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AM0 solar cell calibration laboratories throughout the world are working together to create standard methods for AM0 calibration. In an effort to compare the results of different calibration methods, five different laboratories calibrated GaAs and Si solar cells. The results of this inter-comparison are presented herein.
Atmospheric and surface thermodynamic parameters retrieved with advanced hyperspectral remote sensors of Earth observing satellites are critical for weather prediction and scientific research. The retrieval algorithms and retrieved parameters from satellite sounders must be validated to demonstrate the capability and accuracy of both observation and data processing systems. The European AQUA Thermodynamic Experiment (EAQUATE) was conducted mainly for validation of the Atmospheric InfraRed Sounder (AIRS) on the AQUA satellite, but also for assessment of validation systems of both ground-based and aircraft-based instruments which will be used for other satellite systems such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) from the NPOESS Preparatory Project and the following NPOESS series of satellites. Detailed inter-comparisons were conducted and presented using different retrieval methodologies: measurements from airborne ultraspectral Fourier transform spectrometers, aircraft in-situ instruments, dedicated dropsondes and radiosondes, and ground based Raman Lidar, as well as from the European Center for Medium range Weather Forecasting (ECMWF) modeled thermal structures. The results of this study not only illustrate the quality of the measurements and retrieval products but also demonstrate the capability of these validation systems which are put in place to validate current and future hyperspectral sounding instruments and their scientific products.
This study provides a comprehensive inter-comparison of instantaneous rain estimates from the two rain sensors aboard the TRMM satellite with ground data from thee designated Ground Validation Sites: Kwajalein Atoll, Melbourne, Florida and Houston, Texas. The satellite rain retrievals utilize rain observations collected by the TRMM microwave imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard instantaneous rain products are the generated from the rain information retrieved from the satellite using the TMI, PR and Combined (COM) rain algorithms. The validation data set used in this study was obtained from instantaneous rain rates inferred from ground radars at each GV site. The first comparison used 0.5(sup 0) x 0.5(sup 0) gridded data obtained from the TRMM 3668 product, and similarly gridded GV data obtained from ground-based radars. The comparisons were made at the same spatial and temporal scales in order to eliminate sampling biases in our comparisons. An additional comparison was made by averaging rain rates for the PR, COM and GV estimates within each TMI footprint (approx. 150 square kilometers). For this analysis, unconditional mean rain rates from PR, COM and GV estimates were calculated within each TMI footprint that was observed within 100 km from the respective GV site (and also observed by the PR). This analysis used all the available matching data from the period 1999-2004, representing a sample size of over 50,000 footprints for each site. In the first analysis our results showed that all of the respective rain rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm per hour over the ocean. This mode was noted over ocean areas of Melbourne, Florida and Kwajalein, Republic of the Marshall Islands, and is shown to exist in TRMM tropical-global ocean areas as well. Further research by algorithm developers is needed to explain or justify the seemingly errant observed probability distributions.
High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single field-of-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud top pressure (CTP) and cloud optical thickness (COT) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Center of Medium range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from 38 high-spectral infrared (IR) sounder instruments.
The Joint Airborne IASI Validation Experiment (JAIVEx) was conducted during April 2007 mainly for validation of the Infrared Atmospheric Sounding Interferometer (IASI) on the MetOp satellite, but also included a strong component focusing on validation of the Atmospheric InfraRed Sounder (AIRS) aboard the AQUA satellite. The cross validation of IASI and AIRS is important for the joint use of their data in the global Numerical Weather Prediction process. Initial inter-comparisons of geophysical products have been conducted from different aspects, such as using different measurements from airborne ultraspectral Fourier transform spectrometers (specifically, the NPOESS Airborne Sounder Testbed Interferometer (NAST-I) and the Scanning-High resolution Interferometer Sounder (S-HIS) aboard the NASA WB-57 aircraft), UK Facility for Airborne Atmospheric Measurements (FAAM) BAe146-301 aircraft insitu instruments, dedicated dropsondes, radiosondes, and ground based Raman Lidar. An overview of the JAIVEx retrieval validation plan and some initial results of this field campaign are presented.
The global hydrological cycle is central to the Earth's climate system, with rainfall and the physics of precipitation formation acting as the key links in the cycle. Two-thirds of global rainfall occurs in the tropics with the associated latent heating (LH) accounting for three-fourths of the total heat energy available to the Earth's atmosphere. In addition, fresh water provided by tropical rainfall and its variability exerts a large impact upon the structure and motions of the upper ocean layer. In the last decade, it has been established that standard products of LH from satellite measurements, particularly TRMM measurements, would be a valuable resource for scientific research and applications. Such products would enable new insights and investigations concerning the complexities of convection system life cycles, the diabatic heating controls and feedbacks related to meso-synoptic circulations and their forecasting, the relationship of tropical patterns of LH to the global circulation and climate, and strategies for improving cloud parameterizations in environmental prediction models. The status of retrieved TRMM LH products, TRMM LH inter-comparison and validation project, current TRMM LH applications and critic issues/action items (based on previous five TRMM LH workshops) is presented in this article.
