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NASA NTRS2010

MAPIR: An Airborne Polarmetric Imaging Radiometer in Support of Hydrologic Satellite Observations

In this age of dwindling water resources and increasing demands, accurate estimation of water balance components at every scale is more critical to end users than ever before. Several near-term Earth science satellite missions are aimed at global hydrologic observations. The Marshall Airborne Polarimetric Imaging Radiometer (MAPIR) is a dual beam, dual angle polarimetric, scanning L band passive microwave radiometer system developed by the Observing Microwave Emissions for Geophysical Applications (OMEGA) team at MSFC to support algorithm development and validation efforts in support of these missions. MAPIR observes naturally-emitted radiation from the ground primarily for remote sensing of land surface brightness temperature from which we can retrieve soil moisture and possibly surface or water temperature and ocean salinity. MAPIR has achieved Technical Readiness Level 6 with flight heritage on two very different aircraft, the NASA P-3B, and a Piper Navajo.

Laymon, C.↗
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 NTRS2000

EOS Terra Validation Program

The EOS Terra mission will be launched in July 1999. This mission has great relevance to the atmospheric radiation community and global change issues. Terra instruments include Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Clouds and Earth's Radiant Energy System (CERES), Multi-Angle Imaging Spectroradiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS) and Measurements of Pollution in the Troposphere (MOPITT). In addition to the fundamental radiance data sets, numerous global science data products will be generated, including various Earth radiation budget, cloud and aerosol parameters, as well as land surface, terrestrial ecology, ocean color, and atmospheric chemistry parameters. Significant investments have been made in on-board calibration to ensure the quality of the radiance observations. A key component of the Terra mission is the validation of the science data products. This is essential for a mission focused on global change issues and the underlying processes. The Terra algorithms have been subject to extensive pre-launch testing with field data whenever possible. Intensive efforts will be made to validate the Terra data products after launch. These include validation of instrument calibration (vicarious calibration) experiments, instrument and cross-platform comparisons, routine collection of high quality correlative data from ground-based networks, such as AERONET, and intensive sites, such as the SGP ARM site, as well as a variety field experiments, cruises, etc. Airborne simulator instruments have been developed for the field experiment and underflight activities including the MODIS Airborne Simulator (MAS) AirMISR, MASTER (MODIS-ASTER), and MOPITT-A. All are integrated on the NASA ER-2 though low altitude platforms are more typically used for MASTER. MATR is an additional sensor used for MOPITT algorithm development and validation. The intensive validation activities planned for the first year of the Terra mission will be described with emphasis on derived geophysical parameters of most relevance to the atmospheric radiation community.

Starr, David↗
NASA NTRS2006

Evaluation of Space-Based Constraints on Global Nitrogen Oxide Emissions with Regional Aircraft Measurements over and Downwind of Eastern North America

We retrieve tropospheric nitrogen dioxide (NO 2) columns for May 2004 to April 2005 from the SCIAMACHY satellite instrument to derive top-down emissions of nitrogen oxides (NO(x) = NO + NO2) via inverse modeling with a global chemical transport model (GEOS-Chem). Simulated NO 2 vertical profiles used in the retrieval are evaluated with airborne measurements over and downwind of North America (ICARTT); a northern midlatitude lightning source of 1.6 Tg N/yr minimizes bias in the retrieval. Retrieved NO2 columns are validated (r2 = 0.60, slope = 0.82) with coincident airborne in situ measurements. The top-down emissions are combined with a priori information from a bottom-up emission inventory with error weighting to achieve an improved a posteriori estimate of the global distribution of surface NOx emissions. Our a posteriori NOx emission inventory for land surface NOx emissions (46.1 Tg N/yr) is 22% larger than the GEIA-based a priori bottom-up inventory for 1998, a difference that reflects rising anthropogenic emissions, especially from East Asia A posteriori NOx emissions for East Asia (9.8 Tg N/yr) exceed those from other continents. The a posteriori inventory improves the GEOS-Chem simulation of NOx, peroxyacetylnitrate, and nitric acid with respect to airborne in situ measurements over and downwind of New York City. The a posteriori is 7% larger than the EDGAR 3.2FT2000 global inventory, 3% larger than the NEI99 inventory for the United States, and 68% larger than a regional inventory for 2000 for eastern Asia. SCIAMACHY NO2 columns over the North Atlantic show a weak plume from lightning NO(x).

