NOAA operational sounding products for advanced TOVS

Reale, Anthony; Tilley, Frank; Ferguson, Michael P.; Allegrino, A.

doi:10.1080/01431160802020502

Cited by 31 publications

(33 citation statements)

References 48 publications

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“…The lowest layer has an average relative RMSE of 30 %, whereas for the highest layer this is 107 %. Our results exhibit similar magnitudes to the results presented in Reale et al (2012), who compared humidity profiles from various satellite products, among them the NOAA ATOVS product (Reale et al, 2008), with the Global Telecommunication System radiosonde data and found typical values of 25-50 % below 400 hPa and of 100 % or more in the upper troposphere.…”

Section: Comparison To Guan Datasupporting

confidence: 89%

“…An example of TOVS retrieval is described in Scott et al (1999) and forms the basis for a data record of atmospheric profiles. Retrieval algorithms for ATOVS are described in, for example, Li et al (2000) and Reale et al (2008). Boukabara et al (2011) developed the Microwave Integrated Retrieval System, which uses AMSU-A and MHS observations and is currently being updated to also include Special Sensor Microwave Imager/Sounder observations.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

Courcoux

Schröder

2015

Earth Syst. Sci. Data

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Abstract. Recently, the reprocessed Advanced Television Infrared Observation Satellite (TIROS)-N Operational Vertical Sounder (ATOVS) tropospheric water vapour and temperature data record was released by the EUMETSAT Satellite Application Facility on Climate Monitoring (CM SAF). ATOVS observations from infrared and microwave sounders onboard the National Oceanic and Atmospheric Agency (NOAA)-15-19 satellites and EUMETSAT's Meteorological Operational (Metop-A) satellite have been consistently reprocessed to generate 13 years (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) of global water vapour and temperature daily and monthly means with a spatial resolution of 90 km × 90 km. The data set is referenced under the following digital object identifier (DOI): doi:10.5676/EUM_SAF_CM/WVT_ATOVS/V001. After preprocessing, a maximum likelihood solution scheme was applied to the observations to simultaneously infer temperature and water vapour profiles. In a postprocessing step, an objective interpolation method (Kriging) was applied to allow for gap filling. The product suite includes total precipitable water vapour (TPW), layer-integrated precipitable water vapour (LPW) and layer mean temperature for five tropospheric layers between the surface and 200 hPa, as well as specific humidity and temperature at six tropospheric levels between 1000 and 200 hPa. To our knowledge, this is the first time that the ATOVS record (1998-now) has been consistently reprocessed (1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011) to retrieve water vapour.TPW and LPW products were compared to corresponding products from the Global Climate Observing System (GCOS) Upper-Air Network (GUAN) radiosonde observations and from the Atmospheric Infrared Sounder (AIRS) version 5 satellite data record. TPW shows a good agreement with the GUAN radiosonde data: average bias and root mean square error (RMSE) are −0.2 and 3.3 kg m −2 , respectively. For LPW, the maximum absolute (relative) bias and RMSE values decrease (increase) strongly with height. The maximum bias and RMSE are found at the lowest layer and are −0.7 and 2.5 kg m −2 , respectively. While the RMSE relative to AIRS is generally smaller, the TPW bias relative to AIRS is larger, with dominant contributions from precipitating areas. The consistently reprocessed ATOVS data record exhibits improved quality and stability relative to the operational CM SAF products when compared to the TPW from GUAN radiosonde data over the period 2004-2011. Finally, it became evident that the change in the number of satellites used for the retrieval combined with the use of the Kriging leads to breakpoints in the ATOVS data record; therefore, a variability analysis of the data record is not recommended for the time period from

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Section: Comparison To Guan Datasupporting

confidence: 89%

Section: Introductionmentioning

confidence: 99%

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

Courcoux

Schröder

2015

Earth Syst. Sci. Data

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show abstract

“…ATOVS were onboard many satellite and many retrieval algorithm were developed for it (Li, et al, 2000;Reale, et al, 2008). The ATOVS onboard METOP B was used in this comparison.…”

