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-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.
[1] AIRS was launched on EOS Aqua on 4 May 2002, together with AMSU A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. The primary products of AIRS/AMSU are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an RMS error of 1 K, and layer precipitable water with an RMS error of 20%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the atlaunch algorithm, was described previously. Prelaunch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small and the RMS accuracy of lowertropospheric temperature retrieved with 80% cloud cover is about 0.5 K poorer than for clear cases. HSB failed in February 2003, and consequently, HSB channel radiances are
The Atmospheric Infrared Sounder (AIRS), the hyperspectral infrared sounder on the NASA Aqua mission, both improves operational weather prediction and provides high-quality research data for climate studies. The Atmospheric Infrared Sounder (AIRS), and its two companion microwave instruments, the Advanced Microwave Sounding Unit (AMSU) and the Humidity Sounder for Brazil (HSB), form the integrated atmospheric sounding system flying on the Earth Observing System (EOS) Aqua spacecraft since its launch in May 2002.1 The primary scientific achievement of AIRS has been to improve weather prediction (Le Marshall et al. 2005a,b,c) and to study the water and energy cycle (Tian et al. 2006). AIRS also provides information on several greenhouse gases. The measurement goal of AIRS is the retrieval of temperature and precipitable-water vapor profiles with accuracies approaching those of conventional radiosondes. In the following text we use the terms AIRS and AIRS-AMSU-HSB interchangeably.1 The HSB ceased functioning after 5 February 2003. This did not have an impact on the accuracy, coverage, or resolution of the AIRS core data product, but its loss has had a significant impact on AIRS research products.A comprehensive set of articles on AIRS and AMSU design details, prelaunch calibration, and prelaunch retrieval performance expectations were published in a special issue of IEEE Transactions on Geoscience and Remote Sensing (2003, vol. 41, no. 2). This paper discusses the performance of AIRS and examines how it is meeting its operational and research objectives based on the experience of more than 2 yr with AIRS data. We describe the science background and the performance of AIRS in terms of the accuracy and stability of its observed spectral radiances. We examine the validation of the retrieved temperature and water vapor profiles against collocated operational radiosondes, and then we assess the impact thereof on numerical weather forecasting of the assimilation of the AIRS spectra and the retrieved temperature. We close the paper with a discussion on the retrieval of several minor tropospheric constituents from AIRS spectra.
Human activity has increased the concentration of the earth's atmospheric carbon dioxide, which plays a direct role in contributing to global warming. Mid‐tropospheric CO2 retrieved by the Atmospheric Infrared Sounder shows a substantial spatiotemporal variability that is supported by in situ aircraft measurements. The distribution of middle tropospheric CO2 is strongly influenced by surface sources and large‐scale circulations such as the mid‐latitude jet streams and by synoptic weather systems, most notably in the summer hemisphere. In addition, the effects of stratosphere‐troposphere exchange are observed during a final stratospheric warming event. The results provide the means to understand the sources and sinks and the lifting of CO2 from surface layers into the free troposphere and its subsequent transport around the globe. These processes are not adequately represented in three chemistry‐transport models that have been used to study carbon budgets.
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