Martin, Randall V.↗
NASA NTRS2017

Assimilation of Global Radar Backscatter and Radiometer Brightness Temperature Observations to Improve Soil Moisture and Land Evaporation Estimates

Active radar backscatter (s◦) observations from the Advanced Scatterometer (ASCAT) and passive radiometer brightness temperature (TB) observations from the Soil Moisture Ocean Salinity (SMOS) mission are assimilated either individually or jointly into the Global Land Evaporation Amsterdam Model (GLEAM) to improve its simulations of soil moisture and land evaporation. To enable s◦ and TB assimilation, GLEAM is coupled to the Water Cloud Model and the L-band Microwave Emission from the Biosphere (L-MEB) model. The innovations, i.e. differences between observations and simulations, are mapped onto the model soil moisture states through an Ensemble Kalman Filter. The validation of surface (0-10 cm) soil moisture simulations over the period 2010-2014 against in situ measurements from the International Soil Moisture Network (ISMN) shows that assimilating s◦ or TB alone improves the average correlation of seasonal anomalies (Ran) from 0.514 to 0.547 and 0.548, respectively. The joint assimilation further improves Ran to 0.559. Associated enhancements in daily evaporative flux simulations by GLEAM are validated based on measurements from 22 FLUXNET stations. Again, the singular assimilation improves Ran from 0.502 to 0.536 and 0.533, respectively for s◦ and TB, whereas the best performance is observed for the joint assimilation (Ran = 0.546). These results demonstrate the complementary value of assimilating radar backscatter observations together with brightness temperatures for improving estimates of hydrological variables, as their joint assimilation outperforms the assimilation of each observation type separately.

GLEAM↗
NASA NTRS2008

New Developments for Physically-based Falling Snow Retrievals over Land in Preparation for GPM

The NASA Global Precipitation Measurement mission (GPM) concept centers on deploying a Core spacecraft carrying a dual-frequency precipitation radar and a microwave radiometric imager with channels from 10 to 183 GHz to serve as a precipitation physics observatory and a calibration reference to unify a constellation of dedicated and operational passive microwave sensors. Because of the extended orbit of the Core (plus or minus 65 deg) and the enhanced dual frequency radar and high frequency radiometer, GPM will be able to sense falling snow precipitation and light rain over land. Accordingly, GPM has partnered with the Canadian CloudSat/CALIPSO Validation Project (C3VP) to obtain observations to provide one of several important ground-based validation data sets around which the falling snow models and retrieval algorithms can be further developed and tested. In this work we compare and correlate the long time series (Nov.'06 - March '07) measurements of precipitation rate from parsivels to the passive (89, 150, 183 plus or minus 1, plus or minus 3, plus or minus 7 GHz) observations of NOAA's AMSU-B radiometer. We separate the comparisons into categories of no precipitation, liquid rain and falling snow precipitation. We found that there are similar TBs (especially at 89 and 150 GHz) for cases with falling snow and for non-precipitating cases. The comparisons indicate that surface emissivity contributions to the satellite observed TB over land can add uncertainty in detecting and estimating falling snow. The newest results show that by computing brightness temperatures based on CARE radiosonde data and a rough estimate of surface emissivity show that the cloud ice scattering signal in the AMSU-B data is detected. That is the differences in computed TB and AMSU-B TB for precipitating and non-precipitating cases are unique such that the precipitating and non-precipitating cases can be identified. These results require that the radiosonde releases are within an hour of the AMSU-B data. Forest fraction, snow cover, and measured emissivities were combined to calculate the surface emissivities.

