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.

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 μm 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. One-dimensional variational (1DVAR) and minimum-residual (MR) methods are used to retrieve the CPS and COT from AIRS longwave window region (790–970 cm−1 or 10.31–12.66 μm, and 1050–1130 cm−1 or 8.85–9.52 μm) 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.

The Atmospheric Infrared Sounder (AIRS) onboard the National Aeronautics and Space Administration's Earth Observing System's (EOS) Aqua spacecraft, with its high spectral resolution and radiometric accuracy, provides atmospheric vertical temperature and moisture sounding information with high vertical resolution and accuracy for numerical weather prediction (NWP). Due to its relatively coarse spatial resolution (13.5 km at nadir), the chance for an AIRS footprint to be completely cloud free is small. However, the Moderate Resolution Imaging Spectroradiometer (MODIS), also on the Aqua satellite, provides colocated clear radiances at several spectrally broad infrared (IR) bands with 1-km spatial resolution; many AIRS cloudy footprints contain clear MODIS pixels. An optimal cloud-correction or cloud-clearing (CC) algorithm, an extension of the traditional single-band N/sup */ technique, is developed. The technique retrieves the hyperspectral infrared sounder clear column radiances from the combined multiband imager IR clear radiance observations with high spatial resolution and the hyperspectral IR sounder cloudy radiances on a single-footprint basis. The concurrent AIRS and MODIS data are used to verify the algorithm. The AIRS cloud-removed or cloud-cleared radiance spectrum is convolved to all the possible MODIS IR spectral bands with spectral response functions (SRFs). The convoluted cloud-cleared brightness temperatures (BTs) are compared with MODIS clear BT observations within AIRS cloud-cleared footprints passing our quality tests. The bias and the standard deviation between the convoluted BTs and MODIS clear BT observations is less than 0.25 and 0.5 K, respectively, over both water and land for most MODIS IR spectral bands. The AIRS cloud-cleared BT spectrum is also compared with its nearby clear BT spectrum, the difference, accounting the effects due to scene nonuniformity, is reasonable according to the analysis. The multiband optimal cloud-clearing is also compared with the traditional single-band N/sup */ cloud-clearing; the performance enhancement of the optimal cloud-clearing over the single-band traditional N/sup */ cloud-clearing is demonstrated and discussed. It is found that more than 30% of the AIRS cloudy (partly and overcast) footprints in this study have been successfully cloud-cleared using the optimal cloud-clearing method, revealing the potential application of this method to the operational processing of hyperspectral IR sounder cloudy radiance measurements when the collocated imager IR data are available. The use of a high spatial resolution imager, along with information from a high spectral resolution sounder for cloud-clearing, is analogous to instruments planned for the next-generation Geostationary Operational Environmental Satellite (GOES-R) instruments-the Advanced Baseline Imager and the Hyperspectral Environmental Suite. Since no microwave instruments are being planned for GOES-R, the cloud-clearing methodology demonstrated in this paper will become the most practical approach for obtaining the reliable clear-column radiances.

Intense economic and industrial development in China has been accompanied by severe local air pollution, as well as in other downwind countries in East Asia. This study analyzes satellite observational data of sulfur dioxide (SO₂), nitrogen dioxide (NO₂), and aerosol optical depth (AOD) to explore the spatial distribution, long-term temporal variation, and correlation to meteorological conditions over this region over the period 2005–2015. SO₂ and NO₂ data are retrieved from the ozone monitoring instrument (OMI) onboard the National Aeronautics and Space Administration (NASA) Aura satellite, while AOD data are from the moderate-resolution imaging spectroradiometer (MODIS) onboard the NASA Aqua satellite. Spatial distributions of SO₂, NO₂, and AOD show the highest levels in the North China Plain (NCP), with hotspots also in Southeastern China (SC) and the Sichuan Basin (SB). Biomass burning also contributes to a high level of AOD in Southeast Asia in spring and in Equatorial Asia in fall. Considering the correlation of pollutant levels to meteorological conditions, monitoring data show that higher temperature and higher relative humidity (RH) favor the conversion of SO₂ and NO₂ to sulfate and nitrate aerosol, respectively. The impact of stronger lower tropospheric stability facilitates the accumulation of SO₂ and NO₂ in NCP and SC. Transport of SO₂ and NO₂ from intense source regions to relatively clean regions is highly influential over East Asia; such transport from the NCP leads to a considerable increase of pollutants in SC, SB, Taiwan Island (TW), and Taiwan Strait (TWS), particularly in winter. Aerosols generated by biomass burning in Southeast Asia and anthropogenic aerosol in SC are transported to TW and TWS and lead to the increase of AOD, with the highest levels of AOD in SC, TW, and TWS occurring in spring. Precipitation results in the removal of pollutants, especially in highly polluted regions, the effect of which is most significant in winter and spring.

In this paper, a convective initiation event from the International H2O Project (IHOP) field experiment is used to demonstrate the potential utility of a future geostationary advanced infrared (IR) sounder for severe storm nowcasting applications. An advanced IR sounder would provide detailed stability information (e.g., lifted index and other parameters) with high temporal resolution useful for determining favorable locations for convective initiation. Atmospheric data from a high-resolution Weather Research and Forecasting model simulation was used to generate simulated Hyperspectral Environmental Suite (HES) and Advanced Baseline Imager (ABI) stability products. Comparison of these products shows that the ABI [or the current Geostationary Operational Environmental Satellite (GOES) Sounder] provides limited stability information before the storm development as a result of the limited spectral IR information for temperature and moisture profiling. The high spatial and temporal geostationary advanced IR sounder, however, can provide critical information about the destabilization much earlier than the current GOES Sounder or ABI.