Tom King

Regression of Surface Spectral Emissivity From Hyperspectral Instruments

The operational Atmospheric Infrared Sounder (AIRS) emissivity retrieval uses a National Oceanic and Atmospheric Administration (NOAA) regression emissivity product as a first guess for its retrieval over land. The NOAA approach is based on clear radiances that are simulated from the European Centre for Medium-Range Weather Forecasting forecast and a surface emissivity training data set. The same approach has also been applied to simulated Infrared Atmospheric Sounding Interferometer (IASI) data. Resulted emissivity spectra and maps derived from AIRS and IASI will be presented and discussed.

Multiyear Observations of the Tropical Atlantic Atmosphere: Multidisciplinary Applications of the NOAA Aerosols and Ocean Science Expeditions

This paper gives an overview of a unique set of ship-based atmospheric data acquired over the tropical Atlantic Ocean during boreal spring and summer as part of ongoing National Oceanic and Atmospheric Administration (NOAA) Aerosols and Ocean Science Expedition (AEROSE) field campaigns. Following the original 2004 campaign onboard the Ronald H. Brown, AEROSE has operated on a yearly basis since 2006 in collaboration with the NOAA Prediction and Research Moored Array in the Tropical Atlantic (PIRATA) Northeast Extension (PNE). In this work, attention is given to atmospheric soundings of ozone, temperature, water vapor, pressure, and wind obtained from ozonesondes and radiosondes launched to coincide with low earth orbit environmental satellite overpasses [MetOp and the National Aeronautics and Space Administration (NASA) A-Train]. Data from the PNE/ AEROSE campaigns are unique in their range of marine meteorological phenomena germane to the satellite missions in question, including dust and smoke outflows ...

Using MetOp-A AVHRR Clear-Sky Measurements to Cloud-Clear MetOp-A IASI Column Radiances

AbstractHigh spatial resolution measurements from the Advanced Very High Resolution Radiometer (AVHRR) on the Meteorological Operation (MetOp)-A satellite that are collocated to the footprints from the Infrared Atmospheric Sounding Interferometer (IASI) on the satellite are exploited to improve and quality control cloud-cleared radiances obtained from the IASI. For a partial set of mostly ocean MetOp-A orbits collected on 3 October 2010 for latitudes between 70°S and 75°N, these cloud-cleared radiances and clear-sky subpixel AVHRR measurements within the IASI footprint agree to better than 0.25-K root-mean-squared difference for AVHRR window channels with almost zero bias. For the same dataset, surface skin temperatures retrieved using the combined AVHRR, IASI, and Advanced Microwave Sounding Unit (AMSU) cloud-clearing algorithm match well with ECMWF model surface skin temperatures over ocean, yielding total uncertainties ≤1.2 K for scenes with up to 97% cloudiness.

An Experiment Using High Spectral Resolution CrIS Measurements for Atmospheric Trace Gases: Carbon Monoxide Retrieval Impact Study

We perform a demonstration experiment using the National Oceanic Atmospheric Administration Unique Cross-track Infrared Sounder (CrIS)/Advanced Technology Microwave Sounder Processing System to assess the improvement on trace gas retrievals upon switching to high spectral resolution CrIS radiance measurements (0.625 cm-1). The focus of this study is carbon monoxide retrievals. The experimental high spectral resolution CO retrievals show a remarkable improvement, of almost up to one order of magnitude in the degree of freedom of the signal, with respect to the low-resolution mode. Furthermore, high-resolution CO retrievals show similar skill with respect to existing CO operational products from the Atmospheric InfraRed Sounder, Atmospheric Sounder Interferometer, and Measurements of Pollution In The Troposphere instruments, both in terms of spatial variability and degrees of freedom. The results of this research provide evidence to support the need for high spectral resolution CrIS measurements. This is a fundamental prerequisite in guaranteeing continuity to the CO afternoon orbit monitoring as part of a multisatellite uniformly integrated long-term data record of atmospheric trace gases.

