Housekeeping Telemetry Viewer (HKTV) for Microwave Humidity Sounder (MHS) on Metop

2018 ◽  
Author(s):  
Jakob Livschitz ◽  
Lars Fiedler
Keyword(s):  
Microwave Humidity Sounder

scholarly journals Retrieval of Layer Averaged Relative Humidity Profiles from MHS Observations over Tropical Region

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
R. K. Gangwar ◽  
B. S. Gohil ◽  
A. K. Mathur
Keyword(s):  
Relative Humidity ◽  
Radiative Transfer ◽  
Reanalysis Data ◽  
Tropical Region ◽  
Atmospheric Layer ◽  
Ncep Reanalysis ◽  
Microwave Humidity Sounder ◽  
Using Data ◽  
Profile Errors ◽  
Humidity Profiles

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.

scholarly journals Sensitivity of 89–190-GHz Microwave Observations to Ice Particle Scattering

2020 ◽  
Vol 59 (7) ◽  
pp. 1195-1215
Author(s):  
Ruiyao Chen ◽  
Ralf Bennartz
Keyword(s):  
Radar Reflectivity ◽  
Dual Frequency ◽  
Precipitation Radar ◽  
Brightness Temperatures ◽  
Precipitation Measurement ◽  
Microwave Humidity Sounder ◽  
Slant Path ◽  
The One ◽  
Global Precipitation Measurement ◽  
Global Precipitation

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.

scholarly journals Potential of Passive Microwave around 183 GHz for Snowfall Detection in the Arctic

2019 ◽  
Vol 11 (19) ◽  
pp. 2200 ◽  
Author(s):  
Léo Edel ◽  
Jean-François Rysman ◽  
Chantal Claud ◽  
Cyril Palerme ◽  
Christophe Genthon
Keyword(s):  
Detection Algorithm ◽  
The Arctic ◽  
Mountainous Areas ◽  
Phase Precipitation ◽  
Water Path ◽  
Brightness Temperatures ◽  
Microwave Humidity Sounder ◽  
Snow Water ◽  
Potential Use ◽  
Selection Of

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.

Effects Analysis of Mobile Phone’s Signal to Space-Borne Radiometer

2011 ◽  
Vol 467-469 ◽  
pp. 241-246
Author(s):  
Ying Zhu Huang ◽  
Sheng Wei Zhang ◽  
Yu Zhang ◽  
Jie Ying He
Keyword(s):  
Microwave Radiometer ◽  
Microwave Humidity Sounder ◽  
Meteorological Satellite ◽  
The Way

This paper investigates the mobile phone’s interference to the 183.31 GHz receivers of the MWHS (Microwave Humidity Sounder) in the FY-3 Meteorological Satellite by a set of related experiments, by which way finds the interfering path. And it analyses the influence of the mobile station’s interference to the orbiting Space-borne Microwave Radiometer in theory. The factors related to the jamming distance and their forces are analyzed. The way to prevent and resolve the interference is proposed and it has been proved by the experiment.

scholarly journals Can machine learning correct microwave humidity radiances for the influence of clouds?

2020 ◽  
Author(s):  
Inderpreet Kaur ◽  
Patrick Eriksson ◽  
Simon Pfreundschuh ◽  
David Ian Duncan
Keyword(s):  
Error Distribution ◽  
Channel Noise ◽  
Posterior Distributions ◽  
Limited Information ◽  
High Cloud ◽  
Clear Sky ◽  
Uncertainty Estimates ◽  
Microwave Humidity Sounder ◽  
Error Distributions ◽  
Scattering Index

Abstract. A methodology based on quantile regression neural networks (QRNN) is presented that identifies and corrects the cloud impact on microwave humidity sounder radiances at 183 GHz. This approach estimates the posterior distributions of noise free clear-sky (NFCS) radiances, providing nearly bias-free estimates of clear-sky radiances with a full posterior error distribution. It is first demonstrated by application to a present sensor, the MicroWave Humidity Sounder-2 (MWHS-2), then the applicability to sub-millimeter (sub-mm) sensors is also analysed. The QRNN results improve upon what operational cloud filtering techniques like a scattering index can achieve, but are ultimately imperfect due to limited information content on cirrus impact from traditional microwave channels – the negative departures associated with high cloud impact are successfully corrected, but thin cirrus clouds cannot be fully corrected. In contrast, when sub-mm observations are used, QRNN successfully corrects most cases with cloud impact, with only 2–6 % of the cases left partially corrected. The methodology works well even if only one sub-mm channel (325 GHz) is available. When using sub-mm observations, cloud correction usually results in error distributions with standard deviation less than typical channel noise values. Furthermore, QRNN outputs predicted quantiles for case-specific uncertainty estimates, successfully representing the uncertainty of cloud correction for each observation individually. In comparison to deterministic correction or filtering approaches, the corrected radiances and attendant uncertainty estimates have great potential to be used efficiently in assimilation systems due to being largely unbiased and adding little further uncertainty to the measurements.

scholarly journals Evaluation of the Simulation of Typhoon Lekima (2019) Based on Different Physical Parameterization Schemes and FY-3D Satellite’s MWHS-2 Data Assimilation

2021 ◽  
Vol 13 (22) ◽  
pp. 4556
Author(s):  
Dongmei Xu ◽  
Xuewei Zhang ◽  
Hong Li ◽  
Haiying Wu ◽  
Feifei Shen ◽  
...  
Keyword(s):  
Data Assimilation ◽  
Three Dimensional ◽  
Wrf Model ◽  
Background Field ◽  
Weather Research And Forecasting ◽  
Initial Field ◽  
Parameterization Schemes ◽  
Microwave Humidity Sounder ◽  
Radiance Data ◽  
Physical Parameterization

In this study, the case of super typhoon Lekima, which landed in Jiangsu and Zhejiang Province on 4 August 2019, is numerically simulated. Based on the Weather Research and Forecasting (WRF) model, the sensitivity experiments are carried out with different combinations of physical parameterization schemes. The results show that microphysical schemes have obvious impacts on the simulation of the typhoon’s track, while the intensity of the simulated typhoon is more sensitive to surface physical schemes. Based on the results of the typhoon’s track and intensity simulation, one parameterization scheme was further selected to provide the background field for the following data assimilation experiments. Using the three-dimensional variational (3DVar) data assimilation method, the Microwave Humidity Sounder-2 (MWHS-2) radiance data onboard the Fengyun-3D satellite (FY-3D) were assimilated for this case. It was found that the assimilation of the FY-3D MWHS-2 radiance data was able to optimize the initial field of the numerical model in terms of the model variables, especially for the humidity. Finally, by the inspection of the typhoon’s track and intensity forecast, it was found that the assimilation of FY-3D MWHS-2 radiance data improved the skill of the prediction for both the typhoon’s track and intensity.

Quantifying and Characterizing Striping of Microwave Humidity Sounder with Observation and Simulation

2021 ◽  
pp. 1-1
Author(s):  
John Xun Yang ◽  
Yalei You ◽  
William Blackwell ◽  
Sidharth Misra ◽  
Rachael A. Kroodsma
Keyword(s):  
Microwave Humidity Sounder
Sign in / Sign up

Export Citation Format

Share Document