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NASA NTRS1998

Theoretical Accuracy of Global Snow-Cover Mapping Using Satellite Data in the Earth Observing System (EOS) Era

Following the launch of the Earth Observing System first morning (EOS-AM1) satellite, daily, global snow-cover mapping will be performed automatically at a spatial resolution of 500 m, cloud-cover permitting, using Moderate Resolution Imaging Spectroradiometer (MODIS) data. A technique to calculate theoretical accuracy of the MODIS-derived snow maps is presented. Field studies demonstrate that under cloud-free conditions when snow cover is complete, snow-mapping errors are small (less than 1%) in all land covers studied except forests where errors are greater and more variable. The theoretical accuracy of MODIS snow-cover maps is largely determined by percent forest cover north of the snowline. Using the 17-class International Geosphere-Biosphere Program (IGBP) land-cover maps of North America and Eurasia, the Northern Hemisphere is classified into seven land-cover classes and water. Snow-mapping errors estimated for each of the seven land-cover classes are extrapolated to the entire Northern Hemisphere for areas north of the average continental snowline for each month. Average monthly errors for the Northern Hemisphere are expected to range from 5 - 10%, and the theoretical accuracy of the future global snow-cover maps is 92% or higher. Error estimates will be refined after the first full year that MODIS data are available.

Hall, D. K.↗
NASA NTRS1998

Removal of Thin Cirrus Path Radiances in the 0.4-1.0 micron Spectral Region Using the 1.375-micron Strong Water Vapor Absorption Channel

Through analysis of spectral imaging data acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) from an ER-2 aircraft at 20 km altitude during several field programs, it was found that narrow channels near the center of the strong 1.38-micron water vapor band are very sensitive in detecting thin cirrus clouds. Based on this observation from AVIRIS data, a channel centered at 1.375 microns with a width of 30 nm was selected for the Moderate Resolution Imaging Spectrometer (MODIS) for remote sensing of cirrus clouds from space. The sensitivity of the 1.375-micron MODIS channel to detect thin cirrus clouds during the day time is expected to be one to two orders of magnitude better than the current infrared emission techniques. As a result, a larger fraction of the satellite data will likely be identified as containing cirrus clouds. In order to make better studies of surface reflectance properties, thin cirrus effects must be removed from satellite images. We have developed an empirical approach for removing/correcting thin cirrus effects in the 0.4 - 1.0 micron region using channels near 1.375 microns. This algorithm will be incorporated into the present MODIS atmospheric correction algorithms for ocean color and land applications and will yield improved MODIS atmospheric aerosol, land surface, and ocean color products.

Gao, Bo-Cai↗
NASA NTRS2001

Cloud and Radiation Studies during SAFARI 2000

Though the emphasis of the Southern Africa Regional Science Initiative 2000 (SAFARI-2000) dry season campaign was largely on emission sources and transport, the assemblage of aircraft (including the high altitude NASA ER-2 remote sensing platform and the University of Washington CV-580, UK MRF C130, and South African Weather Bureau JRA in situ aircrafts) provided a unique opportunity for cloud studies. Therefore, as part of the SAFARI initiative, investigations were undertaken to assess regional aerosol-cloud interactions and cloud remote sensing algorithms. In particular, the latter part of the experiment concentrated on marine boundary layer stratocumulus clouds off the southwest coast of Africa. Associated with cold water upwelling along the Benguela current, the Namibian stratocumulus regime has received limited attention but appears to be unique for several reasons. During the dry season, outflow of continental fires and industrial pollution over this area can be extreme. From below, upwelling provides a rich nutrient source for phytoplankton (a source of atmospheric sulphur through DMS production as well as from decay processes). The impact of these natural and anthropogenic sources on the microphysical and optical properties of the stratocumulus is unknown. Continental and Indian Ocean cloud systems of opportunity were also studied during the campaign. Aircraft flights were coordinated with NASA Terra Satellite overpasses for synergy with the Moderate Resolution Imaging Spectroradiometer (MODIS) and other Terra instruments. An operational MODIS algorithm for the retrieval of cloud optical and physical properties (including optical thickness, effective particle radius, and water path) has been developed. Pixel-level MODIS retrievals (11 km spatial resolution at nadir) and gridded statistics of clouds in th SAFARI region will be presented. In addition, the MODIS Airborne Simulator flown on the ER-2 provided high spatial resolution retrievals (50 m at nadir). These retrievals will be discussed and compared with in situ observations.