This study provides a comprehensive inter-comparison of instantaneous rain rates observed by the two rain sensors aboard the TRMM satellite with ground data from two regional sites established for long-term ground validation: Kwajalein Atoll and Melbourne, Florida. The satellite rain algorithms utilize remote observations of precipitation collected by the TRMM microwave imager (TMI) and the Precipitation Radar (PR) aboard the TRMM satellite. Three standard Level I1 rain products are generated from operational applications of the TMI, PR and Combined (COM) rain algorithms using rain information collected from the TMI and the PR along the orbital track of the TRMM satellite. In the first part of the study, 0.25 x 0.25 instantaneous rain rates obtained from the TRMM 3668 product were analyzed and compared to instantaneous GV rain rates gridded at a scale of 0.5deg x 0.5. In the second part of the study, TMI, PR, COM and GV rain rates were spatio-temporally matched and averaged at the scale of TMI footprint (- 150 sq km). This study covered a six-year period 1999-2004 and consisted of over 50,000 footprints for each GV site. In the first analysis our results showed that all of the respective rain rate estimates agree well, with some exceptions. The more salient differences were associated with heavy rain events in which one or more of the algorithms failed to properly retrieve these extreme events. Also, it appears that there is a preferred mode of precipitation for TMI rain rates at or near 2 mm/hr over the ocean. This mode was noted over ocean areas of Kwajalein and Melbourne and has been observed in TRMM tropical-global ocean areas as well.
Both Terra and Aqua MODIS have been making periodic lunar observations since their launch in December 1999 and May 2002, respectively. The primary objective of the MODIS lunar observations is to monitor on-orbit response changes for the reflective solar bands (RSB) and to track long-term radiometric calibration stability. The Moon is an extremely stable surface reflectance reference and, together with the lunar radiometric model developed recently by the US Geological Survey (USGS), the applications of lunar observations for Earth remote sensing missions have been greatly enhanced and expanded. In particular, calibration inter-comparisons among sensors on different platforms and operated in different time frames have been enabled in the VIS/NIR/SWIR spectral regions. In this paper, we discuss various applications of MODIS lunar observations, such as monitoring the RSB radiometric stability and calibration consistency between the two sensors, evaluating the calibration differences among detectors within the same spectral band, and tracking the on-orbit changes of band-to-band registration (BBR). Other applications designed for the thermal emissive bands (TEB) and special sensor characterization purposes are also illustrated. Results from multi-year Terra and Aqua MODIS lunar observations demonstrate clearly that the two sensors have been calibrated consistently to within 1% for most RSB compared to the 2% radiometric calibration requirement. In addition the spatial characterization results derived from lunar observations are in good agreement with those derived from the instrument's on-board calibrator. The applications and results of MODIS lunar observations presented in this paper provide useful references for other sensors that also make use of lunar surface observations.
This paper describes a comprehensive assessment of a new high-resolution, high-quality gauge-satellite based analysis of daily precipitation over continental South America during 2004. This methodology is based on a combination of additive and multiplicative bias correction schemes in order to get the lowest bias when compared with the observed values. Inter-comparisons and cross-validations tests have been carried out for the control algorithm (TMPA real-time algorithm) and different merging schemes: additive bias correction (ADD), ratio bias correction (RAT) and TMPA research version, for different months belonging to different seasons and for different network densities. All compared merging schemes produce better results than the control algorithm, but when finer temporal (daily) and spatial scale (regional networks) gauge datasets is included in the analysis, the improvement is remarkable. The Combined Scheme (CoSch) presents consistently the best performance among the five techniques. This is also true when a degraded daily gauge network is used instead of full dataset. This technique appears a suitable tool to produce real-time, high-resolution, high-quality gauge-satellite based analyses of daily precipitation over land in regional domains.
NASA NEESPI (Northern Eurasia Earth Science Partnership Initiative) data portal is a NASA funded project that focuses on collecting satellite remote sensing data, providing tools, information, and services in support of NEESPI scientific objectives (Leptoukh, et al., 2007). The data can be accessed online through anonymous ftp, through an advanced data searching and ordering system Mirador that uses keywords to find data quickly in a Google-like interface, and through the Goddard Interactive Online Visualization ANd aNalysis Infrastructure (Giovanni). The portal provides preprocessed data from different satellite sensors and numerical models to the same spatial and temporal resolution and the same projection so that the data can be used easily to perform inter-comparison or relationship studies. In addition, it provides parameter and spatially subsetted data for regional studies. Studies of regional carbon, hydrology, aerosols in non-boreal Europe and their interactions with global climate are very challenging research topics. The NASA NEESPI data portal makes many satellite data available for such studies, including information on land cover types, fire, vegetation index, aerosols, land surface temperature, soil moisture, precipitation, snow/ice, and other parameters. This paper will introduce the features and products available in the system, focusing on the online data 1 tool, Giovanni NEESPI. An example that explores different data through Giovanni NEESPI in temperate region of non-boreal Europe will be presented.
