and M5 band pairs may differ by 1.5% for some ATO scene types. Because most of the modern GEOs visible band SRFs encompass the VIIRS I1 band SRF, these evaluations are critical to ensure that the MODIS, VIIRS, and GEO clouds and fluxes are consistent. SBAFs for Libya-4, Dome-C and other Earth invariant target will also be evaluated.

D. R. Doelling↗
NASA NTRSDate not supplied

Evaluation of Spectral Band Adjustment Factors for Cross-Calibration of Visible Imagers

The NASA CERES EBAF dataset provides TOA SW and LW fluxes for long-term monitoring of the Earth’s energy balance and to validate climate models. The EBAF products, based on the Terra, Aqua, and NOAA20 CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS or VIIRS imagers to determine cloud properties used for angular distribution model scene selection, which is required to convert the CERES observed radiances into flux values. Furthermore, CERES utilizes geostationary imager (GEO) hourly fluxes and clouds to infer the regional averaged daily flux in the SYN1deg product. A seamless transition of fluxes and clouds can only occur if the analogous MODIS, VIIRS, and GEO channels are properly inter-calibrated. The analogous band SRFs differ noticeably and require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Given their disparate but overlapping SRFs, the coincident VIIRS I1 and M5 band TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, and Hyperion scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study highlights the SCIAMACHY, GOME-2, and Hyperion based SBAFs for different MODIS, VIIRS, and GEO inter-calibration targets, including all-sky tropical ocean (ATO), Libya-4, Dome-C, and deep convective clouds. To mitigate the observed sensor radiance fluctuations due to atmospheric absorption and aerosol variations, the Earth target observed radiances are correlated with multiple atmospheric parameters, such as precipitable water and ozone. The remaining M5 and I1 mean spectral band radiance difference should be resolved by the SBAF correction. The formulation of hyper-spectral sensor based SBAFs and validation methods can be verified in future utilizing high-accuracy, SI-traceable hyper-spectral measurements from CLARREO Pathfinder.

David R Doelling↗
NASA NTRS2012

Global Air Quality and Health Co-benefits of Mitigating Near-term Climate Change Through Methane and Black Carbon Emission Controls

Tropospheric ozone and black carbon (BC), a component of fine particulate matter (PM < or = 2.5 microns in aerodynamic diameter; PM2.5), are associated with premature mortality and they disrupt global and regional climate. Objectives: We examined the air quality and health benefits of 14 specific emission control measures targeting BC and methane, an ozone precursor, that were selected because of their potential to reduce the rate of climate change over the next 20-40 years. Methods: We simulated the impacts of mitigation measures on outdoor concentrations of PM2.5 and ozone using two composition-climate models, and calculated associated changes in premature PM2.5‑ and ozone-related deaths using epidemiologically derived concentration-response functions. Results: We estimated that, for PM2.5 and ozone, respectively, fully implementing these measures could reduce global population-weighted average surface concentrations by 23-34% and 7-17% and avoid 0.6-4.4 and 0.04-0.52 million annual premature deaths globally in 2030. More than 80% of the health benefits are estimated to occur in Asia. We estimated that BC mitigation measures would achieve approximately 98% of the deaths that would be avoided if all BC and methane mitigation measures were implemented, due to reduced BC and associated reductions of nonmethane ozone precursor and organic carbon emissions as well as stronger mortality relationships for PM2.5 relative to ozone. Although subject to large uncertainty, these estimates and conclusions are not strongly dependent on assumptions for the concentration-response function. Conclusions: In addition to climate benefits, our findings indicate that the methane and BC emission control measures would have substantial co-benefits for air quality and public health worldwide, potentially reversing trends of increasing air pollution concentrations and mortality in Africa and South, West, and Central Asia. These projected benefits are independent of carbon dioxide mitigation measures. Benefits of BC measures are underestimated because we did not account for benefits from reduced indoor exposures and because outdoor exposure estimates were limited by model spatial resolution.

air quality↗
NASA NTRS2021

Future Sea Level Change Under CMIP5 and CMIP6 Scenarios From the Greenland and Antarctic Ice Sheets