Platnick, Steven↗
NASA NTRS2004

The Development of Two Science Investigator-led Processing Systems (SIPS) for NASA's Earth Observation System (EOS)

In 2001, NASA Goddard Space Flight Center's Laboratory for Terrestrial Physics started the construction of a science Investigator-led Processing System (SIPS) for processing data from the Ozone Monitoring Instrument (OMI) which will launch on the Aura platform in mid 2004. The Ozone Monitoring Instrument (OMI) is a contribution of the Netherlands Agency for Aerospace Programs (NIVR) in collaboration with the Finnish Meteorological Institute (FMI) to the Earth Observing System (EOS) Aura mission. It will continue the Total Ozone Monitoring System (TOMS) record for total ozone and other atmospheric parameters related to ozone chemistry and climate. OMI measurements will be highly synergistic with the other instruments on the EOS Aura platform. The LTP previously developed the Moderate Resolution Imaging Spectrometer (MODIS) Data Processing System (MODAPS), which has been in full operations since the launches of the Terra and Aqua spacecrafts in December, 1999 and May, 2002 respectively. During that time, it has continually evolved to better support the needs of the MODIS team. We now run multiple instances of the system managing faster than real time reprocessings of the data as well as continuing forward processing. The new OMI Data Processing System (OMIDAPS) was adapted from the MODAPS. It will ingest raw data from the satellite ground station and process it to produce calibrated, geolocated higher level data products. These data products will be transmitted to the Goddard Distributed Active Archive Center (GDAAC) instance of the Earth Observing System (EOS) Data and Information System (EOSDIS) for long term archive and distribution to the public. The OMIDAPS will also provide data distribution to the OMI Science Team for quality assessment, algorithm improvement, calibration, etc. We have taken advantage of lessons learned from the MODIS experience and software already developed for MODIS. We made some changes in the hardware system organization, database and software to adapt the system for OMI. We replaced the fundamental database system, Sybase, with an Open Source RDBMS called PostgreSQL, and based the entire OMIDAPS on a cluster of Linux based commodity computers rather than the large SGI servers that MODAPS uses. Rather than relying on a central I/O server host, the new system distributes its data archive among multiple server hosts in the cluster. OMI is also customizing the graphical user interfaces and reporting structure to more closely meet the needs of the OMI Science Team. Prior to 2003, simulated OMI data and the science algorithms were not ready for production testing. We initially constructed a prototype system and tested using a 25 year dataset of Total Ozone Mapping Spectrometer (TOMS) and Solar Backscatter Ultraviolet Instrument (SBUV) data. This prototype system provided a platform to support the adaptation of the algorithms for OMI, and provided reprocessing of the historical data aiding in its analysis. In a recent reanalysis of the TOMS data, the OMIDAPS processed 108,000 full orbits of data through 4 processing steps per orbit, producing about 800,000 files (400 GiB) of level 2 and greater data files. More recently we have installed two instances of the OMIDAPS for integration and testing of OM1 science processes as they get delivered from the Science Team. A Test instance of the OMIDAPS has also supported a series of "Interface Confidence Tests" (ICTs) and End-to-End Ground System tests to ensure the launch readiness of the system. This paper will discuss the high-level hardware, software, and database organization of the OMIDAPS and how it builds on the MODAPS heritage system. It will also provide an overview of the testing and implementation of the production OMIDAPS.

Tilmes, Curt↗
NASA NTRS2004

Estimation of Fire Emissions from Satellite-Based Measurements

Biomass burning is a worldwide phenomenon affecting many vegetated parts of the globe regularly. Fires emit large quantities of aerosol and trace gases into the atmosphere, thus influencing the atmospheric chemistry and climate. Traditional methods of fire emissions estimation achieved only limited success, because they were based on peripheral information such as rainfall patterns, vegetation types and changes, agricultural practices, and surface ozone concentrations. During the last several years, rapid developments in satellite remote sensing has allowed more direct estimation of smoke emissions using remotely-sensed fire data. However, current methods use fire pixel counts or burned areas, thereby depending on the accuracy of independent estimations of the biomass fuel loadings, combustion efficiency, and emission factors. With the enhanced radiometric range of its 4-micron fire channel, the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor, which flies aboard both of the Earth Observing System EOS) Terra and Aqua Satellites, is able to measure the rate of release of fire radiative energy (FRE) in MJ/s (something that older sensors could not do). MODIS also measures aerosol distribution. Taking advantage of these new resources, we have developed a procedure combining MODIS fire and aerosol products to derive FRE-based smoke emission coefficients (C(e), in kg/MJ) for different regions of the globe. These coefficients are simply used to multiply FRE from MODIS to derive the emitted smoke aerosol mass. Results from this novel methodology are very encouraging. For instance, it was found that the smoke total particulate mass emission coefficient for the Brazilian Cerrado ecosystem (approximately 0.022 kg/MJ) is about twice the value for North America, Western Europe, or Australia, but about 50% lower than the value for southern Africa.