Jet Propulsion Laboratory currently operates lidar systems at Table Mountain Facility (TMF), California (34.4 deg N, 117.7 deg W at 2300m) and Mauna Loa Observatory (MLO), Hawaii (19.5 deg N, 155.6 deg W at 3400m) under the Network for the Detection of Atmospheric Composition Change (NDACC, formerly NDSC). To complement existing NDACC lidars at TMF, which acts as a primary site for inter-comparisons, a new water vapor and temperature lidar has begun routine operation with typically 3-4 nightly profiles per week. As water vapor is a key greenhouse gas, and is highly variable on annual and seasonal cycles, accurate long term measurements are necessary for predictions of climate change and to increase our understanding of the atmospheric processes it contributes to. The new TMF lidar has demonstrated high spatial and temporal resolution, with a high degree of optimization being achieved over the past year, although the authors believe further improvement may yet be possible. The lidar has been designed for accuracies of 5% up to 12km in the free troposphere with the capability to measure to the tropopause and lower stratosphere with accuracies of 1 ppm. It is anticipated that the data sets produced will be used for Aura validation and for incorporation into NDACC archives. Validation results for the optimized system are presented with intercomparisons using Vaisala RS92-K radiosondes.
The Measurements of Humidity in the Atmosphere and Validation Experiments (MOHAVE, MOHAVE-II) inter-comparison campaigns took place at the Jet Propulsion Laboratory (JPL) Table Mountain Facility (TMF, 34.5(sup o)N) in October 2006 and 2007 respectively. Both campaigns aimed at evaluating the capability of three Raman lidars for the measurement of water vapor in the upper troposphere and lower stratosphere (UT/LS). During each campaign, more than 200 hours of lidar measurements were compared to balloon borne measurements obtained from 10 Cryogenic Frost-point Hygrometer (CFH) flights and over 50 Vaisala RS92 radiosonde flights. During MOHAVE, fluorescence in all three lidar receivers was identified, causing a significant wet bias above 10-12 km in the lidar profiles as compared to the CFH. All three lidars were reconfigured after MOHAVE, and no such bias was observed during the MOHAVE-II campaign. The lidar profiles agreed very well with the CFH up to 13-17 km altitude, where the lidar measurements become noise limited. The results from MOHAVE-II have shown that the water vapor Raman lidar will be an appropriate technique for the long-term monitoring of water vapor in the UT/LS given a slight increase in its power-aperture, as well as careful calibration.
A prototype global satellite-based landslide hazard algorithm has been developed to identify areas that exhibit a high potential for landslide activity by combining a calculation of landslide susceptibility with satellite-derived rainfall estimates. A recent evaluation of this algorithm framework found that while this tool represents an important first step in larger-scale landslide forecasting efforts, it requires several modifications before it can be fully realized as an operational tool. The evaluation finds that the landslide forecasting may be more feasible at a regional scale. This study draws upon a prior work's recommendations to develop a new approach for considering landslide susceptibility and forecasting at the regional scale. This case study uses a database of landslides triggered by Hurricane Mitch in 1998 over four countries in Central America: Guatemala, Honduras, EI Salvador and Nicaragua. A regional susceptibility map is calculated from satellite and surface datasets using a statistical methodology. The susceptibility map is tested with a regional rainfall intensity-duration triggering relationship and results are compared to global algorithm framework for the Hurricane Mitch event. The statistical results suggest that this regional investigation provides one plausible way to approach some of the data and resolution issues identified in the global assessment, providing more realistic landslide forecasts for this case study. Evaluation of landslide hazards for this extreme event helps to identify several potential improvements of the algorithm framework, but also highlights several remaining challenges for the algorithm assessment, transferability and performance accuracy. Evaluation challenges include representation errors from comparing susceptibility maps of different spatial resolutions, biases in event-based landslide inventory data, and limited nonlandslide event data for more comprehensive evaluation. Additional factors that may improve algorithm performance accuracy include incorporating additional triggering factors such as tectonic activity, anthropogenic impacts and soil moisture into the algorithm calculation. Despite these limitations, the methodology presented in this regional evaluation is both straightforward to calculate and easy to interpret, making results transferable between regions and allowing findings to be placed within an inter-comparison framework. The regional algorithm scenario represents an important step in advancing regional and global-scale landslide hazard assessment and forecasting.
