Engineering topics
Publications and source records attributed to Susskind, Joel.
This slide presentation makes the case for the retrieval of data from the Atmospheric Infrared Sounder (AIRS) Advanced Microwave Sounding Unit (AMSU). AIRS only retrieval is not only a risk reduction for failure of AMSU, but also important because NWP centers are reluctant to assimilate AMSU twice.
Simultaneous use of AIRS/AMSU-A observations allow for the determination of accurate atmospheric soundings under partial cloud cover conditions. The methodology involves the determination of the radiances AIRS would have seen if the AIRS fields of view were clear, called clear column radiances, and use of these radiances to infer the atmospheric and surface conditions giving rise to these clear column radiances. Susskind et al. demonstrate via simulation that accurate temperature soundings and clear column radiances can be derived from AIRS/AMSU-A observations in cases of up to 80% partial cloud cover, with only a small degradation in accuracy compared to that obtained in clear scenes. Susskind and Atlas show that these findings hold for real AIRS/AMSU-A soundings as well. For data assimilation purposes, this small degradation in accuracy is more than offset by a significant increase in spatial coverage (roughly 50% of global cases were accepted, compared to 3.6% of the global cases being diagnosed as clear), and assimilation of AIRS temperature soundings in partially cloudy conditions resulted in a larger improvement in forecast skill than when AIRS soundings were assimilated only under clear conditions. Alternatively, derived AIRS clear column radiances under partial cloud cover could also be used for data assimilation purposes. Further improvements in AIRS sounding methodology have been made since the results shown in Susskind and Atlas . A new version of the AIRS/AMSU-A retrieval algorithm, Version 4.0, was delivered to the Goddard DAAC in February 2005 for production of AIRS derived products, including clear column radiances. The major improvement in the Version 4.0 retrieval algorithm is with regard to a more flexible, parameter dependent, quality control. Results are shown of the accuracy and spatial distribution of temperature-moisture profiles and clear column radiances derived from AIRS/AMSU-A as a function of fractional cloud cover using the Version 4.0 algorithm. Use of the Version 4.0 AIRS temperature profiles increased the positive forecast impact arising from AIRS retrievals relative to what was shown in Susskind and Atlas .
The AIRS/AMSU (flying on the EOS-AQUA satellite) sounding retrieval methodology allows for the retrieval of key atmospheric/surface parameters under partially cloudy conditions (Susskind et al.). In addition, cloud parameters are also derived from the AIRS/AMSU observations. Within each AIRS footprint, cloud parameters at up to 2 cloud layers are determined with differing cloud top pressures and effective (product of infrared emissivity at 11 microns and physical cloud fraction) cloud fractions. However, so far the AIRS cloud product has not been rigorously evaluated/validated. Fortunately, collocated/coincident radiances measured by MODIS/AQUA (at a much lower spectral resolution but roughly an order of-magnitude higher spatial resolution than that of AIRS) are used to determine analogous cloud products from MODIS. This allows us for a rather rare and interesting possibility: the intercomparisons and mutual validation of imager vs. sounder-based cloud products obtained from the same satellite positions. First, we present results of small-scale (granules) instantaneous intercomparisons. Next, we will evaluate differences of temporally averaged (monthly) means as well as the representation of inter-annual variability of cloud parameters as presented by the two cloud data sets. In particular, we present statistical differences in the retrieved parameters of cloud fraction and cloud top pressure. We will investigate what type of cloud systems are retrieved most consistently (if any) with both retrieval schemes, and attempt to assess reasons behind statistically significant differences.
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 are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. 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%, in cases with up to 80% effective cloud cover. The basic theory used to analyze AIRS/AMSU/HSB data in the presence of clouds, called the at-launch algorithm, was described previously. Pre-launch simulation studies using this algorithm indicated that these results should be achievable. Some modifications have been made to the at-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. HSB failed in February 2005, and consequently HSB channel radiances are not used in the results shown in this paper. The AIRS/AMSU retrieval algorithm described in this paper, called Version 4, become operational at the Goddard DAAC in April 2005 and is being used to analyze near-real time AIRS/AMSU data. Historical AIRS/AMSU data, going backwards from March 2005 through September 2002, is also being analyzed by the DAAC using the Version 4 algorithm.
