Lena Iredell

Improved Temperature Sounding and Quality Control Methodology Using AIRS/AMSU Data: The AIRS Science Team Version 5 Retrieval Algorithm

This paper describes the Atmospheric Infrared Sounder (AIRS) Science Team Version 5 retrieval algorithm in terms of its three most significant improvements over the methodology used in the AIRS Science Team Version 4 retrieval algorithm: the use of AIRS clear-column radiances in the entire 4.3-μm CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night, with tropospheric sound ing of 15-μm CO2 observations now being used primarily in the generation of clear-column radiances R̂i for all channels; development of a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances and their use in a new approach for quality control; and an approach to provide AIRS soundings in partially cloudy conditions that does not require use of any microwave data. This new AIRS-only sounding methodology, referred to as AIRS Version 5 AO, was developed as a backup to AIRS Version 5 should the Advanced Microwave Sounding Unit (AMSU)-A instrument fail. Results are shown that compare the relative performance of the AIRS Version 4, Version 5, and Version 5 AO. Results using Version 5 retrievals in conjunction with different quality control thresholds are also shown for a recent period to demonstrate that empirical coefficients continue to be applicable in later time periods. The Goddard Data and Information Services Center (DISC) is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper describes the quality control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific purposes.

Significant advances in the AIRS Science Team Version-6 retrieval algorithm

The Goddard DISC generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm became operational at the Goddard DISC in late 2012. This paper describes some of the significant improvements in retrieval methodology contained in the Version-6 retrieval algorithm, compared to that used in Version-5. In particular, the Science Team made major changes with regard to the algorithms used to 1) derive surface skin temperature and surface spectral emissivity; 2) generate the initial state used to start the cloud clearing and retrieval procedures; and 3) determine Quality Control. This paper describes these advances found in the AIRS Version- 6 retrieval algorithm and demonstrates the improvements of some AIRS Version-6 products compared to those obtained using Version-5.

Contributions to climate research using the AIRS Science Team version-5 products

This paper compares recent spatial anomaly time series of OLR (Outgoing Longwave Radiation) and OLRCLR (Clear Sky OLR) as determined using CERES and AIRS observations over the time period September 2002 through June 2010. We find excellent agreement in OLR anomaly time series of both data sets in almost every detail, down to the 1° x 1° spatial grid point level. This extremely close agreement of OLR anomaly time series derived from observations by two different instruments implies that both sets of results must be highly stable. This agreement also validates to some extent the anomaly time series of the AIRS derived products used in the computation of the AIRS OLR product. The paper then examines anomaly time series of AIRS derived products over the extended time period September 2002 through April 2011. We show that OLR anomalies during this period are closely in phase with those of an El Niño index, and that recent global and tropical mean decreases in OLR and OLRCLR are a result of a transition from an El Niño condition at the beginning of the data record to La Niña conditions toward the end of the data period. This relationship can be explained by temporal changes of the distribution of mid-tropospheric water vapor and cloud cover in two spatial regions that are in direct response to El Niño/La Niña activity which occurs outside these spatial regions.

Improved determination of surface and atmospheric temperatures using only shortwave AIRS channels

AIRS was launched on EOS Aqua on May 4, 2002, together with AMSU-A and HSB, to form a next generation polar orbiting infrared and microwave atmospheric sounding system. AIRS is a grating spectrometer with a number of linear arrays of detectors with each detector sensitive to outgoing radiation in a characteristic frequency υi with a spectral band pass Δυi of roughly υi/1200 AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm-1 (15.38 μm) - 2665 cm-1 (3.752 μm). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 μm (longwave) CO2 band, and the 4.3 μm (shortwave) CO2 absorption band. There are also two atmospheric window regions, the 12 μm - 8 μm (longwave) window, and the 4.17 μm - 3.75 μm (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. One reason for this was concerns about the effects, during the day, of reflected sunlight and non-Local Thermodynamic Equilibrium (non-LTE) on the observed radiances in the shortwave portion of the spectrum. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses the longwave channels to determine cloud cleared radiances Ri for all channels, and uses Ri only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used by the AIRS Science Team in preparation for the AIRS Version 6 Retrieval Algorithm. This paper describes how the effects on the radiances of solar radiation reflected by clouds and the Earths surface, and also of non-LTE, are accounted for in the analysis of the data. Results are presented for both daytime and nighttime conditions showing improved surface and atmospheric soundings under partial cloud cover resulted from not using Ri in the retrieval process for any longwave channels sensitive to cloud effects. This improvement is made possible because AIRS NEDT in the shortwave portion of the spectrum is extremely low.

Results from CrIS/ATMS obtained using the AIRS Science Team retrieval methodology

