AIRS near-real-time products and algorithms in support of operational numerical weather prediction

The assimilation of Atmospheric InfraRed Sounder, Advanced Microwave Sounding Unit-A, and Humidity Sounder for Brazil (AIRS/AMSU/HSB) data by Numerical Weather Prediction (NWP) centers is expected to result in improved forecasts. Specially tailored radiance and retrieval products derived from AIRS/AMSU/HSB data are being prepared for NWP centers. There are two types of products - thinned radiance data and full-resolution retrieval products of atmospheric and surface parameters. The radiances are thinned because of limitations in communication bandwidth and computational resources at NWP centers. There are two types of thinning: (1) spatial and spectral thinning and (2) data compression using principal component analysis (PCA). PCA is also used for quality control and for deriving the retrieval first guess used in the AIRS processing software. Results show that PCA is effective in estimating and filtering instrument noise. The PCA regression retrievals show layer mean temperature (1 km in troposphere, 3 km in stratosphere) accuracies of better than 1 K in most atmospheric regions from simulated AIRS data. Moisture errors are generally less than 15% in 2-km layers, and ozone errors are near 10% over approximately 5-km layers from simulation. The PCA and regression methodologies are described. The radiance products also include clear field-of-view (FOV) indicators. The residual cloud amount, based on simulated data, for FOVs estimated to be clear (free of clouds) is about 0.5% over ocean and 2.5% over land.     

AIRS/AMSU/HSB validation

The Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit/Humidity Sounder for Brazil (AIRS/AMSU/HSB) instrument suite onboard Aqua observes infrared and microwave radiances twice daily over most of the planet. AIRS offers unprecedented radiometric accuracy and signal to noise throughout the thermal infrared. Observations from the combined suite of AIRS, AMSU, and HSB are processed into retrievals of atmospheric parameters such as temperature, water vapor, and trace gases under all but the cloudiest conditions. A more limited retrieval set based on the microwave radiances is obtained under heavy cloud cover. Before measurements and retrievals from AIRS/AMSU/HSB instruments can be fully utilized they must be compared with the best possible in situ and other ancillary "truth" observations. Validation is the process of estimating the measurement and retrieval uncertainties through comparison with a set of correlative data of known uncertainties. The ultimate goal of the validation effort is retrieved product uncertainties constrained to those of radiosondes: tropospheric rms uncertainties of 1.0 degC over a 1-km layer for temperature, and 10% over 2-km layers for water vapor. This paper describes the data sources and approaches to be used for validation of the AIRS/AMSU/HSB instrument suite, including validation of the forward models necessary for calculating observed radiances, validation of the observed radiances themselves, and validation of products retrieved from the observed radiances. Constraint of the AIRS product uncertainties to within the claimed specification of 1 K/1 km over well-instrumented regions is feasible within 12 months of launch, but global validation of all AIRS/AMSU/HSB products may require considerably more time due to the novelty and complexity of this dataset and the sparsity of some types of correlative observations.     

Retrieval of atmospheric and surface parameters from AIRS/AMSU/HSB data in the presence of clouds

New state-of-the-art methodology is described to analyze the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit/Humidity Sounder for Brazil (AIRS/AMSU/HSB) data in the presence of multiple cloud formations. The methodology forms the basis for the AIRS Science Team algorithm, which will be used to analyze AIRS/AMSU/HSB data on the Earth Observing System Aqua platform. The cloud-clearing methodology requires no knowledge of the spectral properties of the clouds. The basic retrieval methodology is general and extracts the maximum information from the radiances, consistent with the channel noise covariance matrix. The retrieval methodology minimizes the dependence of the solution on the first-guess field and the first-guess error characteristics. Results are shown for AIRS Science Team simulation studies with multiple cloud formations. These simulation studies imply that clear column radiances can be reconstructed under partial cloud cover with an accuracy comparable to single spot channel noise in the temperature and water vapor sounding regions; temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 1 K in 1-km-thick layers from the surface to 700 mb, 1-km layers from 700-300 mb, 3-km layers from 300-30 mb, and 5-km layers from 30-1 mb; and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 1-km layers from the surface to nearly 200 mb.     

