ALBERT

Description: Over 20 years of investigation by NASA and NOAA scientists and Doppler lidar technologists into a global wind profiling mission from earth orbit have led to the current favored concept of an instrument with both coherent- and direct-detection pulsed Doppler lidars (i.e., a hybrid Doppler lidar) and a stepstare beam scanning approach covering several azimuth angles with a fixed nadir angle. The nominal lidar wavelengths are 2 microns for coherent detection, and 0.355 microns for direct detection. The two agencies have also generated two sets of sophisticated wind measurement requirements for a space mission: science demonstration requirements and operational requirements. The requirements contain the necessary details to permit mission design and optimization by lidar technologists. Simulations have been developed that connect the science requirements to the wind measurement requirements, and that connect the wind measurement requirements to the Doppler lidar parameters. The simulations also permit trade studies within the multi-parameter space. These tools, combined with knowledge of the state of the Doppler lidar technology, have been used to conduct space instrument and mission design activities to validate the feasibility of the chosen mission and lidar parameters. Recently, the NRC Earth Science Decadal Survey recommended the wind mission to NASA as one of 15 recommended missions. A full description of the wind measurement product from these notional missions and the possible trades available are presented in this paper.

Description: The Committee on Earth Observation Satellites (CEOS) provides a brief to the Goddard Institute for Space Studies (GISS) regarding the CEOS Systems Engineering Office (SEO) and current work on climate requirements and analysis. A "system framework" is provided for the Global Earth Observation System of Systems (GEOSS). SEO climate-related tasks are outlined including the assessment of essential climate variable (ECV) parameters, use of the "systems framework" to determine relevant informational products and science models and the performance of assessments and gap analyses of measurements and missions for each ECV. Climate requirements, including instruments and missions, measurements, knowledge and models, and decision makers, are also outlined. These requirements would establish traceability from instruments to products and services allowing for benefit evaluation of instruments and measurements. Additionally, traceable climate requirements would provide a better understanding of global climate models.

Description: Laser beams emitted from the Geoscience Laser Altimeter System (GLAS), as well as other space-borne laser instruments, can only penetrate clouds to a limit of a few optical depths. As a result, only optical depths of thinner clouds (〈 about 3 for GLAS) are retrieved from the reflected lidar signal. This paper presents a comprehensive study of possible retrievals of optical depth of thick clouds using solar background light and treating GLAS as a solar radiometer. To do so we first calibrate the reflected solar radiation received by the photon-counting detectors of GLAS' 532 nm channel, which is the primary channel for atmospheric products. The solar background radiation is regarded as a noise to be subtracted in the retrieval process of the lidar products. However, once calibrated, it becomes a signal that can be used in studying the properties of optically thick clouds. In this paper, three calibration methods are presented: (I) calibration with coincident airborne and GLAS observations; (2) calibration with coincident Geostationary Operational Environmental Satellite (GOES) and GLAS observations of deep convective clouds; (3) calibration from the first principles using optical depth of thin water clouds over ocean retrieved by GLAS active remote sensing. Results from the three methods agree well with each other. Cloud optical depth (COD) is retrieved from the calibrated solar background signal using a one-channel retrieval. Comparison with COD retrieved from GOES during GLAS overpasses shows that the average difference between the two retrievals is 24%. As an example, the COD values retrieved from GLAS solar background are illustrated for a marine stratocumulus cloud field that is too thick to be penetrated by the GLAS laser. Based on this study, optical depths for thick clouds will be provided as a supplementary product to the existing operational GLAS cloud products in future GLAS data releases.

Description: Quality of aerosol retrievals and atmospheric correction depends strongly on accuracy of the cloud mask (CM) algorithm. The heritage CM algorithms developed for AVHRR and MODIS use the latest sensor measurements of spectral reflectance and brightness temperature and perform processing at the pixel level. The algorithms are threshold-based and empirically tuned. They don't explicitly address the classical problem of cloud search, wherein the baseline clear-skies scene is defined for comparison. Here, we report on a new CM algorithm which explicitly builds and maintains a reference clear-skies image of the surface (refcm) using a time series of MODIS measurements. The new algorithm, developed as part of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm for MODIS, relies on fact that clear-skies images of the same surface area have a common textural pattern, defined by the surface topography, boundaries of rivers and lakes, distribution of soils and vegetation etc. This pattern changes slowly given the daily rate of global Earth observations, whereas clouds introduce high-frequency random disturbances. Under clear skies, consecutive gridded images of the same surface area have a high covariance, whereas in presence of clouds covariance is usually low. This idea is central to initialization of refcm which is used to derive cloud mask in combination with spectral and brightness temperature tests. The refcm is continuously updated with the latest clear-skies MODIS measurements, thus adapting to seasonal and rapid surface changes. The algorithm is enhanced by an internal dynamic land-water-snow classification coupled with a surface change mask. An initial comparison shows that the new algorithm offers the potential to perform better than the MODIS MOD35 cloud mask in situations where the land surface is changing rapidly, and over Earth regions covered by snow and ice.

Description: This paper describes an AERONET-based Surface Reflectance Validation Network (ASRVN) and its dataset of spectral surface bidirectional reflectance and albedo based on MODIS TERRA and AQUA data. The ASRVN is an operational data collection and processing system. It receives 50x50 square kilometer subsets of MODIS L1B data from MODAPS and AERONET aerosol and water vapor information. Then it performs an accurate atmospheric correction for about 100 AERONET sites based on accurate radiative transfer theory with high quality control of the input data. The ASRVN processing software consists of L1B data gridding algorithm, a new cloud mask algorithm based on a time series analysis, and an atmospheric correction algorithm. The atmospheric correction is achieved by fitting the MODIS top of atmosphere measurements, accumulated for 16-day interval, with theoretical reflectance parameterized in terms of coefficients of the LSRT BRF model. The ASRVN takes several steps to ensure high quality of results: 1) cloud mask algorithm filters opaque clouds; 2) an aerosol filter has been developed to filter residual semi-transparent and sub-pixel clouds, as well as cases with high inhomogeneity of aerosols in the processing area; 3) imposing requirement of consistency of the new solution with previously retrieved BRF and albedo; 4) rapid adjustment of the 16-day retrieval to the surface changes using the last day of measurements; and 5) development of seasonal back-up spectral BRF database to increase data coverage. The ASRVN provides a gapless or near-gapless coverage for the processing area. The gaps, caused by clouds, are filled most naturally with the latest solution for a given pixels. The ASRVN products include three parameters of LSRT model (k(sup L), k(sup G), k(sup V)), surface albedo, NBRF (a normalized BRF computed for a standard viewing geometry, VZA=0 deg., SZA=45 deg.), and IBRF (instantaneous, or one angle, BRF value derived from the last day of MODIS measurement for specific viewing geometry) for MODIS 500m bands 1-7. The results are produced daily at resolution of 1 km in gridded format. We also provide cloud mask, quality flag and a browse bitmap image. The new dataset can be used for a wide range of applications including validation analysis and science research.

Description: The most practical way to get a spatially broad and continuous measurements of the surface temperature in the data-sparse cryosphere is by satellite remote sensing. The uncertainties in satellite-derived LSTs must be understood to develop internally-consistent decade-scale land-surface temperature (LST) records needed for climate studies. In this work we assess satellite-derived "clear-sky" LST products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), and LSTs derived from the Enhanced Thematic Mapper Plus (ETM+) over snow and ice on Greenland. When possible, we compare satellite-derived LSTs with in-situ air-temperature observations from Greenland Climate Network (GC-Net) automatic-weather stations (AWS). We find that MODIS, ASTER and ETM+ provide reliable and consistent LSTs under clear-sky conditions and relatively-flat terrain over snow and ice targets over a range of temperatures from -40 to 0 C. The satellite-derived LSTs agree within a relative RMS uncertainty of approx.0.5 C. The good agreement among the LSTs derived from the various satellite instruments is especially notable since different spectral channels and different retrieval algorithms are used to calculate LST from the raw satellite data. The AWS record in-situ data at a "point" while the satellite instruments record data over an area varying in size from: 57 X 57 m (ETM+), 90 X 90 m (ASTER), or to 1 X 1 km (MODIS). Surface topography and other factors contribute to variability of LST within a pixel, thus the AWS measurements may not be representative of the LST of the pixel. Without more information on the local spatial patterns of LST, the AWS LST cannot be considered valid ground truth for the satellite measurements, with RMS uncertainty approx.2 C. Despite the relatively large AWS-derived uncertainty, we find LST data are characterized by high accuracy but have uncertain absolute precision.

Description: Dual-polarization weather radars have evolved significantly in the last three decades culminating in the operational deployment by the National Weather Service. In addition to operational applications in the weather service, dual-polarization radars have shown significant potential in contributing to the research fields of ground based remote sensing of rainfall microphysics, study of precipitation evolution and hydrometeor classification. Furthermore the dual-polarization radars have also raised the awareness of radar system aspects such as calibration. Microphysical characterization of precipitation and quantitative precipitation estimation are important applications that are critical in the validation of satellite borne precipitation measurements and also serves as a valuable tool in algorithm development. This paper presents the important role played by dual-polarization radar in validating space borne precipitation measurements. Starting from a historical evolution, the various configurations of dual-polarization radar are presented. Examples of raindrop size distribution retrievals and hydrometeor type classification are discussed. The quantitative precipitation estimation is a product of direct relevance to space borne observations. During the TRMM program substantial advancement was made with ground based polarization radars specially collecting unique observations in the tropics which are noted. The scientific accomplishments of relevance to space borne measurements of precipitation are summarized. The potential of dual-polarization radars and opportunities in the era of global precipitation measurement mission is also discussed.

Description: Coincident observations made over the Moroccan desert during the Sahara mineral dust experiment (SAMUM) 2006 field campaign are used both to validate aerosol amount and type retrieved from multi-angle imaging spectroradiometer (MISR) observations, and to place the suborbital aerosol measurements into the satellite s larger regional context. On three moderately dusty days during which coincident observations were made, MISR mid-visible aerosol optical thickness (AOT) agrees with field measurements point-by-point to within 0.05 0.1. This is about as well as can be expected given spatial sampling differences; the space-based observations capture AOT trends and variability over an extended region. The field data also validate MISR s ability to distinguish and to map aerosol air masses, from the combination of retrieved constraints on particle size, shape and single-scattering albedo. For the three study days, the satellite observations (1) highlight regional gradients in the mix of dust and background spherical particles, (2) identify a dust plume most likely part of a density flow and (3) show an aerosol air mass containing a higher proportion of small, spherical particles than the surroundings, that appears to be aerosol pollution transported from several thousand kilometres away.

Description: The hierarchical image segmentation algorithm (referred to as HSEG) is a hybrid of hierarchical step-wise optimization (HSWO) and constrained spectral clustering that produces a hierarchical set of image segmentations. HSWO is an iterative approach to region grooving segmentation in which the optimal image segmentation is found at N(sub R) regions, given a segmentation at N(sub R+1) regions. HSEG's addition of constrained spectral clustering makes it a computationally intensive algorithm, for all but, the smallest of images. To counteract this, a computationally efficient recursive approximation of HSEG (called RHSEG) has been devised. Further improvements in processing speed are obtained through a parallel implementation of RHSEG. This chapter describes this parallel implementation and demonstrates its computational efficiency on a Landsat Thematic Mapper test scene.

Description: This viewgraph presentation describes the Western states Fire Missions (WSFM) that occurred in 2007. The objectives of this mission are: (1) Demonstrate capabilities of UAS to overfly and collect sensor data on widespread fires throughout Western US. (1) Demonstrate long-endurance mission capabilities (20-hours+). (2) Image multiple fires (greater than 4 fires per mission), to showcase extendable mission configuration and ability to either linger over key fires or station over disparate regional fires. (3) Demonstrate new UAV-compatible, autonomous sensor for improved thermal characterization of fires. (4) Provide automated, on-board, terrain and geo-rectified sensor imagery over OTH satcom links to national fire personnel and Incident commanders. (5) Deliver real-time imagery to (within 10-minutes of acquisition). (6) Demonstrate capabilities of OTS technologies (GoogleEarth) to serve and display mission-critical sensor data, coincident with other pertinent data elements to facilitate information processing (WX data, ground asset data, other satellite data, R/T video, flight track info, etc).

Description: Atmospheric aerosols interact with sun light by scattering and absorbing radiation. By changing irradiance of the Earth surface, modifying cloud fractional cover and microphysical properties and a number of other mechanisms, they affect the energy balance, hydrological cycle, and planetary climate [IPCC, 2007]. In many world regions there is a growing impact of aerosols on air quality and human health. The Earth Observing System [NASA, 1999] initiated high quality global Earth observations and operational aerosol retrievals over land. With the wide swath (2300 km) of MODIS instrument, the MODIS Dark Target algorithm [Kaufman et al., 1997; Remer et al., 2005; Levy et al., 2007] currently complemented with the Deep Blue method [Hsu et al., 2004] provides daily global view of planetary atmospheric aerosol. The MISR algorithm [Martonchik et al., 1998; Diner et al., 2005] makes high quality aerosol retrievals in 300 km swaths covering the globe in 8 days. With MODIS aerosol program being very successful, there are still several unresolved issues in the retrieval algorithms. The current processing is pixel-based and relies on a single-orbit data. Such an approach produces a single measurement for every pixel characterized by two main unknowns, aerosol optical thickness (AOT) and surface reflectance (SR). This lack of information constitutes a fundamental problem of the remote sensing which cannot be resolved without a priori information. For example, MODIS Dark Target algorithm makes spectral assumptions about surface reflectance, whereas the Deep Blue method uses ancillary global database of surface reflectance composed from minimal monthly measurements with Rayleigh correction. Both algorithms use Lambertian surface model. The surface-related assumptions in the aerosol retrievals may affect subsequent atmospheric correction in unintended way. For example, the Dark Target algorithm uses an empirical relationship to predict SR in the Blue (B3) and Red (B1) bands from the 2.1 m channel (B7) for the purpose of aerosol retrieval. Obviously, the subsequent atmospheric correction will produce the same SR in the red and blue bands as predicted, i.e. an empirical function of 2.1. In other words, the spectral, spatial and temporal variability of surface reflectance in the Blue and Red bands appears borrowed from band B7. This may have certain implications for the vegetation and global carbon analysis because the chlorophyll-sensing bands B1, B3 are effectively substituted in terms of variability by band B7, which is sensitive to the plant liquid water. This chapter describes a new recently developed generic aerosol-surface retrieval algorithm for MODIS. The Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm simultaneously retrieves AOT and surface bi-directional reflection factor (BRF) using the time series of MODIS measurements.