Projections of the sea level contribution from the Greenland and Antarctic ice sheets (GrIS and AIS) rely on atmospheric and oceanic drivers obtained from climate models. The Earth System Models participating in the Coupled Model Intercomparison Project phase 6 (CMIP6) generally project greater future warming compared with the previous Coupled Model Intercomparison Project phase 5 (CMIP5) effort. Here we use four CMIP6 models and a selection of CMIP5 models to force multiple ice sheet models as part of the Ice Sheet Model Intercomparison Project for CMIP6 (ISMIP6). We find that the projected sea level contribution at 2100 from the ice sheet model ensemble under the CMIP6 scenarios falls within the CMIP5 range for the Antarctic ice sheet but is significantly increased for Greenland. Warmer atmosphere in CMIP6 models results in higher Greenland mass loss due to surface melt. For Antarctica, CMIP6 forcing is similar to CMIP5 and mass gain from increased snowfall counteracts increased loss due to ocean warming.

Antarctica↗
NASA NTRS2023

Investigating the Response of Land-Atmosphere Interactions and Feedbacks to Spatial Representation of Irrigation in a Coupled Modeling Framework

The transport of water, heat, and momentum from the surface to the atmosphere is dependent in part on the 10 characteristics of the land surface. Together with the model physics, parameterization schemes, and parameters employed, land datasets determine the spatial variability in land surface states (i.e., soil moisture and temperature) and fluxes. Despite the importance of these datasets, they are often chosen out of convenience or regional limitations without due assessment of their impacts on model results. Irrigation is an anthropogenic form of land heterogeneity that has been shown to alter the land surface energy balance, ambient weather, and local circulations. As such, irrigation schemes are becoming more 15 prevalent in weather and climate models with rapid developments in dataset availability and parameterization scheme complexity. Thus, to address pragmatic issues related to modeling irrigation, this study uses a high-resolution, regional coupled modeling system to investigate the impacts of irrigation dataset selection on land-atmosphere (L-A) coupling using a case study from the Great Plains Irrigation Experiment (GRAINEX) field campaign. The simulations are assessed in the context of irrigated versus non-irrigated regions, subregions across the irrigation gradient, and sub-grid scale process 20 representation in coarser scale models. The results show that L-A coupling is sensitive to the choice of irrigation dataset and resolution and that the irrigation impact on surface fluxes and near surface meteorology can be dominant, conditioned on the details of the irrigation map (i.e., boundaries, heterogeneity, etc), or minimal. A consistent finding across several analyses was that even a low percentage of irrigation fraction (i.e., 4-16%) can have significant local and downstream atmospheric impacts (e.g., lower PBL height), suggesting that representation of boundaries and heterogeneous areas within irrigated 25 regions is particularly important for the modeling of irrigation impacts on the atmosphere in this model. When viewing the simulations presented here as a proxy for ‘ideal’ tiling in a Earth System Model scale gridbox, the results show that some ‘tiles’ will reach critical nonlinear moisture and planetary boundary layer (PBL) thresholds that could be important for clouds and convection, implying that heterogeneity resulting from irrigation should be taken into consideration in new sub-grid land-atmosphere exchange parameterizations.

Patricia Lawston-Parker↗
NASA NTRS1999

Selecting Meteorological Input for the Global Modeling Initiative Assessments

The Global Modeling Initiative (GMI) science team has developed a three dimensional chemistry and transport model (CTM) to evaluate the impact of the exhaust of supersonic aircraft on the stratosphere. An important goal of the GMI is to test modules for numerical transport, photochemical integration, and model dynamics within a common framework. This work is focussed on the dependence of the overall assessment on the wind and temperature fields used by the CTM. Three meteorological data sets for the stratosphere were available to GMI: the National Center for Atmospheric Research Community Climate Model (CCM2), the Goddard Earth Observing System Data Assimilation System (GEOS-DAS), and the Goddard Institute for Space Studies general circulation model (GISS-2'). Objective criteria were established by the GMI team to evaluate which of these three data sets provided the best representation of trace gases in the stratosphere today. Tracer experiments were devised to test various aspects of model transport. Stratospheric measurements of long-lived trace gases were selected as a test of the CTM transport. This presentation describes the criteria used in grading the meteorological fields and the resulting choice of wind fields to be used in the GMI assessment. This type of objective model evaluation will lead to a higher level of confidence in these assessments. We suggest that the diagnostic tests shown here be used to augment traditional general circulation model evaluation methods.

