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.

The atmospheric moisture and temperature profiles from the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit on the NASA Aqua mission, in combination with the precipitation from the Tropical Rainfall Measuring Mission (TRMM), are employed to study the vertical moist thermodynamic structure and spatial-temporal evolution of the Madden-Julian oscillation (MJO). The AIRS data indicate that, in the Indian Ocean and western Pacific, the temperature anomaly exhibits a trimodal vertical structure: a warm (cold) anomaly in the free troposphere (800-250 hPa) and a cold (warm) anomaly near the tropopause (above 250 hPa) and in the lower troposphere (below 800 hPa) associated with enhanced (suppressed) convection. The AIRS moisture anomaly also shows markedly different vertical structures as a function of longitude and the strength of convection anomaly. Most significantly, the AIRS data demonstrate that, over the Indian Ocean and western Pacific, the enhanced (suppressed) convection is generally preceded in both time and space by a low-level warm and moist (cold and dry) anomaly and followed by a low-level cold and dry (warm and moist) anomaly.The MJO vertical moist thermodynamic structure from the AIRS data is in general agreement, particularly in the free troposphere, with previous studies based on global reanalysis and limited radiosonde data. However, major differences in the lower-troposphere moisture and temperature structure between the AIRS observations and the NCEP reanalysis are found over the Indian and Pacific Oceans, where there are very few conventional data to constrain the reanalysis. Specifically, the anomalous lower-troposphere temperature structure is much less well defined in NCEP than in AIRS for the western Pacific, and even has the opposite sign anomalies compared to AIRS relative to the wet/dry phase of the MJO in the Indian Ocean. Moreover, there are well-defined eastward-tilting variations of moisture with height in AIRS over the central and eastern Pacific that are less well defined, and in some cases absent, in NCEP. In addition, the correlation between MJO-related midtropospheric water vapor anomalies and TRMM precipitation anomalies is considerably more robust in AIRS than in NCEP, especially over the Indian Ocean. Overall, the AIRS results are quite consistent with those predicted by the frictional Kelvin-Rossby wave/conditional instability of the second kind (CISK) theory for the MJO.

[1] Much of our knowledge about oceanic rainfall comes from spaceborne sensors. These sensors provide direct or indirect information used for precipitation retrievals through various algorithms. A thorough understanding of rain frequency and intensity and its regional distribution, which is especially important in a warming climate, requires an evaluation of the performance of rain-measuring sensors and identification of strengths and limitations offered by each sensor. The Tropical Rainfall Measuring Mission (TRMM) has enabled significant advancement in quantification of moderate to intense rainfall. However, a common limitation of the current suite of rain-measuring sensors is their lack of sensitivity to light rainfall, especially over subtropical and high-latitude oceans. Among various spaceborne sensors, CloudSat enables superior retrieval of light rainfall and drizzle. By using 3 years (2007)(2008)(2009)) of rainfall data from CloudSat and the precipitation radar aboard TRMM, it was determined that the quasi-global (60 S-60 N) oceanic mean rain rate is about 3.05 mm/d, considerably larger than that obtained from any individual sensor product. In the deep tropics, especially within 20 S-20 N, the sensors show the highest agreement, with a large fraction of total rain volume captured by the majority of sensors. However, toward higher latitudes and within the subtropical high-pressure regions, a significant fraction of rainfall, which can exceed 50% or more of total rain volume, is missed by the majority of the sensors.Citation: Behrangi, A., M. Lebsock, S. Wong, and B. Lambrigtsen (2012), On the quantification of oceanic rainfall using spaceborne sensors,

An intercomparison of high-latitude precipitation characteristics from observation-based and reanalysis products is performed. In particular the precipitation products from CloudSat provide an independent assessment to other widely used products, these being the observationally-based GPCP, GPCC and CMAP products and the ERA-Interim, MERRA and NCEP-DOE R2 reanalyses. Seasonal and annual total precipitation in both hemispheres poleward of 55° latitude is considered in all products, and CloudSat is used to assess intensity and frequency of precipitation occurrence by phase, defined as rain, snow or mixed phase. Furthermore, an independent estimate of snow accumulation during the cold season was calculated from the Gravity Recovery and Climate Experiment (GRACE). The intercomparison is performed for the 2007-2010 period when CloudSat was fully operational. It is found that ERA- Interim and MERRA are broadly similar, agreeing more closely with CloudSat over oceans. ERA-Interim also agrees well with CloudSat estimates of snowfall over Antarctica where total snowfall from GPCP and CloudSat is almost identical. A number of disagreements on regional or seasonal scales are identified: CMAP reports much lower ocean precipitation relative to other products, NCEP-DOE R2 reports much higher summer precipitation over northern hemisphere land, GPCP reports much higher snowfall over Eurasia, and CloudSat overestimates precipitation over Greenland, likely due to mischaracterization of rain and mixed-phase precipitation. These outliers are likely unrealistic for these specific regions and time periods. These estimates from observations and reanalyses provide useful insights for diagnostic assessment of precipitation products in high latitudes, quantifying the current uncertainties, improving the products, and establishing a benchmark for assessment of climate models.

[1] We examine differences in total precipitable water vapor (PWV) from the Atmospheric Infrared Sounder (AIRS) and the Advanced Microwave Scanning Radiometer (AMSR-E) experiments sharing the Aqua spacecraft platform. Both systems provide estimates of PWV over water surfaces. We compare AIRS and AMSR-E PWV to constrain AIRS retrieval uncertainties as functions of AIRS retrieved infrared cloud fraction. PWV differences between the two instruments vary only weakly with infrared cloud fraction up to about 70%. Maps of AIRS-AMSR-E PWV differences vary with location and season. Observational biases, when both instruments observe identical scenes, are generally less than 5%. Exceptions are in cold air outbreaks where AIRS is biased moist by 10-20% or 10-60% (depending on retrieval processing) and at high latitudes in winter where AIRS is dry by 5-10%. Sampling biases, from different sampling characteristics of AIRS and AMSR-E, vary in sign and magnitude. AIRS sampling is dry by up to 30% in most high-latitude regions but moist by 5-15% in subtropical stratus cloud belts. Over the northwest Pacific, AIRS samples conditions more moist than AMSR-E by a much as 60%. We hypothesize that both wet and dry sampling biases are due to the effects of clouds on the AIRS retrieval methodology. The sign and magnitude of these biases depend upon the types of cloud present and on the relationship between clouds and PWV. These results for PWV imply that climatologies of height-resolved water vapor from AIRS must take into consideration local meteorological processes affecting AIRS sampling.