Description: The long term Advanced Very High Resolution Radiometer-Normalized Difference Vegetation Index (AVHRR-NDVI) record provides a critical historical perspective on vegetation dynamics necessary for global change research. Despite the proliferation of new sources of global, moderate resolution vegetation datasets, the remote sensing community is still struggling to create datasets derived from multiple sensors that allow the simultaneous use of spectral vegetation for time series analysis. To overcome the non-stationary aspect of NDVI, we use an artificial neural network (ANN) to map the NDVI indices from AVHRR to those from MODIS using atmospheric, surface type and sensor-specific inputs to account for the differences between the sensors. The NDVI dynamics and range of MODIS NDVI data at one degree is matched and extended through the AVHRR record. Four years of overlap between the two sensors is used to train a neural network to remove atmospheric and sensor specific effects on the AVHRR NDVI. In this paper, we present the resulting continuous dataset, its relationship to MODIS data, and a validation of the product.

Description: Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. Space based technology in concert with bird migration modeling and geographical information analysis yields new opportunities to shed light on the distribution and movement of organisms on the planet and their sensitivity to human disturbances and environmental changes. At the NASA Goddard Space Flight Center, we are creating ecological forecasting tools for science and application users to address the consequences of loss of wetlands, flooding, drought or other natural disasters such as hurricanes on avian biodiversity and bird migration. We use an individual-based bird biophysical migration model, driven by remotely sensed land surface data, climate and hydrologic data, and biological field observations to study migratory bird responses to environmental change in North America. Simulation allows us to study bird migration across multiple scales and can be linked to mechanistic processes describing the time and energy budget states of migrating birds. We illustrate our approach by simulating the spring migration of pectoral sandpipers from the Gulf of Mexico to Alaska. Mean stopover length and trajectory patterns are consistent with field observations.

Description: We have studied the effects of the 2006 El Nino on tropospheric O3 and CO at tropical and sub-tropical latitudes measured from the OMI and MLS instruments on the Aura satellite. The 2006 El Nino-induced drought allowed forest fires set to clear land to burn out of control during October and November in the Indonesian region. The effects of these fires are clearly seen in the enhancement of GO concentration measured from the MLS instrument. We have used a global model of atmospheric chemistry and transport (GMI CTM) to quantify the relative irrrportance of biomass burning and large scale transport: in producing observed changes in tropospheric O3 and CO . The model results show that during October and November both biomass burning and meteorological changes contributed almost equally to the observed increase in tropospheric O3 in the Indonesian region. The biomass component was 4-6 DU but it was limited to the Indonesian region where the fires were most intense, The dynamical component was 4-8 DU but it covered a much larger area in the Indian Ocean extending from South East Asia in the north to western Australia in the south. By December 2006, the effect of biomass taming was reduced to zero and the obsemed changes in tropospheric O3 were mostly due to dynamical effects. The model results show an increase of 2-3% in the global burden of tropospheric ozone. In comparison, the global burdean of CO increased by 8-12%.

Description: It is intended that Reindeer Mapper/EALAT will be able to provide reindeer herders with an efficient tool for managing the real-time movements and migrations of their herds through enabling improved efficiency in linking different members of the herder settlements or communities and providing real-time local, satellite or other data (e.g., ice melt in lakes and rivers, weather events), thus enabling real time adjustments to herd movements to avoid problems such as changing weather/climate conditions, freeze-thaw "lock-out" problems, or take advantage of availability of better pasturelands along migration routes. The system is being designed to incorporate local data to allow users to bring their own data into the system for analysis in addition to the data provided by the system itself. With the local information of the population, up to date environmental data and habitat characteristics, the system could generate maps depicting important features of interest for reindeer managers. One of the products derived from the planned Reindeer Mapper system will be a web-based graphic display that allows analysts to quickly pinpoint areas of interest such as those with large concentrations of reindeer and provide surrounding environmental information. The system could be automatically updated with near-real-time information such as hourly precipitation and snowfall rate and accumulation, daily surface and air temperatures, and vegetation cover conditions. The system could bring attention to the proximity of human and animal populations as part of the need for control response. A local GIS will bring these many layers together with several supporting models, showing only a straightforward graphic of the real-time situation in the field. Because the system proposed will be operating in the Internet environment, it should be virtually accessible from any network computers and wireless remote access from the field. The International Center for Reindeer Husbandry in Kautokeino, Norway, is providing regional and international coordination of and access to data sets and expertise, and will act as overall clearinghouse for EALAT information.

Description: We develop a land use map discriminating urban surfaces from other cover types over a semiarid region in North Africa and use it in a land surface model to assess the impact of urbanized land on surface energy, water and carbon balances. Unlike in temperate climates where urbanization creates a marked heat island effect, this effect is not strongly marked in semiarid regions. During summer, the urban class results in an additional warming of 1.45 C during daytime and 0.81 C at night compared to that simulated for needleleaf trees under similar climate conditions. Seasonal temperatures show urban areas warmer than their surrounding during summer and slightly cooler in winter. The hydrological cycle is practically "shut down" during summer and characterized by relatively large amount of runoff in winter. We estimate the annual amount of carbon uptake to 1.94 million metric tons with only 11.9% assimilated during the rainy season. However, if urbanization expands to reach 50% of the total area excluding forests, the annual total carbon uptake will decline by 35% and the July mean temperature would increase only 0.10 C, compared to current situation. In contrast, if urbanization expands to 50% of the total land excluding forests and croplands but all short vegetation is replaced by native broadleaf deciduous trees, the annual carbon uptake would increase 39% and the July mean temperature would decrease by 0.9 C, compared to current configuration. These results provide guidelines for urban planners and land use managers and indicate possibilities for mitigating the urban heat.

Description: Seasonal snow cover in South America was examined in this study using passive microwave satellite data from the Scanning Multichannel Microwave Radiometer (SMMR) on board the Nimbus-7 satellite and the Special Sensor Microwave Imagers (SSM/I) onboard Defense Meteorological Satellite Program (DMSP) satellites. For the period from 1979-2006, both snow cover extent and snow water equivalent (snow mass) were investigated during the coldest months (May-September), primarily in the Patagonia area of Argentina and in the Andes of Chile, Argentina and Bolivia, where most of the seasonal snow is found. Since winter temperatures in this region are often above freezing, the coldest winter month was found to be the month having the most extensive snow cover and usually the month having the deepest snow cover as well. Sharp year-to-year differences were recorded using the passive microwave observations. The average snow cover extent for July, the month with the greatest average extent during the 28-year period of record, is 321,674 km(exp 2). In July of 1984, the average monthly snow cover extent was 701,250 km(exp 2) the most extensive coverage observed between 1979 and 2006. However, in July of 1989, snow cover extent was only 120,000 km(exp 2). The 28-year period of record shows a sinusoidal like pattern for both snow cover and snow mass, though neither trend is significant at the 95% level.

Description: Climate models participating in the IPCC Fourth Assessment Report indicate that under a 2xCO2 environment, runoff would increase faster than precipitation overland. However, observations over large U.S watersheds indicate otherwise. This inconsistency suggests that there may be important feedbacks between climate and land surface unaccounted for in the present generation of models. We postulate that the increase in precipitation associated with the increase in CO2 is also increasing vegetation density, which may already be feeding back onto climate. Including this feedback in a climate model simulation resulted in precipitation and runoff trends consistent with observations and reduced the warming by 0.6OC overland. This unaccounted for missing water may be linked to about 10% of the missing land carbon sink. A recent compilation of outputs from 19 coupled atmosphere-ocean general circulation models used in the IPCC Fourth Assessment Report (AR4) shows projected increases in air temperature, precipitation and river discharge for 24 major rivers in the world in response to doubling CO2 by the end of the century (1). The ensemble mean from these models also indicates that, compared to their respective baselines overland, the global mean of the runoff change would increase faster (8.9% per year) than that of the precipitation (5% per year). We analyze century-scale observed annual runoff time-series (1901-2002) over 9 hydrological units covering large regions of the Eastern United States (Fig.1) compiled by the United States Geological Survey (USGS)(2). These regions were selected because they are the most forested; the least water-limited and are not under extensive irrigation. We compare these time-series to similar time-series of observed annual precipitation anomalies spanning the period 1900-1995 (3). Both time-series exhibit a positive longterm trend (Fig. 2); however, in contrast to the analysis of (I), these historic data records show that the rate of precipitation increase is 5.5 % per year, roughly double the rate of runoff increase of 3.1 % per year.

Description: Human demand for food influences the water cycle through diversion and extraction of fresh water needed to support agriculture. Future population growth and economic development alone will substantially increase water demand and much of it for agricultural uses. For many semi-arid lands, socio-economic shifts are likely to exacerbate changes in climate as a driver of future water supply and demand. For these areas in particular, where the balance between water supply and demand is fragile, variations in regional climate can have potentially predictable effect on agricultural production. Satellite data and biophysically-based models provide a powerful method to quantify the interactions between local climate, plant growth and water resource requirements. In irrigated agricultural lands, satellite observations indicate high vegetation density while the precipitation amount indicates otherwise. This inconsistency between the observed precipitation and the observed canopy leaf density triggers the possibility that the observed high leaf density is due to an alternate source of water, irrigation. We explore an inverse process approach using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), climatological data, and the NASA's Simple Biosphere model, SiB2, to quantitatively assess water demand in a semi-arid agricultural land by constraining the carbon and water cycles modeled under both equilibrium (balance between vegetation and prevailing local climate) and nonequilibrium (water added through irrigation) conditions. We postulate that the degree to which irrigated lands vary from equilibrium conditions is related to the amount of irrigation water used. We added water using two distribution methods: The first method adds water on top of the canopy and is a proxy for the traditional spray irrigation. The second method allows water to be applied directly into the soil layer and serves as proxy for drip irrigation. Our approach indicates that over the study site, for the month of July, spray irrigation resulted in an irrigation amount of about 1.4 mm per occurrence with an average frequency of occurrence of 24.6 hours. The simulated total monthly irrigation for July was 34.85 mm. In contrast, the drip irrigation resulted in less frequent irrigation events with an average water requirement about 57% less than that simulated during the spray irrigation case. The efficiency of the drip irrigation method rests on its reduction of the canopy interception loss compared to the spray irrigation method. When compared to a country-wide average estimate of irrigation water use, our numbers are quite low. We would have to revise the reported country level estimates downward to 17% or less

Description: Many earth science modeling applications employ continuous input data fields derived from satellite data. Environmental factors, sensor limitations and algorithmic constraints lead to data products of inherently variable quality. This necessitates interpolation of one form or another in order to produce high quality input fields free of missing data. The present research tests several interpolation techniques as applied to satellite-derived leaf area index, an important quantity in many global climate and ecological models. The study evaluates and applies a variety of interpolation techniques for the Moderate Resolution Imaging Spectroradiometer (MODIS) Leaf-Area Index Product over the time period 2001-2006 for a region containing the conterminous United States. Results indicate that the accuracy of an individual interpolation technique depends upon the underlying land cover. Spatial interpolation provides better results in forested areas, while temporal interpolation performs more effectively over non-forest cover types. Combination of spatial and temporal approaches offers superior interpolative capabilities to any single method, and in fact, generation of continuous data fields requires a hybrid approach such as this.

Description: Coincident observations made over the Moroccan desert during the SAhara Mineral dUst experiMent (SAMUM) 2006 field campaign are used both to validate aerosol amount and type retrieved from Multi-angle Imaging SpectroRadiometer (MISR) observations, and to place the sub-orbital aerosol measurements into the satellite's larger regional context. On three moderately dusty days for which coincident observations were made, MISR mid-visible aerosol optical thickness (AOT) agrees with field measurements point-by-point to within 0.05 to 0.1. This is about as well as can be expected given spatial sampling differences; the space-based observations capture AOT trends and variability over an extended region. The field data also validate MISR's ability to distinguish and to map aerosol air masses, from the combination of retrieved constraints on particle size, shape, and single-scattering albedo. For the three study days, the satellite observations (a) highlight regional gradients in the mix of dust and background spherical particles, (b) identify a dust plume most likely part of a density flow, and (c) show an air mass containing a higher proportion of small, spherical particles than the surroundings, that appears to be aerosol pollution transported from several thousand kilometers away.

Description: Two decades of war have severely weakened Afghanistan s economy and infrastructure. Along with larger impacts on civil stability, education and health care, the current conflict in Afghanistan has resulted in widespread hunger and destitution. The 2005 National Risk and Vulnerability Assessment conducted by the United Nations found that 6.6 million Afghans do not meet their minimum food requirements and approximately 400,000 people each year are seriously affected by natural disasters, such as droughts, floods and extreme weather conditions. Given the poor security situation in the country, systems that will enable remote observations of variations of climate and their impacts on food production are critical for providing an appropriate and timely response. This chapter describes the remote sensing systems and food security analyses that the US Agency for International Development s Famine Early Warning Systems Network (FEWS NET) conducts in Afghanistan to monitor and provide information to international donors to ensure that adequate assistance is provided during this time of development and recovery.

Description: Laboratory-based bidirectional reflectance distribution functions of radiometric tarp samples used in the vicarious calibration of Earth remote sensing satellite instruments are presented in this paper. The results illustrate the BRDF dependence on the orientation of the tarps weft and warp threads. The study was performed using the GSFC scatterometer at incident zenith angles of 0 deg, 10 deg, and 30 deg; scatter zenith angles from 0 deg. to 60 deg.; and scatter azimuth angles of 0 deg., 45 deg., 90 deg., 135 deg. and 180 deg. The wavelengths were 485nm, 550nm, 633nm and 800nm. The tarp's weft and warp dependence on BRDF is well defined at all measurement geometries and wavelengths. The BRDF difference can be as high as 8% at 0o incident angle and 12% at 30 deg. incident angle. The fitted BRDF data shows a very small discrepancy from the measured ones. New data on the forward and backscatter properties of radiometric tarps are reported. The backward scatter is well pronounced for the white samples. The black sample has well pronounced forward scatter. The provided BRDF characterization of radiometric tarps is an excellent reference for anyone interested in using tarps for radiometric calibrations. The results are NIST traceable.