Strahan, Susan↗
NASA NTRS1994

A proposal for the intercomparison of the dynamical cores of atmospheric general circulation models

A benchmark calculation is proposed for evaluating the dynamical cores of atmospheric general circulation models (GCMs) independently of the physical parameterizations. The test focuses on the long-term statistical properties of a fully developed general circulation; thus, it is particularly appropriate for intercomparing the dynamics used in climate models. To illustrate the use of this benchmark, two very different atmospheric dynamical cores--one spectral, one finite difference--are compared. It is found that the long-term statistics produced by the two models are very similar. Selected results from these calculations are presented to initiate the intercomparison.

Held, Isaac M.↗
NASA NTRS2017

Modelling the Passive Microwave Signature from Land Surfaces: A Review of Recent Results and Application to the L-Band SMOS SMAP Soil Moisture Retrieval Algorithms

Two passive microwave missions are currently operating at L-band to monitor surface soil moisture (SM) over continental surfaces. The SMOS sensor, based on an innovative interferometric technology enabling multi-angular signatures of surfaces to be measured, was launched in November 2009. The SMAP sensor, based on a large mesh reflector 6 m in diameter providing a conically scanning antenna beam with a surface incidence angle of 40deg, was launched in January of 2015. Over the last decade, an intense scientific activity has focused on the development of the SM retrieval algorithms for the two missions. This activity has relied on many field (mainly tower-based) and airborne experimental campaigns, and since 2010-2011, on the SMOS and Aquarius space-borne L-band observations. It has relied too on the use of numerical, physical and semi-empirical models to simulate the microwave brightness temperature of natural scenes for a variety of scenarios in terms of system configurations (polarization, incidence angle) and soil, vegetation and climate conditions. Key components of the inversion models have been evaluated and new parameterizations of the effects of the surface temperature, soil roughness, soil permittivity, and vegetation extinction and scattering have been developed. Among others, global maps of select radiative transfer parameters have been estimated very recently. Based on this intense activity, improvements of the SMOS and SMAP SM inversion algorithms have been proposed. Some of them have already been implemented, whereas others are currently being investigated. In this paper, we present a review of the significant progress which has been made over the last decade in this field of research with a focus on L-band, and a discussion on possible applications to the SMOS and SMAP soil moisture retrieval approaches.

SMOS↗
NASA NTRS2021

Optimized MODIS Channel Selection to Improve the NASA CERES FluxByCloudType Product Fluxes

The NASA Clouds and the Earth’s Radiant Energy System (CERES) project has provided the climate community more than a 20-year record of top of the atmosphere (TOA) reflected shortwave (SW) and emitted longwave (LW) fluxes. The fluxes used to monitor the Earth’s energy balance as well as for climate model validation and cloud feedback studies. One of the largest uncertainties in climate models is the response of clouds in feedback studies. To reduce this uncertainty requires more stringently validation of model generated fluxes by cloud-type. Rather than relying on radiative transfer model generated fluxes from observed cloud-type retrievals, the CERES FluxByCloudType (FBCT) product, relies on MODIS empirical narrowband to broadband relationships to convert the cloudy portions of the CERES footprints into fluxes. The overcast footprint and sub-footprint cloud layer fluxes are then stratified by 7 pressure layers and 6 optical depth bins and temporally averaged into daily and monthly regional cloud-type fluxes. The CERES project analyzed a total of 19 MODIS channels for use in the next generation FBCT product narrowband to broadband conversion. This was accomplished by comparing the narrowband to broadband RMS errors from all possible 5-channel combinations. The SW and LW optimized channels were selected by also considering analogous geostationary, MODIS and VIIRS imager channels as well as channel combinations that provided the lowest RMS errors across all surface types. The optimized channel combinations will be tested in the FBCT algorithm to investigate any cloud fraction, effective pressure, optical depth, PW, solar and view angle, surface type and regional narrowband to broadband dependencies.