Monthly mean fields of select geophysical parameters derived from analysis of AIRS/AMSU data, and their interannual differences, are shown and compared with analogous fields derived from other sources. All AIRS fields are derived using the AIRS Science Team Version 4 algorithm. Monthly mean results are shown for January 2004, as are interannual differences between January 2004 and January 2003. AIRS temperature and water vapor profile fields are compared with monthly mean collocated ECMWF 3 hour forecast and monthly mean TOVS Pathfinder Path A data. AIRS Tropospheric and Stratospheric coarse climate indicators are compared with analogous MSU products derived by Spencer and christy and found in the TOVS Pathfinder Path A data set. Total ozone is compared with results produced by TOMS. OLR is compared with OLR derived using CERES data and found in the TOVS Pathfinder Path A data set. AIRS results agree well in all cases, especially in the interannual difference sense.
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/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. 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%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correction coefficients and the prediction of location and intensity of cyclones.
"Introduction to AIRS and CrIS" is a chapter in a book dealing with various aspects of remote sensing. AIRS and CrIS are both high spectral resolution IR sounding instruments, which were recently launched (AIRS) or will soon be launched (CrIS). The chapter explains the general principles of infra-red remote sensing, and explains the significance and information content of high spectral resolution IR measurements. The chapter shows results obtained using AIRS observations, and explains why similar quality results should be obtainable from CrIS data.
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/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and 1 km tropospheric layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as alluded to in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and temperature profiles are validated as a function of retrieved effective fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis. Assimilation of AIRS temperature soundings in up to 80% cloud cover for the month of January 2003 into the GSFC FVSSI data assimilation system resulted in improved 5 day forecasts globally, both with regard to anomaly correlation coefficients and the prediction of location and intensity of cyclones.
There are several microwave instruments in low Earth orbit (LEO) that are used for atmospheric temperature and humidity sounding in conjunction with companion IR sounders as well as by themselves. These instruments have achieved a certain degree of maturity and undergoing a redesign to minimize their size, mass, and power from the previous generation instruments. An example of these instruments is the AMSU-A series, now flying on POES and AQUA spacecraft with the IR sounders HIRS and AIRS. These older microwave instruments are going to be replaced by the ATMS instruments that will fly on NPP and NPOESS satellites with the CrIS sounder. A number of techniques learned from the ATMS project in instrument hardware design and data processing are directly applicable to a similar microwave sounder on a geosynchronous platform. These techniques can significantly simplify the design of a Geostationary orbit (GEO) microwave instrument, avoiding costly development and minimizing the risk of not being able to meet the scientific requirements. In fact, some of the 'enabling' technology, such as the use of MMIC microwave components (which is the basis for the ATMS' much reduced volume) can be directly applied to a GEO sounder. The benefits of microwave sounders are well known; for example, they penetrate non-precipitating cloud cover and allow for use of colocated IR observations in up to 80% cloud cover. The key advantages of a microwave instrument in GEO will be the ability to provide high temporal resolution as well as uniform spatial resolution and extend the utility of a colocated advanced IR sounder to cases in which partial cloud cover exists. A footprint of the order of 100 km by 100 km resolution with hemispherical coverage within one hour can be easily achieved for sounding channels in the 50 to 59 GHz range. A GEO microwave sounder will also allow mesoscale sampling of select regions.
AIRS was launched on EOS Aqua on May 5, 2002, together with AMSU A and HSB, to form a next generation polar orbiting infiared and microwave atmospheric sounding system. The primary products of AIRS/AMSU/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an rms error of lK, and layer precipitable water with an rms error of 20%, in cases with up to 80% effective cloud cover. Pre-launch simulation studies indicated that these results should be achievable. Minor modifications have been made to the pre-launch retrieval algorithm as described in this paper. Sample fields of parameters retrieved from AIRS/AMSU/HSB data are presented and validated as a function of retrieved fractional cloud cover. As in simulation, the degradation of retrieval accuracy with increasing cloud cover is small. Select fields are also compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis.
