[1] An evaluation of the temperature and moisture profile retrievals from the Atmospheric Infrared Sounder (AIRS) data is performed using more than 2 years of collocated data sets. The Aqua-AIRS retrievals, global radiosonde (RAOB) measurements, forecast data from the National Center for Environmental Prediction Global Forecasting System (NCEP_GFS), the European Center for Medium Range Forecast (ECMWF), and the operational retrievals from the NOAA 16 satellite Advanced TIROS Operational Vertical Sounder (ATOVS) instrument are used in this validation. Using RAOB observations as the reference, bias and RMS differences are computed for ''sea,'' ''land,'' and ''all'' categories for the AIRS retrievals and other collocated data sets. The results of the intercomparison reveal that temperature and water vapor retrievals from the AIRS are in very good agreement with the RAOBs. The RMS difference for clear-only cases over ''sea'' and ''all'' categories is close to the expected goal accuracies, namely, 1°K in 1 km layers for the temperature and better than 15% in 2-km layers for the water vapor in the troposphere. The overall RMS difference for the cloud-cleared cases is also close to the expected product goal accuracy except for a slight degradation at the surface. When AIRS and ATOVS retrievals are compared with the RAOBs, the AIRS temperature retrievals show an improvement over ATOVS of at least 0.5°K for all the accepted cases. Both the ECMWF and the NCEP_GFS forecasts match the RAOB temperatures within 1°K and water vapor within 14%. With respect to biases, the AIRS final retrieval shows a larger bias with the RAOBs relative to ATOVS, NCEP_GFS, and ECMWF. The bias is highly influenced by a larger bias contribution from ''land'' samples and shows a month-to-month and annual variation that correlates with the CO 2 variations. This coupling suggests a need to include CO 2 and possibly other trace gas climatologies in the AIRS initial guess to partially mitigate the effects in the final physical retrieval.

The Infrared Atmospheric Sounding Interferometer (IASI) forms the main infrared sounding component of the European Organisation for the Exploitation of Meteorological Satellites's (EUMETSAT's) Meteorological Operation (MetOp)-A satellite (Klaes et al. 2007), which was launched in October 2006. This article presents the results of the first 4 yr of the operational IASI mission. The performance of the instrument is shown to be exceptional in terms of calibration and stability. The quality of the data has allowed the rapid use of the observations in operational numerical weather prediction (NWP) and the development of new products for atmospheric chemistry and climate studies, some of which were unexpected before launch. The assimilation of IASI observations in NWP models provides a significant forecast impact; in most cases the impact has been shown to be at least as large as for any previous instrument. In atmospheric chemistry, global distributions of gases, such as ozone and carbon monoxide, can be produced in near–real time, and short-lived species, such as ammonia or methanol, can be mapped, allowing the identification of new sources. The data have also shown the ability to track the location and chemistry of gaseous plumes and particles associated with volcanic eruptions and fires, providing valuable data for air quality monitoring and aircraft safety. IASI also contributes to the establishment of robust long-term data records of several essential climate variables. The suite of products being developed from IASI continues to expand as the data are investigated, and further impacts are expected from increased use of the data in NWP and climate studies in the coming years. The instrument has set a high standard for future operational hyperspectral infrared sounders and has demonstrated that such instruments have a vital role in the global observing system.

[1] The measurements from microwave sounding unit (MSU) on board different NOAA polar-orbiting satellites have been extensively used for detecting atmospheric temperature trend during the last several decades. However, temperature trends derived from these measurements are under significant debate, mostly caused by calibration errors. This study recalibrates the MSU channel 2 observations at level 0 using the postlaunch simultaneous nadir overpass (SNO) matchups and then provides a well-merged new MSU 1b data set for climate studies. The calibration algorithm consists of a dominant linear response of the MSU raw counts to the Earth-view radiance plus a smaller quadratic term. Uncertainties are represented by a constant offset and errors in the coefficient for the nonlinear quadratic term. A SNO matchup data set for nadir pixels with criteria of simultaneity of less than 100 s and within a ground distance of 111 km is generated for all overlaps of NOAA satellites. The simultaneous nature of these matchups eliminates the impact of orbital drifts on the calibration. A radiance error model for the SNO pairs is developed and then used to determine the offsets and nonlinear coefficients through regressions of the SNO matchups. It is found that the SNO matchups can accurately determine the differences of the offsets as well as the nonlinear coefficients between satellite pairs, thus providing a strong constraint to link calibration coefficients of different satellites together. However, SNO matchups alone cannot determine the absolute values of the coefficients because there is a high degree of colinearity between satellite SNO observations. Absolute values of calibration coefficients are obtained through sensitivity experiments, in which the percentage of variance in the brightness temperature difference time series that can be explained by the warm target temperatures of overlapping satellites is a function of the calibration coefficient. By minimizing these percentages of variance for overlapping observations, a new set of calibration coefficients is obtained from the SNO regressions. These new coefficients are significantly different from the prelaunch calibration values, but they result in bias-free SNO matchups and near-zero contaminations by the warm target temperatures in terms of the calibrated brightness temperature. Applying the new calibration coefficients to the Level 0 MSU observations, a well-merged MSU pentad data set is generated for climate trend studies. To avoid errors caused by small SNO samplings between NOAA 10 and 9, observations only from and after NOAA 10 are used. In addition, only ocean averages are investigated so that diurnal cycle effect can be ignored. The global ocean-averaged intersatellite biases for the pentad data set are between 0.05 and 0.1 K, which is an order of magnitude smaller than that obtained when using the unadjusted calibration algorithm. The ocean-only anomaly trend for the combined MSU channel 2 brightness temperature is found to be 0.

T he NASA Atmospheric InfraRed Sounder (AIRS), the first of the new generation of meteorological advanced sounders for operational and research use, is part of a large international investment to upgrade the operational meteorological satellite systems. The new systems include the NOAA Crosstrack Infrared Sounder (CrIS) and the Hyperspectral Environmental Suite (HES) instruments, on U.S. operational polar-orbiting and geostationary platforms, respectively, and the Infrared Atmospheric Sounding TABLE I. The characteristics of the AIRS and current operational HIRS sounding instruments. Instrument HIRS AIRS Spectral range 3.7-15 pm 3.7-15 JL/M Spatial resolution 17.4-km subsatellite 13.5-km subsatellite Number of channels 20 2378 A XIX-1/70-1/1200 Vertical resolution-3 km-1 km Temperature accuracy ~ 1.5-2 K 1 K accuracy in I-km layers Moisture accuracy-30%

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