Retrieval, validation, and application of the 1-km aerosol optical depth from MODIS measurements over Hong Kong

The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol retrieval algorithm was developed to derive aerosol properties at a global scale, suitable for climate studies. Under favorable conditions (clear sky and over dark surfaces), the standard 10/spl times/10 km MODIS aerosol products are also useful on regional scales to monitor aerosol distributions and transports. However, the 10-km resolution is insufficient to depict aerosol variation on local or urban scales, due to inherent aerosol variability as well as complex surface terrain. In this study, we have modified the MODIS algorithm to retrieve aerosol optical depth (AOD) at 1-km resolution over Hong Kong, a city of just over 1000 km/sup 2/ with very complex surface features. Accompanied by the increased spatial resolution are new aerosol models derived with single-scattering albedo (SSA) around 0.91-0.94 to accommodate higher aerosol absorption encountered in Hong Kong than that was presumed for MODIS standard products (SSA/spl sim/0.97) over the region. The derived AOD data are compared to handheld Microtops II sunphotometer observations at the Hong Kong University of Science and Technology and other locations across Hong Kong. Retrieval errors within 15% to 20% of sunphotometer measurements are found. Moreover, when compared with the standard 10-km AOD products, the 1-km AOD data are much better correlated with PM/sub 10/ measurements across Hong Kong, suggesting that the new 1-km AOD data can be used to better characterize the particulate matter distribution for cities like Hong Kong than the MODIS standard products.     

Terra MODIS on-orbit spectral characterization and performance

The Moderate Resolution Imaging Spectroradiometer (MODIS) protoflight model onboard the National Aeronautics and Space Administration's Earth Observing System Terra spacecraft has been in operation for over five years since its launch in December 1999. It makes measurements using 36 spectral bands with wavelengths from 0.41 to 14.5 /spl mu/m. Bands 1-19 and 26 with wavelengths below 2.2 /spl mu/m, the reflective solar bands (RSBs), collect daytime reflected solar radiance at three nadir spatial resolutions: 0.25 km (bands 1-2), 0.5 km (bands 3-7), and 1 km (bands 8-19 and 26). Bands 20-25 and 27-36, the thermal emissive bands, collect both daytime and nighttime thermal emissions, at 1-km nadir spatial resolution. The MODIS spectral characterization was performed prelaunch at the system level. One of the MODIS onboard calibrators, the Spectroradiometric Calibration Assembly (SRCA), was designed to perform on-orbit spectral characterization of the MODIS RSB. This paper provides a brief overview of MODIS prelaunch spectral characterization, but focuses primarily on the algorithms and results of using the SRCA for on-orbit spectral characterization. Discussions are provided on the RSB center wavelength measurements and their relative spectral response retrievals, comparisons of on-orbit results with those from prelaunch measurements, and the dependence of center wavelength shifts on instrument temperature. For Terra MODIS, the center wavelength shifts over the past five years are less than 0.5 nm for most RSBs, indicating excellent stability of the instrument's spectral characteristics. Similar spectral performance has also been obtained from the Aqua MODIS (launched in May 2002) SRCA measurements.     