Jackson, Gail S.↗
NASA NTRS1993

Land surface temperature measurements from EOS MODIS data

The task objectives of this reporting phase included: (1) completing the draft of the LST Algorithms Theoretical Basic Document by July 30, 1993; (2) making a detailed characterization of the thermal infrared measurement system including spectrometer, blackbody, and radiation sources; (3) making TIR spectral measurements of water and snow-cover surfaces with the MIDAC M2401 spectrometer; and (4) making conceptual and engineering design of an accessory system for spectrometric measurements at variable angles. These objectives are based on the requirements by the MODIS Science Team and the unique challenge in the development of MODIS LST algorithms: to acquire accurate spectral emissivity data of land covers in the near-term and to make ground validations of the LST product in the long-term with a TIR measurement system.

Wan, Zhengming↗
NASA NTRSDate not supplied

Detectability of anthropogenic impacts on terrestrial carbon storage through space-based greenhouse gas observations

While changes in human activity and their impact on the terrestrial biosphere may be apparent in inventory and land-surface satellite data, reliably matching these changes to signals in atmospheric greenhouse gases remains challenging. The dominant signals in atmospheric carbon dioxide (CO2) are those of the seasonal and diurnal variability of the terrestrial biosphere. As a result, the historically large short-term change in anthropogenic fossil fuel emissions due to COVID-19 produced an atmospheric CO2 signal near the threshold of detectability of the current space-based observing system. Impacts of anthropogenic activity on terrestrial carbon storage are likewise expected to be difficult, if not impossible, to detect and validate with atmospheric observations. For example, many forest management projects involve reduction of wood removals that would otherwise be taken off site and decompose years later and are thus not reflected in immediate onsite carbon fluxes. Nevertheless, changes implemented over a jurisdictional scale, as opposed to individual projects, may be detectable. This presentation will analyze to what extent NASA’s Goddard Earth Observing System (GEOS)/Orbiting Carbon Observatory 2 (OCO-2) assimilated column CO2 (XCO2) product is able to detect anthropogenic changes to terrestrial carbon storage and the results of several simulation experiments meant to represent potential forest management scenarios. As examples, we consider past and future changes due to conversion in the Tropics to agricultural land use from slash-and-burn, e.g., from Reducing emissions from deforestation and forest degradation in developing countries (REDD+) efforts. This has the potential to inform what practices may be observable with current and future technology, e.g., Europe’s upcoming CO2 monitoring mission (CO2M), and where improvement is needed.

Brad Weir↗
NASA NTRSDate not supplied

The Surface Longwave Downward Fluxes of the NASA GEWEX SRB Release 4.0 IP Products: Validation Against the Surface-Based BSRN and PMEL Observed Data

Since the NASA Global Energy Water Exchanges (GEWEX) Surface Radiation Budget (SRB) project released its 3rd version of products in 2010, the GEWEX Data Assessments Panel (GDAP) has been working on integrating various data products to address issues in the closing of the global energy and water cycles. The 4th version of the SRB products, Rel. 4.0-IP, has integrated data products from the cloud, aerosol, atmosphere, ocean surface, and land surface projects, coordinating within GDAP, to produce a long-term time series of TOA and surface radiative estimates. The Rel. 4-IP shortwave products span 34 years continuously from July 1983 to June 2017 on a quasi-equal-area 1degree longitude by 1degree latitude grid system. The longwave products are for land only from 1983-07 to 1987-12; for both land and ocean from 1988-01 to 2009-12; and ocean only from 2010-01 to 2017-06. The data are provided at 3 hourly, 3-hourly-monthly, daily and monthly means. The ISCCP HXS clouds and radiances are the key cloud input of the current GEWEX SRB algorithms. In addition, the longwave algorithm has also made changes in cloud microphysical property, surface skin temperature input, surface emissivity, atmospheric profile, adding longwave aerosol optical properties, revising cloud overlap procedure, and so on. Details of changes in both inputs and algorithms are documented in a NASA Algorithm Theoretical Basis Document (ATBD). We have validated the surface longwave downward fluxes against the surface-based Baseline Surface Radiation Network (BSRN) and the Pacific Marine Environmental Laboratory (PMEL) buoy data. As of 2020, the BSRN archive has 12,116 site-months of observed records from 73 stations on all seven continents, and as of 2017, PMEL archive has 4389 buoy months of observed records from 64 buoys deployed in the tropics of Pacific, Atlantic and Indian Oceans. This paper presents how the SRB Rel. 4.0-IP surface longwave downward fluxes compare with these surface-based measurements and how the comparison statistics differ from that of Rel. 3.0.