AIRS (Atmospheric Infra-Red Sounder) and AMSU (Advanced Microwave Sounding Unit) comprise the advanced atmospheric and surface sounding system flying on the Aqua satellite launched in May 2002. Monthly mean fields derived from AIRS/AMSU data will be used to extend the climate record (1979-2002) contained in the TOVS Pathfinder Path A Data Set to further study climate variability and trends. Sample daily and monthly mean results derived from AIRS/AMSU data are presented, validated, and compared to equivalent results taken from ECMWF analyses.
AIRS was launched on EOS Aqua on May 5, 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/HSB are twice daily global fields of atmospheric temperature-humidity profiles, ozone profiles, sea/land surface skin temperature, and cloud related parameters including OLR. The sounding goals of AIRS are to produce 1 km tropospheric layer mean temperatures with an RMS error of 1K, and 1 km layer precipitable water with an rms error of 1K, and 1 km layer precipitable water with an rms error of 20 percent, in cases with up to 80 percent cloud cover. The AIRS data products are significant for studying climate variability and change, as well as for use in initialization of General Circulation Models with the objective of improving analysis fields and subsequent forecast skill. Data assimilation experiments to evaluate the impact of AIRS retrievals on analysis and forecast skill are being conducted. Sample fields of parameters retrieved from AIRS/AMSU/HSB data will be presented and validated as a function of retrieved fractional cloud cover. Select fields will also be compared to those contained in the ECMWF analysis, done without the benefit of AIRS data, on both an instantaneous and monthly mean basis, to demonstrate information that AIRS can add to that already contained in the ECMWF analysis.
New state of the art methodology is described to analyze AIRS/AMSU/HSB data in the presence of multiple cloud formations. The methodology forms the basis for the AIRS Science Team algorithm which will be used to analyze AIRS/AMSU/HSB data on EOS Aqua. The cloud clearing methodology requires no knowledge of the spectral properties of the clouds. The basic retrieval methodology is general and extracts the maximum information from the radiances, consistent with the channel noise covariance matrix. The retrieval methodology minimizes the dependence of the solution on the first guess field and the first guess error characteristics. Results are shown for AIRS Science Team simulation studies with multiple cloud formations. These simulation studies imply that clear column radiances can be reconstructed under partial cloud cover with an accuracy comparable to single spot channel noise in the temperature and water vapor sounding regions, temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 1deg K in 1 km thick layers from the surface to 700 mb, 1 km layers from 700 mb to 300 mb, 3 km layers from 300 mb to 30 mb, and 5 km layers from 30 mb to 1 mb, and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 1 km layers from the surface to nearly 200 mb.
Intraseasonal oscillations appearing in a newly available 20-year record of satellite-derived surface air temperature are composited with respect to the lunar phase. Polar regions exhibit strong lunar phase modulation with higher temperatures occurs near full moon and lower temperatures at new moon, in agreement with previous studies. The polar response to the apparent lunar forcing is shown to be most robust in the winter months when solar influence is minimum. In addition, the response appears to be influenced by ENSO events. The highest mean temperature range between full moon and new moon in the polar region between 60 deg and 90 deg latitude was recorded in 1983, 1986/87, and 1990/91. Although the largest lunar phase signal is in the polar regions, there is a tendency for meridional equatorward progression of anomalies in both hemispheres so that the warning in the tropics occurs at the time of the new moon.