AIRS radiance validation over ocean from sea surface temperature measurements

Demonstrates the accuracy of methods and in situ data for early validation of calibrated Earth scene radiances measured by the Atmospheric InfraRed Sounder (AIRS) on the Aqua spacecraft. We describe an approach for validation that relies on comparisons of AIRS radiances with drifting buoy measurements, ship radiometric observations and mapped sea surface temperature products during the first six months after launch. The focus of the validation is on AIRS channel radiances in narrow spectral window regions located between 800-1250 cm/sup -1/ and between 2500 and 2700 cm/sup -1/. Simulated AIRS brightness temperatures are compared to in situ and satellite-based observations of sea surface temperature colocated in time and space, to demonstrate accuracies that can be achieved in clear atmospheres. An error budget, derived from single channel, single footprint matchups, indicates AIRS can be validated to better than 1% in absolute radiance (equivalent to 0.5 K in brightness temperature, at 300 K and 938 cm/sup -1/) during early mission operations. The eventual goal is to validate instrument radiances close to the demonstrated prelaunch calibration accuracy of about 0.4% (equivalent to 0.2 K in brightness temperature, at 300 K and 938 cm/sup -1/).     

Validation of MODIS Albedo Products of Paddy Fields in Japan

A study was conducted in Chiba, Japan, to validate Moderate Resolution Imaging Spectroradiometer (MODIS) albedo products by taking the field measurements of shortwave band albedos in paddy fields. A large difference in spatial scale, from field-measured point data to 1-km resolution, complicates the validation process. To assess such effect of different spatial scales, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Enhanced Thematic Mapper Plus (ETM+) data were used. Spatial scale effects on the albedo were examined from three viewpoints: 1) comparison between point-based albedo and mean of albedo in homogeneous area; 2) comparison between point-based albedo and 1-km aggregated albedo; and 3) assessment of semivariogram of albedo in homogeneous area. In implementation of viewpoint 2), Liang's regression model was applied to convert ASTER reflectance into shortwave band albedo. The 1-km ASTER albedo was estimated using the point spread function, and in the same manner, 1-km ETM+ albedo was estimated. All results represent that an area around the measurement site can be assumed to be homogeneous, indicating negligible effects of spatial resolution difference during most of the periods. Comparison of ground-point-based albedos with MODIS actual albedo, estimated from MODIS black-sky albedo, white-sky albedo, and a fraction of diffuse skylight, showed that the accuracy of MODIS albedo products for paddy fields in Japan is within approximately 0.026 by absolute value (root-mean-square error) and 15.1% by relative value     

Vertical Resolution Estimates in Version 5 of AIRS Operational Retrievals

In this paper, we present an overview of averaging-kernel computations from the Atmospheric Infrared Sounder (AIRS) Version 5 product retrieval software. Temperature and moisture retrievals form the focus of this paper; however, some results for all other retrieved gas amounts are presented. The theory and methodology required to utilize the averaging kernels for comparison of AIRS retrievals with correlative measurements are given. The averaging kernels are used to transform correlative measurements to AIRS effective resolution and are used to assess and derive the vertical resolution of Version 5 temperature and moisture retrievals in different atmospheric conditions. We find that depending on the scene, AIRS Version 5 tropospheric temperature (moisture) retrieval resolution, which is as determined by the full-width at half-maximum of the averaging kernels, ranges between 2.5 km (2.7 km) near the surface and 7.1 km (4.3 km) near the tropopause.      

Aerosol Optical Depth Retrieval Over the NASA Stennis Space Center: MTI, MODIS, and AERONET

The Multispectral Thermal Imager (MTI) and the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-based aerosol optical depth (AOD) retrievals are compared to each other and to the sun photometer AOD measurements at the National Aeronautics and Space Administration's Stennis Aerosol Robotic Network (AERONET) site. The overall accuracy of the MODIS AOD retrieval is approximately the same as the accuracy of the MTI with close-to-nadir view (at large scattering angles) when compared with AERONET measurements. The accuracy of the MODIS AOD retrieval is found to be a function of the scattering angle (the angle between the direction of the incoming and the scattered photons). The root mean square error of the MODIS AOD retrieval at the Stennis site is found to increase from 0.04 at scattering angles between 90$^circ$and 105$^circ$to over 0.12 at scattering angles from 140$^circ$to 165$^circ$. Using only moderate scattering angles$(≪105^circ)$can significantly increase the accuracy of the MODIS AOD retrievals.     

