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Fang Pan, Xianglei Huang, L. Larabbe Strow, and Huan Guo

Abstract

The Atmospheric Infrared Sounder (AIRS) level-1b radiances have been shown to be well calibrated (~0.3 K or higher) and have little secular drift (~4 mK yr−1) since operation started in September 2002. This paper investigates the linear trends of 10 years (2003–12) of AIRS global-mean radiances in the CO2 v 2 band that are sensitive to emissions from the stratosphere (stratospheric channels). AIRS lower-stratospheric channels have a cooling trend of no more than 0.23 K decade−1 whereas the midstratospheric channels consistently show a statistically significant cooling trend as large as 0.58 K decade−1. The 95% confidence interval for the trend is ~±0.20 K decade−1. Two sets of synthetic AIRS radiances are computed using the principal component–based radiative transfer model (PCRTM), one based on a free-running GFDL Atmospheric Model, version 3 (AM3), over the same period and one based on ERA-Interim. The GFDL AM3 simulations overestimate the cooling trends in the mid- to upper-stratospheric channels but slightly underestimate them in the lower-stratospheric channels. The synthetic radiances based on ERA-Interim, however, have statistically significant positive trends at virtually all stratospheric channels. This confirms the challenge to the GCM modeling and reanalysis community to create a better simulation or assimilation of the stratospheric climate. It is shown that the linear trends in AIRS radiances can be reproduced to a large extent by the spectral radiative kernel technique and the trends from the AIRS L2 temperature retrievals and from the change of CO2. This suggests a closure between AIRS L1 radiances and L2 retrievals and the potential merit of AIRS data in studies of stratosphere changes.

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Fang Pan, Xianglei Huang, Stephen S. Leroy, Pu Lin, L. Larrabee Strow, Yi Ming, and V. Ramaswamy

Abstract

Global-mean radiances observed by the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Sounding Unit A (AMSU-A) are analyzed from 2003 to 2012. The focus of this study is on channels sensitive to emission and absorption in the stratosphere. Optimal fingerprinting is used to obtain estimates of changes of stratospheric temperature in five vertical layers due to external forcing in the presence of natural variability. Natural variability is estimated using synthetic radiances based on the 500-yr GFDL CM3 and 240-yr HadGEM2-CC control runs. The results show a cooling rate of 0.65 ± 0.11 (2σ) K decade−1 in the upper stratosphere above 6 hPa, approximately 0.46 ± 0.24 K decade−1 in two midstratospheric layers between 6 and 30 hPa, and 0.39 ± 0.32 K decade−1 in the lower stratosphere (30–60 hPa). The cooling rate in the lowest part of the stratosphere (60–100 hPa) is −0.014 ± 0.22 K decade−1, which is smallest among all five layers and statistically insignificant. The synergistic use of well-calibrated passive infrared and microwave radiances permits disambiguation of trends of carbon dioxide and stratospheric temperature, increases vertical resolution of detected stratospheric temperature trends, and effectively reduces uncertainties of estimated temperature trends.

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Sergio De Souza-Machado, Andrew Tangborn, Philip Sura, Christopher Hepplewhite, and L. Larrabee Strow

Abstract

Statistical relationships between higher-order moments of probability density functions (PDFs) are used to analyze top-of-atmosphere radiance measurements made by the Atmospheric Infrared Sounder (AIRS) and radiance calculations from the ECMWF Re-Analysis (ERA) and the Modern-Era Retrospective Analysis for Research and Applications (MERRA) over a 10-yr period. The statistical analysis used in this paper has previously been applied to sea surface temperature, and here the authors show that direct satellite radiance observations of atmospheric variability also exhibit stochastic forcing characteristics. The authors have chosen six different AIRS channels based on the sensitivity of their measured radiances to a variety of geophysical properties. In each of these channels, the authors have found evidence of correlated additive and multiplicative (CAM) stochastic forcing. In general, channels sensitive to tropospheric humidity and surface temperature show the strongest evidence of CAM forcing, while those sensitive to stratospheric temperature and ozone exhibit the weakest forcing. Radiance calculations from ERA and MERRA agree well with AIRS measurements in the Gaussian part of the PDFs but show some differences in the tails, indicating that the reanalyses may be missing some extrema there. The CAM forcing is investigated through numerical simulation of simple stochastic differential equations (SDEs). The authors show how measurements agree better with weaker CAM forcing, achieved by reducing the multiplicative forcing or by increasing the spatial correlation of the added noise in the case of an SDE with one spatial dimension. This indicates that atmospheric models could be improved by adjusting nonlinear terms that couple long and short time scales.

