scholarly journals A study of the NOAA near-nadir Microwave Humidity Sounder brightness temperatures over Antarctica

Author(s):  
Tsan Mo ◽  
Yong Han ◽  
Fuzhong Weng
2020 ◽  
Vol 59 (7) ◽  
pp. 1195-1215
Author(s):  
Ruiyao Chen ◽  
Ralf Bennartz

AbstractThe sensitivity of microwave brightness temperatures (TBs) to hydrometeors at frequencies between 89 and 190 GHz is investigated by comparing Fengyun-3C (FY-3C) Microwave Humidity Sounder-2 (MWHS-2) measurements with radar reflectivity profiles and retrieved products from the Global Precipitation Measurement mission’s Dual-Frequency Precipitation Radar (DPR). Scattering-induced TB depressions (ΔTBs), calculated by subtracting simulated cloud-free TBs from bias-corrected observed TBs for each channel, are compared with DPR-retrieved hydrometeor water path (HWP) and vertically integrated radar reflectivity ZINT. We also account for the number of hydrometeors actually visible in each MWHS-2 channel by weighting HWP with the channel’s cloud-free gas transmission profile and the observation slant path. We denote these transmission-weighted, slant-path-integrated quantities with a superscript asterisk (e.g., HWP*). The so-derived linear sensitivity of ΔTB with respect to HWP* increases with frequency roughly to the power of 1.78. A retrieved HWP* of 1 kg m−2 at 89 GHz on average corresponds to a decrease in observed TB, relative to a cloud-free background, of 11 K. At 183 GHz, the decrease is about 34–53 K. We perform a similar analysis using the vertically integrated, transmission-weighted slant-path radar reflectivity and find that ΔTB also decreases approximately linearly with . The exponent of 0.58 corresponds to the one we find in the purely DPR-retrieval-based ZINT–HWP relation. The observed sensitivities of ΔTB with respect to and HWP* allow for the validation of hydrometeor scattering models.


2019 ◽  
Vol 11 (19) ◽  
pp. 2200 ◽  
Author(s):  
Léo Edel ◽  
Jean-François Rysman ◽  
Chantal Claud ◽  
Cyril Palerme ◽  
Christophe Genthon

This study evaluates the potential use of the Microwave Humidity Sounder (MHS) for snowfall detection in the Arctic. Using two years of colocated MHS and CloudSat observations, we develop an algorithm that is able to detect up to 90% of the most intense snowfall events (snow water path ≥400 g m−2 and 50% of the weak snowfall rate events (snow water path ≤50 g m−2. The brightness temperatures at 190.3 GHz and 183.3 ± 3 GHz, the integrated water vapor, and the temperature at 2 m are identified as the most important variables for snowfall detection. The algorithm tends to underestimate the snowfall occurrence over Greenland and mountainous areas (by as much as −30%), likely due to the dryness of these areas, and to overestimate the snowfall occurrence over the northern part of the Atlantic (by up to 30%), likely due to the occurrence of mixed phase precipitation. An interpretation of the selection of the variables and their importance provides a better understanding of the snowfall detection algorithm. This work lays the foundation for the development of a snowfall rate quantification algorithm.


2019 ◽  
Vol 2019 ◽  
pp. 1-8 ◽  
Author(s):  
Martin J. Burgdorf ◽  
Stefan A. Buehler ◽  
Imke Hans ◽  
Marc Prange

Measurements of the disk-integrated brightness temperature of the Moon at 89, 157, 183, and 190 GHz are presented for phase angles between -80° and 50° relative to full Moon. They were obtained with the Microwave Humidity Sounder (MHS) on NOAA-18 from 39 instances when the Moon appeared in the deep space view of the instrument. Polynomials were fitted to the measured values and the maximum temperature and the phase angle of its occurrence were determined. A comparison of these results with the predictions from three different models or rather parametrical expressions by Keihm, Mo & Kigawa, and Yang et al. revealed significantly larger phase lags for the lower frequencies in the measurements with MHS. As the Moon has appeared thousands of times in the field of view of all microwave sounders combined, this investigation demonstrates the potential of weather satellites for fine tuning models and establishing the Moon as extremely accurate calibration reference.


2005 ◽  
Vol 22 (7) ◽  
pp. 909-929 ◽  
Author(s):  
Hirohiko Masunaga ◽  
Christian D. Kummerow

Abstract A methodology to analyze precipitation profiles using the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) and precipitation radar (PR) is proposed. Rainfall profiles are retrieved from PR measurements, defined as the best-fit solution selected from precalculated profiles by cloud-resolving models (CRMs), under explicitly defined assumptions of drop size distribution (DSD) and ice hydrometeor models. The PR path-integrated attenuation (PIA), where available, is further used to adjust DSD in a manner that is similar to the PR operational algorithm. Combined with the TMI-retrieved nonraining geophysical parameters, the three-dimensional structure of the geophysical parameters is obtained across the satellite-observed domains. Microwave brightness temperatures are then computed for a comparison with TMI observations to examine if the radar-retrieved rainfall is consistent in the radiometric measurement space. The inconsistency in microwave brightness temperatures is reduced by iterating the retrieval procedure with updated assumptions of the DSD and ice-density models. The proposed methodology is expected to refine the a priori rain profile database and error models for use by parametric passive microwave algorithms, aimed at the Global Precipitation Measurement (GPM) mission, as well as a future TRMM algorithms.


2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
R. K. Gangwar ◽  
B. S. Gohil ◽  
A. K. Mathur

The present paper deals with the retrieval of the atmospheric layer averaged relative humidity profiles using data from the Microwave Humidity Sounder (MHS) onboard the MetOp satellite. The retrieval has been innovatively performed by firstly retrieving humidity for pairs of thick overlapping layers (TOLs) used subsequently to derive humidity for associated thin isolated layer (TIL). A water vapour dependent (WVD) algorithm has been developed and applied to infer the humidity of TOLs. Thus, the retrieved profiles have been finally compared with standard algorithm (NORM). These algorithms have been developed based on radiative transfer simulations and study of sensitivities of MHS channels on humidity of various types of layers (TOL, TIL). The algorithm has been tested with MHS data and validated using concurrent radiosonde as well as NCEP reanalysis data indicating profile errors of ~15% and ~19%, respectively.


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