TES level 1 algorithms: interferogram processing, geolocation, radiometric, and spectral calibration

The Tropospheric Emission Spectrometer (TES) on the Earth Observing System (EOS) Aura satellite measures the infrared radiance emitted by the Earth's surface and atmosphere using Fourier transform spectrometry. The measured interferograms are converted into geolocated, calibrated radiance spectra by the L1 (Level 1) processing, and are the inputs to L2 (Level 2) retrievals of atmospheric parameters, such as vertical profiles of trace gas abundance. We describe the algorithmic components of TES Level 1 processing, giving examples of the intermediate results and diagnostics that are necessary for creating TES L1 products. An assessment of noise-equivalent spectral radiance levels and current systematic errors is provided. As an initial validation of our spectral radiances, TES data are compared to the Atmospheric Infrared Sounder (AIRS) (on EOS Aqua), after accounting for spectral resolution differences by applying the AIRS spectral response function to the TES spectra. For the TES L1 nadir data products currently available, the agreement with AIRS is 1 K or better.     

AIRS/Vis near IR instrument

A component of the Atmospheric Infrared Sounder (AIRS) instrument system is the AIRS/Visible Near InfraRed (Vis/NIR) instrument. With a nadir ground resolution of 2.28 km and four channels, the Vis/NIR instrument provides diagnostic support to the infrared retrievals from the AIRS instrument and several research products, including surface solar flux studies. The AIRS Vis/NIR is composed of three narrowband (channel 1: 0.40-0.44 /spl mu/m; channel 2: 0.58-0.68 /spl mu/m, and channel 3: 0.71-0.92 /spl mu/m) and one broadband (channel 4: 0.49-0.94 /spl mu/m) channel, each a linear detector array of nine pixels. It is calibrated onboard with three tungsten lamps. Vicarious calibrations using ground targets of known reflectance and a cross-calibration with the Moderate Resolution Imaging Spectroradiometer (MODIS) augment the onboard calibration. One of AIRS Vis/NIR's principal supporting functions is the detection of low clouds to flag these conditions for atmospheric temperature retrievals. Once clouds are detected, a cloud height index is obtained based on the ratio (channel 2 - channel 3)/channel 1 that is sensitive to the partitioning of water vapor absorption above and below clouds. The determination of the surface solar radiation flux is principally based on channel 4 broadband measurements and the well-established relationship between top-of-the atmosphere (broadband) radiance and the surface irradiance.     

A neural-network technique for the retrieval of atmospheric temperature and moisture profiles from high spectral resolution sounding data

A novel statistical method for the retrieval of atmospheric temperature and moisture profiles has been developed and evaluated with simulated clear-air and observed partially cloudy sounding data from the Atmospheric InfraRed Sounder (AIRS) and the Advanced Microwave Sounding Unit (AMSU). The algorithm is implemented in two stages. First, a projected principal components (PPC) transform is used to reduce the dimensionality of and optimally extract geophysical profile information from the cloud-cleared infrared radiance data. Second, a multilayer feedforward neural network (NN) is used to estimate the desired geophysical parameters from the PPCs. For the first time, NN temperature and moisture retrievals are presented using actual microwave and hyperspectral infrared observations of cloudy atmospheres, over both ocean and land (with variable terrain elevation), and at all sensor scan angles. The performance of the NN retrieval method (henceforth referred to as the PPC/NN method) was evaluated using global Earth Observing System Aqua orbits colocated with European Center for Medium-range Weather Forecasting fields for seven days throughout 2002 and 2003. Over 350,000 partially cloudy footprints were used in the study, and retrieval performance was compared with the AIRS Science Team Level-2 retrieval algorithm (version 3). Performance compares favorably with that obtained with simulated clear-air observations from the NOAA88b radiosonde set of approximately 7500 profiles. The PPC/NN method requires significantly less computation than traditional variational retrieval methods, while achieving comparable performance.     