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B. Soden, S. Tjemkes, J. Schmetz, R. Saunders, J. Bates, B. Ellingson, R. Engelen, L. Garand, D. Jackson, G. Jedlovec, T. Kleespies, D. Randel, P. Rayer, E. Salathe, D. Schwarzkopf, N. Scott, B. Sohn, S. de Souza-Machado, L. Strow, D. Tobin, D. Turner, P. van Delst, and T. Wehr

An intercomparison of radiation codes used in retrieving upper-tropospheric humidity (UTH) from observations in the ν2 (6.3 μm) water vapor absorption band was performed. This intercomparison is one part of a coordinated effort within the Global Energy and Water Cycle Experiment Water Vapor Project to assess our ability to monitor the distribution and variations of upper-tropospheric moisture from spaceborne sensors. A total of 23 different codes, ranging from detailed line-by-line (LBL) models, to coarser-resolution narrowband (NB) models, to highly parameterized single-band (SB) models participated in the study. Forward calculations were performed using a carefully selected set of temperature and moisture profiles chosen to be representative of a wide range of atmospheric conditions. The LBL model calculations exhibited the greatest consistency with each other, typically agreeing to within 0.5 K in terms of the equivalent blackbody brightness temperature (Tb). The majority of NB and SB models agreed to within ±1 K of the LBL models, although a few older models exhibited systematic Tb biases in excess of 2 K. A discussion of the discrepancies between various models, their association with differences in model physics (e.g., continuum absorption), and their implications for UTH retrieval and radiance assimilation is presented.

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AIRS

Improving Weather Forecasting and Providing New Data on Greenhouse Gases

MOUSTAFA T. CHAHINE, THOMAS S. PAGANO, HARTMUT H. AUMANN, ROBERT ATLAS, CHRISTOPHER BARNET, JOHN BLAISDELL, LUKE CHEN, MURTY DIVAKARLA, ERIC J. FETZER, MITCH GOLDBERG, CATHERINE GAUTIER, STEPHANIE GRANGER, SCOTT HANNON, FREDRICK W. IRION, RAMESH KAKAR, EUGENIA KALNAY, BJORN H. LAMBRIGTSEN, SUNG-YUNG LEE, JOHN Le MARSHALL, W. WALLACE MCMILLAN, LARRY MCMILLIN, EDWARD T. OLSEN, HENRY REVERCOMB, PHILIP ROSENKRANZ, WILLIAM L. SMITH, DAVID STAELIN, L. LARRABEE STROW, JOEL SUSSKIND, DAVID TOBIN, WALTER WOLF, and LIHANG ZHOU

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 NOAA's 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, ECMWF and the Met Office have also reported positive forecast impacts due AIRS.

AIRS is a hyperspectral sounder with 2,378 infrared channels between 3.7 and 15.4 μm. NOAA/NESDIS routinely distributes AIRS data within 3 hours to NWP centers around the world. The AIRS design represents a breakthrough in infrared space instrumentation with measurement stability and accuracies far surpassing any current research or operational sounder..The results we describe in this paper are “work in progress,” and although significant accomplishments have already been made much more work remains in order to realize the full potential of this suite of instruments.

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