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.     

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.     

AIRS/AMSU/HSB on the Aqua mission: design, science objectives, data products, and processing systems

The Atmospheric Infrared Sounder (AIRS), the Advanced Microwave Sounding Unit (AMSU), and the Humidity Sounder for Brazil (HSB) form an integrated cross-track scanning temperature and humidity sounding system on the Aqua satellite of the Earth Observing System (EOS). AIRS is an infrared spectrometer/radiometer that covers the 3.7-15.4-/spl mu/m spectral range with 2378 spectral channels. AMSU is a 15-channel microwave radiometer operating between 23 and 89 GHz. HSB is a four-channel microwave radiometer that makes measurements between 150 and 190 GHz. In addition to supporting the National Aeronautics and Space Administration's interest in process study and climate research, AIRS is the first hyperspectral infrared radiometer designed to support the operational requirements for medium-range weather forecasting of the National Ocean and Atmospheric Administration's National Centers for Environmental Prediction (NCEP) and other numerical weather forecasting centers. AIRS, together with the AMSU and HSB microwave radiometers, will achieve global retrieval accuracy of better than 1 K in the lower troposphere under clear and partly cloudy conditions. This paper presents an overview of the science objectives, AIRS/AMSU/HSB data products, retrieval algorithms, and the ground-data processing concepts. The EOS Aqua was launched on May 4, 2002 from Vandenberg AFB, CA, into a 705-km-high, sun-synchronous orbit. Based on the excellent radiometric and spectral performance demonstrated by AIRS during prelaunch testing, which has by now been verified during on-orbit testing, we expect the assimilation of AIRS data into the numerical weather forecast to result in significant forecast range and reliability improvements.     

Rapid radiative transfer model for AMSU/HSB channels

The atmospheric transmittance model for the Advanced Microwave Sounding Unit-A (AMSU-A) and the Humidity Sounder for Brazil (HSB) channels on the Aqua spacecraft uses a polynomial approximation to the temperature dependence of oxygen-band opacity within atmospheric layers. It uses lookup tables to calculate local water-vapor line intensity and pressure-broadening parameters as well as contributions to absorption from the water-vapor continuum, distant lines, and cloud liquid water. The algorithm includes water-line self-broadening and the magnetic-field effect on AMSU-A channel 14. The microwave surface emission model is based on a preliminary classification of the surface type, with subsequent adjustments to the emissivity spectrum that are obtained from the retrieval algorithm. A simple approximate correction for surface nonspecularity is included. The algorithm has been tested by comparisons to a line-by-line calculation and to measurements made by the NOAA-15 AMSU-A.     

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/).     

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.     

Formulation and validation of simulated data for the Atmospheric Infrared Sounder (AIRS)

Models for synthesizing radiance measurements by the Atmospheric Infrared Sounder (AIRS) are described. Synthetic radiances have been generated for developing and testing data processing algorithms. The radiances are calculated from geophysical states derived from weather forecasts and climatology using the AIRS rapid transmission algorithm. The data contain horizontal variability at the spatial resolution of AIRS from the surface and cloud fields. This is needed to test retrieval algorithms under partially cloudy conditions. The surface variability is added using vegetation and International Geosphere Biosphere Programme surface type maps, while cloud variability is added randomly. The radiances are spectrally averaged to create High Resolution Infrared Sounder (HIRS) data, and this is compared with actual HIRS2 data on the NOAA 14 satellite. The simulated data under-represent high-altitude equatorial cirrus clouds and have too much local variability. They agree in the mean to within 1-4 K, and global standard deviation agrees to better than 2 K. Simulated data have been a valuable tool for developing retrieval algorithms and studying error characteristics and will continue to be so after launch.     

Microwave land emissivity calculations using AMSU measurements

Atmospheric parameter retrievals over land from Advanced Microwave Sounding Unit (AMSU) measurements, such as atmospheric temperature and moisture profiles, could be possible using a reliable estimate of the land emissivity. The land surface emissivities have been calculated using six months of data, for 30 beam positions (observation zenith angles from -58/spl deg/ to +58/spl deg/) and the 23.8-, 31.4-, 50.3-, 89-, and 150-GHz channels. The emissivity calculation covers a large area including Africa, Eurasia, and Eastern South America. The day-to-day variability of the emissivity is less than 2% in these channels. The angular and spectral dependence of the emissivity is studied. The obtained AMSU emissivities are in good agreement with the previously derived SSMI ones. The scan asymmetry problem has been evidenced for AMSU-A channels. And possible extrapolation of the emissivity from window channels to sounding ones has been successfully tested.     

大气红外探测仪的探测器序列定位误差

大气红外探测仪AIRS的核心是一个光栅光谱仪序列,2378个红外探测器分装在17个探测器序列上,本文以实例说明了由于探测器序列在视轴方向有偏移,即空间错误定位误差给AIRS的观测值带来的影响及其光谱分布特征,以及观测值误差对后继红外晴空订正和大气廓线反演的影响.建议以后在设计同类仪器时要避免探测器序列错误定位问题,或选用干涉式分光系统.     

Calibration of the AIRS microwave instruments

Aqua carries three microwave radiometers that form an integral part of the Atmospheric Infrared Sounder (AIRS) sounding suite. Two Advanced Microwave Sounding Unit-A modules, one operating with two channels in the 23-31-GHz range and one operating with 12 channels in the 50-60-GHz range and one channel at 89 GHz, provide all-weather temperature soundings and cloud information. The Humidity Sounder for Brazil operates with four channels in the 150-190-GHz range and provides all-weather humidity and cloud soundings. All are cross-track scanners, as is AIRS. While there are significant differences between these three instruments, they are sufficiently alike that a common approach can be used to calibrate them. We describe the instruments and their heritage, the onboard calibration system, and the ground-based calibration processing.     