Key characteristics of MODIS data products

Forty science products totaling 600 GB of storage volume per day will be produced from NASA's Moderate Resolution Imaging Spectroradiometer (MODIS). Eighty-five percent of this data volume is in products that are in the instrument's scan geometry (processing Levels 1 and 2) that are not Earth located. Before ordering MODIS data products, users should consider processing level, data formats, product size, and the unique characteristics of MODIS products. Given the data volumes associated with the MODIS Levels 1 and 2 products, the resources required to process them and the issues associated with the scanning geometry of the instrument, users are encouraged to order data products that are Earth located. These include Level 3 products, which are produced on fixed global grids and Level 2G products, in which observations and their Earth location have been stored in bins of the MODIS global grids     

AIRS/AMSU/HSB precipitation estimates

Precipitation rates (mm per hour) with 15- and 50-km horizontal resolution are among the initial products of Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit/Humidity Sounder for Brazil (AIRS/AMSU/HSB). They will help identify the meteorological state of the atmosphere and any AIRS soundings potentially contaminated by precipitation. These retrieval methods can also be applied to the AMSU 23-191-GHz data from operational weather satellites such as NOAA-15, -16, and -17. The global extension and calibration of these methods are subjects for future research. The precipitation-rate estimation method presented is based on the opaque-channel approach described by Staelin and Chen (2000), but it utilizes more channels (17) and training data and infers 54-GHz band radiance perturbations at 15-km resolution. The dynamic range now reaches 100 mm/h. The method utilizes neural networks trained using the National Weather Service's Next Generation Weather Radar (NEXRAD) precipitation estimates for 38 coincident rainy orbits of NOAA-15 AMSU data obtained over the eastern United States and coastal waters during a full year. The rms discrepancies between AMSU and NEXRAD were evaluated for the following NEXRAD rain-rate categories: <0.5, 0.5-1, 1-2, 2-4, 4-8, 8-16, 16-32, and >32 mm/h. The rms discrepancies for the 3790 15-km pixels not used to train the estimator were 1.0, 2.0, 2.3, 2.7, 3.5, 6.9, 19.0, and 42.9 mm/h, respectively. The 50-km retrievals were computed by spatially filtering the 15-km retrievals. The rms discrepancies over the same categories for all 4709 50-km pixels flagged as potentially precipitating were 0.5, 0.9, 1.1, 1.8, 3.2, 6.6, 12.9, and 22.1 mm/h, respectively. Representative images of precipitation for tropical, mid-latitude, and snow conditions suggest the method's potential global applicability.     

Aerosol-cloud interaction-Misclassification of MODIS clouds in heavy aerosol

The accuracy of the spaceborne Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask was evaluated for possible contamination by areas of heavy aerosol that may be misclassified as clouds. Analysis for several aerosol types shows that the cloud mask and products can be safely used in the presence of aerosol up to optical thickness of 0.6. Here we define as cloudy all MODIS 1-km (at nadir) pixels that were used to derive the cloud effective radius and optical thickness of water and ice clouds. The findings make it possible to study aerosol-cloud interaction from the MODIS aerosol and cloud products.     

Implementation and Evaluation of Concurrent Gradient Search Method for Reprojection of MODIS Level 1B Imagery