GEWEX SRB↗
NASA NTRS2009

Strategies to Improve the Accuracy of Mars-GRAM Sensitivity Studies at Large Optical Depths

The Mars Global Reference Atmospheric Model (Mars-GRAM) is an engineering-level atmospheric model widely used for diverse mission applications. 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 (EDL). It has been discovered during the Mars Science Laboratory (MSL) site selection process that Mars-GRAM when used for sensitivity studies for MapYear=0 and large optical depth values such as tau=3 is less than realistic. A comparison study between Mars atmospheric density estimates from Mars- GRAM and measurements by Mars Global Surveyor (MGS) has been undertaken for locations of varying latitudes, Ls, and LTST on Mars. The preliminary results from this study have validated the Thermal Emission Spectrometer (TES) limb data. From the surface to 80 km altitude, Mars- GRAM is based on the NASA Ames Mars General Circulation Model (MGCM). MGCM results that were used for Mars-GRAM with MapYear=0 were from a MGCM run with a fixed value of tau=3 for the entire year at all locations. Unrealistic energy absorption by uniform atmospheric dust leads to an unrealistic thermal energy balance on the polar caps. The outcome is an inaccurate cycle of condensation/sublimation of the polar caps and, as a consequence, an inaccurate cycle of total atmospheric mass and global-average surface pressure. Under an assumption of unchanged temperature profile and hydrostatic equilibrium, a given percentage change in surface pressure would produce a corresponding percentage change in density at all altitudes. Consequently, the final result of a change in surface pressure is an imprecise atmospheric density at all altitudes. To solve this pressure-density problem, a density factor value was determined for tau=.3, 1 and 3 that will adjust the input values of MGCM MapYear 0 pressure and density to achieve a better match of Mars-GRAM MapYear=0 with MapYears 1 and 2 MGCM output at comparable dust loading. Currently, these density factors are fixed values for all latitudes and Ls. Results will be presented of the work underway to derive better multipliers by including possible variation with latitude and/or Ls. This is achieved by comparison of Mars-GRAM MapYear=0 output with TES limb data. The addition of these density factors to Mars-GRAM will improve the results of the sensitivity studies done for large optical depths. Answers may also be provided to the issues raised in a recent study by Desai(2008). Desai has shown that the actual landing sites of Mars Pathfinder, the Mars Exploration Rovers and the Phoenix Mars Lander have been further downrange than predicted by models prior to landing. Desai s reconstruction of their entries into the Martian atmosphere showed that the models consistently predicted higher densities than those found upon EDL. The solution of this problem would be important to the Mars Program since future exploration of Mars by landers and rovers will require more accurate landing capabilities, especially for the proposed Mars Sample Return mission.

Justh, Hilary L.↗
NASA NTRSDate not supplied

How Well Satellite Remote Sensing Can Inform Surface Level Ozone Production Sensitivity to Precursor Trace Gas Emissions?