基于HSB与LSB的半脆弱水印算法

提出了一种能够精确定位并能恢复原图像的半脆弱数字水印算法。本算法利用LSB(最低比特位)所含水印信息大容量的特点,由于在图像篡改和水印攻击情况下HSB(最高比特位)具有相对稳定性,故利用HSB作为水印信息,利用一种新的置乱算法产生水印嵌入位置,结合混沌序列,修改该位置图像像素的LSB,完成水印的嵌入调制。实验结果表明,该算法不仅可对图像内容的恶意篡改进行精确地检测与定位,而且能够大致恢复出被篡改的原图像信息,并对原图质量的影响非常小。     

Surface Emissivity of Arctic Sea Ice at AMSU Window Frequencies

A method to retrieve the surface emissivity of sea ice at the window channels of the Advanced Microwave Sounding Unit (AMSU) radiometers in the polar region is presented. The instruments are on the new-generation satellites of the U.S. National Oceanic and Atmospheric Administration (NOAA-15, NOAA-16, and NOAA-17). The method assumes hypothetical surfaces with emissivities zero and one and simulates brightness temperatures at the top of the atmosphere using profiles of atmospheric parameters, e.g., from the European Centre for Medium-Range Weather Forecasts (ECMWF) model runs, as input for a radiative transfer model. The retrieval of surface emissivity is done by combining simulated brightness temperatures with the satellite-measured brightness temperature. The AMSU window channels differ in surface penetration depths and, thus, in the surface microphysical parameters that they depend on. Lowest layer air temperatures from ECMWF are used to infer temperatures of emitting layers at different frequencies of sea ice. A complete yearly cycle of monthly average emissivities in two selected regions (first- and multiyear ice) is giving insight into the variation of emissivities in various development stages of sea ice.      

先进微波探测器资料反演地表微波辐射率试验

利用美国环境卫星A型先进微波探测器AMSU-A资料反演中国陆地区域地表微波辐射率.通过辐射传输正演模拟,提出了AMSU-A窗区通道反演地表微波辐射率的指数分析方法.利用模拟数据对比了指数分析方法和以往通道亮温组合方法.结果表明:对于地表比较干燥的地区,指教分析的反演结果略优于通道亮温组合的反演结果.在此基础上利用IGBP(International Geosphere-Biosphere Program)的地表分类数据,提取AMSU-A像元裸土组分的面积百分比信息,并进一步应用于AMSU-A像元裸土组分地表微波辐射率的反演试验,提高了反演精度,并可进一步应用于区域地表湿度信息提取和大气参数反演,以及AMSU-A窗区通道陆地区域遥感信息在数值预报模式中的同化应用.     

An overview of the AIRS radiative transfer model

The two main elements of the Atmospheric Infrared Sounder radiative transfer algorithm (AIRS-RTA) are described in this paper: 1) the fast parameterization of the atmospheric transmittances that are used to perform the AIRS physical retrievals and 2) the spectroscopy used to generate the parameterized transmittances. We concentrate on those aspects of the spectroscopy that are especially relevant for temperature and water vapor retrievals. The AIRS-RTA is a hybrid model in that it parameterizes most gases on a fixed grid of pressures, while the water optical depths are parameterized on a fixed grid of water amounts. Water vapor, ozone, carbon monoxide, and methane profiles can be varied, in addition to the column abundance of carbon dioxide.     

Verification of AIRS boresight accuracy using coastline detection

The longitude and latitude of the centroids of the Atmospheric Infrared Sounder (AIRS) infrared spectrometer footprints are calculated by the Level 1a calibration software based on transformations of scan angles, instrument alignment angles relative to the Earth Observing System Aqua spacecraft, and the spacecraft ephemeris. The detection of coastline crossings is used to determine the accuracy of these coordinates. Tests using simulated AIRS data derived from real Moderate Resolution Imaging Spectroradiometer (MODIS) Terra satellite 10-/spl mu/m window data indicate that an accuracy of 1.7 km is easily achievable with modest amounts of data, such as should be available from AIRS by launch +90 days. This accuracy is a small fraction of the 13.5-km AIRS footprint and is consistent with the accuracy required by the Level 2 software. Preliminary results from actual AIRS data indicate that the algorithm works as predicted. For combined use of the AIRS 13.5-km footprints with MODIS 1-km footprints, accuracy of the order of 0.5 km is desirable. This accuracy may be achievable with several months of data, but depends on the accuracy of the reference map and whether a sufficient number of large clear homogeneous surface scenes can be found.     

Coalignment and synchronization of the AIRS instrument suite

Previous multispectral sounders have consisted of infrared and microwave instruments operated asynchronously, with the data interpolated during ground processing to common fields of view (FOVs) for geophysical retrieval processing. To help achieve the high retrieval accuracy required for the Atmospheric Infrared Sounder (AIRS) system, the four instruments making up the AIRS suite are aligned and synchronized in such a way as to achieve common FOVs without interpolation. We describe the system, how the alignment is accomplished, and the plans to verify performance after launch and compensate for misalignments that might be revealed then.     

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.      

TCP/IP modeling and validation

We discuss the different issues to be considered when modeling the TCP protocol in a real environment. The discussion is based on measurements we made over the Internet. We show that the Internet is so heterogeneous that a simplistic assumption about TCP congestion control or the network may lead to erroneous results. We outline some of our results in this field, and we present a novel approach For a correct validation of a model for TCP