Description: In 2007, the citizens of Harare, Zimbabwe began experiencing an intense food security crisis. The crisis, due to a complex mix of poor government policies, high inflation rates and production decline due to drought, resulted in a massive increase in the number of food insecure people in Harare. The international humanitarian aid response to this crisis was largely successful due to the early agreement among donors and humanitarian aid officials as to the size and nature of the problem. Remote sensing enabled an early and decisive movement of resources greatly assisting the delivery of food aid in a timely manner. Remote sensing data gave a clear and compelling assessment of significant crop production shortfalls, and provided donors of humanitarian assistance a single number around which they could come to agreement. This use of remote sensing data typifies how remote sensing may be used in early warning systems in Africa.

Description: This book describes the interdisciplinary work of USAID's Famine Early Warning System Network (FEWS NET) and its influence on how food security crises are identified, documented and the kind of responses that result. The book describes FEWS NET's systems and methods for using satellite remote sensing to identify and describe how biophysical hazards impact the lives and livelihoods of the population where they occur. It presents several illustrative case studies that will demonstrate the integration of both physical and social science disciplines in its work. FEWS NET s operational needs have driven science in biophysical remote sensing applications through its collaboration with the US Geological Survey, the National Aeronautics and Space Administration, National Oceanographic and Atmospheric Administration, and US Department of Agriculture, as well as methodologies in the social science domain through its support of the US Agency for International Development, UNWorld Food Program and numerous international non-governmental organizations such as Save the Children, Oxfam and others. Because FEWS NET is an organization that must provide a global picture of food insecurity to decision makers, the information it relies on are by necessity observable and able to be documented. Thus many aspects of traditional livelihood analysis, for example, cannot be used by FEWS NET as they rely upon relationships, and ways of expressing power and knowledge at the local scale that cannot be easily scaled up to express variations in access to food at a community level. The book focuses on the ways that remote sensing information is transformed into an understanding of the actions that must be taken in order to ensure that lives and livelihoods are protected, including describing the remote sensing observations and models needed to identify hazards and the information gathering requirements and analytical frameworks needed to understand their impact. Its focus is primarily analysis conducted in Africa, but also touches upon FEWS NET s work in Central America, Haiti and Afghanistan. As an organization that seeks to integrate social and physical science methodologies and strategies into its work on a daily basis, it is a fascinating and rich example of interdisciplinary knowledge generation and innovation.

Description: The Modern. Era Retrospective-analysis for Research and Applications (MERRA) reanalyses has produced several years of data, on the way to a completing. the 1979-present modern satellite era. Here, we present a preliminary evaluation of those years currently available, includin g comparisons with the existing long reanalyses (ERA40, JRA25 and NCE P I and II) as well as with global data sets for the water and energy cycle Time series shows that the MERRA budgets can change with some of the variations in observing systems. We will present all terms of the budgets in MERRA including the time rates of change and analysis increments (tendency due to the analysis of observations)

Description: Measurement of fire radiative energy (FRE) release rate or power (FRP) from satellite provides a vital mechanism for distinguishing different strengths of fires. Analysis of 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, showed instantaneous FRP values ranging between 0.02 MW and 1866 MW, to which simple thresholds can be applied to categorize fires by strength, in a similar fashion as the strengths of earthquakes and hurricanes. Analysis of regional mean FRP per unit area of land (FRP flux) shows that at peak fire season in certain regions, fires can be responsible for up to 0.2 W/m2 at peak time of day. When considered as the active fire contribution to the direct surface radiative forcing (RF) in the different fire regions, this order of magnitude of FRF fluxes is non negligible. It has been determined experimentally that the amount of FRE released by a fire over the course of its duration is directly proportional to the amount of biomass consumed by it. Furthermore, at the satellite observation scale, the rate of release of FRE (i.e. FRP) is proportional to the rate of biomass consumption, and that of emission of smoke particulates and eventually also other smoke constituents. Therefore, current research efforts are geared toward deriving simple parameterizations that will facilitate direct input of FRP measurements in models, not only to improve the accuracy of burned-biomass and smoke emissions estimations, but also to reduce the hitherto practiced heavy reliance on multiple indirect parameters with indeterminate uncertainties.

Description: The first-ever true-color, high-resolution digital mosaic of Antarctica has been produced from nearly 11 00 Landsat-7 ETM+ images. This project is an early 1999-2001 benchmark data set of the International Polar Year and represents a close and successful collaboration between NASA, USGS, the British Antarctic Survey and the National Science Foundation. The production of the mosaic required the development of new procedures for treating sensor saturation, adjusting for non-diffusive reflectance and for balancing color between images to remove distracting image edges. All adjustments were physically based to achieve the goal that each pixel's value is surface reflectance. This makes this mosaic more than just a pretty picture to guide users to individual scenes, but one where the mosaics can be used directly for quantitative research. The 15-m resolution, pan-sharpened mosaic, numerous derivative mosaics that enhance various ice sheet features, and the individual scenes are all served to the public via a web site hosted by the USGS. This site also enables on-line exploration of the various mosaics, including panning and zooming functions. Datasets can be customized by the user and downloaded. An associated web site, hosted by NASA, uses the mosaic as a means to demonstrate the value of satellite imagery of Antarctica. It is hoped this data set will enable the public and researcher alike a new and realistic view of the seventh continent.

Description: As part of an ongoing effort to validate satellite remote sensing snow products for the recentlydeveloped U.S. Air Force Weather Agency (AFWA) - NASA blended snow product, Satellite and in-situ data for snow extent and snow water equivalent (SWE) are evaluated in Finland for the 2006-2007 snow season Finnish Meteorological Institute (FMI) daily weather station data and Finnish Environment Institute (SYKE) bi-monthly snow course data are used as ground truth. Initial comparison results display positive agreement between the AFWA NASA Snow Algorithm (ANSA) snow extent and SWE maps and in situ data, with discrepancies in accordance with known AMSR-E and MODIS snow mapping limitations. Future ANSA product improvement plans include additional validation and inclusion of fractional snow cover in the ANSA data product. Furthermore, the AMSR-E 19 GHz (horizontal channel) with the difference between ascending and descending satellite passes (Diurnal Amplitude Variations, DAV) will be used to detect the onset of melt, and QuikSCAT scatterometer data (14 GHz) will be used to map areas of actively melting snow.

Description: We demonstrate an ensemble-based radiometric data assimilation (DA) methodology for estimating snow depth and snow grain size using ground-based passive microwave (PM) observations at 18.7 and 36.5 GHz collected during the NASA CLPX-1, March 2003, Colorado, USA. A land surface model was used to develop a prior estimate of the snowpack states, and a radiative transfer model was used to relate the modeled states to the observations. Snow depth bias was -53.3 cm prior to the assimilation, and -7.3 cm after the assimilation. Snow depth estimated by a non-DA-based retrieval algorithm using the same PM data had a bias of -18.3 cm. The sensitivity of the assimilation scheme to the grain size uncertainty was evaluated; over the range of grain size uncertainty tested, the posterior snow depth estimate bias ranges from -2.99 cm to -9.85 cm, which is uniformly better than both the prior and retrieval estimates. This study demonstrates the potential applicability of radiometric DA at larger scales.

Description: The objective of the program is to assess the feasibility of combining a dust transport model with MODIS derived phenology to study pollen transport for integration with a public health decision support system. The use of pollen information has specifically be identified as a critical need by the New Mexico State Health department for inclusion in the Environmental Public Health Tracking (EPHT) program. Material and methods: Pollen can be transported great distances. Local observations of plan phenology may be consistent with the timing and source of pollen collected by pollen sampling instruments. The Dust REgional Atmospheric Model (DREAM) is an integrated modeling system designed to accurately describe the dust cycle in the atmosphere. The dust modules of the entire system incorporate the state of the art parameterization of all the major phases of the atmospheric dust life such as production, diffusion, advection, and removal. These modules also include effects of the particles size distribution on aerosol dispersion. The model was modified to use pollen sources instead of dust. Pollen release was estimated based on satellite-derived phenology of key plan species and vegetation communities. The MODIS surface reflectance product (MOD09) provided information on the start of the plant growing season, growth stage, and pollen release. The resulting deterministic model is useful for predicting and simulating pollen emission and downwind concentration to study details of phenology and meteorology and their dependencies. The proposed linkage in this project provided critical information on the location timing and modeled transport of pollen directly to the EPHT〉 This information is useful to support the centers for disease control and prevention (CDC)'s National EPHT and the state of New Mexico environmental public health decision support for asthma and allergies alerts.

Description: Fires bum many vegetated regions of the world to a variety of degrees and frequency depending on season. Extensive biomass burning occurs in most parts of sub-Saharan Africa, posing great threat to ecosystem stability among other real and potential adverse impacts. In Africa, such landscape-scale fires are used for various agricultural purposes, including land clearing and hunting, although there may be a limited number of cases of fires ignited by accident or due to arson. Satellite remote sensing provides the most practical means of mapping fires, because of their sudden and aggressive nature coupled with the tremendous heat they generate. Recent advancements in satellite technology has enabled, not only the identification of fire locations, but also the measurement of fire radiative energy (FRE) release rate or power (FRP), which has been found to have a direct linear relationship with the rate of biomass combustion. A recent study based on FRP measurements from the Moderate-resolution imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites revealed that, among all the regions of the world where fires occur, African regions rank the highest in the intensity of biomass burning per unit area of land during the peak of the burning season. In this study, we will analyze the burning patterns in West Africa during the last several years and examine the extent of their impacts on the ecosystem dynamics, using a variety of satellite data. The study introduces a unique methodology that can be used to build up the knowledge base from which decision makers can obtain scientific information in fomulating policies for regulating biomass burning in the region.

Description: The MODerate resolution Imaging Spectroradiometer (MODIS) aerosol algorithms have been working steadily since early 2000 to transform the MODIS-measured spectral solar reflectance from the Earth's surface and atmosphere into a variety of aerosol products. In this lecture I will proceed through a survey of these products, answering the following questions as I proceed. What are the products? How do they compare with ground truth? How do we use these products to describe the global aerosol system? Are aerosols increasing or decreasing? How do aerosols affect climate and clouds?

Description: Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. Outbreaks of Asian dust storms occur often in the arid and semi-arid areas of northwestern China -about 1.6x10(exp 6) square kilometers including the Gobi and Taklimakan deserts- with continuous expanding of spatial coverage. These airborne dust particles, originating in desert areas far from polluted regions, interact with anthropogenic sulfate and soot aerosols emitted from Chinese mega-cities during their transport over the mainland. Adding the intricate effects of clouds and marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from their sources. Furthermore, these aerosols, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol properties (e.g., optical thickness, single scattering albedo) over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. This new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Reasonable agreements have been achieved between Deep Blue retrievals of aerosol optical thickness and those directly from AERONET sunphotometers over desert and semi-desert regions. New Deep Blue products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. Long-term satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the Asian dust storm outbreaks. In addition, monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Description: The Balloon-borne Experiment with a Superconducting Spectrometer, BESS, has been developed to study elementary particle phenomena in the early universe through measurements of low energy antiprotons to investigate their origin and through a search for antihelium. The BESS collaboration carried out nine northern latitude flights between 1993 and 2002. BESS-Polar is an advanced program of the BESS collaboration to study these topics with much greater precision using long duration flights above Antarctica. The BESS-Polar spectrometer was successfully developed to accumulate much larger numbers of events during long duration flights around the South Pole. Approximately a factor of four reductions in the amount of material in the particle beam enables measurement of much lower energy antiprotons down to 100 MeV (at top of atmosphere). The first BESS-Polar flight (BESS-Polar I) of 8.5 days was carried out above Antarctica in December 2004. recording 900 million cosmic-ray events. The second BESS-Polar flight (BESS-Polar 11) was successfully carried out in the austral summer season of 2007-2008. Based on experience with BESS-Polar I, the spectrometer was improved in performance and achieved long term stability during the flight. A newly constructed magnet with a larger liquid He capacity and improved thermal insulation and an upgraded data storage system with larger capacity of hard disk drives (HDDs) enabled longer observation time. BESS-Polar II was launched on December 22, 2007 from Williams Field, McMurdo Station, in Antarctica. The spectrometer worked properly and observed cosmic rays for about 24.5 days at float altitude, recording 4.6 billion events on the HDDs until the limit of the magnet operation was reached on January 16, 2008. The flight was terminated and the spectrometer was safely landed on the West Antarctic ice sheet (1000 km from the South Pole) on January 21, 2008. Here, the BESS-Polar instrument is discussed, highlighting improvements made for BESS-Polar II, and overviews of the flight and performance are reported.