This paper presents details regarding implementation of a novel algorithm for reprojection of Moderate Resolution Imaging Spectroradiometer (MODIS) Level 1B imagery. The method is based on a simultaneous 2-D search in latitude and longitude geolocation fields by using their local gradients. Due to the segmented structure of MODIS imagery caused by the instrument whiskbroom electrooptical design, the gradient search is realized in the following two steps: intersegment and intrasegment search. This approach resolves the discontinuity of the latitude/longitude geolocation fields caused by overlap between consecutively scanned MODIS multidetector image segments. The structure of the algorithm allows equal efficiency with nearest neighbor and bilinear interpolation. A special procedure that combines analytical and numerical schemes is designed for reprojecting imagery near the polar region, where the standard gradient search may become unstable. The performance of the method was validated by comparison of reprojected MODIS/Terra and MODIS/Aqua images with georectified Landsat-7 Enhanced Thematic Mapper Plus imagery over Canada. It was found that the proposed method preserves the absolute geolocation accuracy of MODIS pixels determined by the MODIS geolocation team. The method was implemented to reproject MODIS Level 1B imagery over Canada, North America, and Arctic circumpolar zone in the following four popular geographic projections: Plate Care (cylindrical equidistant), Lambert Conic Conformal, Universal Transverse Mercator, and Lambert Azimuthal Equal-Area. It was also found to be efficient for reprojection of Advanced Very High Resolution Radiometer and Medium Resolution Imaging Spectrometer satellite images and general-type meteorological fields, such as the North American Regional Reanalysis data sets.     

An overview of MODIS capabilities for ocean science observations

The Moderate Resolution Imaging Spectroradiometer (MODIS) will add a significant new capability for investigating the 70% of the Earth's surface that is covered by oceans, in addition to contributing to the continuation of a decadal scale time series necessary for climate change assessment in the oceans. Sensor capabilities of particular importance for improving the accuracy of ocean products include high SNR and high stability for narrow or spectral bands, improved onboard radiometric calibration and stability monitoring, and improved science data product algorithms. Spectral bands for resolving solar-stimulated chlorophyll fluorescence and a split window in the 4-μm region for SST will result in important new global ocean science products for biology and physics. MODIS will return full global data at 1-km resolution. The complete suite of Levels 2 and 3 ocean products is reviewed, and many areas where MODIS data are expected to make significant, new contributions to the enhanced understanding of the oceans' role in understanding climate change are discussed. In providing a highly complementary and consistent set of observations of terrestrial, atmospheric, and ocean observations, MODIS data will provide important new information on the interactions between Earth's major components     

RADARSAT [SAR imaging]

RADARSAT, the first Canadian remote-sensing spacecraft, is designed to provide Earth observation information for five years. The satellite is scheduled for launch in 1994. The only payload instrument is a 5.6-cm-wavelength (C-band) synthetic aperture imaging radar (SAR). RADARSAT will gather data on command for up to 28 min during each cycle of its 800-km (nominal) near-polar orbit. Image resolutions from 10 to 100 m at swath widths of 45 to 500 km will be available. The RADARSAT mission is reviewed, and the design, characteristics, and implementation of the radar are introduced. Technical problems addressed include calibration, rapid data processing, the phased array antenna that provides controlled beam steering, and the first satellite implementation of a special radar technique known as ScanSAR     

The GPS Contribution to the Error Budget of Surface Elevations Derived From Airborne LIDAR

When using airborne LIDAR to produce digital elevation models, the Global Positioning System (GPS) positioning of the LIDAR instrument is often the limiting factor, with accuracies typically quoted as being 10–30 cm. However, a comprehensive analysis of the accuracy and precision of GPS positioning of aircraft over large temporal and spatial scales is lacking from the literature. Here, an assessment is made of the likely GPS contribution to the airborne LIDAR measurement error budget by analyzing more than 500 days of continuous GPS data over a range of baseline lengths (3–960 km) and elevation differences (400–2000 m). Height errors corresponding to the 95th percentile are $≪$ 0.15 m when using algorithms commonly applied in commercial software over 3-km baselines. These errors increase to 0.25 m at 45 km and $≫,$0.5 m at 250 km. At aircraft altitudes, relative heights are shown to be potentially biased by additional errors approaching 0.2 m, partly due to unmodeled tropospheric zenith total delay (ZTD). The application of advanced algorithms, including parameterization of the residual ZTD, gives error budgets that are largely constant despite baseline length and elevation differences. In this case, height errors corresponding to the 95th percentile are $≪$ 0.22 m out to 960 km, and similar levels are shown for one randomly chosen day over a 2300-km baseline.