Microwave sounding of earth covers at the frequencies near 118.75 GHz oxygen line

Author(s):  
L.I. Fedoseev ◽  
A.A. Shvetsov ◽  
D.V. Korotaev
Keyword(s):  
2018 ◽  
Vol 146 (12) ◽  
pp. 3949-3976 ◽  
Author(s):  
Herschel L. Mitchell ◽  
P. L. Houtekamer ◽  
Sylvain Heilliette

Abstract A column EnKF, based on the Canadian global EnKF and using the RTTOV radiative transfer (RT) model, is employed to investigate issues relating to the EnKF assimilation of Advanced Microwave Sounding Unit-A (AMSU-A) radiance measurements. Experiments are performed with large and small ensembles, with and without localization. Three different descriptions of background temperature error are considered: 1) using analytical vertical modes and hypothetical spectra, 2) using the vertical modes and spectrum of a covariance matrix obtained from the global EnKF after 2 weeks of cycling, and 3) using the vertical modes and spectrum of the static background error covariance matrix employed to initiate a global data assimilation cycle. It is found that the EnKF performs well in some of the experiments with background error description 1, and yields modest error reductions with background error description 3. However, the EnKF is virtually unable to reduce the background error (even when using a large ensemble) with background error description 2. To analyze these results, the different background error descriptions are viewed through the prism of the RT model by comparing the trace of the matrix , where is the RT model and is the background error covariance matrix. Indeed, this comparison is found to explain the difference in the results obtained, which relates to the degree to which deep modes are, or are not, present in the different background error covariances. The results suggest that, after 2 weeks of cycling, the global EnKF has virtually eliminated all background error structures that can be “seen” by the AMSU-A radiances.


2014 ◽  
Vol 31 (4) ◽  
pp. 808-825 ◽  
Author(s):  
Wenhui Wang ◽  
Cheng-Zhi Zou

Abstract The Advanced Microwave Sounding Unit-A (AMSU-A, 1998–present) not only continues but surpasses the Microwave Sounding Unit’s (MSU, 1978–2006) capability in atmospheric temperature observation. It provides valuable satellite measurements for higher vertical resolution and long-term climate change research and trend monitoring. This study presented methodologies for generating 11 channels of AMSU-A-only atmospheric temperature data records from the lower troposphere to the top of the stratosphere. The recalibrated AMSU-A level 1c radiances recently developed by the Center for Satellite Applications and Research group were used. The recalibrated radiances were adjusted to a consistent sensor incidence angle (nadir), channel frequencies (prelaunch-specified central frequencies), and observation time (local solar noon time). Radiative transfer simulations were used to correct the sensor incidence angle effect and the National Oceanic and Atmospheric Administration-15 (NOAA-15) channel 6 frequency shift. Multiyear averaged diurnal/semidiurnal anomaly climatologies from climate reanalysis as well as climate model simulations were used to adjust satellite observations to local solar noon time. Adjusted AMSU-A measurements from six satellites were carefully quality controlled and merged to generate 13+ years (1998–2011) of a monthly 2.5° × 2.5° gridded atmospheric temperature data record. Major trend features in the AMSU-A-only atmospheric temperature time series, including global mean temperature trends and spatial trend patterns, were summarized.


2009 ◽  
Vol 26 (8) ◽  
pp. 1493-1509 ◽  
Author(s):  
Carl A. Mears ◽  
Frank J. Wentz

Abstract Measurements made by microwave sounding instruments provide a multidecadal record of atmospheric temperature in several thick atmospheric layers. Satellite measurements began in late 1978 with the launch of the first Microwave Sounding Unit (MSU) and have continued to the present via the use of measurements from the follow-on series of instruments, the Advanced Microwave Sounding Unit (AMSU). The weighting function for MSU channel 2 is centered in the middle troposphere but contains significant weight in the lower stratosphere. To obtain an estimate of tropospheric temperature change that is free from stratospheric effects, a weighted average of MSU channel 2 measurements made at different local zenith angles is used to extrapolate the measurements toward the surface, which results in a measurement of changes in the lower troposphere. In this paper, a description is provided of methods that were used to extend the MSU method to the newer AMSU channel 5 measurements and to intercalibrate the results from the different types of satellites. Then, satellite measurements are compared to results from homogenized radiosonde datasets. The results are found to be in excellent agreement with the radiosonde results in the northern extratropics, where the majority of the radiosonde stations are located.


2015 ◽  
Vol 8 (10) ◽  
pp. 4025-4041 ◽  
Author(s):  
H.-J. Kang ◽  
J.-M. Yoo ◽  
M.-J. Jeong ◽  
Y.-I. Won

Abstract. Uncertainties in the satellite-derived surface skin temperature (SST) data in the polar oceans during two periods (16–24 April and 15–23 September) 2003–2014 were investigated and the three data sets were intercompared as follows: MODerate Resolution Imaging Spectroradiometer Ice Surface Temperature (MODIS IST), the SST of the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit-A (AIRS/AMSU), and AIRS only. The AIRS only algorithm was developed in preparation for the degradation of the AMSU-A. MODIS IST was systematically warmer up to 1.65 K at the sea ice boundary and colder down to −2.04 K in the polar sea ice regions of both the Arctic and Antarctic than that of the AIRS/AMSU. This difference in the results could have been caused by the surface classification method. The spatial correlation coefficient of the AIRS only to the AIRS/AMSU (0.992–0.999) method was greater than that of the MODIS IST to the AIRS/AMSU (0.968–0.994). The SST of the AIRS only compared to that of the AIRS/AMSU had a bias of 0.168 K with a RMSE of 0.590 K over the Northern Hemisphere high latitudes and a bias of −0.109 K with a RMSE of 0.852 K over the Southern Hemisphere high latitudes. There was a systematic disagreement between the AIRS retrievals at the boundary of the sea ice, because the AIRS only algorithm utilized a less accurate GCM forecast over the seasonally varying frozen oceans than the microwave data. The three data sets (MODIS, AIRS/AMSU and AIRS only) showed significant warming rates (2.3 ± 1.7 ~ 2.8 ± 1.9 K decade−1) in the northern high regions (70–80° N) as expected from the ice-albedo feedback. The systematic temperature disagreement associated with surface type classification had an impact on the resulting temperature trends.


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