Description: The CALIPSO and Twilight Zone (CATZ) field campaign was carried out between June 26th and August 29th of 2007 in the multi-state Maryland-Virginia-Pennsylvania region of the U.S. to study aerosol properties and cloud-aerosol interactions during overpasses of the CALIPSO satellite. Field work was conducted on selected days when CALIPSO ground tracks occurred in the region. Ground-based measurements included data from multiple Cimel sunphotometers that were placed at intervals along a segment of the CALIPSO ground-track. These measurements provided sky radiance and AOD measurements to enable joints inversions and comparisons with CALIPSO retrievals. As part of this activity, four ground-based lidars provided backscatter measurements (at 523 nm) in the region. Lidars at University of Maryland Baltimore County (Catonsville, MD) and Goddard Space Flight Center (Greenbelt, MD) provided continuous data during the campaign, while two micro-pulse lidar (MPL) systems were temporarily stationed at various field locations directly on CALIPSO ground-tracks. As a result, thirteen on-track ground-based lidar observations were obtained from eight different locations in the region. In some cases, nighttime CALIPSO coincident measurements were also obtained. In most studies reported to date, ground-based lidar validation efforts for CALIPSO rely on systems that are at fixed locations some distance away from the satellite ground-track. The CATZ ground-based lidar data provide an opportunity to examine vertical structure properties of aerosols and clouds both on and off-track simultaneously during a CALIPSO overpass. A table of available ground-based lidar measurements during this campaign will be presented, along with example backscatter imagery for a number of coincident cases with CALIPSO. Results indicate that even for a ground-based measurements directly on-track, comparisons can still pose a challenge due to the differing spatio-temporal properties of the ground and satellite observations. The multiple-lidar data during the CATZ campaign is expected to provide additional information on regional aerosol and cloud dynamics for give overpass, and enable a more realistic assessment of ground-to-satellite correlations. Future work is anticipated to finalize calibrated lidar backscatter profiles and utilization of wind trajectory information to further enable comparisons to CALIPS data.

Description: The fifth generation of the Goddard Earth Observing System (GEOS-5) Data Assimilation System (DAS) is a 3d-var system that uses the Grid-point Statistical Interpolation (GSI) system developed in collaboration with NCEP, and a general circulation model developed at Goddard, that includes the finite-volume hydrodynamics of GEOS-4 wrapped in the Earth System Modeling Framework and physical packages tuned to provide a reliable hydrological cycle for the integration of the Modern Era Retrospective-analysis for Research and Applications (MERRA). This MERRA system is essentially complete and the next generation GEOS is under intense development. A prototype next generation system is now complete and has been producing preliminary results. This prototype system replaces the GSI-based Incremental Analysis Update procedure with a GSI-based 4d-var which uses the adjoint of the finite-volume hydrodynamics of GEOS-4 together with a vertical diffusing scheme for simplified physics. As part of this development we have kept the GEOS-5 IAU procedure as an option and have added the capability to experiment with a First Guess at the Appropriate Time (FGAT) procedure, thus allowing for at least three modes of running the data assimilation experiments. The prototype system is a large extension of GEOS-5 as it also includes various adjoint-based tools, namely, a forecast sensitivity tool, a singular vector tool, and an observation impact tool, that combines the model sensitivity tool with a GSI-based adjoint tool. These features bring the global data assimilation effort at Goddard up to date with technologies used in data assimilation systems at major meteorological centers elsewhere. Various aspects of the next generation GEOS will be discussed during the presentation at the Workshop, and preliminary results will illustrate the discussion.

Description: Accurate representation of the physical and radiative properties of clouds in climate models continues to be a challenge. At present, both remote sensing observations and modeling of microphysical properties of clouds rely heavily on parameterizations or assumptions on particle size distribution (PSD) and cloud phase. In this study, we compare Ice Water Path (IWP), an important physical and radiative property that provides the amount of ice present in a cloud column, using measurements obtained via three different retrieval strategies. The datasets we use in this study include Visible/Near-IR IWP from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument flying aboard the Aqua satellite, Radar-only IWP from the CloudSat instrument operating at 94 GHz, and NOAA/NESDIS operational IWP from the 89 and 157 GHz channels of the Microwave Humidity Sounder (MHS) instrument flying aboard the NOAA-18 satellite. In the Visible/Near-IR, IWP is derived from observations of optical thickness and effective radius. CloudSat IWP is determined from measurements of cloud backscatter and assumed PSD. MHS IWP retrievals depend on scattering measurements at two different, non-water absorbing channels, 89 and 157 GHz. In order to compare IWP obtained from these different techniques and collected at different vertical and horizontal resolutions, we examine summertime cases in the tropics (30S - 30N) when all 3 satellites are within 4 minutes of each other (approximately 1500 km). All measurements are then gridded to a common 15 km x 15 km box determined by MHS. In a grid box comparison, we find CloudSat to report the highest IWP followed by MODIS, followed by MHS. In a statistical comparison, probability density distributions show MHS with the highest frequencies at IWP of 100-1000 g/m(exp 2) and CloudSat with the longest tail reporting IWP of several thousands g/m(exp 2). For IWP greater than 30 g/m(exp 2), MODIS is consistently higher than CloudSat, and it is higher at the lower IWPs but lower at the higher IWPs that overlap with MHS. Some of these differences can be attributed to the limitations of the measuring techniques themselves, but some can result from the assumptions made in the algorithms that generate the IWP product. We investigate this issue by creating categories based on various conditions such as cloud type, precipitation presence, underlying liquid water content, and surface type (land vs. ocean) and by comparing the performance of the IWP products under each condition.

Description: I will discuss the science of satellite remote sensing which involves the interpretation and inversion of radiometric measurements made from space. The goal of remote sensing is to retrieve some physical aspects of the medium which are sensitive to the radiation at specific wavelengths. This requires the use of fundamentals of atmospheric radiative transfer. I will talk about atmospheric radiation or, more specifically, about the interactions of solar radiation with aerosols and cloud particles. The focus will be more on cloudy atmospheres. I will also show how a standard one-dimensional approach, that is traced back at least 100 years, can fail to interpret the complexity of real clouds. I n these cases, three-dimensional radiative transfer should be used. Examples of satellite retrievals will illustrate the cases.

Description: This presentation will summarize ongoing 'chemical observing system simulation experiment (OSSE)' work in the Global Modeling and Assimilation Office (GMAO). Weather OSSEs are being studied in detail, with a 'nature run' based on the European Centre for Medium-Range Weather Forecasts (ECMWF) model that can be sampled by a synthesized suite of satellites that reproduces present-day observations. Chemical OSSEs are based largely on the carbon-cycle project and aim to study (1) how well we can reproduce the observed carbon distribution with the Atmospheric Infrared Sounder (AIRS) and Orbiting Carbon Observatory (OCO) sensors and (2) with what accuracy can we deduce surface sources and sinks of carbon species in an assimilation system.

Description: From radiometric principles, it is expected that the retrieved properties of extensive aerosols and clouds from reflected/emitted measurements by satellite (and/or aircraft) should be consistent with those retrieved from transmitted/emitted radiance observed at the surface. Although space-borne remote sensing observations cover large spatial domain, they are often plagued by contamination of surface signatures. Thus, ground-based in-situ and remote-sensing measurements, where signals come directly from atmospheric constituents, the sun, and/or the Earth-atmosphere interactions, provide additional information content for comparisons that confirm quantitatively the usefulness of the integrated surface, aircraft, and satellite data sets. The development and deployment of SMARTCOMMIT (Surface-sensing Measurements for Atmospheric Radiative Transfer - Chemical, Optical & Microphysical Measurements of In-situ Troposphere) mobile facilities are aimed for the optimal utilization of collocated ground-based observations as constraints to yield higher fidelity satellite retrievals and to determine any sampling bias due to target conditions. To quantify the energetics of the surface-atmosphere system and the atmospheric processes, SMART-COMMIT instruments fall into three categories: flux radiometer, radiance sensor and in-situ probe. In this paper, we will demonstrate the capability of SMART-COMMIT in recent field campaigns (e.g., CRYSTAL-FACE, UAE 2, BASEASIA, NAMMA) that were designed and executed to study the compelling variability in temporal scale of both anthropogenic and natural aerosols (e.g., biomass-burning smoke, airborne dust) and cirrus clouds. We envision robust approaches in which well-collocated ground-based measurements and space-borne observations will greatly advance our knowledge of extensive aerosols and clouds.

Description: Among the many components that contribute to air pollution, airborne mineral dust plays an important role due to its biogeochemical impact on the ecosystem and its radiative-forcing effect on the climate system. In East Asia, dust storms frequently accompany the cold and dry air masses that occur as part of springtime cold front systems. Outbreaks of Asian dust storms occur often in the arid and semi-arid areas of northwestern China -about 1.6x10(exp 6) square kilometers including the Gobi and Taklimakan deserts- with continuous expanding of spatial coverage. These airborne dust particles, originating in desert areas far from polluted regions, interact with anthropogenic sulfate and soot aerosols emitted from Chinese megacities during their transport over the mainland. Adding the intricate effects of clouds and marine aerosols, dust particles reaching the marine environment can have drastically different properties than those from their sources. Furthermore, these aerosols, once generated over the source regions, can be transported out of the boundary layer into the free troposphere and can travel thousands of kilometers across the Pacific into the United States and beyond. In this paper, we will demonstrate the capability of a new satellite algorithm to retrieve aerosol properties (e.g., optical thickness, single scattering albedo) over bright-reflecting surfaces such as urban areas and deserts. Such retrievals have been difficult to perform using previously available algorithms that use wavelengths from the mid-visible to the near IR because they have trouble separating the aerosol signal from the contribution due to the bright surface reflectance. This new algorithm, called Deep Blue, utilizes blue-wavelength measurements from instruments such as SeaWiFS and MODIS to infer the properties of aerosols, since the surface reflectance over land in the blue part of the spectrum is much lower than for longer wavelength channels. Reasonable agreements have been achieved between Deep Blue retrievals of aerosol optical thickness and those directly from AERONET sunphotometers over desert and semi-desert regions. New Deep Blue products will allow scientists to determine quantitatively the aerosol properties near sources using high spatial resolution measurements from SeaWiFS and MODIS-like instruments. Long-term satellite measurements (1998 - 2007) from SeaWiFS will be utilized to investigate the interannual variability of source, pathway, and dust loading associated with the Asian dust storm outbreaks. In addition, monthly averaged aerosol optical thickness during the springtime from SeaWiFS will also be compared with the MODIS Deep Blue products.

Description: The Arctic Ice Mapping group (Project AIM) at the NASA Goddard Space Flight Center Wallops Flight Facility has been conducting systematic topographic surveys of the Greenland Ice Sheet (GIS) since 1993, using scanning airborne laser altimeters combined with Global Positioning System (UPS) technology. Earlier surveys showed the ice sheet above 2000-rn elevation to be in balance, but with localized regions of thickening or thinning. Thinning predominates at lower elevations and thinning rates have recently increased, resulting in a negative mass balance for the entire ice sheet. Recently, critical segments of near-coastal flight lines in Greenland were resurveyed. Results from the new data will be presented.

Description: Energetic precipitating particles (EPPs) can cause significant constituent changes in the polar mesosphere and stratosphere (middle atmosphere) during certain periods. Both protons and electrons can influence the polar middle atmosphere through ionization and dissociation processes. EPPs can enhance HOx (H, OH, HO2) through the formation of positive ions followed by complex ion chemistry and NOx (N, NO, NO2) through the dissociation of molecular nitrogen. The HO, increases can lead to ozone destruction in the mesosphere and upper stratosphere via several catalytic loss cycles. Such middle atmospheric HOx,-caused ozone loss is rather short-lived due to the relatively short lifetime (hours) of the HOx constituents. The HOx,-caused ozone depletion has been observed during several solar proton events (SPEs) in the past 40 years. HOx enhancements due to SPEs were confirmed by observations in the past solar cycle. A number of modeling studies have been undertaken over this time period that show predictions of enhanced HO, accompanied by decreased ozone due to energetic particles. The NO, family has a longer lifetime than the HOx family and can also lead to catalytic ozone destruction. EPP-caused enhancements of the NOx family can affect ozone promptly, if produced in the stratosphere, or subsequently, if produced in the 1ow.er thermosphere or mesosphere and transported to the stratosphere. NOx enhancements due to auroral electrons, medium and high energy electrons, relativistic electron precipitation (REP) events, and SPEs have been measured and/or modeled for decades Only a small number of SPEs (less than 10) in each solar cycle have sufficient flux of high energy protons (greater than 30 MeV) to produce a significant amount of NOx directly in the stratosphere to cause a measurable ozone destruction. Very high energy electrons (greater than 1500 keV) during REP events can also produce NOx directly in the stratosphere, however, the frequency and intensity of these electrons is uncertain. Indirect stratospheric EPP effects result when NO, is produced in the mesosphere and lower thermosphere and transported to the stratosphere during the late fall or winter. Such EPP-produced NOx may last up to months beyond its initial production. This EPP-produced mesospheric and lower thermospheric NOx primarily results from auroral electrons (approx. 1- 30 keV), medium- and high-energy electrons (approx. 30-1500 keV), and medium energy protons (approx. 1-30 MeV). The EPP-caused direct and indirect effects on the stratosphere are important in the polar regions during particular years, especially near solar maximum. This talk will attempt to provide an overview of several of the EPP-related important processes and their impact on the mesosphere and stratosphere. Much progress has been made in this field in the past several years and it is anticipated that other workshop participants will address aspects of this topic in their presentations.

Description: In satellite remote sensing clouds are usually considered an annoying interference. Satellite investigators go to unusual lengths to try to avoid clouds or to correct for their effects, and satellite data users routinely exclude cloudy data from analysis. Yet it was shown about a decade ago using TOMS data that for the study of tropospheric constituents, such as ozone, clouds can play a very beneficial role by allowing one to measure what otherwise cannot be directly measured from space. We call this technique "cloud Slicing". The so-called Convective Cloud Differential (CCD) method is one particular application of cloud slicing that has been applied successfully to data from TOMS and other similar satellite instruments to study the behavior of tropical tropospheric ozone at variety of spatial and temporal scales. However, there has been considerable confusion in the literature as to what exactly one measures from reflected sunlight instruments such as TOMS in cloudy atmospheres. We will discuss recently completed analysis of data taken by the Ozone Monitoring Instrument (OMI) on the Aura satellite in conjunction with several other instruments on the A-train satellite constellation to present new insight on how clouds affect absorption by aerosols and trace gases at reflected wavelengths (UV-SWIR). We will show several examples to illustrate how this insight is helping us to study the behavior of trace gases and aerosols in the atmosphere that cannot be studied by focusing only on cloud-free scenes.