CERES↗
NASA NTRS2011

An Update on Experimental Climate Prediction and Analysis Products Being Developed at NASA's Global Modeling and Assimilation Office

The Global Modeling and Assimilation Office at NASA's Goddard Space Flight Center is developing a number of experimental prediction and analysis products suitable for research and applications. The prediction products include a large suite of subseasonal and seasonal hindcasts and forecasts (as a contribution to the US National MME), a suite of decadal (10-year) hindcasts (as a contribution to the IPCC decadal prediction project), and a series of large ensemble and high resolution simulations of selected extreme events, including the 2010 Russian and 2011 US heat waves. The analysis products include an experimental atlas of climate (in particular drought) and weather extremes. This talk will provide an update on those activities, and discuss recent efforts by WCRP to leverage off these and similar efforts at other institutions throughout the world to develop an experimental global drought early warning system.

Schubert, Siegfried↗
NASA NTRS2002

Sensitivity of Lower Stratospheric Assimilated Ozone on Error Covariance Modeling and Data Selection

Assimilated ozone is produced at the NASA/Goddard Data Assimilation Office by blending ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line transport model. The current system tends to overestimate the amount of lower stratospheric ozone. This is a region where ozone plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. Since these are all important applications of assimilated ozone products, effort is being directed towards reducing this bias. The SBUV ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone in the lower stratosphere, and its vertical distribution in particular, are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Accordingly, the sensitivity of the assimilated lower stratospheric ozone fields to changes in the TOMS error-covariance modeling and the SBUV data selection has been investigated. The use of a spatially correlated TOMS error covariance model led to improvements in the product. However, withholding the SBUV/2 data for the layer between 63 and 126 hPa typically degraded the product, a result which vindicates the use of this layer ozone product, despite its known errors. These efforts to improve the lower stratospheric distribution will be extended to include a more advanced forecast error covariance model, and by assimilating ozone products from new instruments on Envisat and EOS Aura.

Stajner, Ivanka↗
NASA NTRS2022

Implementation and Evaluation of Irrigation Techniques in the Community Land Model

Several previous studies have highlighted the irrigation-induced impacts on the global and regional water cycle, energy budget, and near-surface climate. While land models are widely used to address this question, the implementations of irrigation in these models vary in complexity. Here, we expand the representation of irrigation in Community Land Model to enable six different irrigation methods. We find that using a combination of irrigation methods, including default, sprinkler, flood and paddy techniques performs best as determined by evaluating the simulated irrigation water withdrawals against observations, and therefore select this combination as the new irrigation scheme. Then, the impact of the new irrigation scheme on surface fluxes is evaluated and detected using single-point simulations. Finally, the global and regional irrigation-induced impacts on surface energy and water fluxes are compared using both the original and the new irrigation scheme. The new irrigation scheme substantially reduces the bias and root-mean-square error of simulated irrigation water withdrawal in the USA and other countries, but considerably overestimates withdrawals in Central China. Results of single-point experiments show that different irrigation methods have different effects on surface fluxes, while the magnitudes are small. At the global scale, the new scheme enlarges the irrigation-induced impacts on water and energy variables relative to the original scheme, with varying magnitudes across regions. Overall, our results suggest that this newly developed scheme is a better tool for simulating irrigation-induced impacts on climate, and highlight the added value of incorporating human water management in Earth system models.

