Upper tropospheric humidity and wind fields observed with the METEOSAT water vapor channel

1994 ◽  
Author(s):  
Leopold Van de Berg ◽  
John Whitlock ◽  
Carlos Geijo ◽  
Johannes Schmetz
Keyword(s):  
Water Vapor ◽  
Wind Fields ◽  
Vapor Channel ◽  
Upper Tropospheric Humidity

scholarly journals Water vapor transport in the lower mesosphere of the subtropics: a trajectory analysis

2008 ◽  
Vol 8 (23) ◽  
pp. 7273-7280 ◽  
Author(s):  
T. Flury ◽  
S. C. Müller ◽  
K. Hocke ◽  
N. Kämpfer
Keyword(s):  
Water Vapor ◽  
Trajectory Analysis ◽  
Microwave Radiometer ◽  
Rotational Transition ◽  
Transport Processes ◽  
Water Vapor Transport ◽  
Transition Line ◽  
Wind Fields ◽  
Large Variability ◽  
Northern India

Abstract. The Institute of Applied Physics operates an airborne microwave radiometer AMSOS that measures the rotational transition line of water vapor at 183.3 GHz. Water vapor profiles are retrieved for the altitude range from 15 to 75 km along the flight track. We report on a water vapor enhancement in the lower mesosphere above India and the Arabian Sea. The measurements took place on our flight from Switzerland to Australia and back in November 2005 conducted during EC- project SCOUT-O3. We find an enhancement of up to 25% in the lower mesospheric H2O volume mixing ratio measured on the return flight one week after the outward flight. The origin of the air is traced back by means of a trajectory model in the lower mesosphere and wind fields from ECMWF. During the outward flight the air came from the Atlantic Ocean around 25 N and 40 W. On the return flight the air came from northern India and Nepal around 25 N and 90 E. Mesospheric H2O measurements from Aura/MLS confirm the transport processes of H2O derived by trajectory analysis of the AMSOS data. Thus the large variability of H2O VMR during our flight is explained by a change of the winds in the lower mesosphere. This study shows that trajectory analysis can be applied in the mesosphere and is a powerful tool to understand the large variability in mesospheric H2O.

scholarly journals Relationships between Low-Level Jet and Low Visibility Associated with Precipitation, Air Pollution, and Fog in Tianjin

Atmosphere ◽  
2020 ◽  
Vol 11 (11) ◽  
pp. 1197
Author(s):  
Tingting Ju ◽  
Bingui Wu ◽  
Zhaoyu Wang ◽  
Jingle Liu ◽  
Dehua Chen ◽  
...  
Keyword(s):  
Air Pollution ◽  
Water Vapor ◽  
Air Masses ◽  
Low Level ◽  
Vapor Channel ◽  
Low Visibility ◽  
Low Level Jet ◽  
Industrial Regions ◽  
Statistical Results ◽  
Pm2.5 Concentration

In this study, relationships between low-level jet (LLJ) and low visibility associated with precipitation, air pollution, and fog in Tianjin are investigated based on observational data from January to December, 2016. Statistical results show 55% of precipitation is accompanied by LLJ, and two causes responsible for the relatively high percentage are presented. The result of case analysis shows that some southwesterly LLJs are favorable for the formation of precipitation by transporting water vapor when the water vapor channel from the South China Sea or Bengal Bay to Bohai Rim region is established. Statistical results show 55% of pollution episodes (PEs) are accompanied by LLJs. When pollutions are observed in the southern industrial regions, nocturnal southwesterly LLJ, which can carry polluted air masses from polluted regions to Tianjin and induce turbulent mixing, can enhance surface PM2.5 concentration and is favorable for the formation of surface pollution at night. Nocturnal northerly or southeasterly LLJ leads to clear air masses mixing with polluted air masses and is favorable for increasing visibility. Contributions of southwesterly LLJs to the formation of fog and precipitation are similar, which both rely on establishing the water vapor channel despite occurrence heights of LLJs being different.

scholarly journals Diffuse sunlight based calibration of the water vapor channel in the upc raman lidar

2018 ◽  
Vol 176 ◽  
pp. 05035
Author(s):  
Constantino Muñoz-Porcar ◽  
Adolfo Comeron ◽  
Michaël Sicard ◽  
Ruben Barragan ◽  
David Garcia-Vizcaino ◽  
...  
Keyword(s):  
Water Vapor ◽  
Raman Scattering ◽  
Calibration Factor ◽  
Raman Lidar ◽  
Lidar System ◽  
System Parameters ◽  
Vapor Channel ◽  
Technical University

A method for determining the calibration factor of the water vapor channel of a Raman lidar, based on zenith measurements of diffuse sunlight and on assumptions regarding some system parameters and Raman scattering models, has been applied to the lidar system of Universitat Politècnica de Catalunya (UPC; Technical University of Catalonia, Spain). Results will be analyzed in terms of stability and comparison with typical methods relying on simultaneous radiosonde measurements.