Description: The next generation of space-based, active remote sensing instruments for measurement of tropospheric CO2 promises a capability to quantify global carbon sources and sinks at regional scales. Active (laser) methods will extend CO2 measurement coverage in time, space, and perhaps precision such that the underlying mechanisms for carbon exchange at the surface can be understood with .sufficient detail to confidently project the future of carbon-climate interaction and the influence of remediative policy actions. The recent Decadal Survey for Earth Science by the US National Research Council has recommended such a mission called the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) for launch in 2013-2016. We have been developing a laser technique for measurement of tropospheric CO2 for a number of years. Our immediate goal is to develop and demonstrate the method and instrument technology that will permit measurements of the CO2 column abundance over a horizontal path and from aircraft at the few-ppmv level. Our longer-term goal is to demonstrate the required capabilities of the technique, develop a space mission approach, and design the instrument for an ASCENDS-type mission. Our approach is to use a dual channel laser absorption spectrometer (i.e., differential absorption in altimeter mode), which continuously measures from a near-polar circular orbit. We use several co-aligned tunable fiber laser transmitters allowing simultaneous measurement of the absorption from a CO2 line in the 1570 nm band, O2 extinction in the oxygen A-band (near 765 nm), and aerosol backscatter in the same measurement path. We measure the energy of the laser echoes at nadir reflected from land and water surfaces, day and night. The lasers have spectral widths much narrower than the gas absorption lines and are turned on and off the selected CO2 and O2 lines at kHz rates. The gas extinction and column densities for the CO2 and O2 gases are estimated from the ratio of the on and off-line singnals via the DIAL technique. We used pulsed laser signals, photon counting detectors, and time gating to isolate the laser returns from the surface, and to reject photons scattered from thin clouds and aerosols. High signal-to-noise ratios are required and the CO2 estimates can be sensitive to small drifts or other errors in the instrument, so the absorption estimates need to be quite stable for hours. We have constructed a breadboard version of the CO2 sensor that uses a low power fiber laser and a 20 cm diameter telescope. We have used it to make measurements of CO2 absorption in the laboratory and over 200-m to 2-km long open horizontal paths. These have been done in several sessions extending over multiple days, which allows us to assess the measurement stability and to compare absorption variations to readings from an external in situ CO2 sensor. We have also calculated characteristics of the technique for space including its expected measurement performance for different modulation types, and have performed an initial space mission accommodation study. We sill describe these results in the presentation.

Description: Natural fluctuations in the availability of critical stopover sites coupled with anthropogenic destruction of wetlands, land-use change, and anticipated losses due to climate change present migratory birds with a formidable challenge. We have developed an individual-based, spatially explicit bird migration model that simulates the migration routes, timing and energy budgets of individual birds under dynamic weather and land surface conditions. Our model incorporates biophysical constraints, individual bird energy status, bird behavior, and flight aerodynamics. We model the speed, direction, and timing of individual birds moving through a user specified Lagrangian grid. The model incorporates environmental properties including wind speed and direction, topography, dynamic hydrologic properties of the landscape, and environmental suitability. The model is driven by important variables estimated from satellite observations of the land surface, by data assimilation products from weather and climate models, and biological field data. We illustrate the use of the model to study the impact of both short- and long-term environmental variatios, e.g. climate, drought, anthropogenic, on migration timing (phenology), spatial pattern, and fitness (survival and reproductive success). We present several theoretical simulations of the spring migration of Pectoral Sandpiper (Calidris melanotos) in North America with emphasis on the Central flyway from the Gulf of Mexico to Alaska.

Description: As part of the U.S. National Environmental Public Health Tracking Network (EPHTN), the National Center for Environmental Health (NCEH) at the U.S. Centers for Disease Control and Prevention (CDC) led a project in collaboration with the National Aeronautics and Space Administration (NASA) Marshall Space Flight Center (MSFC) called Health and Environment Linked for Information Exchange (HELIX-Atlanta). Under HELIX-Atlanta, pilot projects were conducted to develop methods to better characterize exposure; link health and environmental datasets; and analyze spatial/temporal relationships. This paper describes and demonstrates different techniques for surfacing daily environmental hazards data of particulate matter with aerodynamic diameter less than or equal to 2.5 micrometers (PM(sub 2.5) for the purpose of integrating respiratory health and environmental data for the CDC's pilot study of HELIX-Atlanta. It describes a methodology for estimating ground-level continuous PM(sub 2.5) concentrations using spatial surfacing techniques and leveraging NASA Moderate Resolution Imaging Spectrometer (MODIS) data to complement the U.S. Environmental Protection Agency (EPA) ground observation data. The study used measurements of ambient PM(sub 2.5) from the EPA database for the year 2003 as well as PM(sub 2.5) estimates derived from NASA's MODIS data. Hazard data have been processed to derive the surrogate exposure PM(sub 2.5) estimates. The paper has shown that merging MODIS remote sensing data with surface observations of PM(sub 2.5), may provide a more complete daily representation of PM(sub 2.5), than either data set alone would allow, and can reduce the errors in the PM(sub 2.5) estimated surfaces. Future work in this area should focus on combining MODIS column measurements with profile information provided by satellites like the National Polar-orbiting Operational Environmental Satellite System (NPOESS). The Visible Infrared Imager/Radiometer Suite (VIIRS) and the Aerosol Polarimeter Sensor (APS) NPOESS sensors will provide first-order information on aerosol particle size and are anticipated to provide information on aerosol products at higher resolution and accuracy than MODIS. Use of the NPOESS remote sensing data should result in more robust remotely sensed data that can be coupled with the methods discussed in this paper to generate surface concentrations of PM(2.5) for linkage with health data in Environmental Public Health Tracking.

Description: The green vegetation fraction (Fg) is an important climate and hydrologic model parameter. A common method to calculate Fg is to create a simple linear mixing rnodeP between two NDVI endmembers: bare soil NDVI (NDVI(sub o)) and full vegetation NDVI (NDVI(sub infinity)). Usually it is assumed that NDVI(sub o), is close to zero (NDVI(sub o) approx.-0.05) and is generally chosen from the lowest observed NDVI values. However, the mean soil NDVI computed from 2906 samples is much larger (NDVI=0.2) and is highly variable (standard deviation=O. 1). We show that the underestimation of NDVI(sub o) yields overestimations of Fg. The largest errors occur in grassland and shrubland areas. Using parameters for NDVI(sub o) and NDVI(sub infinity) derived from global scenes yields overestimations of Fg ((Delta) Fg*) that are larger than 0.2 for the majority of U.S. land cover types when pixel NDVI values are 0.2〈NDVI(sub pixel)〈0.4. Figure 1 shows how the Fg overestimation varies for the most common land cover types in the conterminous U.S. for typical seasonal NDVI values. When using conterminous U.S. scenes to derive NDV(sub o) and NDVI(sub infinity), the overestimation is less (0.10-0.17 for 0.2〈NDVI(sub pixel)〈0.4). As a result, parts of the conterminous U.S. are affected at different times of the year depending on the local seasonal NDVI cycle. We propose using global databases of NDVI(sub o) along with information on historical NDVI(sub pixel) values to compute a statistically most-likely estimate of Fg (Fg*). Using in situ measurements made at the Sevilleta LTER, we show that this approach yields better estimates of Fg than using global invariant NDVI(sub o) values estimated from whole scenes (Figure 2). At the two studied sites, the Fg estimate was adjusted by 52% at the grassland and 86% at the shrubland. More significant advances will require information on spatial distribution of soil reflectance.

Description: 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.

Description: NASA's Earth Science Mission Directorate recently completed the deployment of the Earth Observation System (EOS) which is a coordinated series of polar-orbiting and low inclination satellites for long-term global observations of the land surface, biosphere, solid Earth, atmosphere, and oceans. One of the many applications derived from EOS is the advancement of archaeological research and applications. Using satellites, manned and unmanned airborne platform, NASA scientists and their partners have conducted archaeological research using both active and passive sensors. The NASA Stennis Space Center (SSC) located in south Mississippi, near New Orleans, has been a leader in space archaeology since the mid-1970s. Remote sensing is useful in a wide range of archaeological research applications from landscape classification and predictive modeling to site discovery and mapping. Remote sensing technology and image analysis are currently undergoing a profound shift in emphasis from broad classification to detection, identification and condition of specific materials, both organic and inorganic. In the last few years, remote sensing platforms have grown increasingly capable and sophisticated. Sensors currently in use, including commercial instruments, offer significantly improved spatial and spectral resolutions. Paired with new techniques of image analysis, this technology provides for the direct detection of archaeological sites. As in all archaeological research, the application of remote sensing to archaeology requires a priori development of specific research designs and objectives. Initially targeted at broad archaeological issues, NASA space archaeology has progressed toward developing practical applications for cultural resources management (CRM). These efforts culminated with the Biloxi Workshop held by NASA and the University of Mississippi in 2002. The workshop and resulting publication specifically address the requirements of cultural resource managers through the use of remote sensing. In 2007, NASA awarded six competitively chosen projects in Space Archaeology through an open solicitation whose purpose, among several, was to addresses the potential benefits to modern society that can be derived through a better understanding of how past cultures succeeded or failed to adapt to local, regional, and global change. A further objective of NASA's space archaeology is the protection and preservation of cultural heritage sites while planning for the sustainable development of cultural resources. NASA s archaeological approach through remote sensing builds on traditional methods of aerial archaeology (i.e. crop marks) and utilizes advanced technologies for collecting and analyzing archaeological data from digital imagery. NASA s archaeological research and application projects using remote sensing have been conducted throughout the world. In North America, NASA has imaged prehistoric mound sites in Mississippi; prehistoric shell middens in Louisiana, Puebloan sites in New Mexico and more recently the sites associated with the Lewis and Clark Corps of Discovery Expedition (1804-1806). In Central America, NASA archaeologists have researched Mayan sites throughout the region, including the Yucatan and Costa Rica, as well as Olmec localities in Veracruz. Other data has been collected over Angkor, Cambodia, Giza in Egypt, the lost city of Ubar on the Arabian Peninsula.

Description: Observations of the Earth from space over the past 30 years has enabled an increasingly detailed view of our Earth's atmosphere, land, oceans, and cryosphere, and its many alterations over time. With the advent of improvements in technology, together with increased understanding of the physical principles of remote sensing, it is now possible to routinely observe the global distribution of atmospheric constituents, including both cloud and aerosol optical properties, land surface reflectance, sea ice and glaciers, and numerous properties of the world's oceans. This talk will review the current status of recent NASA Earth observing missions, and summarize key findings. These missions include EOS missions such as Landsat 7, QuikScat, Terra, Jason-1, Aqua, ICESat, SORCE, and Aura, as well as Earth probe missions such as TRMM and SeaWiFS. Recent findings from Cloud- Sat and CALIPSO from the Earth System Science Pathfinder program will also be summarized, if time permits. Due to its wide utilization by the Earth science community, both in the US and abroad, special emphasis will be placed on the Moderate Resolution Imaging Spectroradiometer (MODIS), developed by NASA and launched onboard the Terra spacecraft in 1999 and the Aqua spacecraft in 2002. As the quintessential instrument of the Earth Observing System, it is widely used for studies of the oceans, land, and atmosphere, and its lengthening time series of Earth observations is finding utilization in many communities for both climate, weather, and applications use.

Description: NASA's Global Land Data Assimilation System (GLDAS) produces global fields of land surface states (e.g., soil moisture and temperature) and fluxes (e.g., latent heat flux and runoff) by driving offline land surface models with observation-based inputs, using the Land Information System (LIS) software. Since production began in 2001, GLDAS has supported more than 100 scientific investigations and applications. Some examples are GEWEX and NASA Energy and Water Cycle Study (NEWS) global water and energy budget analyses, interpretations of hydrologic data derived from the Gravity Recovery and Climate Experiment (GRACE) satellite mission, and forecast model initiation studies at NOAA and NASA. At the same time, the GLDAS team has continued improve results through the development of new modeling and data assimilation techniques. Here we describe several recent and ongoing innovations. These include global implementation of a runoff routing procedure, GRACE data assimilation, advanced snow cover assimilation, and irrigation modeling.

Description: NASA's award-winning Earth Resources Laboratory Applications Software (ELAS) package was developed at Stennis Space Center. Since 1978, ELAS has been used worldwide for processing satellite and airborne sensor imagery data of the Earth's surface into readable and usable information. DATASTAR Inc., of Picayune, Mississippi, has used ELAS software in the DATASTAR Image Processing Exploitation (DIPEx) desktop and Internet image processing, analysis, and manipulation software. The new DIPEx Version III includes significant upgrades and improvements compared to its esteemed predecessor. A true World Wide Web application, this product evolved with worldwide geospatial dimensionality and numerous other improvements that seamlessly support the World Wide Web version.

Description: This report documents the GEOS-5 global atmospheric model and data assimilation system (DAS), including the versions 5.0.1, 5.1.0, and 5.2.0, which have been implemented in products distributed for use by various NASA instrument team algorithms and ultimately for the Modem Era Retrospective analysis for Research and Applications (MERRA). The DAS is the integration of the GEOS-5 atmospheric model with the Gridpoint Statistical Interpolation (GSI) Analysis, a joint analysis system developed by the NOAA/National Centers for Environmental Prediction and the NASA/Global Modeling and Assimilation Office. The primary performance drivers for the GEOS DAS are temperature and moisture fields suitable for the EOS instrument teams, wind fields for the transport studies of the stratospheric and tropospheric chemistry communities, and climate-quality analyses to support studies of the hydrological cycle through MERRA. The GEOS-5 atmospheric model has been approved for open source release and is available from: http://opensource.gsfc.nasa.gov/projects/GEOS-5/GEOS-5.php.