Ichoku, Charles↗
NASA NTRS2004

Dynamics of the Cold Water Event off the Southeast Coast of the United States in the Summer of 2003: An Application of NASA's Remote Sensing Data to Coastal Studies

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments onboard of Terra and Aqua satellites provide, for the first time, concurrent measurements of sea surface temperature (SST) and ocean color, which are suitable for coastal upwelling studies. The accuracy, the 1-km spatial resolution, and the almost complete daily coverage of the MODIS data compared with historical measurements make it advantageous for resolving important coastal fronts of chlorophyll concentration and temperature. The cold SST anomaly during summer 2003 off the coast of the South Atlantic Bight is an event that is comprehensively covered by NASA's MODIS and SeaWinds satellite observations. These data combined with in situ tide gauge, mooring, and ship measurements can be used to identify important dynamics responsible for the anomalous cold water event. The analysis of the data suggests that coastal upwelling occurs in the climatological summer forced by the climatological southerlies over the South Atlantic Bight area in summer. However, the strong buoyancy barrier in summer prevents the cold water below the thermocline from reaching the ocean surface. In summer 2003, the southwesterlies in July through August were extraordinarily strong and persistent, which generated the upwelling currents strong enough to overcome the buoyancy resistance. The results of this analysis demonstrate the possibility of monitoring and forecasting the event using combination of the satellite and in situ observations. The MODIS data are archived and distributed by the NASA's Goddard Earth Science (GES) Distributed Active Archive Center (DAAC). The data can be accessed via the URL http://wwv.daac.gsfc.nasa.gov/MODIS.

Yuan, Dongliang↗
NASA NTRS2005

The NASA Short-term Prediction and Research Transition (SPoRT) Center: A Research to Operations Test Bed

Over the last three years, NASA/MSFC scientists have embarked on an effort to transition unique NASA EOS data/products and research technology to selected NWSEOs in the southeast U.S. This activity, called the Short-term Prediction and - Research Transition (SPoRT) program, supports the NASA Science Mission Directorate and its Earth-Sun System Mission to develop a scientific understanding of the Earth System and its response to natural or human-induced changes that will enable improved prediction capability for climate, weather, and natural hazards. The overarching question related to weather prediction is "How well can weather forecasting duration and reliability be improved by new space-based observations, data assimilation, and modeling?" The transition activity has included the real-time delivery of MODIS data and products to several NWS Forecast Offices. Local NWS FOs have used the MODIS data to complement the coarse resolution GOES data for a number of applications. Specialized products have also been developed and made available to local and remote offices for their weather applications. Data from &e Lightning Mapping Array (LMA) network has been used in severe storm forecasts at several offices in the region. At the regional scale and forecast horizons from 0-1 day, the next generation of high-resolution mesoscale forecast and data assimilation models have been used to provide local offices with unique weather forecasts not otherwise available. The continued use of near red-time infusion of NASA science products into high-resolution mesoscale forecast and decision-making models can be expected to improve the model initialization as well as short-term forecasts. A current focus of SPoRT is to expand collaborations to include contributions from the assimilation of AMSR-E data in the ADASIARPS forecast system (OU), inclusion of MODIS SSTs and AIRS thermodynamic profiles in the WRF, and to extend the distribution of real-time MODIS and AMSR-E data and products to the Florida coastal WFOs. A SPoRT Test bed, together with input from other interagency and university partners, will provide a means and a process to effectively transition ESE observations and technology to NWS operations and decision makers at both the globdnational and regional scales. The transition of emerging experimental products into operations through the SPoRT infrastructure will allow NASA to foster and accelerate the progress of this Science Mission Directorate research strategy over the coming years.

