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NASA NTRS2008

Assimilation of Atmospheric InfraRed Sounder (AIRS) Profiles using WRF-Var

The Weather Research and Forecasting (WRF) model contains a three-dimensional variational (3DVAR) assimilation system (WRF-Var), which allows a user to join data from multiple sources into one coherent analysis. WRF-Var combines observations with a background field traditionally generated using a previous model forecast through minimization of a cost function. In data sparse regions, remotely-sensed observations may be able to improve analyses and produce improved forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The combined AIRS/AMSU system provides radiance measurements used as input to a sophisticated retrieval scheme which has been shown to produce temperature profiles with an accuracy of 1 K over 1 km layers and humidity profiles with accuracy of 15% in 2 km layers in both clear and partly cloudy conditions. The retrieval algorithm also provides estimates of the accuracy of the retrieved values at each pressure level, allowing the user to select profiles based on the required error tolerances of the application. The purpose of this paper is to describe a procedure to optimally assimilate high-resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type using gen_be and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics in the WRF-Var. The AIRS thermodynamic profiles are obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators are used to select the highest quality temperature and moisture data for each profile location and pressure level. Analyses are run to produce quasi-real-time regional weather forecasts over the continental U.S. The preliminary assessment of the impact of the AIRS profiles will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes.

Zavodsky, Brad↗

NASA NTRS2007

Investigation of the NOAA N' S Search and Rescue Antenna Inadvertent Deployment: Type C Mishap

The NOAA N' Search and Rescue Antenna (SRA) inadvertently deployed during a spacecraft rotation on April 14,2007. This rotation was part of a normal operation to configure the spacecraft for additional antenna and the solar array boom deployments. This procedure (red flag written) had been modified to look for a lost metal washer and a thermal blanket button. The modification to the procedure was reviewed and approved by the Lockheed Martin Missiles and Space (LMMS) Material Review Board (MRB) per standard procedures. The flag to the procedure introduced a counter clockwise rotation before the normal clockwise rotation. The antenna was temporally stowed and held in place via lacing cord. The lacing cord broke and allowed the SRA to inadvertently deploy during the clockwise rotation. The SRA broke through a hard stop bracket and damaged an instrument optical sensor radiator panel. The satellite damage appears to be minimal and there were no injuries to personnel. The damage to the Advanced Microwave Sounding Unit (AMSU)-A1 instrument has not been fully assessed. Based on mishap site visits, interviews and data analysis, the Mishap Investigation Team (MIT) identified the underlying causes of the mishap. Event and causal factor tree diagrams were developed, resulting in the identification of the proximate (or direct) cause and root causes of the mishap.

Sabelhaus, Phil↗

NASA NTRS2007

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

clouds↗

NASA NTRS2008

Climate Variability during the TRMM Era: Relationships between TRMM Precipitation and Upper-Tropospheric Hydrometeors

Tropical rainfall as seen by the TRMM radar has multiple scales of organization, one prominent example of which is mesoscale deep convection that supports the production of strong, widespread anvil systems important to the planet's water and energy balance. TRMM PR precipitation retrievals (i.e. the 2A25 algorithm) are reliable down to rates below 1.0 mm/h which captures the majority of near-surface rainfall. However, much of the precipitating hydrometeor mass above the freezing level in these anvil systems may be associated with particles where TRMM PR s/n is low. In out analysis we are examining the question of 'What portions of the total hydrometeor spectrum can we see individually with TRMM, CloudSat, high frequency passive microwave (e.g. AMSU-B, MHS) and MODIS'. This will allow us to pursue fundamental issues of precipitation, efficiency, maintenance of upper-troposheric humidity, and cloud forcing variability in the tropical climate system. We do this by generating frequency distributions of ice water content (IWC), integrated IWC (IWP), and precipitation as appropriate for these sensors and relate these to TRMM near-surface rainfall. Joint frequency distributions are developed from more limited coincidence between TRMM and these sensors. We interpret these results in terms of a climate regime descriptor and as an index of precipitation efficiency for tropical rain systems.