Expanding human presence in space, and enabling the commercialization of this frontier, is part of the strategic goals for NASA's Human Exploration and Development of Space (HEDS) enterprise. Future near-Earth and planetary missions will support the use of high-frequency Earth-space communication systems. Additionally, increased commercial demand on low-frequency Earth-space links in the S- and C-band spectra have led to increased interest in the use of higher frequencies in regions like Ku and Ka-band. Attenuation of high-frequency signals, due to a precipitating medium, can be quite severe and can cause considerable disruptions in a communications link that traverses such a medium. Previously, ground radar measurements were made along the Earth-space path and compared to satellite beacon data that was transmitted to a ground station. In this paper, quantitative estimation of the attenuation along the propagation path is made via inter-comparisons of radar data taken from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) and ground-based polarimetric radar observations. Theoretical relationships between the expected specific attenuation (k) of spaceborne measurements with ground-based measurements of reflectivity (Zh) and differential propagation phase shift (Kdp) are developed for various hydrometeors that could be present along the propagation path, which are used to estimate the two-way path-integrated attenuation (PIA) on the PR return echo. Resolution volume matching and alignment of the radar systems is performed, and a direct comparison of PR return echo with ground radar attenuation estimates is made directly on a beam-by-beam basis. The technique is validated using data collected from the TExas and Florida UNderflights (TEFLUN-B) experiment and the TRMM large Biosphere-Atmosphere experiment in Amazonia (LBA) campaign. Attenuation estimation derived from this method can be used for strategiC planning of communication systems for future HEDS missions.
The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.
Impervious surface area (ISA) from the National Geophysical Data Center (NGDC) and land surface temperature (LST) from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the urban heat island (UHI) signature on LST amplitude and its relationship to development intensity, size, and ecological setting for more than 3000 urban settlements over the globe. Development intensity zones based on fractional ISA are defined for each urban area emanating outward from the urban core to the nearby non-urban rural areas and used to stratify sampling for LST. Sampling is further constrained by biome type and elevation data to insure objective inter-comparisons between zones and between cities in different biomes. We find that the ecological context and settlement size significantly influence the amplitude of summer daytime UHI. Globally, an average of 3.8 C UHI is found in cities built in biomes dominated by forests; 1.9 C UHI in cities embedded in grass/shrub biomes, and only a weak UHI or sometimes an Urban Heat Sink (UHS) in cities in and and semi-arid biomes. Overall, the amplitude of the UHI is negatively correlated (R = -0.66) to the difference in vegetation density between urban and rural zones represented by MODIS Normalized Difference Vegetation Index (NDVI). Globally averaged, the daytime UHI amplitude for all settlement is 2.6 C in summer and 1.4 C in winter. Globally, the average summer daytime UHI is 4.7 C for settlements larger than 500 square kilometers, compared to 2.5 C for settlements smaller than 50 square kilometers and larger than 10 square kilometers. The stratification of cities by size indicates that the aggregated amount of ISA is the primary driver of UHI amplitude with variations between ecological contexts and latitudinal zones. More than 60% of the total LST variances is explained by ISA for urban settlements within forests at mid-to-high latitudes. This percentage will increase to more than 80% when only USA settlements are examined.
This slide presentation describes transport codes and their use for studying and designing space radiation shielding. When combined with risk projection models radiation transport codes serve as the main tool for study radiation and designing shielding. There are three criteria for assessing the accuracy of transport codes: (1) Ground-based studies with defined beams and material layouts, (2) Inter-comparison of transport code results for matched boundary conditions and (3) Comparisons to flight measurements. These three criteria have a very high degree with NASA's HZETRN/QMSFRG.
Determination of the calibration accuracy and traceability of a remote sensing instrument is a driving issue in the use of satellite data for calibration inter-comparisons and studying climate change. The Terra and Aqua MODerate Resolution Imaging Spectroradiometer (MODIS) instruments have successfully operated for more than 11 and 9 years, respectively. Twenty of the thirty six MODIS spectral bands are in the reflected solar region with center wavelengths ranging from 0.41 to 2.2 microns. MODIS reflective solar band (RSB) on-orbit calibration is reflectance based through the use of an on-board solar diffuser (SO). The calibration uncertainty requirements are +/-2.0% for the RSB reflectance factors at sensor specified typical scene reflectances or radiances. The SO bi-directional reflectance factor (BRF) was characterized pre-launch and its on-orbit changes are tracked by an on-board solar diffuser stability monitor (SDSM). This paper provides an assessment of MODIS RSB on-orbit calibration traceability and uncertainty for its Level 1B (L1B) reflectance factors. It examines in details each of the uncertainty contributors, including those from pre-launch measurements as well as on-orbit observations. Common challenging issues and differences due to individual sensors' specific characteristics and on-orbit performance are also discussed in this paper. Guidance and recommendations are presented, based on lessons from MODIS RSB calibration uncertainty assessment, for the development of future instrument calibration and validation plans.