Surface-level ozone (O3) pollution mitigation strategies rely on a clear understanding of the atmospheric chemical processes involving O3, NOx (nitric oxide (NO) + nitrogen dioxide (NO2)) and volatile organic compounds (VOCs). A robust spatiotemporal classification of O3 photochemical regimes with relative chemical sensitivity of local O3 formation to emission reductions of NOx (NOx-limited regime) versus VOCs (radical-limited regime) is required to design anthropogenic emission reduction policies in order to improve surface air quality. Numerous studies found that the ratio of satellite-retrieved Vertical Column Densities (VCDs) of formaldehyde (HCHO) to NO2 can diagnose O3 production sensitivity. However, uncertainty still remains about the accuracy of such estimates using satellite-based retrievals. This study conducts an investigation to identify how well satellite data can inform surface-level O3 sensitivity by validating satellite-based estimates against aircraft-based retrievals taken during the Long Island Sound Tropospheric Ozone Study (LISTOS-2018) and Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaigns. For this study, we use HCHO and NO2 retrievals from the Ozone Monitoring Instrument (OMI) onboard the Aura satellite, and high spatiotemporal resolution TROPOspheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5 Precursor (S5P) satellite. The Community Multiscale Air Quality (CMAQ) modelling system is used to provide trace gas vertical profiles to recalculate air mass factor for deriving consistent satellite-based VCDs. To demonstrate the ability of satellites to diagnose O3 production regimes, we validate satellite-derived O3 sensitivity regimes, along with the OMI and TROPOMI products applied, using HCHO and NO2 retrievals from the aircraft-based instruments: Geostationary Trace gas and Aerosol Sensor Optimization (GeoTASO) spectrometer and Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) instruments deployed during the LISTOS-2018 and OWLETS-2 campaigns. The results of this work will advance our fundamental knowledge of the spatiotemporal evolution of the complex O3-NOx-VOC chemistry, and will advance our understanding about the quality of remote-sensing, suborbital, and satellite data for accurately observing surface-level O3 production sensitivity.

Satellite↗
NASA NTRS2021

Applications of Dynamic Land Surface Information for Passive Microwave Precipitation Retrieval

Accurate, physically based precipitation retrieval over global land surfaces is an important goal of the NASA/JAXA Global Precipitation Measurement Mission (GPM). This is a difficult problem for the passive microwave constellation, as the signal over radiometrically warm land surfaces in the microwave frequencies means that the measurements used are indirect and typically require inferring some type of relationship between an observed scattering signal and precipitation at the surface. GPM, with collocated radiometer and dual-frequency radar, is an excellent tool for tackling this problem and improving global retrievals. In the years following the launch of the GPM Core Observatory satellite, physically based passive microwave retrieval of precipitation over land continues to be challenging. Validation efforts suggest that the operational GPM passive microwave algorithm, the Goddard profiling algorithm (GPROF), tends to overestimate precipitation at the low (<5 mm h−1) end of the distribution over land. In this work, retrieval sensitivities to dynamic surface conditions are explored through enhancement of the algorithm with dynamic, retrieved information from a GPM-derived optimal estimation scheme. The retrieved parameters describing surface and background characteristics replace current static or ancillary GPROF information including emissivity, water vapor, and snow cover. Results show that adding this information decreases probability of false detection by 50% and, most importantly, the enhancements with retrieved parameters move the retrieval away from dependence on ancillary datasets and lead to improved physical consistency.

Sarah Ringerud↗
DOE OSTI2024

Pan-tropical daily L-band microwave land surface emissivity retrieval from GNSS-R observations

The uncertainties in microwave land surface emissivity (MLSE) measurements have long limited the use of spaceborne microwave radiometer data. As an emerging observation method, Global Navigation Satellite System Reflectometry (GNSS-R) has demonstrated great potential in several land and ocean applications. In this study, a method for obtaining daily MLSE dataset in the pan-tropical region from Cyclone GNSS (CYGNSS) observations is presented and evaluated. The CYGNSS observations are first aggregated into the Equal-Area-Scalable-Earth (EASE) 2.0 36 km grid by a combined weight function of distance, time, and signal-to-noise ratio variance. Then, the method employs a pixel-by-pixel regression algorithm to conduct the daily MLSE retrieval using reference emissivity derived from the Soil Moisture Active Passive (SMAP) brightness temperature. The CYGNSS MLSE shows good agreement with SMAP MLSE, delivering an overall root-mean-square error (RMSE) of 0.022 and 0.017 for horizontal and vertical polarization, respectively, during the training set spanning the whole year of 2018. Furthermore, on the test set from January 2019 to May 2019, the RMSE values amounted to 0.030 and 0.023 for horizontal and vertical polarization, respectively. Temperature records from the International Soil Moisture Network are employed to calculate the emissivity and for in-situ validation, which yield an RMSE of 0.034 and 0.026 for the two polarizations, respectively. The proposed algorithm provides an encouraging approach to obtain accurate daily MLSE dataset for microwave remote sensing. Compared to the SMAP MLSE, the CYGNSS MLSE has a remarkable improvement of 86% in temporal resolution, greatly complementing the existing microwave emissivity datasets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2009