Community land models↗
NASA NTRSDate not supplied

The NASA Ames Mars Global Climate Model: Benchmarking Publicly Released Source Code and Model Output

We have recently publicly released source code from the new NASA Ames Mars Global Climate Model (MGCM), which is based on NOAA/GFDL cubed-sphere finite volume (FV3-based) dynamical core (https://github.com/nasa/AmesGCM). We also we have a manuscript in preparation that aims to document the status of the new MGCM, and present selected simulations generated from it with interpretations and comparisons to both observations and the Ames Legacy MGCM. Output from our reference simulation will be made publicly available as well. One of our ongoing goals is to understand the underlying causes for differences between results produced with the new FV3-based dynamical core compared to the Legacy C-grid dynamical core. While the thermal and dynamical fields predicted with the new and Legacy GCMs are broadly similar for much of the year, there are key differences at low resolution when no external drag is applied to the new MGCM. This is particularly clear during a seasonal window of ~100 degrees of Ls surrounding southern summer solstice, when the predicted northern hemisphere polar warming is significantly over-predicted in the new MGCM. When we apply Rayleigh drag throughout much of the tropics and sub-tropics to the new MGCM, the simulated zonal mean structure of the atmosphere is much more consistent with both MCS observations and Legacy MGCM simulations. We note that the Kling et al. (2023; this meeting) study demonstrates that the behavior that we see with Rayleigh drag here can be recovered with high resolution simulations (in the horizontal and in the vertical) or with parameterized orographic and non-orographic gravity waves at lower resolution. While this work is still in progress, our preliminary conclusion is that the new dynamical core is less dissipative than the Legacy dynamical core. At low to moderate resolution, users of the new MGCM will need to be careful to use some sort of external drag, either in the form of gravity wave drag parameterizations or the simpler Rayleigh drag.

Melinda April Kahre↗
NASA NTRS2012

Human Settlements in the South-Central U.S., Viewed at Night from the International Space Station

A recent innovation of astronauts observing Earth from the International Space Station (ISS) is documenting human footprints by photographing city lights at night time. One of the earliest night-time images from the ISS was the US-Mexico border at El Paso-Ciudad Juarez. The colors, patterns and density of city lights document the differences in the cultural settlement patterns across the border region, as well as within the urban areas themselves. City lights help outline the most populated areas in settlements around the world, and can be used to explore relative population densities, changing patterns of urban/suburban development, transportation networks, spatial relationship to geographic features, and more. The data also provides insight into parameters such as surface roughness for input into local and regional climate modeling and studies of light pollution. The ground resolution of night-time astronaut photography from the ISS is typically an order of magnitude greater than current Defense Meteorological Satellite Program (DMSP) data, and therefore can serve as a "zoom lens" for selected urban areas. Current handheld digital cameras in use on the ISS, optimized for greater light sensitivity, provide opportunities to obtain new detailed imagery of atmospheric phenomena such as airglow, aurora, and noctilucent clouds in addition to documenting urban patterns. ISS astronauts have taken advantage of increasingly sensitive digital cameras to document the world at night in unprecedented detail. In addition, the capability to obtain time-lapse imagery from fixed cameras has been exploited to produce dynamic videos of both changing surface patterns around the world and atmospheric phenomena. We will profile some spectacular images of human settlements over the South-Central U.S., and contrast with other images from around the world. More data can be viewed at http://eol.jsc.nasa.gov/Videos/CrewEarthObservationsVideos/. US-Mexico border is obvious by the different lighting pattern. Not surprisingly, the densely illuminated city of Juarez indicates a higher population; El Paso's smaller population is spread out over a larger area.

Dawson, Melissa↗
NASA NTRS2013

Daily MODIS 500 m Reflectance Anisotropy Direct Broadcast (DB) Products for Monitoring Vegetation Phenology Dynamics