Robertson, Franklin↗

NASA NTRS2008

Water Vapor Feedback and Links to Mechanisms of Recent Tropical Climate Variations

Recent variations of tropical climate on interannual to near-decadal scales have provided a useful target for studying feedback processes. A strong warm/cold ENSO couplet (e.g. 1997-2000) along with several subsequent weaker events are prominent interannual signals that are part of an apparent longer term strengthening of the Walker circulation during the mid to late1990 s with some weakening thereafter. Decadal scale changes in tropical SST structure during the 1990s are accompanied by focusing of precipitation over the Indo-Pacific warm pool and an increase in tropical ocean evaporation of order 1.0 %/decade. Here we use a number of diverse satellite measurements to explore connections between upper-tropospheric humidity (UTH) variations on these time scales and changes in other water and energy fluxes. Precipitation (GPCP, TRMM), turbulent fluxes (OAFlux), and radiative fluxes (ERBE / CERES, SRB) are use to analyze vertically-integrated divergence of moist static energy, divMSE, and its dry and moist components. Strong signatures of MSE flux transport linking ascending and descending regions of tropical circulations are found. Relative strengths of these transports compared to radiative flux changes are interpreted as a measure of efficiency in the overall process of heat rejection during episodes of warm or cold SST forcing. In conjunction with the diagnosed energy transports we explore frequency distributions of upper-tropospheric humidity as inferred from SSM/T-2 and AMSU-B passive microwave measurements. Relating these variations to SST changes suggests positive water vapor feedback, but at a level reduced from constant relative humidity.

Robertson, F. R.↗

NASA NTRS2009

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

This paper describes the 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. Improved physics in Version 5 allows for use of AIRS clear column radiances in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations are now used primarily in the generation of clear column radiances .R(sub i) for all channels. This new approach allows for the generation of more accurate values of .R(sub i) and T(p) under most cloud conditions. Secondly, Version 5 contains a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 also contains for the first time 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 AMSU-A instrument fail. Results are shown comparing the relative performance of the AIRS Version 4, Version 5, and Version 5 AO for the single day, January 25, 2003. The Goddard DISC is now generating and distributing products derived using the AIRS Science Team Version 5 retrieval algorithm. This paper also described the Quality Control flags contained in the DISC AIRS/AMSU retrieval products and their intended use for scientific research purposes.

Susskind, Joel↗

NASA NTRS2009

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 v(sub i) with a spectral band pass delta v(sub i) of roughly v(sub i) /1200. AIRS contains 2378 spectral channels covering portions of the spectral region 650 cm(exp -1) (15.38 gm) - 2665 cm(exp -1)' (3.752 micrometers). These spectral regions contain significant absorption features from two CO2 absorption bands, the 15 micrometer (longwave) CO2 band, and the 4.3 micrometer (shortwave) CO, absorption band. There are also two atmospheric window regions, the 12 micrometerm - 8 micrometer (longwave) window, and the 4.17 micrometer - 3.75 micrometer (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 R(sub i) for all channels, and uses R(sub i) 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 Earth's 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 R(sub i) 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.

Susskind,Joel↗

NASA NTRS2003

Ultraspectral Infrared Measurements from the Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft

Aqua measures the Earth's water cycle, energy fluxes, vegetation and temperatures. The Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit (AMSU) and Humidity Sounder for Brazil (HSB) were launched on the EOS Aqua spacecraft in May 2002. AIRS has had good radiometric and spectral sensitivity, stability, and accuracy and is suitable for climate studies. Temperature products compare well with radiosondes and models over the limited test range (|LAT| less than 40 degrees). Early trace gas products demonstrate the potential of AIRS. NASA is developing the next generation of hyperspectral IR imagers. JPL is ready to participate with US government agencies and US industry to transfer AIRS technology and science experience.

infrared↗

NASA NTRS2009

Data Assimilation and Regional Forecasts Using Atmospheric InfraRed Sounder (AIRS) Profiles

In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radiosondes. The purpose of this paper is to describe a procedure to optimally assimilate AIRS thermodynamic profiles--obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm-into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses will be used to conduct a month-long series of regional forecasts over the continental U.S. The long-tern1 impact of AIRS profiles on forecast will be assessed against verifying radiosonde and stage IV precipitation data.

