Knowledge of cloud properties like cloud top height (CTH) is essential to understand their impact on the earth's radiation budget and on climate change. High spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) are well suited to reveal valuable information about cloud altitude. The CTH retrievals derived from AIRS single field‐of‐view (FOV) radiance measurements are compared with the operational MODIS (Moderate Resolution Imaging Spectroradiometer) cloud product, and Level 2 products obtained from radar and lidar instruments onboard the EOS (Earth Observing System) CloudSat and the CALIPSO (Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation) satellites. Two cases containing a variety of cloud conditions have been studied, and the strengths/shortcomings of CTH products from infrared (IR) sounder radiances are discussed.

[1] Retrieval of temperature, moisture profiles and surface skin temperature from hyperspectral infrared (IR) radiances requires spectral information about the surface emissivity. Using constant or inaccurate surface emissivities typically results in large temperature and moisture profile errors, particularly over semi-arid or arid areas where the variation in emissivity is large both spectrally and spatially. A physically based algorithm has been developed to retrieve a hyperspectral IR emissivity spectrum simultaneously with the temperature and moisture profiles, as well as the surface skin temperature. To make the solution stable and efficient, the hyperspectral emissivity spectrum is represented by eigenvectors, derived from the laboratory measured hyperspectral emissivity database, in the retrieval process. Experience with Atmospheric InfraRed Sounder (AIRS) radiances shows that simultaneous retrieval of the emissivity spectrum and the sounding improves the surface skin temperature and temperature and moisture profiles, particularly in the near surface layer. Citation: Li, J.,

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the NASA Earth Observing System Aqua satellite enable global monitoring of the distribution of clouds during day and night. The MODIS is able to provide a high-spatial-resolution (1-5 km) cloud mask, cloud classification mask, cloud-phase mask, cloud-top pressure (CTP), and effective cloud amount during both the daytime and the nighttime, as well as cloud particle size (CPS) and cloud optical thickness (COT) at 0.55 m during the daytime. The AIRS high-spectral-resolution measurements reveal cloud properties with coarser spatial resolution (13.5 km at nadir). Combined, MODIS and AIRS provide cloud microphysical properties during both the daytime and nighttime. A fast cloudy radiative transfer model for AIRS that accounts for cloud scattering and absorption is described in this paper. Onedimensional variational (1DVAR) and minimum-residual (MR) methods are used to retrieve the CPS and COT from AIRS longwave window region (790-970 cm Ϫ1 or 10.31-12.66 m, and 1050-1130 cm Ϫ1 or 8.85-9.52 m) cloudy radiance measurements. In both 1DVAR and MR procedures, the CTP is derived from the AIRS radiances of carbon dioxide channels while the cloud-phase information is derived from the collocated MODIS 1-km phase mask for AIRS CPS and COT retrievals. In addition, the collocated 1-km MODIS cloud mask refines the AIRS cloud detection in both 1DVAR and MR procedures. The atmospheric temperature profile, moisture profile, and surface skin temperature used in the AIRS cloud retrieval processing are from the European Centre for Medium-Range Weather Forecasts forecast analysis. The results from 1DVAR are compared with the operational MODIS products and MR cloud microphysical property retrieval. A Hurricane Isabel case study shows that 1DVAR retrievals have a high correlation with either the operational MODIS cloud products or MR cloud property retrievals. 1DVAR provides an efficient way for cloud microphysical property retrieval during the daytime, and MR provides the cloud microphysical property retrievals during both the daytime and nighttime.

A fast physically based dual-regression (DR) method is developed to produce, in real time, accurate profile and surface- and cloud-property retrievals from satellite ultraspectral radiances observed for both clear- and cloudy-sky conditions. The DR relies on using empirical orthogonal function (EOF) regression “clear trained” and “cloud trained” retrievals of surface skin temperature, surface-emissivity EOF coefficients, carbon dioxide concentration, cloud-top altitude, effective cloud optical depth, and atmospheric temperature, moisture, and ozone profiles above the cloud and below thin or broken cloud. The cloud-trained retrieval is obtained using cloud-height-classified statistical datasets. The result is a retrieval with an accuracy that is much higher than that associated with the retrieval produced by the unclassified regression method currently used in the International Moderate Resolution Imaging Spectroradiometer/Atmospheric Infrared Sounder (MODIS/AIRS) Processing Package (IMAPP) retrieval system. The improvement results from the fact that the nonlinear dependence of spectral radiance on the atmospheric variables, which is due to cloud altitude and associated atmospheric moisture concentration variations, is minimized as a result of the cloud-height-classification process. The detailed method and results from example applications of the DR retrieval algorithm are presented. The new DR method will be used to retrieve atmospheric profiles from Aqua AIRS, MetOp Infrared Atmospheric Sounding Interferometer, and the forthcoming Joint Polar Satellite System ultraspectral radiance data.