Alternative cloud clearing methodologies for the Atmospheric Infrared Sounder (AIRS)

Traditional cloud clearing methods utilize a clear estimate of the atmosphere inferred from a microwave sounder to extrapolate cloud cleared radiances (CCRs) from a spatial interpolation of multiple cloudy infrared footprints. Unfortunately, sounders have low information content in the lower atmosphere due to broad weighting functions, interference from surface radiance and the microwave radiances can also suffer from uncorrected side-lobe contamination. Therefore, scenes with low altitude clouds can produce errant CCRs that, in-turn, produce errant sounding products. Radiances computed from the corrupted products can agree with the measurements within the error budget making detection and removal of the errant scenes impractical; typically, a large volume of high quality retrievals are rejected in order to remove a few errant scenes. In this paper we compare and contrast the yield and accuracy of the traditional approach with alternative methods of obtaining CCRs. The goal of this research is three-fold: (1) to have a viable approach if the microwave instruments fail on the EOS-AQUA platform; (2) to improve the accuracy and reliability of infrared products derived from CCRs; and (3) to investigate infrared approaches for geosynchronous platforms where microwave sounding is difficult. The methods discussed are (a) use of assimilation products, (b) use of a statistical regression trained on cloudy radiances, (c) an infrared multi-spectral approach exploiting the non-linearity of the Planck function, and (d) use of clear MODIS measurements in the AIRS sub-pixel space. These approaches can be used independently of the microwave measurements; however, they also enhance the traditional approach in the context of quality control, increased spatial resolution, and increased information content.

Using MODIS with AIRS to develop an operational cloud-cleared radiance product

Today, most Numerical Weather Prediction (NWP) centers are assimilating cloud-free radiances. Radiances from the Atmospheric Infrared Sounder have been directly assimilated in NWP models with modest positive impacts. However, since only 5% percentage of AIRS fields of view (fovs) are cloud-free, only very small amounts of the data in the lower troposphere are assimilated. (Note that channels in the mid-upper stratosphere are always assimilated since they are never contaminated by clouds.) The highest vertical resolving power of AIRS is in the lower troposphere. To further improve forecast skill we must increase the use of channels in the lower troposphere. This can be accomplished by assimilating cloud-cleared radiances, which has a yield of about 50%. Since cloud-cleared radiance may have residual cloud contamination and forecast accuracy is very sensitive to the accuracy of the input observations, a technique has been developed to use the 1 km infrared channels on the Moderate Resolution Imaging Spectroradiometer (MODIS) to quality control the cloud-cleared radiances derived from an array of 3 x 3 high spectral infrared sounder AIRS 14 km fovs. This is accomplished by finding MODIS clear radiances values within the AIRS field of view. The MODIS clear radiances are compared to cloud-cleared AIRS radiances that have been convolved to the MODIS spectral resolution. Our studies have found that the cloud-cleared radiances error statistics are very similar to cloud-free (clear) when MODIS data are used to remove potential outliers in the population of AIRS cloud-cleared radiances.

On the angular effect of residual clouds and aerosols in clear-sky IR window radiance observations

This paper summarizes work investigating the zenith angular dependence of residual cloud and/or aerosol contamination on “clear-sky” infrared observations, which include cloud-cleared radiances and cloud-masked data, along with the implication for achieving agreement with forward calculations over the scanning range of the sensor.

An integration system for the collocation of polar and geostationary satellite observations

Satellite observation collocation algorithms are generally used to spatially match observations or products from different satellite systems. The spatially matched and integrated satellite datasets are commonly used in integrated retrievals, satellite instrument inter-calibration and satellite observation validation. Instrument physical based collocation algorithms are developed at NOAA/NESDIS/STAR to support the development of the satellite observation integration system. The algorithms are applied within the Geostationary satellite & Polar satellite (GEO-LEO) integration system for IASI/SEVRI and will applied in the future CrIS/GOES-R observation integration system. In this paper, the details of the algorithms for IASI/SEVERI and AIRS/SEVIRI collocation are described and some results for both are presented.

A Cross-Comparison of The NOAA/NESDIS AIRS, IASI and CrIS Operational Channel Selections: Methodology and Information Content

We present a cross-comparison of the NOAA/NESDIS operational channel selection for AIRS, IASI and CrIS. The focus of this study is on the channel selection methodology and the final information content in the three systems.

Validation of AIRS and IASI Temperature and Water Vapor Retrievals with Global Radiosonde Measurements and Model Forecasts

Atmospheric temperature and water vapor profiles retrieved from the Aqua-Atmospheric Infrared Sounder instrument and the MetOp-Infrared Atmospheric Sounding Interferometer instrument are validated with global radiosonde measurements and forecasts.