Scan asymmetries in AMSU‐B data

Buehler, Stefan; Kuvatov, M.; John, Viju O.

doi:10.1029/2005gl024747

Cited by 39 publications

(29 citation statements)

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“…Far from nadir, channels sounding deep into the troposphere, located on the wings of the 183.31 GHz line, might be more affected by antenna issues than higher peaking channels, located in the center of the line, due to radiation measured by the side lobes. Such asymmetries were found for AMSU-B and MHS (Buehler et al, 2005b;John et al, 2013b), but so far the monitoring of SAPHIR has not shown any scan asymmetry. For ATMS, comparisons of temperature data records (TDRs, calibrated antenna temperatures) and sensor data records (SDRs, BT after further applying beam efficiency and scan-position-dependent bias corrections) for the 183 GHz channels show the same behavior meaning that the TDR to SRD conversion is not responsible for the bias, although it seems to introduce some dependence on the viewing angle that warrants further investigation.…”

Section: Scan Asymmetrymentioning

confidence: 86%

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

et al. 2016

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Abstract. Several recent studies have observed systematic differences between measurements in the 183.31 GHz water vapor line by space-borne sounders and calculations using radiative transfer models, with inputs from either radiosondes (radiosonde observations, RAOBs) or short-range forecasts by numerical weather prediction (NWP) models. This paper discusses all the relevant categories of observation-based or model-based data, quantifies their uncertainties and separates biases that could be common to all causes from those attributable to a particular cause. Reference observations from radiosondes, Global Navigation Satellite System (GNSS) receivers, differential absorption lidar (DIAL) and Raman lidar are thus overviewed. Biases arising from their calibration procedures, NWP models and data assimilation, instrument biases and radiative transfer models (both the models themselves and the underlying spectroscopy) are presented and discussed. Although presently no single process in the comparisons seems capable of explaining the observed structure of bias, recommendations are made in order to better understand the causes.

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Section: Scan Asymmetrymentioning

confidence: 86%

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

et al. 2016

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“…Consequently, potential non-linear effects as a function of scene brightness temperature are not considered. It has also been shown that there might be scan asymmetry in the AMSU-B brightness temperatures (Buehler et al, 2005;John et al, 2013), which has not been accounted for here.…”

Section: Assumptions and Known Limitationsmentioning

confidence: 89%

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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“…These instrumental errors can severely degrade the quality of the retrieved IWP if not properly corrected. For example, there was a radio-frequency interference (RFI) problem in CH#3 and CH#4 of AMSU-B (Atkinson, 2001;Buehler et al, 2005), and gain variations/degredations are found in CH#3-CH#5 of AMSU-B on NOAA-16 and NOAA-17 (John et al, 2013). MHS exhibits smaller scandependent biases than AMSU-B, but suspicious behaviors have been reported for CH#3 on NOAA-18 and NOAA-19 and Metop-A (John et al, 2013).…”

Section: Description Of Data Sets and Modelsmentioning

confidence: 99%

CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances

Gong

2014

Atmos. Meas. Tech.

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Abstract. Ice water path (IWP) and cloud top height (h t ) are two of the key variables in determining cloud radiative and thermodynamical properties in climate models. Large uncertainty remains among IWP measurements from satellite sensors, in large part due to the assumptions made for cloud microphysics in these retrievals. In this study, we develop a fast algorithm to retrieve IWP from the 157, 183.3 ± 3 and 190.3 GHz radiances of the Microwave Humidity Sounder (MHS) such that the MHS cloud ice retrieval is consistent with CloudSat IWP measurements. This retrieval is obtained by constraining the empirical forward models between collocated and coincident measurements of CloudSat IWP and MHS cloud-induced radiance depression (T cir ) at these channels. The empirical forward model is represented by a lookup table (LUT) of T cir -IWP relationships as a function of h t and the frequency channel. With h t simultaneously retrieved, the IWP is found to be more accurate. The useful range of the MHS IWP retrieval is between 0.5 and 10 kg m −2 , and agrees well with CloudSat in terms of the normalized probability density function (PDF). Compared to the empirical model, current operational radiative transfer models (RTMs) still have significant uncertainties in characterizing the observed T cir -IWP relationships. Therefore, the empirical LUT method developed here remains an effective approach to retrieving ice cloud properties from the MHS-like microwave channels.

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Scan asymmetries in AMSU‐B data

Cited by 39 publications

References 5 publications

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

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

CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances

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Scan asymmetries in AMSU‐B data

Cited by 39 publications

References 5 publications

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

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

CloudSat-constrained cloud ice water path and cloud top height retrievals from MHS 157 and 183.3 GHz radiances

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A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz

A review of sources of systematic errors and uncertainties in observations and simulations at 183 GHz