The One-Degree Daily (1DD) technique is described for producing globally complete daily estimates of precipitation on a 1 deg x 1 deg lat/long grid from currently available observational data. Where possible (40 deg N-40 deg S), the Threshold-Matched Precipitation Index (TMPI) provides precipitation estimates in which the 3-hourly infrared brightness temperatures (IR T(sub b)) are thresholded and all "cold" pixels are given a single precipitation rate. This approach is an adaptation of the Geostationary Operational Environmental Satellite (GOES) Precipitation Index (GPI), but for the TMPI the IR Tb threshold and conditional rain rate are set locally by month from Special Sensor Microwave/Imager (SSM/I)-based precipitation frequency and the Global Precipitation Climatology Project (GPCP) satellite-gauge (SG) combined monthly precipitation estimate, respectively. At higher latitudes the 1DD features a rescaled daily Television Infrared Observation Satellite (TIROS) Operational Vertical Sounder (TOVS) precipitation. The frequency of rain days in the TOVS is scaled down to match that in the TMPI at the data boundaries, and the resulting non-zero TOVS values are scaled locally to sum to the SG (which is a globally complete monthly product). The time series of the daily 1DD global images shows good continuity in time and across the data boundaries. Various examples are shown to illustrate uses. Validation for individual grid -box values shows a very high root-mean-square error but, it improves quickly when users perform time/space averaging according to their own requirements.
Extreme seasonal fluctuations of the surface-air temperature characterize the climate of central Europe, 45-60 deg North Temperature difference between warm 1990 and cold 1996 in the January-March period, persisting for more than two weeks at a time, amounted to 18 C for extensive areas. These anomalies in the surface-air temperature stem in the first place from differences in the low level flow from the eastern North-Atlantic: the value of the Index 1na of southwesterlies over the eastern North-Atlantic was 8.0 m/s in February 1990, but only 2.6 m/ s in February 1996. The primary forcing by warm advection to positive anomalies in monthly mean surface temperature produced strong synoptic-scale uplift at the 700 mb level over some regions in Europe. The strong uplift contributed in 1990 to a much larger cloud-cover over central Europe, which reduced heat-loss to space (greenhouse effect). Thus, spring arrived earlier than usual in 1990, but later than usual in 1996.
AIRS (Atmospheric Infra Red Sounder) is the first of a series of next generation high spectral resolution infrared sounders which will fly on satellite missions in the next decade. AIRS is a 2368 channel grating spectrometer, with spectral resolving power of roughly upsilon /Delta(upsilon) = 1200, which will fly on the EOS Aqua platform in December 2000 accompanied by AMSU A and HSB, which is similar to AMSU B. New methodology has been developed by the AIRS Science Team to analyze AIRS/AMSU/HSB data in the presence of multilayer broken clouds. The baseline AIRS/AMSU products include surface skin temperature, surface spectral emissivity, atmospheric temperature-moisture-ozone profiles and cloud heights and amounts. Research products include CO and CH4 profiles, total CO2 burden, and OLR. This methodology will be briefly described and results will be shown of AIRS Science Team simulations, based on one day of simulated global data.. RMS errors of atmospheric temperature profiles are expected to be better than 1 K for 1 km layer mean temperatures in up to 80% multilayer fractional cloud cover and RMS errors for moisture profiles are better than 15% for 2 km layers throughout the troposphere.
A radiative transfer model developed to calculate outgoing longwave radiation (OLR) and downwelling longwave, surface flux (DSF) from the Television and Infrared Operational Satellite (TIROS) Operational Vertical Sounder (TOVS) Pathfinder Path A retrieval products is described. The model covers the spectral range of 2 to 2800 cm in 14 medium medium spectral bands. For each band, transmittances are parameterized as a function of temperature, water vapor, and ozone profiles. The form of the band transmittance parameterization is a modified version of the approach we use to model channel transmittances for the High Resolution Infrared Sounder 2 (HIRS2) instrument. We separately derive effective zenith angle for each spectral band such that band-averaged radiance calculated at that angle best approximates directionally integrated radiance for that band. We develop the transmittance parameterization at these band-dependent effective zenith angles to incorporate directional integration of radiances required in the calculations of OLR and DSF. The model calculations of OLR and DSF are accurate and differ by less than 1% from our line-by-line calculations. Also, the model results are within 1% range of other line-by-line calculations provided by the Intercomparison of Radiation Codes in Climate Models (ICRCCM) project for clear-sky and cloudy conditions. The model is currently used to calculate global, multiyear (1985-1998) OLR and DSF from the TOVS Pathfinder Path A Retrievals.