scholarly journals Evaluation of operational INSAT-3D UTH product, using Radiosonde, Meteosat-7 and NCEP Analysis

2014 ◽  
Vol XL-8 ◽  
pp. 247-252 ◽  
Author(s):  
I. Dey ◽  
M. V. Shukla ◽  
P. K. Thapliyal ◽  
C. M. Kishtawal
Keyword(s):  
Linear Correlation ◽  
Reasonable Agreement ◽  
Regression Line ◽  
Correlation Coefficients ◽  
Good Match ◽  
Satellite Measurements ◽  
Vapor Channel ◽  
Upper Tropospheric Humidity ◽  
Humidity Profiles

Recently available satellite observations from the water vapor channel (6.5–7.1 μm) of the Imager on-board India's geostationary satellite, INSAT-3D have been used to estimate Upper Tropospheric Humidity (UTH). In this study, operationally retrieved UTH product has been compared and validated for the period of Jan–Jun, 2014, using in-situ and satellite measurements. In-situ measurements of UTH have been indirectly derived using humidity profiles obtained from a network of radiosonde stations from NOAA/ESRL database. Meteosat-7 UTH products have been used as satellite measurements. The validation of INSAT-3D UTH against UTH derived from radiosonde profiles shows reasonable agreement, with linear correlation coefficients ranging from 0.78 to 0.87 and the slope of the regression line ranging from 0.52 to 0.77. The UTH tends to overestimate observed humidity by ~4 % with RMS difference of ~12 %. Comparison of INSAT-3D UTH product with Meteosat-7 UTH product suggests a good match with RMS difference of 7.61% and a mean bias of −0.43 %, linear correlation coefficients varying from 0.88 to 0.93 and slope of the regression line varying from 0.64 to 1.08. The UTH products from INSAT-3D and Meteosat-7 have also been inter-compared by validating the two against the UTH derived from a set of collocated radiosonde observations. INSAT-3D UTH shows a RMSD of 10.65 % and bias of 0.78 % which matches very well with Meteosat-7 UTH with a RMSD of 10.31 % and bias of −0.53 %.

scholarly journals Correction: Tabata, T., et al. Recalibration of over 35 Years of Infrared and Water Vapor Channel Radiances of the JMA Geostationary Satellites. Remote Sens. 2019, 11, 1189

2020 ◽  
Vol 12 (5) ◽  
pp. 861
Author(s):  
Tasuku Tabata ◽  
Viju O. John ◽  
Rob A. Roebeling ◽  
Tim Hewison ◽  
Jörg Schulz
Keyword(s):  
Water Vapor ◽  
Vapor Channel ◽  
Geostationary Satellites

The authors wish to make the following corrections to this paper [...]

Calibration of Meteosat water vapor channel observations with independent satellite observations

2001 ◽  
Vol 106 (D6) ◽  
pp. 5199-5209 ◽  
Author(s):  
Stephen A. Tjemkes ◽  
Marianne König ◽  
Hans-Joachim Lutz ◽  
Leo van de Berg ◽  
Johannes Schmetz
Keyword(s):  
Water Vapor ◽  
Satellite Observations ◽  
Vapor Channel

scholarly journals Retrieval of upper tropospheric water vapor and upper tropospheric humidity from AMSU radiances

2005 ◽  
Vol 5 (8) ◽  
pp. 2019-2028 ◽  
Author(s):  
A. Houshangpour ◽  
V. O. John ◽  
S. A. Buehler
Keyword(s):  
Water Vapor ◽  
Synthetic Data ◽  
Weighted Average ◽  
Radiosonde Data ◽  
Atmospheric Conditions ◽  
Data Set ◽  
Microwave Sounding Unit ◽  
Upper Tropospheric Humidity ◽  
Microwave Sounding ◽  
Average Relative Humidity

Abstract. A regression method was developed to retrieve upper tropospheric water vapor (UTWV in kg/m2) and upper tropospheric humidity (UTH in % RH) from radiances measured by the Advanced Microwave Sounding Unit (AMSU). In contrast to other UTH retrieval methods, UTH is defined as the average relative humidity between 500 and 200hPa, not as a Jacobian weighted average, which has the advantage that the UTH altitude does not depend on the atmospheric conditions. The method uses AMSU channels 6-10, 18, and 19, and should achieve an accuracy of 0.48 kg/m2 for UTWV and 6.3% RH for UTH, according to a test against an independent synthetic data set. This performance was confirmed for northern mid-latitudes by a comparison against radiosonde data from station Lindenberg in Germany, which yielded errors of 0.23 kg/m2 for UTWV and 6.1% RH for UTH.

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