Description: One of the strategic goals of the U.S. National Aeronautics and Space Administration (NASA) is to "Develop a balanced overall program of science, exploration, and aeronautics consistent with the redirection of the human spaceflight program to focus on exploration". An important sub-goal of this goal is to "Study Earth from space to advance scientific understanding and meet societal needs." NASA meets this subgoal in partnership with other U.S. agencies and international organizations through its Earth science program. A major component of NASA s Earth science program is the Earth Observing System (EOS). The EOS program was started in 1990 with the primary purpose of modeling global climate change. This program consists of a set of space-borne instruments, science teams, and a data system. The instruments are designed to obtain highly accurate, frequent and global measurements of geophysical properties of land, oceans and atmosphere. The science teams are responsible for designing the instruments as well as scientific algorithms to derive information from the instrument measurements. The data system, called the EOS Data and Information System (EOSDIS), produces data products using those algorithms as well as archives and distributes such products. The first of the EOS instruments were launched in November 1997 on the Japanese satellite called the Tropical Rainfall Measuring Mission (TRMM) and the last, on the U.S. satellite Aura, were launched in July 2004. The instrument science teams have been active since the inception of the program in 1990 and have participation from Brazil, Canada, France, Japan, Netherlands, United Kingdom and U.S. The development of EOSDIS was initiated in 1990, and this data system has been serving the user community since 1994. The purpose of this chapter is to discuss the history and evolution of EOSDIS since its beginnings to the present and indicate how it continues to evolve into the future. this chapter is organized as follows. Sect. 7.2 provides a discussion of EOSDIS, its elements and their functions. Sect. 7.3 provides details regarding the move towards more distributed systems for supporting both the core and community needs to be served by NASA Earth science data systems. Sect. 7.4 discusses the use of standards and interfaces and their importance in EOSDIS. Sect. 7.5 provides details about the EOSDIS Evolution Study. Sect. 7.6 presents the implementation of the EOSDIS Evolution plan. Sect. 7.7 briefly outlines the progress that the implementation has made towards the 2015 Vision, followed by a summary in Sect. 7.8.

Description: This software represents a complete, unsupervised processing chain that generates a continuously updating global image of the Earth from the most recent available MODIS Level 1B scenes. The software constantly updates a global image of the Earth at 250 m per pixel.

Description: An imaging lidar system is being developed for use in navigation, relative to the local terrain. This technology will potentially be used for future spacecraft landing on the Moon. Systems like this one could also be used on Earth for diverse purposes, including mapping terrain, navigating aircraft with respect to terrain and military applications. The system has been field-tested aboard a helicopter in the Mojave Desert. When this system was designed, digitizers with sufficient sampling rate (2 GHz) were only available with very limited memory. Also, it was desirable to limit the amount of data to be transferred between the digitizer and the mass storage between individual frames. One of the novelty design features of this system was to design the system around the limited amount of memory of the digitizer. The system is required to operate over an altitude (distance) range from a few meters to approximately 1 km, but for each scan across the full field of view, the digitizer memory is only able to hold data for an altitude range no more than 100 m. Data acquisition methods in support of the limited 100 m wide altitude range are described.

Description: The Visual Data Analysis Package is a collection of programs and scripts that facilitate visual analysis of data available from NASA and NOAA satellites, as well as dropsonde, buoy, and conventional in-situ observations. The package features utilities for data extraction, data quality control, statistical analysis, and data visualization. The Hierarchical Data Format (HDF) satellite data extraction routines from NASA's Jet Propulsion Laboratory were customized for specific spatial coverage and file input/output. Statistical analysis includes the calculation of the relative error, the absolute error, and the root mean square error. Other capabilities include curve fitting through the data points to fill in missing data points between satellite passes or where clouds obscure satellite data. For data visualization, the software provides customizable Generic Mapping Tool (GMT) scripts to generate difference maps, scatter plots, line plots, vector plots, histograms, timeseries, and color fill images.

Description: A Global Positioning System (GPS)- reflection/occultation interferometry was examined as a means of altimetry of water and ice surfaces in polar regions. In GPS-reflection/occultation interferometry, a GPS receiver aboard a satellite in a low orbit around the Earth is used to determine the temporally varying carrier- phase delay between (1) one component of a signal from a GPS transmitter propagating directly through the atmosphere just as the GPS transmitter falls below the horizon and (2) another component of the same signal, propagating along a slightly different path, reflected at glancing incidence upon the water or ice surface.

Description: Vegetation disturbances are known to alter the functioning of forested ecosystems by contributing to export ('leakage') of dissolved nitrogen (N), typically nitrate-N, from watersheds that can contribute to acidification of acid-sensitive streams, leaching of base cations, and eutrophication of downstream receiving waters. Yet, at a landscape scale, direct evaluation of how disturbance is linked to spatial variability in N leakage is complicated by the fact that disturbances operate at different spatial scales, over different timescales, and at different intensities. In this paper we explore whether data from synoptic streamwater surveys conducted in an Appalachian oak-dominated forested river basin in western MD (USA) can be used to test and validate a scalable, synthetic, and integrative forest disturbance index (FDI) derived from Landsat imagery. In particular, we found support for the hypothesis that the interannual variation in spring baseflow total dissolved nitrogen (TDN) and nitrate-N concentrations measured at 35 randomly selected stream stations varied as a linear function of the change in FDI computed for the corresponding set of subwatersheds. Our results demonstrate that the combined effects of forest disturbances can be detected using synoptic water quality data. It appears that careful timing of the synoptic baseflow sampling under comparable phenological and hydrometeorological conditions increased our ability to identify a forest disturbance signal.

Description: This study uses 3-dimensional finite difference time domain method to accurately calculate single-scattering properties of randomly orientated leaves and evaluate the influences of vegetation water content (VWC) on these properties at 19 and 37 GHz frequencies. The studied leaves are assumed to be thin elliptic disks with two different sizes and have various VWC values. Although the leaf moisture produces considerable absorption during scattering processes, the effective efficiencies of extinction and scattering of leaves still near-linearly increase with VWC. Calculated asymmetry factors and phase functions indicate that there are significant amounts of scattering at large scattering angles in microwave wavelengths, which provides good opportunities for off-nadir microwave remote sensing of forests. This study lays a basic foundation in future quantifications of the relations between satellite measurements and physical properties of vegetation canopies.

Description: The international experiment called EAQUATE (European AQUA Thermodynamic Experiment) was held in September 2004 in Italy and the United Kingdom to demonstrate certain ground-based and airborne systems useful for validating hyperspectral satellite sounding observations. A range of flights over land and marine surfaces were conducted to coincide with overpasses of the AIRS instrument on the EOS Aqua platform. Direct radiance evaluation of AIRS using NAST-I and SHIS has shown excellent agreement. Comparisons of level 2 retrievals of temperature and water vapor from AIRS and NAST-I validated against high quality lidar and drop sonde data show that the 1K/1km and 10%/1km requirements for temperature and water vapor (respectively) are generally being met. The EAQUATE campaign has proven the need for synergistic measurements from a range of observing systems for satellite cal/val and has paved the way for future cal/val activities in support of IASI on the European Metop platform and CrIS on the US NPP/NPOESS platform.

Description: Laboratory-based Bidirectional Reflectance Distribution Function (BRDF) analysis of vegetation leaves, soil, and leaf litter samples is presented. The leaf litter and soil samples, numbered 1 and 2, were obtained from a site located in the savanna biome of South Africa (Skukuza: 25.0degS, 31.5degE). A third soil sample, number 3, was obtained from Etosha Pan, Namibia (19.20degS, 15.93degE, alt. 1100 m). In addition, BRDF of local fresh and dry leaves from tulip tree (Liriodendron tulipifera) and acacia tree (Acacia greggii) were studied. It is shown how the BRDF depends on the incident and scatter angles, sample size (i.e. crushed versus whole leaf,) soil samples fraction size, sample status (i.e. fresh versus dry leaves), vegetation species (poplar versus acacia), and vegetation s biochemical composition. As a demonstration of the application of the results of this study, airborne BRDF measurements acquired with NASA's Cloud Absorption Radiometer (CAR) over the same general site where the soil and leaf litter samples were obtained are compared to the laboratory results. Good agreement between laboratory and airborne measured BRDF is reported.

Description: Closing the global water and energy budgets has been an elusive Global Energy and Water-cycle Experiment (GEWEX) goal. It has been difficult to gather many of the needed global water and energy variables and processes, although, because of GEWEX, we now have globally gridded observational estimates for precipitation and radiation and many other relevant variables such as clouds and aerosols. Still, constrained models are required to fill in many of the process and variable gaps. At least there are now several atmospheric reanalyses ranging from the early National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) and NCEP/Department of Energy (DOE) reanalyses to the more recent ERA40 and JRA-25 reanalyses. Atmospheric constraints include requirements that the models state variables remain close to in situ observations or observed satellite radiances. This is usually done by making short-term forecasts from an analyzed initial state; these short-term forecasts provide the next guess, which is corrected by comparison to available observations. While this analysis procedure is likely to result in useful global descriptions of atmospheric temperature, wind and humidity, there is no guarantee that relevant hydroclimate processes like precipitation, which we can observe and evaluate, and evaporation over land, which we cannot, have similar verisimilitude. Alternatively, the Global Land Data Assimilation System (GLDAS), drives uncoupled land surface models with precipitation, surface solar radiation, and surface meteorology (from bias-corrected reanalyses during the study period) to simulate terrestrial states and surface fluxes. Further constraints are made when a tuned water balance model is used to characterize the global runoff observational estimates. We use this disparate mix of observational estimates, reanalyses, GLDAS and calibrated water balance simulations to try to characterize and close global and terrestrial atmospheric and surface water and energy budgets to within 10-20% for long term (1986-1995), large-scale global to regional annual means.

Description: The Moderate Resolution Imaging Spectrometer (MODIS) on-board NASA's Earth Observing System (EOS) Terra and Aqua Satellites are key instruments for providing data on global land, atmosphere, and ocean dynamics. Derived MODIS land, atmosphere and ocean products are central to NASA's mission to monitor and understand the Earth system. NASA has developed and generated on a systematic basis a suite of MODIS products starting with the first Terra MODIS data sensed February 22, 2000 and continuing with the first MODIS-Aqua data sensed July 2, 2002. The MODIS Land products are divided into three product suites: radiation budget products, ecosystem products, and land cover characterization products. The production and distribution of the MODIS Land products are described, from initial software delivery by the MODIS Land Science Team, to operational product generation and quality assurance, delivery to EOS archival and distribution centers, and product accuracy assessment and validation. Progress and lessons learned since the first MODIS data were in early 2000 are described.

Description: In this study, we present an improved physical model to retrieve snowfall rate over land using brightness temperature observations from the National Oceanic and Atmospheric Administration's (NOAA) Advanced Microwave Sounder Unit-B (AMSU-B) at 89 GHz, 150 GHz, 183.3 +/- 1 GHz, 183.3 +/- 3 GHz, and 183.3 +/- 7 GHz. The retrieval model is applied to the New England blizzard of March 5, 2001 which deposited about 75 cm of snow over much of Vermont, New Hampshire, and northern New York. In this improved physical model, prior retrieval assumptions about snowflake shape, particle size distributions, environmental conditions, and optimization methodology have been updated. Here, single scattering parameters for snow particles are calculated with the Discrete-Dipole Approximation (DDA) method instead of assuming spherical shapes. Five different snow particle models (hexagonal columns, hexagonal plates, and three different kinds of aggregates) are considered. Snow particle size distributions are assumed to vary with air temperature and to follow aircraft measurements described by previous studies. Brightness temperatures at AMSU-B frequencies for the New England blizzard are calculated using these DDA calculated single scattering parameters and particle size distributions. The vertical profiles of pressure, temperature, relative humidity and hydrometeors are provided by MM5 model simulations. These profiles are treated as the a priori data base in the Bayesian retrieval algorithm. In algorithm applications to the blizzard data, calculated brightness temperatures associated with selected database profiles agree with AMSU-B observations to within about +/- 5 K at all five frequencies. Retrieved snowfall rates compare favorably with the near-concurrent National Weather Service (NWS) radar reflectivity measurements. The relationships between the NWS radar measured reflectivities Z(sub e) and retrieved snowfall rate R for a given snow particle model are derived by a histogram matching technique. All of these Z(sub e)-R relationships fall in the range of previously established Z(sub e)-R relationships for snowfall. This suggests that the current physical model developed in this study can reliably estimate the snowfall rate over land using the AMSU-B measured brightness temperatures.

Description: This viewgraph presentation reviews the planned global sensor network that will monitor the Earth's climate, and resources using airborne sensor systems. The vision is an intelligent, affordable Earth Observation System. Global Test Range is a lab developing trustworthy services for airborne instruments - a specialized Internet Service Provider. There is discussion of several current and planned missions.

Description: Preliminary analyses of the POLSCAT data acquired from the CLPX-II in winter 2006-2007 are described in this paper. The data showed the response of the Ku-band radarechoes to snowpack changes for various types of background vegetation. We observed about 0.2 to 0.4 dB increases in backscatter for every 1 cm SWE accumulation for sage brush and agricultural fields. The co-polarized VV and HH radar resposnes are similar, while the corss-polarized (VH or HV) echoes showedgreater resposne to the change of SWE. The data also showed the impact of surface hoar growth and freeze/thaw cycles, whichcreated large snow grain sizes and ice lenses, respectively, and consequently increased the radar signals by a few dBs.

Description: The presentation focuses on study questions, effort, and result. Study questions include a focus on MW/LW, error sources and what can be expected, how validation will be performed and what resolution is required, and spatial resolution required for cross-calibration. Study effort includes empirical approach by examining AIRS ,IASI and MODIS cross-calibration methods already in place and estimate the number of clear and Dome C observations possible versus spatial resolution. Study results include 5000 sampler per cross-calibration recommended, insufficient cloud free and Dome C AWS observations for cross calibration and validation at 100km, and less than 20 km IFOV at 100 km swath needed to achieve sufficient samples for cross-calibration of CLARREO.

Description: The presentation includes an introduction, Lake Tahoe site layout and measurements, Salton Sea site layout and measurements, field instrument calibration and cross-calculations, data reduction methodology and error budgets, and example results for MODIS. Summary and conclusions are: 1) Lake Tahoe CA/NV automated validation site was established in 1999 to assess radiometric accuracy of satellite and airborne mid and thermal infrared data and products. Water surface temperatures range from 4-25C.2) Salton Sea CA automated validation site was established in 2008 to broaden range of available water surface temperatures and atmospheric water vapor test cases. Water surface temperatures range from 15-35C. 3) Sites provide all information necessary for validation every 2 mins (bulk temperature, skin temperature, air temperature, wind speed, wind direction, net radiation, relative humidity). 4) Sites have been used to validate mid and thermal infrared data and products from: ASTER, AATSR, ATSR2, MODIS-Terra, MODIS-Aqua, Landsat 5, Landsat 7, MTI, TES, MASTER, MAS. 5) Approximately 10 years of data available to help validate AVHRR.