[1] An efficient temperature and humidity retrieval algorithm for radiometric measurements at high spectral resolution is introduced and applied to climatological profiles. The algorithm is developed for analyzing Infrared Atmospheric Sounding Interferometer (IASI) data of the European weather satellite METOP-1 (launch scheduled 2005) for climatological purposes but is also applicable for other purposes and to other similar data. The algorithm's core features are a channel selection methodology followed by a linearized optimal estimation. The key concept of the former is that a small subset (5-10%) of all available IASI channels ($8000) is selected based on maximizing a suitable information content measure at each retrieval level. This enables efficiency and robustness of the retrieval algorithm and curtails the high redundancy in the measurements. In addition to profile and error covariance estimates optimal estimation furnishes various sensitivity functions of which we used ''weighting functions'' for quantifying the utility of measurement channels and ''averaging kernel functions'' for assessing the resolution of retrieved profiles. Results based on simulated IASI spectra computed from a set of standard climatological profiles and a realistic radiometric noise model demonstrate, for clear air, the capabilities of high spectral resolution measurements for improving temperature and humidity soundings compared to current operational sensors. In the troposphere (below $200 hPa), retrieved profiles exhibit temperature errors of <1 K and specific humidity errors of <10% at most heights, associated with a vertical resolution of $1.5-2 km. Promising performance was found in the upper troposphere (500-200 hPa), where about five independent reliable values of temperature and humidity are available indicating the high potential of the IASI sensor for monitoring climatic changes in upper tropospheric moisture. Tests on the sensitivity of retrieved profiles to the quality of a priori profiles showed weak sensitivity of temperature but significant sensitivity of humidity. The results provide a solid basis and clear guidance for improvements of the presented algorithm for reliable large-scale application on cloud-free spectra.

No abstract

[1] High-spectral resolution measurements from the Atmospheric Infrared Sounder (AIRS) onboard the EOS (Earth Observing System) Aqua satellite provide unique information about atmospheric state, surface and cloud properties. This paper presents an AIRS alone single fieldof-view (SFOV) retrieval algorithm to simultaneously retrieve temperature, humidity and ozone profiles under all weather conditions, as well as cloud-top pressure (CTP) under cloudy skies. For optically thick cloud conditions the above-cloud soundings are derived, whereas for clear skies and optically thin cloud conditions the profiles are retrieved from 0.005 hPa down to the earth's surface. Initial validation has been conducted by using the operational MODIS (Moderate Resolution Imaging Spectroradiometer) product, ECMWF (European Centre for Medium-Range Weather Forecasts) analysis fields and radiosonde observations (RAOBs). These inter-comparisons clearly demonstrate the potential of this algorithm to process data from high-spectral infrared (IR) sounder instruments. Citation:

The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Atmospheric Infrared Sounder (AIRS) measurements from the Earth Observing System's (EOS's) Aqua satellite enable global monitoring of the distribution of clouds. MODIS is able to provide a cloud mask, surface and cloud types, cloud phase, cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size, and cloud optical thickness at high spatial resolution (1-5 km). The combined MODIS-AIRS system offers the opportunity for improved cloud products, better than from either system alone; this improvement is demonstrated in this paper with both simulated and real radiances. A one-dimensional variational (1DVAR) methodology is used to retrieve the CTP and ECA from AIRS longwave (650-790 cm Ϫ1 or 15.38-12.65 m) cloudy radiance measurements (hereinafter referred to as MODIS-AIRS 1DVAR). The MODIS-AIRS 1DVAR cloud properties show significant improvement over the MODIS-alone cloud properties and slight improvement over AIRS-alone cloud properties in a simulation study, while MODIS-AIRS 1DVAR is much more computationally efficient than the AIRS-alone 1DVAR; comparisons with radiosonde observations show that CTPs improve by 10-40 hPa for MODIS-AIRS CTPs over those from MODIS alone. The 1DVAR approach is applied to process the AIRS longwave cloudy radiance measurements; results are compared with MODIS and Geostationary Operational Environmental Satellite sounder cloud products. Data from ground-based instrumentation at the Atmospheric Radiation Measurement Program Cloud and Radiation Test Bed in Oklahoma are used for validation; results show that MODIS-AIRS improves the MODIS CTP, especially in low-level clouds. The operational use of a high-spatial-resolution imager, along with information from a high-spectral-resolution sounder will be possible with instruments planned for the next-generation geostationary operational instruments.