Section: Comparison To Atovs Retrievalmentioning

confidence: 99%

Retrieval of atmospheric and surface parameters from VASS/FY-3C data under non-precipitation condition

et al. 2014

SPIE Proceedings

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The Vertical Atmospheric Sounding Suits (VASS) onboard FY-3C satellite includes The Infrared Atmospheric Sounder (IRAS), Microwave Temperature Sounder (MWTS) and Microwave Temperature and moisture sounder (MWTHS-II). The IRAS is similar to that onboard FY-3A/B, while the MWTS-II/MWTHS-II is more sophisticated than their precursors. MWTS has 13 channels mainly at the window region and 57 O2 absorption band, and MWTHS has 15 channels mainly at the 118 O2 absorption band and the 183 H2O absorption band. A package has been developed to retrieve the atmospheric temperature profile, moisture profile, atmospheric total ozone, and other parameters in both clear and cloudy atmospheres from the VASS measurements, which is remap to IRAS Field of view. The algorithm that retrieves these parameters contains four steps: 1) cloud and precipitation detection, 2) bias adjustment for VASS measurements, 3) regression retrieval processes, and 4) a nonlinear iterative physical retrieval. The package does not process precipitation FOV, and for non-precipitation cloud FOV, the measurements from middle to low channels of IRAS are excluded. Till now all instruments are under orbit examination stage, and the primary results show that temperature soundings can be produced under partial cloud cover with RMS errors on the order of, or better than, 2.0 K in 1-km-thick layers from the surface to 700 mb, 1-km layers from 700-300 mb, 3-km layers from 300-30 mb, and 5-km layers from 30-1 mb; and moisture profiles can be obtained with an accuracy better than 20% absolute errors in 2-km layers from the surface to nearly 300 mb.

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“…Furthermore, such intercomparisons can also highlight the merits of different retrieval sensors/algorithms, including the benefits of hyperspectral IR. Example sounder EDR data sets include AIRS, IASI, and the Advanced TIROS Operational Vertical Sounder [e.g., Li et al, 2000;Reale et al, 2008a]. A critical limitation of these data for validation, however, is that they inherently possess similar retrieval error characteristics [Fetzer et al, 2003] and otherwise require proper rigorous treatment of each sensor's averaging kernels [Rodgers and Connor, 2003].…”

Section: Satellite Edr Intercomparisonsmentioning

confidence: 99%

Validation of satellite sounder environmental data records: Application to the Cross‐track Infrared Microwave Sounder Suite

Nalli

Barnet²,

Reale

et al. 2013

JGR Atmospheres

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The Joint Polar Satellite System (JPSS) Cross‐track Infrared Microwave Sounder Suite (CrIMSS) is an advanced operational satellite sounding system concept comprised of the Cross‐track Infrared Sounder and the Advanced Technology Microwave Sounder. These are synergistically designed to retrieve key environmental data records (EDR), namely atmospheric vertical temperature, moisture, and pressure profiles. CrIMSS will serve as the low‐Earth orbit satellite sounding system, starting with the Suomi National Polar‐orbiting Partnership (S‐NPP) satellite and spanning the JPSS‐1 and JPSS‐2 satellites. This paper organizes the general paradigm for validation of atmospheric profile EDR retrieved from satellite nadir sounder systems (e.g., CrIMSS) as a synthesis of complementary methods and statistical assessment metrics. The validation methodology is ordered hierarchically to include global numerical model comparisons, satellite EDR intercomparisons, radiosonde matchup assessments (conventional, dedicated, and reference), and intensive campaign “dissections.” We develop and recommend the proper approach for computing profile statistics relative to correlative data derived from high‐resolution in situ data (viz., radiosondes) reduced to forward model layers. The standard statistical metrics used for EDR product assessments on “coarse layers” are defined along with an overview of water vapor weighting schemes and the use of averaging kernels. We then overview the application of the methodology to CrIMSS within the context of the JPSS calibration/validation program, with focus given to summarizing the core data sets to be used for validation of S‐NPP sounder EDR products.

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NOAA operational sounding products for advanced TOVS

Cited by 31 publications

References 48 publications

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

The CM SAF ATOVS data record: overview of methodology and evaluation of total column water and profiles of tropospheric humidity

Retrieval of atmospheric and surface parameters from VASS/FY-3C data under non-precipitation condition

Validation of satellite sounder environmental data records: Application to the Cross‐track Infrared Microwave Sounder Suite

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