Jedlovec, Gary J.↗
NASA NTRS2006

Improved Thin Cirrus and Terminator Cloud Detection in CERES Cloud Mask

Thin cirrus clouds account for about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is caused by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 micron ) and infrared (11 micron ) channels. In the Clouds and the Earth s Radiant Energy System (CERES) Aqua Edition 1 (AEd1) and Terra Edition 3 (TEd3) Cloud Masks, thin cirrus detection is significantly improved over both land and ocean using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 micron channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 micron channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 micron reflectance and the 11-12 and 8.5-11 micron BTDs using 70 granules of MODIS data in 2002 and 2003. Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 micron channel and the estimated solar component of 3.7 micron channel becomes less reliable. As a result, clouds are often underestimated or misidentified near the terminator over land and ocean. Comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 N indicate significant amounts of missing clouds from CLAVR-x because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products (MOD06) and GLAS in the same region also show similar difficulties with MODIS cloud retrievals. The consistent detection of clouds through out the day is needed to provide reliable cloud and radiation products for CERES and other research efforts involving the modeling of clouds and their interaction with the radiation budget.

Trepte, Qing↗
NASA NTRS2006

First Results from the OMI Rotational Raman Scattering Cloud Pressure Algorithm

We have developed an algorithm to retrieve scattering cloud pressures and other cloud properties with the Aura Ozone Monitoring Instrument (OMI). The scattering cloud pressure is retrieved using the effects of rotational Raman scattering (RRS). It is defined as the pressure of a Lambertian surface that would produce the observed amount of RRS consistent with the derived reflectivity of that surface. The independent pixel approximation is used in conjunction with the Lambertian-equivalent reflectivity model to provide an effective radiative cloud fraction and scattering pressure in the presence of broken or thin cloud. The derived cloud pressures will enable accurate retrievals of trace gas mixing ratios, including ozone, in the troposphere within and above clouds. We describe details of the algorithm that will be used for the first release of these products. We compare our scattering cloud pressures with cloud-top pressures and other cloud properties from the Aqua Moderate-Resolution Imaging Spectroradiometer (MODIS) instrument. OMI and MODIS are part of the so-called A-train satellites flying in formation within 30 min of each other. Differences between OMI and MODIS are expected because the MODIS observations in the thermal infrared are more sensitive to the cloud top whereas the backscattered photons in the ultraviolet can penetrate deeper into clouds. Radiative transfer calculations are consistent with the observed differences. The OMI cloud pressures are shown to be correlated with the cirrus reflectance. This relationship indicates that OMI can probe through thin or moderately thick cirrus to lower lying water clouds.

Joiner, Joanna↗
NASA NTRS2007

Comparison of Water Vapor Measurements by Airborne Sun Photometer and Near-Coincident in Situ and Satellite Sensors during INTEX/ITCT 2004

We have retrieved columnar water vapor (CWV) from measurements acquired by the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS-14) during 19 Jetstream 31 (J31) flights over the Gulf of Maine in summer 2004 in support of the Intercontinental Chemical Transport Experiment (INTEX)/Intercontinental Transport and Chemical Transformation (ITCT) experiments. In this paper we compare AATS-14 water vapor retrievals during aircraft vertical profiles with measurements by an onboard Vaisala HMP243 humidity sensor and by ship radiosondes and with water vapor profiles retrieved from AIRS measurements during eight Aqua overpasses. We also compare AATS CWV and MODIS infrared CWV retrievals during five Aqua and five Terra overpasses. For 35 J31 vertical profiles, mean (bias) and RMS AATS-minus-Vaisala layer-integrated water vapor (LWV) differences are -7.1 percent and 8.8 percent, respectively. For 22 aircraft profiles within 1 hour and 130 km of radiosonde soundings, AATS-minus-sonde bias and RMS LWV differences are -5.4 percent and 10.7 percent, respectively, and corresponding J31 Vaisala-minus-sonde differences are 2.3 percent and 8.4 percent, respectively. AIRS LWV retrievals within 80 lan of J31 profiles yield lower bias and RMS differences compared to AATS or Vaisala retrievals than do AIRS retrievals within 150 km of the J31. In particular, for AIRS-minus-AATS LWV differences, the bias decreases from 8.8 percent to 5.8 percent, and the RMS difference decreases from 2 1.5 percent to 16.4 percent. Comparison of vertically resolved AIRS water vapor retrievals (LWVA) to AATS values in fixed pressure layers yields biases of -2 percent to +6 percent and RMS differences of -20 percent below 700 hPa. Variability and magnitude of these differences increase significantly above 700 hPa. MODIS IR retrievals of CWV in 205 grid cells (5 x 5 km at nadir) are biased wet by 10.4 percent compared to AATS over-ocean near-surface retrievals. The MODIS-Aqua subset (79 grid cells) exhibits a wet bias of 5.1 percent, and the MODIS-Terra subset (126 grid cells) yields a wet bias of 13.2 percent.