Assessment of Tropical Cyclone Induced Transgression of the Chandeleur Islands for Restoration and Wildlife Management

The Chandeleur Islands are the first line of defense against tropical storms and hurricanes for coastal Louisiana. They provide habitats for birds species and are a wildlife refuge; however, distressingly, they are eroding and transgressing at an alarming rate. In 1998, Hurricane Georges caused severe damage to the chain, prompting restoration and monitoring efforts by both Federal and State agencies. Since then, storm events have steadily diminished the condition of the islands. Quantification of shoreline erosion, vegetation, and land loss, from 1979 to 2009, was achieved through the analysis of imagery from Landsat 2-4 Multispectral Scanner, Landsat 4 & 5 Thematic Mapper, and Advanced Spaceborne Thermal Emission and Reflection Radiometer sensors. QuickBird imagery was used to validate the accuracy of these results. In addition, this study presents an application of Moderate Resolution Imaging Spectroradiometer data to assist in tracking the transgression of the Chandeleur Islands. The use of near infrared reflectance calculated from MOD09 surface reflectance data from 2000 to 2009 was analyzed using the Time Series Product Tool. The scope of this project includes not only assessments of the tropical cyclonic events during this time period, but also the effects of tides, winds, and cold fronts on the spatial extent of the islands. Partnering organizations, such as the Pontchartrain Institute for Environmental Research, will utilize those results in an effort to better monitor and address the continual change of the island chain.

Mitchell, Brandie↗
NASA NTRS2002

Mars-Gram Validation with Mars Global Surveyor Data

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many b4ars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model (MGCM), while above 80 km it is based on University of Arizona Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter (MOLA). Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science (RS) and Thermal Emission Spectrometer (TES) data. RS data from 2480 profiles were used, covering latitudes 75deg S to 72deg N, surface to approx. 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160deg and 265-310deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, measured RS density varied by about a factor of 2.5 over the range of latitudes and Ls values observed. Evaluated at matching positions and times, average RS/Mars-GRAM density ratios were generally lf0.05, except at heights above approx. 25 km and latitudes above approx.50deg N. Average standard deviation of RS/Mars-GRAM density ratio was 6%. TES data were used covering surface to approx. 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of Mars global dust storm). Depending on season, TES data covered latitudes 85deg S to 85deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (> 45deg N), or at most altitudes in the southern hemisphere at Ls approx. 90 and 180deg). Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approx. 6.5-10.5% (varying with height) for all data, or approx. 5- 12%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for 1o:al time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about the same as the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C. G.↗
NASA NTRS2003

Mars Global Reference Atmospheric Model (Mars-GRAM) and Database for Mission Design

Mars Global Reference Atmospheric Model (Mars-GRAM 2001) is an engineering-level Mars atmosphere model widely used for many Mars mission applications. From 0-80 km, it is based on NASA Ames Mars General Circulation Model, while above 80 km it is based on Mars Thermospheric General Circulation Model. Mars-GRAM 2001 and MGCM use surface topography from Mars Global Surveyor Mars Orbiting Laser Altimeter. Validation studies are described comparing Mars-GRAM with Mars Global Surveyor Radio Science and Thermal Emission Spectrometer data. RS data from 2480 profiles were used, covering latitudes 75 deg S to 72 deg N, surface to approximately 40 km, for seasons ranging from areocentric longitude of Sun (Ls) = 70-160 deg and 265-310 deg. RS data spanned a range of local times, mostly 0-9 hours and 18-24 hours. For interests in aerocapture and precision landing, comparisons concentrated on atmospheric density. At a fixed height of 20 km, RS density varied by about a factor of 2.5 over ranges of latitudes and Ls values observed. Evaluated at matching positions and times, these figures show average RSMars-GRAM density ratios were generally 1+/-)0.05, except at heights above approximately 25 km and latitudes above approximately 50 deg N. Average standard deviation of RSMars-GRAM density ratio was 6%. TES data were used covering surface to approximately 40 km, over more than a full Mars year (February, 1999 - June, 2001, just before start of a Mars global dust storm). Depending on season, TES data covered latitudes 85 deg S to 85 deg N. Most TES data were concentrated near local times 2 hours and 14 hours. Observed average TES/Mars-GRAM density ratios were generally 1+/-0.05, except at high altitudes (15-30 km, depending on season) and high latitudes (greater than 45 deg N), or at most altitudes in the southern hemisphere at Ls approximately 90 and 180 deg. Compared to TES averages for a given latitude and season, TES data had average density standard deviation about the mean of approximately 2.5% for all data, or approximately 1-4%, depending on time of day and dust optical depth. Average standard deviation of TES/Mars-GRAM density ratio was 8.9% for local time 2 hours and 7.1% for local time 14 hours. Thus standard deviation of observed TES/Mars-GRAM density ratio, evaluated at matching positions and times, is about three times the standard deviation of TES data about the TES mean value at a given position and season.