Description: Topics include AIRS on Aqua, 2002-present with discussion about continued operation to 2011 and beyond and background, including spectrum, weighting functions, and initialization; comparison with aircraft and FTIR measurements in Masueda (CONTRAIL) JAL flask measurements, Park Falls, WI FTIR, Bremen, GDF, and Spitsbergen, Norway; AIRS retrievals over addition FTIR sites in Darwin, AU and Lauder, NZ; and mid-tropospheric carbon dioxide weather and contribution from major surface sources. Slide titles include typical AIRS infrared spectrum, AIRS sensitivity for retrieving CO2 profiles, independence of CO2 solution with respect to the initial guess, available in situ measurements for validation and comparison, comparison of collocated V1.5x AIRS CO2 (N_coll greater than or equal to 9) with INTEX-NA and SPURT;

Description: Radiation reflected from vegetation canopies exhibits high spatial variation. Satellite-borne sensors measure the mean intensities emanating from heterogeneous vegetated pixels. The theory of radiative transfer in stochastic media provides the most logical linkage between satellite observations and the three-dimensional canopy structure through a closed system of simple equations which contains the mean intensity and higher statistical moments directly as its unknowns. Although this theory has been a highly active research field in recent years, its potential for satellite remote sensing of vegetated surfaces has not been fully realized because of the lack of models of a canopy pair-correlation function that the stochastic radiative transfer equations require. The pair correlation function is defined as the probability of finding simultaneously phytoelements at two points. This paper presents analytical and Monte Carlo generated pair correlation functions. Theoretical and numerical analyses show that the spatial correlation between phytoelements is primarily responsible for the effects of the three-dimensional canopy structure on canopy reflective and absorptive properties. The pair correlation function, therefore, is the most natural and physically meaningful measure of the canopy structure over a wide range of scales. The stochastic radiative transfer equations naturally admit this measure and thus provide a powerful means to investigate the three-dimensional canopy structure from space. Canopy reflectances predicted by the stochastic equations are assessed by comparisons with the PARABOLA measurements from coniferous and broadleaf forest stands in the BOREAS Southern Study Areas. The pair correlation functions are derived from data on tree structural parameters collected during field campaigns conducted at these sites. The simulated canopy reflectances compare well with the PARABOLA data.

Description: ATDD is a web based tool which provides collocated data and display products for a number of A-train instruments Cloudsat, Calipso, OMI, AIRS, MODIS, MLS, POLDER-3, and ECWMF model data. Products provided include Clouds, Aerosols, Water Vapor, Temperatures and trace gases. All input data is online and in HDF4, HDF5 format. Display products include curtain images, horizontal strips, line plot overlays, and GE kmz files. Sample products are shown for two type of events. Hurricane event, Norbert, Oct 8, 2008 and a dust storm event over the Arabian Sea, Nov 13-14, 2008.

Description: Objectives: Demonstrate capabilities of UAS to overfly and collect sensor data on wildfires throughout Western US. Demonstrate long-endurance mission capabilities (20+ hours). Image multiple fires (greater than 4 fires per mission), to showcase extendable mission configuration and ability to either linger over key fires or station over disparate regional fires. Deliver real-time imagery to (within 10-minutes of acquisition).

Description: This viewgraph document reviews the contribution that NASA has made and the plans for future missions that will assist the mission of the Gulf of Mexico Alliance (GOMA). Specific reference to the work of the Stennis Space Center is reviewed. Some of the projects are: Coastal Online Assessment and Synthesis Tool (COAST), Regional Sediment Management, Coral Reef Early Warning System, Harmful Algal Bloom, Hypoxia, Land-Use and Land-Cover (LULC) Change from 1974-2008 around Mobile Bay, AL, Satellite Estimation of Suspended Particulate Loads in and around Mobile Bay, AL, Estimating Relative Nutrient Contributions of Agriculture and Forests Using MODIS Time Series, Coastal Marsh Monitoring for Persistent Saltwater Intrusion, Standardized Remote Sensing PRoduct for Water Clarity estimation within Gulf of Mexico Coastal Waters.

Description: Soil moisture is recognized as an important component of the water, energy, and carbon cycles at the interface between the Earth's surface and atmosphere. Current baseline soil moisture retrieval algorithms for microwave space missions have been developed and validated only over grasslands, agricultural crops, and generally light to moderate vegetation. Tree areas have commonly been excluded from operational soil moisture retrieval plans due to the large expected impact of trees on masking the microwave response to the underlying soil moisture. Our understanding of the microwave properties of trees of various sizes and their effect on soil moisture retrieval algorithms at L band is presently limited, although research efforts are ongoing in Europe, the United States, and elsewhere to remedy this situation. As part of this research, a coordinated sequence of field measurements involving the ComRAD (for Combined Radar/Radiometer) active/passive microwave truck instrument system has been undertaken. Jointly developed and operated by NASA Goddard Space Flight Center and George Washington University, ComRAD consists of dual-polarized 1.4 GHz total-power radiometers (LH, LV) and a quad-polarized 1.25 GHz L band radar sharing a single parabolic dish antenna with a novel broadband stacked patch dual-polarized feed, a quad-polarized 4.75 GHz C band radar, and a single channel 10 GHz XHH radar. The instruments are deployed on a mobile truck with an 19-m hydraulic boom and share common control software; real-time calibrated signals, and the capability for automated data collection for unattended operation. Most microwave soil moisture retrieval algorithms developed for use at L band frequencies are based on the tau-omega model, a simplified zero-order radiative transfer approach where scattering is largely ignored and vegetation canopies are generally treated as a bulk attenuating layer. In this approach, vegetation effects are parameterized by tau and omega, the microwave vegetation opacity and single scattering albedo. One goal of our current research is to determine whether the tau-omega model can work for tree canopies given the increased scatter from trees compared to grasses and crops, and. if so, what are effective values for tau and omega for trees.

Description: The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere s thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The GIFTS calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts, therefore, enhancing the absolute calibration accuracy. This method is applied to data collected during the GIFTS Ground Based Measurement (GBM) experiment, together with simultaneous observations by the accurately calibrated AERI (Atmospheric Emitted Radiance Interferometer), both simultaneously zenith viewing the sky through the same external scene mirror at ten-minute intervals throughout a cloudless day at Logan Utah on September 13, 2006. The accurately calibrated GIFTS radiances are produced using the first four PC scores in the GIFTS-AERI regression model. Temperature and moisture profiles retrieved from the PC-calibrated GIFTS radiances are verified against radiosonde measurements collected throughout the GIFTS sky measurement period. Using the GIFTS GBM calibration model, we compute the calibrated radiances from data collected during the moon tracking and viewing experiment events. From which, we derive the lunar surface temperature and emissivity associated with the moon viewing measurements.

Description: This presentation describes the objectives of the 2007 Western States Fire Mission (WSFM), which included demonstrating capabilities of the Ikhana unmanned aerial system (UAS) to overfly and collect sensor data on widespread fires throughout the Western United States, demonstrating long-endurance (20+ hours) mission capabilities, and delivering real-time imagery within 10 minutes of acquisition. Additionally, the operations concept, operational zones, and landing sites are highlighted. Provisions of the certificate of authorization are also addressed. Imagery obtained from the WSFM are included.

Description: Since modern ultra-spectral remote sensors have thousands of channels, it is difficult to include all of them in a 1D-var retrieval system. We will describe a physical inversion algorithm, which includes all available channels for the atmospheric temperature, moisture, cloud, and surface parameter retrievals. Both the forward model and the inversion algorithm compress the channel radiances into super channels. These super channels are obtained by projecting the radiance spectra onto a set of pre-calculated eigenvectors. The forward model provides both super channel properties and jacobian in EOF space directly. For ultra-spectral sensors such as Infrared Atmospheric Sounding Interferometer (IASI) and the NPOESS Airborne Sounder Testbed Interferometer (NAST), a compression ratio of more than 80 can be achieved, leading to a significant reduction in computations involved in an inversion process. Results will be shown applying the algorithm to real IASI and NAST data.

Description: The National Aeronautics and Space Administration, United States Forest Service, and National Interagency Fire Center have developed a partnership to develop and demonstrate technology to improve airborne wildfire imaging and data dissemination. In the summer of 2007, a multi-spectral infrared scanner was integrated into NASA's Ikhana Unmanned Aircraft System (UAS) (a General Atomics Predator-B) and launched on four long duration wildfire mapping demonstration missions covering eight western states. Extensive safety analysis, contingency planning, and mission coordination were key to securing an FAA certificate of authorization (COA) to operate in the national airspace. Infrared images were autonomously geo-rectified, transmitted to the ground station by satellite communications, and networked to fire incident commanders within 15 minutes of acquisition. Close coordination with air traffic control ensured a safe operation, and allowed real-time redirection around inclement weather and other minor changes to the flight plan. All objectives of the mission demonstrations were achieved. In late October, wind-driven wildfires erupted in five southern California counties. State and national emergency operations agencies requested Ikhana to help assess and manage the wildfires. Four additional missions were launched over a 5-day period, with near realtime images delivered to multiple emergency operations centers and fire incident commands managing 10 fires.

Description: Three NASA-funded field campaigns have been hosted at the Howard University Research Campus in Beltsville, MD. In each of the years 2006, 2007 and 2008, WAVES field campaigns have coordinated ozonesonde launches, lidar operations and other measurements with A-train satellite overpasses for the purposes of satellite validation. The unique mix of measurement systems, physical location and the interagency, international group of researchers and students has permitted other objectives, such as mesoscale meteorological studies, to be addressed as well. We review the goals and accomplishments of the three WAVES missions with the emphasis on the nonsatellite validation component of WAVES, as the satellite validation activities have been reported elsewhere.

Description: Laboratory Bi-directional Reflectance Distribution Function (BRDF) measurements of salt pan regolith samples are presented in this study in an effort to understand the role of spatial and spectral variability of the natural biome. The samples were obtained from Etosha Pan, Namibia (19.20 deg S, 15.93 deg E, alt. 1100 m). It is shown how the BRDF depends on the measurement geometry - incident and scatter angles and on the sample particle sizes. As a demonstration of the application of the results, airborne BRDF measurements acquires with NASA's Cloud Absorption Radiometer (CAR) over the same general site where the regolith samples were collected are compared with the laboratory results. Good agreement between laboratory measured and field measured BRDF is reported.

Description: The project showed potential of MODIS and VIIRS time series data for contributing defoliation detection products to the USFS forest threat early warning system. This study yielded the first satellite-based wall-to-wall 2001 gypsy moth defoliation map for the study area. Initial results led to follow-on work to map 2007 gypsy moth defoliation over the eastern United States (in progress). MODIS-based defoliation maps offer promise for aiding aerial sketch maps either in planning surveys and/or adjusting acreage estimates of annual defoliation. More work still needs to be done to assess potential of technology for "now casts"of defoliation.

Description: Observing Earth from space over the past 50 years has fundamentally transformed the way people view our home planet. The image of the "blue marble" is taken for granted now, but it was revolutionary when taken in 1972 by the crew on Apollo 17. Since then the capability to look at Earth from space has grown increasingly sophisticated and has evolved from simple photographs to quantitative measurements of Earth properties such as temperature, concentrations of atmospheric trace gases, and the exact elevation of land and ocean. Imaging Earth from space has resulted in major scientific accomplishments; these observations have led to new discoveries, transformed the Earth sciences, opened new avenues of research, and provided important societal benefits by improving the predictability of Earth system processes. This report highlights the scientific achievements made possible by the first five decades of Earth satellite observations by space-faring nations. It follows on a recent report from the National Research Council (NRC) entitled Earth Science and Applications from Space: National Imperatives for the Next Decade and Beyond, also referred to as the "decadal survey." Recognizing the increasing need for space observations, the decadal survey identifies future directions and priorities for Earth observations from space. This companion report was requested by the National Aeronautics and Space Administration (NASA) to highlight, through selected examples, important past contributions of Earth observations from space to our current understanding of the planet.

Description: The area of North American forests affected by gypsy moth defoliation continues to expand despite efforts to slow the spread. With the increased area of infestation, ecological, environmental and economic concerns about gypsy moth disturbance remain significant, necessitating coordinated, repeatable and comprehensive monitoring of the areas affected. In this study, our primary objective was to estimate the magnitude of defoliation using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery for a gypsy moth outbreak that occurred in the US central Appalachian Mountains in 2000 and 2001. We focused on determining the appropriate spectral MODIS indices and temporal compositing method to best monitor the effects of gypsy moth defoliation. We tested MODIS-based Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Normalized Difference Water Index (NDWI), and two versions of the Normalized Difference Infrared index (NDIIb6 and NDIIb7, using the channels centered on 1640 nm and 2130 nm respectively) for their capacity to map defoliation as estimated by ground observations. In addition, we evaluated three temporal resolutions: daily, 8-day and 16-day data. We validated the results through quantitative comparison to Landsat based defoliation estimates and traditional sketch maps. Our MODIS based defoliation estimates based on NDIIb6 and NDIIb7 closely matched Landsat defoliation estimates derived from field data as well as sketch maps. We conclude that daily MODIS data can be used with confidence to monitor insect defoliation on an annual time scale, at least for larger patches (greater than 0.63 km2). Eight-day and 16-day MODIS composites may be of lesser use due to the ephemeral character of disturbance by the gypsy moth.

Description: The goal of the Sensor Management Applied Research Technologies (SMART) On-Demand Modeling project is to develop and demonstrate the readiness of the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) capabilities to integrate both space-based Earth observations and forecast model output into new data acquisition and assimilation strategies. The project is developing sensor web-enabled processing plans to assimilate Atmospheric Infrared Sounding (AIRS) satellite temperature and moisture retrievals into a regional Weather Research and Forecast (WRF) model over the southeastern United States.