Livingston, J.↗
NASA NTRS2008

Evaluation and Assimilation of Cloud Cleared Radiances for AIRS in GEOS-5

The use of clear (cloud-free) channels for AIRS in GEOS-5 had shown positive impact on forecast skills in both hemispheres. However, improvements in forecast skills due to the assimilation of AIRS data are less impressive since the number of assimilated channels from AIRS is much larger than that from other Infrared sounders such as HIRS-3 onboard NOAA 15-17 satellites. This limitation of AIRS radiance data to improve the forecast skill is mainly due to the fact that channels capable of peaking below clouds are not used in the assimilation and yet those have highest vertical resolving capability of AIRS instrument are concentrated in the lower troposphere. On average, the percentage of AIRS footprints completely clear for all channels is less than 10%. The percentage of assimilated AIRS channel radiances however ranges from 100% for channels peaking in the upper stratosphere, above the cloud, to no more that 5% in the lower atmosphere due to cloud contamination. Our current ability to model and predict clouds accurately in global model, and to fully characterize and parameterize optical properties of cloud particles in radiative transfer model are the two major obstacles prohibiting us to use cloudy radiance directly in the assimilation. To further improve forecast skill using AIRS data, we ought to use the channels peaking below the clouds in the troposphere, which can be accomplished by assimilating cloud-cleared radiance. The cloud-cleared radiance data for AIRS used in this study were obtained from optimal cloud clearing procedures developed by researchers at CIMSS of University of Wisconsin at Madison to retrieve clear column radiances for all AIRS channels by collocating multi-band MODIS IR clear radiance observations with the AIRS cloudy radiances on a single footprint basis. Two adjacent AIRS cloudy footprints are used to retrieve one AIRS cloud-cleared radiance spectrum and no background information (first guess) is needed. To assimilate the cloud-cleared radiance data, the errors of the cloud-cleared radiances need to be addressed. The details of convolving AIRS radiances with MODIS spectral response function and comparison with MODIS-measured cloud-free radiance will be presented. The range of errors of cloud-cleared radiances for AIRS using collocated MODIS clear and near-by AIRS clear data will be shown. The NASA. global data assimilation model, GEOS-5, is used to evaluate and assimilate the cloud-cleared radiance for AIRS. The residues between the cloud-cleared brightness temperature and the simulated brightness temperature from background (i.e., OMFs) will be investigated. The quality control procedures will be documented based on error estimation and the OMFs. Finally, the impacts between assimilation of clear channel radiances and cloud-cleared radiances will be addressed.

Liu, Hui-chun↗
NASA NTRS2008

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

A set of cloud retrieval algorithms developed for CERES and applied to MODIS data have been adapted to analyze other satellite imager data in near-real time. The cloud products, including single-layer cloud amount, top and base height, optical depth, phase, effective particle size, and liquid and ice water paths, are being retrieved from GOES- 10/11/12, MTSAT-1R, FY-2C, and Meteosat imager data as well as from MODIS. A comprehensive system to normalize the calibrations to MODIS has been implemented to maximize consistency in the products across platforms. Estimates of surface and top-of-atmosphere broadband radiative fluxes are also provided. Multilayered cloud properties are retrieved from GOES-12, Meteosat, and MODIS data. Native pixel resolution analyses are performed over selected domains, while reduced sampling is used for full-disk retrievals. Tools have been developed for matching the pixel-level results with instrumented surface sites and active sensor satellites. The calibrations, methods, examples of the products, and comparisons with the ICESat GLAS lidar are discussed. These products are currently being used for aircraft icing diagnoses, numerical weather modeling assimilation, and atmospheric radiation research and have potential for use in many other applications.