Justus, C. G.↗
NASA NTRS2001

Fires and Smoke Observed from the Earth Observing System MODIS Instrument: Products, Validation, and Operational Use

The MODIS sensor, launched on NASA's Terra satellite at the end of 1999, was designed with 36 spectral channels for a wide array of land, ocean, and atmospheric investigations. MODIS has a unique ability to observe fires, smoke, and burn scars globally. Its main fire detection channels saturate at high brightness temperatures: 500 K at 4 microns and 400 K at 11 microns, which can only be attained in rare circumstances at the I kin fire detection spatial resolution. Thus, unlike other polar orbiting satellite sensors with similar thermal and spatial resolutions, but much lower saturation temperatures (e.g. AVHRR and ATSR), MODIS can distinguish between low intensity ground surface fires and high intensity crown forest fires. Smoke column concentration over land is for the first time being derived from the MOMS solar channels, extending from 0.41 microns to 2.1 microns. The smoke product has been provisionally validated both globally and regionally over southern Africa and central and south America. Burn scars are observed from MODIS even in the presence of smoke, using the 1.2 to 2.1 micron channels. MODIS burned area information is used to estimate pyrogenic emissions. A wide range of these fire and related products and validation are demonstrated for the wild fires that occurred in northwestern United States in the summer of 2000. The MODIS rapid response system and direct broadcast capability is being developed to enable users to obtain and generate data in near real time. It is expected that health and land management organizations will use these systems for monitoring the occurrence of fires and the dispersion of smoke within two to six hours after data acquisition.

Kaufman, Y. J.↗
NASA NTRS2013

Intercomparison of Satellite Dust Retrieval Products over the West African Sahara During the Fennec Campaign in June 2011

Dust retrievals over the Sahara Desert during June 2011 from the IASI, MISR, MODIS, and SEVIRI satellite instruments are compared against each other in order to understand the strengths and weaknesses of each retrieval approach. Particular attention is paid to the effects of meteorological conditions, land surface properties, and the magnitude of the dust loading. The period of study corresponds to the time of the first Fennec intensive measurement campaign, which provides new ground-based and aircraft measurements of the dust characteristics and loading. Validation using ground-based AERONET sunphotometer data indicate that of the satellite instruments, SEVIRI is most able to retrieve dust during optically thick dust events, whereas IASI and MODIS perform better at low dust loadings. This may significantly affect observations of dust emission and the mean dust climatology. MISR and MODIS are least sensitive to variations in meteorological conditions, while SEVIRI tends to overestimate the aerosol optical depth (AOD) under moist conditions (with a bias against AERONET of 0.31), especially at low dust loadings where the AOD<1. Further comparisons are made with airborne LIDAR measurements taken during the Fennec campaign, which provide further evidence for the inferences made from the AERONET comparisons. The effect of surface properties on the retrievals is also investigated. Over elevated surfaces IASI retrieves AODs which are most consistent with AERONET observations, while the AODs retrieved by MODIS tend to be biased low. In contrast, over the least emissive surfaces IASI significantly underestimates the AOD (with a bias of -0.41), while MISR and SEVIRI show closest agreement.

Fennec Campaign↗