Larry M. McMillin

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 Administrations 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 Administrations 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.

AIRS: Improving Weather Forecasting and Providing New Data on Greenhouse Gases

Abstract The Atmospheric Infrared Sounder (AIRS) and its two companion microwave sounders, AMSU and HSB were launched into polar orbit onboard the NASA Aqua Satellite in May 2002. NASA required the sounding system to provide high-quality research data for climate studies and to meet NOAAs requirements for improving operational weather forecasting. The NOAA requirement translated into global retrieval of temperature and humidity profiles with accuracies approaching those of radiosondes. AIRS also provides new measurements of several greenhouse gases, such as CO2, CO, CH4, O3, SO2, and aerosols. The assimilation of AIRS data into operational weather forecasting has already demonstrated significant improvements in global forecast skill. At NOAA/NCEP, the improvement in the forecast skill achieved at 6 days is equivalent to gaining an extension of forecast capability of six hours. This improvement is quite significant when compared to other forecast improvements over the last decade. In addition to NCEP, ECM...

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.

Radiance and Jacobian Intercomparison of Radiative Transfer Models Applied to HIRS and AMSU Channels

The goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line-by-line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: 7 HIRS (High-resolution Infrared Sounder) and 4 AMSU (advanced microwave sounding unit) channels. Interest in this topic was evident by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances but also Jacobians (of temperature, water vapor, and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05-0.15 K (standard deviation) in terms of top-of-the-atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging. In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However, significant differences were noted among LBL models. Extending the intercomparison to the Jacobians proved very useful in detecting subtle or more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences.

Retrieval of Precipitable Water from Observations in the Split Window over Varying Surface Temperatures

Abstract The split window technique makes use of two differentially absorbing channels in the 11 μm region to remove the attenuating effects of atmospheric absorption so as to achieve a better estimate of the underlying skin temperature than could be produced by a single channel measurement. Since the primary absorber in this region is water vapor, it follows that split window measurements should be able to produce bulk water vapor retrievals as well. When observations are made with split window channels under conditions where the surface contribution to measured radiance changes, but the atmospheric contribution does not, it is possible to estimate the ratio of the transmittance of the two split window channels. This transmittance ratio is inversely related to precipitable water. This paper applies this technique to observations from the Advanced Very High Resolution Radiometer, and the VISSR Atmospheric Sounder, and demonstrates the capability of both instruments to determine precipitable water under tw...

Atmospheric transmittance of an absorbing gas: a computationally fast and accurate transmittance model for absorbing gases with constant mixing ratios in inhomogeneous atmospheres

At a given pressure level the atmospheric transmittance for an absorbing gas with a constant mixing ratio varies only with the temperature profile of the atmosphere. A simple transmittance model based on temperature differences is derived for monochromatic radiation. This model then is extended to the more important case of polychromatic radiation through the use of scaling approximations. The resulting algorithm for calculating transmittances for an arbitrary temperature profile is simple to use, accurate, and computationally fast because only arithmetic operations are required. In fact, resulting transmittances agreed with line-by-line calculations to within 0.0031 for the cases tried. Details for calculating the expansion coefficients are provided.

Atmospheric transmittance of an absorbing gas. 3: A computationally fast and accurate transmittance model for absorbing gases with variable mixing ratios.

Atmospheric transmittance models for absorbing gases with constant mixing ratios were described in the two preceding papers of this series. In this paper a method for calculating atmospheric transmittances for absorbing gases with variable mixing ratios is described. Because the model uses only arithmetic operations, it is computationally fast as well as accurate. Details of the computational algorithm are given, including the calculation of the expansion coefficients. In a test of eleven independent profiles, the resulting transmittances agreed with line-by-line calculations in an rms sense to within 0.0090 in the worst case and to within 0.0018 in all other cases. This paper also includes a discussion for computing transmittances when several gases absorb in the same spectral interval. These three papers provide a complete treatment for modeling transmittances in inhomogeneous atmospheres.

Intersatellite Radiance Biases for the High-Resolution Infrared Radiation Sounders (HIRS) on board NOAA-15, -16, and -17 from Simultaneous Nadir Observations

Abstract Intersatellite radiance comparisons for the 19 infrared channels of the High-Resolution Infrared Radiation Sounders (HIRS) on board NOAA-15, -16, and -17 are performed with simultaneous nadir observations at the orbital intersections of the satellites in the polar regions, where each pair of the HIRS views the same earth target within a few seconds. Analysis of such datasets from 2000 to 2003 reveals unambiguous intersatellite radiance differences as well as calibration anomalies. The results show that in general, the intersatellite relative biases are less than 0.5 K for most HIRS channels. The large biases in different channels differ in both magnitude and sign, and are likely to be caused by the differences and measurement uncertainties in the HIRS spectral response functions. The seasonal bias variation in the stratosphere channels is found to be highly correlated with the lapse rate factor approximated by the channel radiance differences. The method presented in this study works particularly...

Atmospheric transmittance of an absorbing gas. 5. Improvements to the optran approach

Improvements to a fast and accurate transmittance-calculation procedure, Optical Path TRANsmittance (OPTRAN), are described. The previous version computed a transmittance ratio for an absorbing layer. It required special attention to the interpolation methodology. The new approach reported here computes the absorption coefficient for an absorbing layer. This modified approach is not only simpler but also runs in one twentieth the time of the original OPTRAN approach with the same accuracy.

The Validation of AIRS Retrievals of Integrated Precipitable Water Vapor Using Measurements from a Network of Ground-Based GPS Receivers over the Contiguous United States

A robust and easily implemented verification procedure based on the column-integrated precipitable water (IPW) vapor estimates derived from a network of ground-based global positioning system (GPS) receivers has been used to assess the quality of the Atmospheric Infrared Sounder (AIRS) IPW retrievals over the contiguous United States. For a period of six months from April to October 2004, excellent agreement has been realized between GPS-derived IPW estimates and those determined from AIRS, showing small monthly bias values ranging from 0.5 to 1.5 mm and root-mean-square (rms) differences of 4 mm or less. When the spatial (latitude–longitude) window for the GPS and AIRS matchup observations is reduced from the initial 1U2 °b y1U2 °t o1U4 °b y1U4°, the rms differences are reduced. Analysis revealed that the observed IPW biases between the instruments are strongly correlated to the reported surface pressure differences between the GPS and AIRS observational points. Adjusting the AIRS IPW values to account for the surface pressure discrepancies resulted in significant reductions of the bias between GPS and AIRS. A similar reduction can be obtained by comparing only (GPS–AIRS) match-up pairs for which the corresponding surface pressure differences are 0.5 mb or less. The comparisons also revealed that the AIRS IPW tends to be relatively dry in moist atmospheres (when IPW values 40 mm) but wetter in dry cases (when IPW values 10 mm). This is consistent with the documented bias of satellite measurements toward the first guess used in retrieval algorithms. However, additional study is needed to verify whether the AIRS water vapor retrieval process is the source of the discrepancies. It is shown that the IPW bias and rms differences have a seasonal dependency, with a maximum in summer (bias 1.2 mm, rms 4.14 mm) and minimum in winter (bias 0.5 mm, rms 3 mm).