Minnis, Patrick↗
NASA NTRS2009

Impact of Lake Okeechobee Sea Surface Temperatures on Numerical Predictions of Summertime Convective Systems over South Florida

The NASA Short-term Prediction Research and Transition (SPoRT) Center, the Florida Institute of Technology, and the NOAA/NWS Weather Forecast Office at Miami, FL (MFL) are collaborating on a project to investigate the impact of using high-resolution, 2-km Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composites within the Weather Research and Forecasting (WRF) prediction system. The NWS MFL is currently running WRF in real-time to support daily forecast operations, using the National Centers for Environmental Prediction Nonhydrostatic Mesoscale Model dynamical core within the NWS Science and Training Resource Center's Environmental Modeling System (EMS) software. Twenty-seven hour forecasts are run daily initialized at 0300, 0900, 1500, and 2100 UTC on a domain with 4-km grid spacing covering the southern half of Florida and adjacent waters of the Gulf of Mexico and Atlantic Ocean. The SSTs are initialized with the NCEP Real-Time Global (RTG) analyses at 1/12deg resolution. The project objective is to determine whether more accurate specification of the lower-boundary forcing over water using the MODIS SST composites within the 4-km WRF runs will result in improved sea fluxes and hence, more accurate e\~olutiono f coastal mesoscale circulations and the associated sensible weather elements. SPoRT conducted parallel WRF EMS runs from February to August 2007 identical to the operational runs at NWS MFL except for the use of MODIS SST composites in place of the RTG product as the initial and boundary conditions over water. During the course of this evaluation, an intriguing case was examined from 6 May 2007, in which lake breezes and convection around Lake Okeechobee evolved quite differently when using the high-resolution SPoRT MODIS SST composites versus the lower-resolution RTG SSTs. This paper will analyze the differences in the 6 May simulations, as well as examine other cases from the summer 2007 in which the WRF-simulated Lake Okeechobee breezes evolved differently due to the SST initialization. The effects on wind fields and precipitation systems will be emphasized, including validation against surface mesonet observations and Stage IV precipitation grids.

Case, Jonathan L.↗
NASA NTRS2009

Combined MODIS/AMSR-E SST Composites for Regional Weather Applications

Recent applications of a high resolution MODlS composite SST product have clearly shown the importance of developing high-resolution SST data sets for coastal applications and modeling. In general, coupling between the oceans and atmospheres has been closely linked to SST gradients and fronts, indicating a need for high resolution SSTs, specifically in the areas of large gradients associated with coastal regions. Thus an accurate determination of SST gradients has become critical for determining the appropriate air-sea coupling and the influence on ocean modeling. Recent research is focused on improving the accuracy and spatial coverage of the current operational MODIS SST composite product provided by the Short-term Prediction Research and Transition (SPORT) project and distributed to the community. GHRSST-PP MODlS data and microwave AMSR-E data are being combined to produce composite data sets for both the West Coast and East Coast of the United States, including the Gulf of Mexico. The use of 1 km MODIS data has explicit advantages over other SST products including its global coverage and high resolution. The AMSR-E data will reduce the latency of the composites. A strategy for utilizing the error characteristics contained in the GHRSST data has been developed. This strategy will include using the error characteristics directly to calculate weights in the SST composites, uncertainty maps based on the composite biases and RMS errors, and latency products calculated in the compositing process. Recent accomplishments include the development of an enhanced compositing approach based on the error-weighted combination of recent clear MODIS SST values, where the error contributions come from measurement error, potential cloud contamination, and data latency sources. Future plans call for the inclusion of AMSR-E SST values with appropriate weights based upon measurement accuracy, MODIS-AMSR-E SST bias, and latency.

Jedlovec, Gary↗
NASA NTRS2008

Global Characterization of Biomass-Burning Patterns using Satellite Measurements of Fire Radiative Energy