Description: The United States Environmental Protection Agency (EPA) has declared that "significant benefits accrue to growers, the public, and the environment" from the use of transgenic pesticidal crops due to reductions in pesticide usage for crop pest management. Large increases in the global use of transgenic pesticidal crops has reduced the amounts of broad spectrum pesticides used to manage pest populations, improved yield and reduced the environmental impact of crop management. A significant threat to the continued use of this technology is the evolution of resistance in insect pest populations to the insecticidal Bt toxins expressed by the plants. Management of transgenic pesticidal crops with an emphasis on conservation of Bt toxicity in field populations of insect pests is important to the future of sustainable agriculture. A vital component of this transgenic pesticidal crop management is establishing the proof of concept basic understanding, situational awareness, and monitoring and decision support system tools for more than 133650 square kilometers (33 million acres) of bio-engineered corn and cotton for development of insect resistance . Early and recent joint NASA, US EPA and ITD remote imagery flights and ground based field experiments have provided very promising research results that will potentially address future requirements for crop management capabilities.

Description: This project is a Gulf of Mexico Application Pilot in which NASA Stennis Space Center (SSC) is working within a regional collaboration network of the Gulf of Mexico Alliance. NASA researchers, with support from the NASA SSC Applied Science Program Steering Committee, employed multi-temporal Landsat data to assess land-use and land-cover (LULC) changes in the coastal counties of Mobile and Baldwin, AL, between 1974 and 2008. A multi-decadal time-series, coastal LULC product unique to NASA SSC was produced. The geographic extent and nature of change was quantified for the open water, barren, upland herbaceous, non-woody wetland, upland forest, woody wetland, and urban landscapes. The National Oceanic and Atmospheric Administration (NOAA) National Coastal Development Data Center (NCDDC) will assist with the transition of the final product to the operational end user, which primarily is the Mobile Bay National Estuary Program (MBNEP). We found substantial LULC change over the 34-year study period, much more than is evident when the change occurring in the last years. Between 1974 and 2008, the upland forest landscape lost almost 6% of the total acreage, while urban land cover increased by slightly more than 3%. With exception to open water, upland forest is the dominant landscape, accounting for about 25-30% of the total area.

Description: The CEOS Systems Engineering Office will present a 2007 status report of the CEOS constellation process, present a new systems engineering framework, and analysis results from the GEO Societal Benefit Area (SBA) assessment and the OST constellation requirements assessment.

Description: This viewgraph presentation reviews the classification of Remote Sensing data in relation to epidemiology. Classification is a way to reduce the dimensionality and precision to something a human can understand. Classification changes SCALAR data into NOMINAL data.

Description: Remote sensing is measuring something without touching it. Most methods measure a portion of the electro-magnetic spectrum using energy reflected from or emitted by a material. Moving the instrument away makes it easier to see more at one time. Airplanes are good but satellites are much better. Many things can not be easily measured on the scale of an individual person. Example - measuring all the vegetation growing at one time in even the smallest country. A satellite can see things over large areas repeatedly and in a consistent way. Data from the detector is reported as digital values for a grid that covers some portion of the Earth. Because it is digital and consistent a computer can extract information or enhance the data for a specific purpose.

Description: Remote sensing data has long been used to monitor global ecosystems for floods and droughts and AVHRR data, as one of the first product, has many users interested in receiving the data within hours of acquisition. With the introduction of a new series of sensors in 2000 (the AVHRR/3 series), the quality of the NDVI datasets available for real time environmental monitoring has declined. This paper provides evidence of problems of cloud contamination, calibration and noise in the real time data which are not present in the historical AVHRR NDVIg dataset. These differences introduce significant uncertainty in the use of the real time data, degrading their utility for detecting climate variations in near real time.

Description: Around the Gulf of Mexico, high-input crops in several regions make a significant contribution to nutrient loading of small to medium estuaries and to the near-shore Gulf. Some crops cultivated near the coast include sorghum in Texas, rice in Texas and Louisiana, sugarcane in Florida and Louisiana, citrus orchards in Florida, pecan orchards in Mississippi and Alabama, and heavy sod and ornamental production around Mobile and Tampa Bay. In addition to crops, management of timberlands in proximity to the coasts also plays a role in nutrient loading. In the summer of 2008, a feasibility project is planned to explore the use of NASA data to enhance the spatial and temporal resolution of near-coast nutrient source information available to the coastal community. The purpose of this project is to demonstrate the viability of nutrient source information products applicable to small to medium watersheds surrounding the Gulf of Mexico. Conceptually, these products are intended to complement estuarine nutrient monitoring.

Description: Infrared detector development and characterization at NASA Langley Research Center will be reviewed. These detectors were intended for ground, airborne, and space borne remote sensing applications. Discussion will be focused on recently developed single-element infrared detector and future development of near-infrared focal plane arrays (FPA). The FPA will be applied to next generation space-based instruments. These activities are based on phototransistor and avalanche photodiode technologies, which offer high internal gain and relatively low noise-equivalent-power. These novel devices will improve the sensitivity of active remote sensing instruments while eliminating the need for a high power laser transmitter.

Description: As part of the North American Carbon Program effort to quantify the terrestrial carbon budget of North America, we have been examining the possibility of retrieving ecosystem light use efficiency (LUE, the carbon sequestered per unit photosynthetically active radiation) directly from satellite observations. Our novel approach has been to compare LUE derived from tower fluxes with LUE estimated using spectral indices computed from MODIS satellite observations over forests in the Fluxnet-Canada Research Network, using the MODIS narrow ocean bands acquired over land. We matched carbon flux data collected around the time of the MODIS mid-day overpass for over one hundred relatively clear days in five years (2001-2006) from a mature Douglas fir forest in British Columbia. We also examined hyperspectral reflectance data collected diurnally from the tower in conjunction with the eddy correlation fluxes and meteorological measurements made throughout the 2006 growing season at this site. The tower-based flux data provided an opportunity to examine diurnal and seasonal LUE processes and their relationship to spectral indices at the scale of the forest stand. We evaluated LUE in conjunction with the Photochemical Reflectance Index (PRI), a normalized difference spectral index that uses 531 nm and a reference band to capture responses to high light induced stress afforded by the xanthophyll cycle. Canopy structure information, retrieved from airborne laser scanning radar (LiDAR) observations, was used to partition the forest canopy into sunlit and shaded fractions throughout the day, on numerous days during 2006. At each observation period throughout a day, the PRI was examined for the sunlit, shaded, and intermediate canopy segments defined by their instantaneous position relative to the solar principal plane (SPP). The sunlit sector was associated with the illumination "hotspot" (the reflectance backscatter maximum), the shaded sector with the "cold or dark spot" (the reflectance forward scatter minimum), while the intermediate, mixed sunlit/shade sector was located in the cross-plane to the SPP. The PRI indices clearly captured the differences in leaf groups, with sunlit foliage exhibiting the lowest values on sunny days throughout the 2006 season. When tower-based canopy-level LUE was recalculated to estimate foliage-based values (LUE(sub foilage) for the three foliage groups under their incident light environments, a strong linear relationship for PRI:LUE(sub foilage) was demonstrated (0.6 less than or equal to r(sup 2) less than or equal to 0.8, n=822, P〈0.0001). The MODIS data represent relatively large areas when acquired at nadir (approx.1 sq km) or at variable off-nadir view angles (greater than or equal to 1 sq km) looking forward or aft. Nevertheless, a similar relationship between MODIS PRI and tower-based LUE was obtained from satellite observations (r(sup 2) = 0.76, n=105, P= 0.026) when the azimuth offsets from the SPP for off-nadir observations were considered. At this relatively high latitude of 50 degrees, the MODIS directional observations were offset from the SPP by approximately 50 degrees, but still represented backscatter or forward scatter sectors of the bidirectional reflectance distribution function (BRDF). The backscatter observations sampled the sunlit forest and provided lower PRI values, in general, than the forward scatter observations from the shaded forest. Since the hotspot and darkspot were not typically directly observed, the dynamic range for MODIS PRI was less than that observed in the SPP at the canopy level; therefore, MODIS PRI values were more similar to those observed in sifu in the BRDF cross-plane. While not ideal in terms of spatial resolution or optimal viewing configuration, the MODIS observations nevertheless provide a means to monitor forest under stress using narrow spectral band indices and off-nadir observations. This research has stimulated several spin-off studies for remote sensinf LUE, and demonstrates the importance of the connection between ecosystem structure and physiological function.

Description: The Moderate Resolution Imaging Spectroradiometer (MODIS) has 36 spectral bands with a total of 490 detectors, covering spectral regions in the visible (VIS), near-infrared (NIR), short-wave infrared (SWIR), mid-wave infrared (MWIR), and long-wave infrared (LWIR). MODIS is a cross-track scanning radiometer which collects data using a rotating scan mirror (both sides) over a wide range of scan angles. The VIS, NIR, and SWIR bands (bands 1-19 and 26) make measurements of daytime surface reflected radiances, thus are referred to as the reflective solar bands (RSB). MODIS was built with a complete set of on-board calibrators, capable of providing radiometric, spatial, and spectral calibration and characterization during its entire mission. The RSB on-orbit calibration is primarily provided using a solar diffuser (SD) and a solar diffuser stability monitor (SDSM). The SD and SDSM calibration system is operated on a regular (weekly to bi-weekly) basis. The spectro-radiometric calibration assembly (SRCA) is another on-hoard calibrator that also provides RSB radiometric calibration support. For this purpose, the SRCA is operated in a radiometric mode on a monthly basis. A complete SRCA radiometric calibration is performed using different lamp configurations, or different radiance levels, to cover the range of RSB gain. Two additional SRCA modes with slightly different configurations are designed and operated for sensor on-orbit spectral and spatial characterization. In addition to its on-hoard calibrators, each MODIS makes monthly lunar observations to monitor RSB radiometric calibration stability. The MODIS lunar observations are made through its space view (SV) port at nearly the same lunar phase angles via spacecraft roll maneuvers. The SD, SRCA, and lunar measurements are made at different scan angles and data samples are collected for all spectral bands and detectors using both sides of the scan minor. Since launch, Terra and Aqua MODIS have operated successfully for more than 8 years and 6 years, respectively. Many SD/SDSM, SRCA, and lunar observations have been made by each instrument and used to derive RSB on-orbit calibration parameters, enabling corrections for sensor response changes and changes of the response versus scan angle (RVS). In general, the RSB calibration parameters are updated regularly into the MODIS Level 1B (LIB) code in support of continuous data processing for all MODIS science data products. This paper provides a brief description of MODIS RSB calibration methodologies and approaches, and summarizes on-orbit changes of their responses (gains), particularly for the VIS spectral bands.

Description: Since March 2002, the Gravity Recovery and Climate Experiment (GRACE) has provided first estimates of land water storage variations by monitoring the time-variable component of Earth's gravity field. Here we characterize spatial-temporal variations in terrestrial water storage changes (TWSC) from GRACE and compare them to those simulated with the Global Land Data Assimilation System (GLDAS). Additionally, we use GLDAS simulations to infer how TWSC is partitioned into snow, canopy water and soil water components, and to understand how variations in the hydrologic fluxes act to enhance or dissipate the stores. Results quantify the range of GRACE-derived storage changes during the studied period and place them in the context of seasonal variations in global climate and hydrologic extremes including drought and flood, by impacting land memory processes. The role of the largest continental river basins as major locations for freshwater redistribution is highlighted. GRACE-based storage changes are in good agreement with those obtained from GLDAS simulations. Analysis of GLDAS-simulated TWSC illustrates several key characteristics of spatial and temporal land water storage variations. Global averages of TWSC were partitioned nearly equally between soil moisture and snow water equivalent, while zonal averages of TWSC revealed the importance of soil moisture storage at low latitudes and snow storage at high latitudes. Evapotranspiration plays a key role in dissipating globally averaged terrestrial water storage. Latitudinal averages showed how precipitation dominates TWSC variations in the tropics, evapotranspiration is most effective in the midlatitudes, and snowmelt runoff is a key dissipating flux at high latitudes. Results have implications for monitoring water storage response to climate variability and change, and for constraining land model hydrology simulations.

Description: This viewgraph presentation reviews a project, the goal of which is to study the potential of MODIS data for monitoring historic gypsy moth defoliation. A NASA/USDA Forest Service (USFS) partnership was formed to perform the study. NASA is helping USFS to implement satellite data products into its emerging Forest Threat Early Warning System. The latter system is being developed by the USFS Eastern and Western Forest Threat Assessment Centers. The USFS Forest Threat Centers want to use MODIS time series data for regional monitoring of forest damage (e.g., defoliation) preferably in near real time. The study's methodology is described, and the results of the study are shown.

Description: The Time Series Product Tool (TSPT) is software, developed in MATLAB , which creates and displays high signal-to- noise Vegetation Indices imagery and other higher-level products derived from remotely sensed data. This tool enables automated, rapid, large-scale regional surveillance of crops, forests, and other vegetation. TSPT temporally processes high-revisit-rate satellite imagery produced by the Moderate Resolution Imaging Spectroradiometer (MODIS) and by other remote-sensing systems. Although MODIS imagery is acquired daily, cloudiness and other sources of noise can greatly reduce the effective temporal resolution. To improve cloud statistics, the TSPT combines MODIS data from multiple satellites (Aqua and Terra). The TSPT produces MODIS products as single time-frame and multitemporal change images, as time-series plots at a selected location, or as temporally processed image videos. Using the TSPT program, MODIS metadata is used to remove and/or correct bad and suspect data. Bad pixel removal, multiple satellite data fusion, and temporal processing techniques create high-quality plots and animated image video sequences that depict changes in vegetation greenness. This tool provides several temporal processing options not found in other comparable imaging software tools. Because the framework to generate and use other algorithms is established, small modifications to this tool will enable the use of a large range of remotely sensed data types. An effective remote-sensing crop monitoring system must be able to detect subtle changes in plant health in the earliest stages, before the effects of a disease outbreak or other adverse environmental conditions can become widespread and devastating. The integration of the time series analysis tool with ground-based information, soil types, crop types, meteorological data, and crop growth models in a Geographic Information System, could provide the foundation for a large-area crop-surveillance system that could identify a variety of plant phenomena and improve monitoring capabilities.