Land surface vegetation phenology is an efficient bio-indicator for monitoring ecosystem variation in response to changes in climatic factors. The primary objective of the current article is to examine the utility of the daily MODIS 500 m reflectance anisotropy direct broadcast (DB) product for monitoring the evolution of vegetation phenological trends over selected crop, orchard, and forest regions. Although numerous model-fitted satellite data have been widely used to assess the spatio-temporal distribution of land surface phenological patterns to understand phenological process and phenomena, current efforts to investigate the details of phenological trends, especially for natural phenological variations that occur on short time scales, are less well served by remote sensing challenges and lack of anisotropy correction in satellite data sources. The daily MODIS 500 m reflectance anisotropy product is employed to retrieve daily vegetation indices (VI) of a 1 year period for an almond orchard in California and for a winter wheat field in northeast China, as well as a 2 year period for a deciduous forest region in New Hampshire, USA. Compared with the ground records from these regions, the VI trajectories derived from the cloud-free and atmospherically corrected MODIS Nadir BRDF (bidirectional reflectance distribution function) adjusted reflectance (NBAR) capture not only the detailed footprint and principal attributes of the phenological events (such as flowering and blooming) but also the substantial inter-annual variability. This study demonstrates the utility of the daily 500 m MODIS reflectance anisotropy DB product to provide daily VI for monitoring and detecting changes of the natural vegetation phenology as exemplified by study regions comprising winter wheat, almond trees, and deciduous forest.

Vegetation↗
NASA NTRS2014

Independent Verification of Mars-GRAM 2010 with Mars Climate Sounder Data

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission and engineering applications. Applications of Mars-GRAM include systems design, performance analysis, and operations planning for aerobraking, entry, descent and landing, and aerocapture. Atmospheric influences on landing site selection and long-term mission conceptualization and development can also be addressed utilizing Mars-GRAM. Mars-GRAM's perturbation modeling capability is commonly used, in a Monte Carlo mode, to perform high-fidelity engineering end-to-end simulations for entry, descent, and landing. Mars-GRAM is an evolving software package resulting in improved accuracy and additional features. Mars-GRAM 2005 has been validated against Radio Science data, and both nadir and limb data from the Thermal Emission Spectrometer (TES). From the surface to 80 km altitude, Mars-GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). Above 80 km, Mars-GRAM is based on the University of Michigan Mars Thermospheric General Circulation Model (MTGCM). The most recent release of Mars-GRAM 2010 includes an update to Fortran 90/95 and the addition of adjustment factors. These adjustment factors are applied to the input data from the MGCM and the MTGCM for the mapping year 0 user-controlled dust case. The adjustment factors are expressed as a function of height (z), latitude and areocentric solar longitude (Ls).

Justh, Hilary L.↗
NASA NTRS2011

Simultaneous Retrieval of Aerosol and Cloud Properties During the MILAGRO Field Campaign

Estimation of Direct Climate Forcing (DCF) due to aerosols in cloudy areas has historically been a difficult task, mainly because of a lack of appropriate measurements. Recently, passive remote sensing instruments have been developed that have the potential to retrieve both cloud and aerosol properties using polarimetric, multiple view angle, and multi spectral observations, and therefore determine DCF from aerosols above clouds. One such instrument is the Research Scanning Polarimeter (RSP), an airborne prototype of a sensor on the NASA Glory satellite, which unfortunately failed to reach orbit during its launch in March of 2011. In the spring of 2006, the RSP was deployed on an aircraft based in Veracruz, Mexico, as part of the Megacity Initiative: Local and Global Research Observations (MILAGRO) field campaign. On 13 March, the RSP over flew an aerosol layer lofted above a low altitude marine stratocumulus cloud close to shore in the Gulf of Mexico. We investigate the feasibility of retrieving aerosol properties over clouds using these data. Our approach is to first determine cloud droplet size distribution using the angular location of the cloud bow and other features in the polarized reflectance. The selected cloud was then used in a multiple scattering radiative transfer model optimization to determine the aerosol optical properties and fine tune the cloud size distribution. In this scene, we were able to retrieve aerosol optical depth, the fine mode aerosol size distribution parameters and the cloud droplet size distribution parameters to a degree of accuracy required for climate modeling. This required assumptions about the aerosol vertical distribution and the optical properties of the coarse aerosol size mode. A sensitivity study was also performed to place this study in the context of future systematic scanning polarimeter observations, which found that the aerosol complex refractive index can also be observed accurately if the aerosol optical depth is larger than roughly 0.8 at a wavelength of (0.555 m).

Knobelspiesse, K.↗