Remote sensing is the most practical means of measuring energy release from large open-air biomass burning. Satellite measurement of fire radiative energy (FRE) release rate or power (FRP) enables distinction between fires of different strengths. Based on a 1-km resolution fire data acquired globally by the MODerate-resolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites from 2000 to 2006, instanteaneous FRP values ranged between 0.02 MW and 1866 MW, with global daily means ranging between 20 and 40 MW. Regionally, at the Aqua-MODIS afternoon overpass, the mean FRP values for Alaska, Western US, Western Australia, Quebec and the rest of Canada are significantly higher than these global means, with Quebec having the overall highest value of 85 MW. Analysis of regional mean FRP per unit area of land (FRP flux) shows that a peak fire season in certain regions, fires can be responsible for up to 0.2 W/m(sup 2) at peak time of day. Zambia has the highest regional monthly mean FRP flux of approximately 0.045 W/m(sup 2) at peak time of day and season, while the Middle East has the lowest value of approximately 0.0005 W/m(sup 2). A simple scheme based on FRP has been devised to classify fires into five categories, to facilitate fire rating by strength, similar to earthquakes and hurricanes. The scheme uses MODIS measurements of FRP at 1-km resolution as follows: catagory 1 (less than 100 MW), category 2 (100 to less than 500 MW), category 3 (500 to less than 1000 MW), category 4 (1000 to less than 1500 MW), catagory 5 (greater than or equal to 1500 MW). In most regions of the world, over 90% of fires fall into category 1, while only less than 1% fall into each of categories 3 to 5, although these proportions may differ significantly from day to day and by season. The frequency of occurence of the larger fires is region specific, and could not be explained by ecosystem type alone. Time-series analysis of the propertions of higher category fires based on MODIS measured FRP from 2002 to 2006 does not show any moticeable trend because of the short time period.

Ichoku, Charles↗
NASA NTRS2010

Clear-Sky Remote Sensing in the Vicinity of Clouds: What Can Be Learned About Aerosol Changes?

Studies on aerosol direct and indirect effects require a precise separation of cloud-free and cloudy air. However, separation between cloud-free and cloudy areas from remotely-sensed measurements is ambiguous. The transition zone in the regions around clouds often stretches out tens of km, which are neither precisely clear nor precisely cloudy. We study the transition zone between cloud-free and cloudy air using MODerate-resolution Imaging Spectroradiometer (MODIS) and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements. Both instruments show enhanced clear-sky reflectance (MODIS) and clear-sky backscatterer (CALIPSO) near clouds. Analyzing a large dataset of MODIS observations we examine the effect of three-dimensional (3D) radiative interactions between clouds and cloud-free areas, also known as a cloud adjacency effect. Comparing with CALIPSO clear-sky backscatterer measurements, we show that the cloud adjacency effect may be responsible for a large portion of the enhanced clear sky reflectance observed by MODIS. While aerosol particles are responsible for a large part of the near-cloud enhancements in CALIPSO observations, misidentified or undetected cloud particles are also likely to contribute. As a result, both the nature of these particles (cloud vs. aerosol) and the processes creating them need to be clarified using a quantitative assessment of remote sensing limitations in particle detection and identification. "The width and ubiquity of the transition zone near clouds imply that studies of-aerosol-cloud -interactions and aerosol direct radiative effects need to account for aerosol changes near clouds. Not accounted, these changes can cause systematic biases toward smaller aerosol radiative forcing. On the other hand, including aerosol products near clouds despite their uncertainties may overestimate aerosol radiative forcing. Therefore, there is an urgent need for developing methods that can assess and account for remote sensing challenges and thus allow for including the transition zone into the study. We describe a simple model that estimates the cloud-induced enhanced reflectances of cloud-free areas in the vicinity of clouds. The model assumes that the enhancement is due entirely to Rayleigh scattering and is therefore bigger at shorter wavelengths, thus creating a so-called apparent "bluing" of aerosols in remote sensing retrievals.

Marshak, Alexander↗
NASA NTRS2010

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station a are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS- derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant trend toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management.

Hall, Dorothy K.↗
NASA NTRS2010

A Methodology to Assess the Impact of Optical and Electronic Crosstalk in a New Generation of Sensors Using Heritage Sensors

Electronic and optical crosstalk are radiometric challenges that often exist in the focal plane design in many sensors Such as MODIS. A methodology is described to assess the impact due to optical and electronic crosstalk on the measured radiance, and thereafter, the retrieval of geophysical products using MODIS Level I data sets. Based on a postulated set of electronic and optical crosstalk coefficients, and a set of MODIS scenes, we have simulated a system signal contamination on any detector on a focal plane when another detector on that focal plane is stimulated with a geophysical signal. The original MODIS scenes and the crosstalk impacted scenes can be used with validated geophysical algorithms to derive the final data products. Products contaminated with crosstalk are then compared to those without contamination to assess the impact magnitude and location, and will allow us to separate Out-Of-Band (OOB) leaks from hand-to-hand optical crosstalk, and identify potential failures to meet climate research requirements.

Oudrari, Hassan↗