Chou, Shih-Hung↗

NASA NTRS2009

Data Assimilation and Regional Forecasts using Atmospheric InfraRed Sounder (AIRS) Profiles

In data sparse regions, remotely-sensed observations can be used to improve analyses, which in turn should lead to better forecasts. One such source comes from the Atmospheric Infrared Sounder (AIRS), which, together with the Advanced Microwave Sounding Unit (AMSU), provides temperature and moisture profiles with an accuracy comparable to that of radionsondes. The purpose of this poster is to describe a procedure to optimally assimilate AIRS thermodynamic profiles, obtained from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm, into a regional configuration of the Weather Research and Forecasting (WRF) model using WRF-Var. The poster focuses on development of background error covariances for the regional domain and background field type, a methodology for ingesting AIRS profiles as separate over-land and over-water retrievals with different error characteristics, and utilization of level-by-level quality indicators to select only the highest quality data. The assessment of the impact of the AIRS profiles on WRF-Var analyses will focus on intelligent use of the quality indicators, optimized tuning of the WRF-Var, and comparison of analysis soundings to radiosondes. The analyses are used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impact of AIRS profiles on forecast will be assessed against NAM analyses and stage IV precipitation data.

Zabodsky, Brad↗

NASA NTRS2009

Improving Regional Forecast by Assimilating Atmospheric InfraRed Sounder (AIRS) Profiles into WRF Model

In data sparse regions, remotely-sensed observations can be used to improve analyses and produce improved forecasts. One such source comes from the Atmospheric InfraRed Sounder (AIRS), which together with the Advanced Microwave Sounding Unit (AMSU), represents one of the most advanced space-based atmospheric sounding systems. The purpose of this paper is to describe a procedure to optimally assimilate high resolution AIRS profile data into a regional configuration of the Advanced Research WRF (ARW) version 2.2 using WRF-Var. The paper focuses on development of background error covariances for the regional domain and background type, and an optimal methodology for ingesting AIRS temperature and moisture profiles as separate overland and overwater retrievals with different error characteristics. The AIRS thermodynamic profiles are derived from the version 5.0 Earth Observing System (EOS) science team retrieval algorithm and contain information about the quality of each temperature layer. The quality indicators were used to select the highest quality temperature and moisture data for each profile location and pressure level. The analyses were then used to conduct a month-long series of regional forecasts over the continental U.S. The long-term impacts of AIRS profiles on forecast were assessed against verifying NAM analyses and stage IV precipitation data.

Chou, Shih-Hung↗

NASA NTRS2009

WRF Simulations of the 20-22 January 2007 Snow Events over Eastern Canada: Comparison with In-Situ and Satellite Observations

One of the grand challenges of the Global Precipitation Measurement (GPM) mission is to improve cold season precipitation measurements in middle and high latitudes through the use of high-frequency passive microwave radiometry. For this, the Weather Research and Forecasting (WRF) model with the Goddard microphysics scheme is coupled with a satellite data simulation unit (WRF-SDSU) that has been developed to facilitate over-land snowfall retrieval algorithms by providing a virtual cloud library and microwave brightness temperature (Tb) measurements consistent with the GPM Microwave Imager (GMI). This study tested the Goddard cloud microphysics scheme in WRF for two snowstorm events, a lake effect and a synoptic event, that occurred between 20 and 22 January 2007 over the Canadian CloudSAT/CALIPSO Validation Project (C3VP) site in Ontario, Canada. The 24h-accumulated snowfall predicted by the WRF model with the Goddard microphysics was comparable to the observed accumulated snowfall by the ground-based radar for both events. The model correctly predicted the onset and ending of both snow events at the CARE site. WRF simulations capture the basic cloud properties as seen by the ground-based radar and satellite (i.e., CloudSAT, AMSU-B) observations as well as the observed cloud streak organization in the lake event. This latter result reveals that WRF was able to capture the cloud macro-structure reasonably well.