AIRS was launched on EOS Aqua in May 2002, together with AMSU-A and HSB (which subsequently failed early in the mission), to form a next generation polar orbiting infrared and microwave atmospheric sounding system. AIRS/AMSU had two primary objectives. The first objective was to provide real-time data products available for use by the operational Numerical Weather Prediction Centers in a data assimilation mode to improve the skill of their subsequent forecasts. The second objective was to provide accurate unbiased sounding products with good spatial coverage that are used to generate stable multi-year climate data sets to study the earth’s interannual variability, climate processes, and possibly long-term trends. AIRS/AMSU data for all time periods are now being processed using the state of the art AIRS Science Team Version-6 retrieval methodology. The Suomi-NPP mission was launched in October 2011 as part of a sequence of Low Earth Orbiting satellite missions under the “Joint Polar Satellite System” (JPSS). NPP carries CrIS and ATMS, which are advanced infra-red and microwave atmospheric sounders that were designed as follow-ons to the AIRS and AMSU instruments. The main objective of this work is to assess whether CrIS/ATMS will be an adequate replacement for AIRS/AMSU from the perspective of the generation of accurate and consistent long term climate data records, or if improved instruments should be developed for future flight. It is critical for CrIS/ATMS to be processed using an algorithm similar to, or at least comparable to, AIRS Version-6 before such an assessment can be made. We have been conducting research to optimize products derived from CrIS/ATMS observations using a scientific approach analogous to the AIRS Version-6 retrieval algorithm. Our latest research uses Version-5.70 of the CrIS/ATMS retrieval algorithm, which is otherwise analogous to AIRS Version-6, but does not yet contain the benefit of use of a Neural-Net first guess start-up system which significantly improved results of AIRS Version-6. Version-5.70 CrIS/ATMS temperature profile and surface skin temperature retrievals are of very good quality, and are better than AIRS Version-5 retrievals, but are still significantly poorer than those of AIRS Version-6. CrIS/ATMS retrievals should improve when a Neural-Net start-up system is ready for use. We also examined CrIS/ATMS retrievals generated by NOAA using their NUCAPS retrieval algorithm, which is based on earlier versions of the AIRS Science Team retrieval algorithms. We show that the NUCAPS algorithm as currently configured is not well suited for climate monitoring purposes.

Recent Advances in Improvement of Forecast Skill and Understanding Climate Processes Using AIRS Version-5 Products

The NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC) generates products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. This paper shows results of some of our research using Version-5 products from the points of view of improving forecast skill as well as aiding in the understanding of climate processes.

Retrieved Products from Simulated Hyperspectral Observations of a Hurricane

This research uses General Circulation Model (GCM) derived products, with 1 km spatial resolution and sampled every 10 minutes, over a moving area following the track of a simulated severe Atlantic storm. Model products were aggregated over sounder footprints corresponding to 13 km in LEO, 2 km in LEO, and 5 km in GEO sampled every 72 minutes. We simulated radiances for instruments with AIRS-like spectral coverage, spectral resolution, and channel noise, using these aggregated products as the truth, and analyzed them using a slightly modified version of the operational AIRS Version-6 retrieval algorithm. Accuracy of retrievals obtained using simulated AIRS radiances with a 13 km footprint was similar to that obtained using real AIRS data. Spatial coverage and accuracy of retrievals are shown for all three sounding scenarios. The research demonstrates the potential significance of flying Advanced AIRS-like instruments on future LEO and GEO missions.

Results from CrIS/ATMS Obtained Using an AIRS "Version-6 like" Retrieval Algorithm

A main objective of AIRS/AMSU on EOS is to provide accurate sounding products that are used to generate climate data sets. Suomi NPP carries CrIS/ATMS that were designed as follow-ons to AIRS/AMSU. Our objective is to generate a long term climate data set of products derived from CrIS/ATMS to serve as a continuation of the AIRS/AMSU products. We have modified an improved version of the operational AIRS Version-6 retrieval algorithm for use with CrIS/ATMS. CrIS/ATMS products are of very good quality, and are comparable to, and consistent with, those of AIRS.

Improved Surface and Tropospheric Temperatures Determined Using Only Shortwave Channels: The AIRS Science Team Version-6 Retrieval Algorithm

The Goddard DISC has generated products derived from AIRS/AMSU-A observations, starting from September 2002 when the AIRS instrument became stable, using the AIRS Science Team Version-5 retrieval algorithm. The AIRS Science Team Version-6 retrieval algorithm will be finalized in September 2011. This paper describes some of the significant improvements contained in the Version-6 retrieval algorithm, compared to that used in Version-5, with an emphasis on the improvement of atmospheric temperature profiles, ocean and land surface skin temperatures, and ocean and land surface spectral emissivities. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm-1 (15.38 μm) - 2665 cm-1 (3.752 μm). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 μm (longwave) CO2 band, and the 4.3 μm (shortwave) CO2 absorption band. There are also two atmospheric window regions, the 12 μm - 8 μm (longwave) window, and the 4.17 μm - 3.75 μm (shortwave) window. Historically, determination of surface and atmospheric temperatures from satellite observations was performed using primarily observations in the longwave window and CO2 absorption regions. According to cloud clearing theory, more accurate soundings of both surface skin and atmospheric temperatures can be obtained under partial cloud cover conditions if one uses observations in longwave channels to determine coefficients which generate cloud cleared radiances Ri for all channels, and uses Ri only from shortwave channels in the determination of surface and atmospheric temperatures. This procedure is now being used in the AIRS Version-6 Retrieval Algorithm. Results are presented for both daytime and nighttime conditions showing improved Version-6 surface and atmospheric soundings under partial cloud cover.

Improved determination of surface and atmospheric temperatures using only shortwave AIRS channels: The AIRS Version-6 retrieval algorithm

AIRS was launched on EOS Aqua on May 4, 2002 together with ASMU-A and HSB to form a next generation polar orbiting infrared and microwave atmosphere sounding. The AIRS Science Team Version 6 retrieval system uses only shortwave CO2 channels to determine temperature profile, and only window observations in the shortwave window region, 4.0 µm – 3.76 µm, to determine both surface skin temperatures and shortwave surface spectral emissivities. The current use of only shortwave AIRS channels in the retrieval of both atmospheric and surface parameters has resulted in significant improvement in the ability to obtain accurate temperature profiles and surface skin temperatures under more stressing partial cloud cover conditions than achieved previously. In this paper, we will show the improvement in retrieved Quality Controlled values of sea surface temperature and ocean spectral surface emissivity compared to those obtained using the AIRS Version-5 retrieval algorithm which used longwave and shortwave window observations simultaneously to determine surface parameters.