Shi, J. J.↗

NASA NTRS2008

Global Daily Atmospheric State Profiles from the Atmospheric Infrared Sounder

The Atmospheric Infrared Sounder (AIRS) is a hyperspectral infrared instrument on the EOS Aqua Spacecraft, launched on May 4, 2002. AIRS has 2378 infrared channels ranging from 3.7 (micro)m to 15.4 (micro)m and a 13.5 km footprint. AIRS, in conjunction with the Advanced Microwave Sounding Unit (AMSU), produces temperature profiles with 1K/km accuracy on a global scale, as well as water vapor profiles, clouds, dust and trace gas amounts for CO2, CO, SO2, O3 and CH4.[1] AIRS data are used for weather forecasting and studies of global climate change. The AIRS is a 'facility' instrument developed by NASA as an experimental demonstration of advanced technology for remote sensing and the benefits of high resolution infrared spectra to science investigations.

sounder↗

NASA NTRS2009

Climatological Features of the Upper Troposphere and Stratosphere in the GEOS-5 "MERRA" Analyses (1979-2008)

The realism of various aspects of the upper troposphere and stratosphere in the "Modern Era Retrospective-analysis for Research and Applications" (MERRA) dataset will be examined. The MERRA reanalysis extends from 1979 until the present, using the Goddard Earth Observing System, Version 5 (GEOS-5) data assimilation system. The model and analysis have a half-degree spatial resolution with 72 layers that are constrained by observations between the Earth's surface and the stratopause. A comprehensive, time-evolving suite of meteorological observations (e.g., in-situ temperature, moisture, wind and pressure measurements and space-based infrared and microwave radiances) is assimilated. Results show realistic depiction of dominant features, such as the quasi-biennial oscillation, jet structures (including interannual variaficns) and tropopause characteristics, as validated using independent observations and system statistics. Challenges for such reanalyses include the stability to transitions in the observing system, such as the replacement of MSU/SSU by the AMSU-A data in the middle atmosphere. The paper will discuss the use of satellite radiances and examine impacts of satellite drifts and instrument changes on the analyses.

Pawson, S.↗

NASA NTRS2010

Use of Quality Controlled AIRS Temperature Soundings to Improve Forecast Skill

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. The primary products of AIRS/AMSU-A are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. Also included are the clear column radiances used to derive these products which are representative of the radiances AIRS would have seen if there were no clouds in the field of view. All products also have error estimates. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of 1K, and layer precipitable water with an rms error of 20 percent, in cases with up to 90 percent effective cloud cover. The products are designed for data assimilation purposes for the improvement of numerical weather prediction, as well as for the study of climate and meteorological processes. With regard to data assimilation, one can use either the products themselves or the clear column radiances from which the products were derived. The AIRS Version 5 retrieval algorithm is now being used operationally at the Goddard DISC in the routine generation of geophysical parameters derived from AIRS/AMSU data. A major innovation in Version 5 is the ability to generate case-by-case level-by-level error estimates for retrieved quantities and clear column radiances, and the use of these error estimates for Quality Control. The temperature profile error estimates are used to determine a case-by-case characteristic pressure pbest, down to which the profile is considered acceptable for data assimilation purposes. The characteristic pressure p(sub best) is determined by comparing the case dependent error estimate (delta)T(p) to the threshold values (Delta)T(p). The AIRS Version 5 data set provides error estimates of T(p) at all levels, and also profile dependent values of pbest based on use of a Standard profile dependent threshold (Delta)T(p). These Standard thresholds were designed as a compromise between optimal use for data assimilation purposes, which requires highest accuracy (tighter Quality Control), and climate purposes, which requires more spatial coverage (looser Quality Control). Subsequent research using Version 5 sounding and error estimates showed that tighter Quality Control performs better for data assimilation proposes, while looser Quality Control better spatial coverage) performs better for climate purposes. We conducted a number of data assimilation experiments using the NASA GEOS-5 Data Assimilation System as a step toward finding an optimum balance of spatial coverage and sounding accuracy with regard to improving forecast skill. The model was run at a horizontal resolution of 0.5 degree latitude x 0.67 degree longitude with 72 vertical levels. These experiments were run during four different seasons, each using a different year. The AIRS temperature profiles were presented to the GEOS-5 analysis as rawinsonde profiles, and the profile error estimates (delta)T(p) were used as the uncertainty for each measurement in the data assimilation process.

Susskind, Joel↗

NASA NTRS2010

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 system (Pagano et al 2003). The theoretical approach used to analyze AIRS/AMSU/HSB data in the presence of clouds in the AIRS Science Team Version 3 at-launch algorithm, and that used in the Version 4 post-launch algorithm, have been published previously. Significant theoretical and practical improvements have been made in the analysis of AIRS/AMSU data since the Version 4 algorithm. Most of these have already been incorporated in the AIRS Science Team Version 5 algorithm (Susskind et al 2010), now being used operationally at the Goddard DISC. The AIRS Version 5 retrieval algorithm contains three significant improvements over Version 4. Improved physics in Version 5 allowed for use of AIRS clear column radiances (R(sub i)) in the entire 4.3 micron CO2 absorption band in the retrieval of temperature profiles T(p) during both day and night. Tropospheric sounding 15 micron CO2 observations were used primarily in the generation of clear column radiances (R(sub i)) for all channels. This new approach allowed for the generation of accurate Quality Controlled values of R(sub i) and T(p) under more stressing cloud conditions. Secondly, Version 5 contained a new methodology to provide accurate case-by-case error estimates for retrieved geophysical parameters and for channel-by-channel clear column radiances. Thresholds of these error estimates are used in a new approach for Quality Control. Finally, Version 5 contained for the first time 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 was developed as a backup to AIRS Version 5 should the AMSU-A instrument fail. Susskind et al 2010 shows that Version 5 AIRS Only sounding are only slightly degraded from the AIRS/AMSU soundings, even at large fractional cloud cover.

Susskind, Joel↗

NASA NTRS2010

NASA's Advancements in Space-Based Spectrometry Lead to Improvements in Weather Prediction and Understanding of Climate Processes

AIRS (Atmospheric Infra-Red Sounder), was launched, in conjunction with AMSU-A (Advanced Microwave Sounding Unit-A) on the NASA polar orbiting research satellite EOS (Earth Observing System) Aqua satellite in May 2002 as a next generation atmospheric sounding system. Atmospheric sounders provide information primarily about the vertical distribution of atmospheric temperature and water vapor distribution. This is achieved by measuring outgoing radiation in discrete channels (spectral intervals) which are sensitive primarily to variations of these geophysical parameters. The primary objectives of AIRS/AMSU were to utilize such information in order to improve the skill of numerical weather prediction as well as to measure climate variability and trends. AIRS is a multi-detector array grating spectrometer with 2378 channels covering the spectral range 650/cm (15 microns) to 2660/cm (3.6 microns) with a resolving power (i/a i) of roughly 1200 where a i is the spectral channel bandpass. Atmospheric temperature profile can be determined from channel observations taken within the 15 micron (the long-wave CO2 absorption band) and within the 4.2 micron (the short-wave CO2 absorption band). Radiances in these (and all other) spectral intervals in the infrared are also sensitive to the presence of clouds in the instrument?s field of view (FOV), which are present about 95% of the time. AIRS was designed so as to allow for the ability to produce accurate Quality Controlled atmospheric soundings under most cloud conditions. This was achieved by having 1) extremely low channel noise values in the shortwave portion of the spectrum and 2) a very flat spatial response function within a channel?s FOV. IASI, the high spectral resolution IR interferometer flying on the European METOP satellite, does not contain either of these important characteristics. The AIRS instrument was also designed to be extremely stabile with regard to its spectral radiometric characteristics, which is critical with regard to the ability to measure accurate long term trends.

Susskind, Joel↗

NASA NTRS2010

Improving Forecast Skill by Assimilation of AIRS Temperature Soundings

Susskind, Joel↗