Observations of Atmospheric Water Vapor and Precipitation: Observation Progress, Retrieval Challenges, and Their Correlations

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Meteorology".

Deadline for manuscript submissions: closed (31 October 2023) | Viewed by 2004

Special Issue Editors

State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China
Interests: water vapor; clouds; precipitation; atmospheric remote sensing; microwave remote sensing

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Guest Editor
National Satellite Meteorological Center, China Meteorological Administration, Beijing 100081, China
Interests: water vapor; precipitation; atmospheric remote sensing; ecological remote sensing
Institute of Remote Sensing and Geographical Information Systems, School of Earth and Space Sciences, Peking University, Beijing 100871, China
Interests: satellite remote sensing; infrared precipitation estimation; microwave precipitation retrieval; multi-precipitation merging; global change
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Guest Editor
Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan 430077, China
Interests: GNSS meteorology; climate change

Special Issue Information

Dear Colleagues,

Water vapor and precipitation are key parameters in the hydrological process and weather systems. In particular, extreme precipitation is usually correlated with atmospheric rivers or the deep convergence of water vapor. Moreover, increasing atmospheric water vapor under the warming climate is significantly increasing the probability of extreme precipitation. Motion vectors derived from high spatial and temporal resolution total column water vapor are also key parameters to extrapolate precipitation in the process of merging multi-satellite precipitation. The existence of rain drops and cloud particles under precipitation conditions will also bring great uncertainties to the retrieval of water vapor at microwave bands. Therefore, studying the interaction between water vapor and precipitation will be helpful to improve the accuracy of both water vapor and precipitation. However, satellite-based IR/PMW/Radar precipitation retrieving theories and techniques are still not very insufficient. Obtaining water vapor at high spatial and temporal resolution also faces great challenges under cloudy or precipitation conditions. To explore innovative avenues for more accurately monitoring the quick spatial–temporal variations in water vapor and precipitation and study the interaction between water vapor and precipitation under the warming climate, we encourage researchers to share their new methods of water vapor and precipitation observations based on various platforms and sensors, new datasets of water vapor and precipitation, new findings related to the change in water vapor and precipitation, and their correlations. Potential topics include but are not limited to:

  • New methods to retrieve total column water vapor or moisture profiles using various platforms;
  • New theories and techniques for satellite precipitation estimations and retrievals;
  • New multisource blended precipitation or water vapor datasets;
  • New data fusion methods for precipitation or water vapor under various sensors/platforms;
  • Error characteristic analysis on satellite precipitation products;
  • Radiative transfer model for precipitation and clouds;
  • The changing characteristics of water vapor and precipitation under the warming climate and their correlations.

Dr. Dabin Ji
Dr. Shihao Tang
Dr. Ziqiang Ma
Dr. Wei Li
Dr. Yingzhao Ma
Guest Editors

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Keywords

  • water vapor
  • precipitation
  • remote sensing
  • GNSS
  • radiative transfer model
  • data fusion
  • climate change

Published Papers (2 papers)

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Research

36 pages, 28783 KiB  
Article
Evaluation of Rain Estimates from Several Ground-Based Radar Networks and Satellite Products for Two Cases Observed over France in 2022
by Antoine Causse, Céline Planche, Emmanuel Buisson and Jean-Luc Baray
Atmosphere 2023, 14(12), 1726; https://doi.org/10.3390/atmos14121726 - 24 Nov 2023
Cited by 1 | Viewed by 984
Abstract
The recent development of satellite products for observing precipitation based on different technologies (microwaves, infrared, etc.) allows for near-real-time meteorological studies. The purpose of this article is to evaluate 11 satellite products (GHE, PDIR, IMERG-Early v6, IMERG-Late v6, CMORPH v0.x, CMORPH-RT v0.x, GSMaP-NRT [...] Read more.
The recent development of satellite products for observing precipitation based on different technologies (microwaves, infrared, etc.) allows for near-real-time meteorological studies. The purpose of this article is to evaluate 11 satellite products (GHE, PDIR, IMERG-Early v6, IMERG-Late v6, CMORPH v0.x, CMORPH-RT v0.x, GSMaP-NRT v7, GSMaP-NRT-GC v7, GSMaP-NOW v7, GSMaP-NOW-GC v7, and DATABOURG) currently available and compare them to 2 ground-based radar networks (PANTHERE and OPERA) and the French rain-gauge network RADOME. Two case studies of intense precipitation over France (22 to 25 April 2022 and 24 to 29 June 2022) were selected. The radar estimations are closer to the RADOME observations than the satellite-based estimations, which tend to globally underestimate the precipitation amounts over the areas of interest while OPERA tends to strongly overestimate precipitation amounts during the June case study. The PANTHERE radar product and the carrier-to-noise product DATABOURG shows promising results. Near-real-time satellite products tend to have closer precipitation amounts to the reference dataset than satellite products with a shorter latency. The use of these datasets for nowcasting developments is plausible but further analyses must be conducted beforehand. Full article
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13 pages, 2681 KiB  
Article
The Difference in Cloud Water Resources and Precipitation on the Eastern and Western Sides of the Liupan Mountains Caused by Topographic Effects
by Rui Xu and Yujun Qiu
Atmosphere 2023, 14(10), 1502; https://doi.org/10.3390/atmos14101502 - 28 Sep 2023
Cited by 1 | Viewed by 576
Abstract
In order to explore the possible impact of topography on precipitation between the eastern and western sides of the Liupan Mountains (LMs) in the northwest region of China, the differences in distribution characteristics of total column water vapor (TCWV), total column cloud water [...] Read more.
In order to explore the possible impact of topography on precipitation between the eastern and western sides of the Liupan Mountains (LMs) in the northwest region of China, the differences in distribution characteristics of total column water vapor (TCWV), total column cloud water (TCCW), and total precipitation (TP) were studied by using the 40-year hourly data of the fifth generation reanalysis (ERA5) from the European Centre for Medium-Range Weather Forecasts (ECMWF). The results showed the following: (1) The TCCW and TP on the eastern and western sides of the LMs decrease gradually from south to north, following a southwestward bias along the latitude. The high values of the TCCW and TP are predominantly concentrated in the period from July to September. The greatest difference between the two sides occurs in September, with the eastern side exhibiting 15% and 18% higher values compared to the western side, respectively. (2) Both the TCCW and TP exhibit distinct diurnal distribution patterns. The high values on the eastern side persist for a longer duration throughout the day compared to the western side, and they occur in more consecutive months. There is a certain correlation between the steepness of the eastern slope and the gentle gradient of the western slope. Additionally, the occurrence of these high values in the afternoon is earlier on the eastern side compared to the western side. (3) The monthly mean TP is significantly linearly correlated with the TCWV and TCCW, with slightly higher coefficients for the western side compared to the eastern side. This relationship is closely related to the topography of the mountain range. The regression equation provides a quantitative tool for predicting the monthly mean TP in the LM region and serves as a reference basis for the development of cloud water resources in the area. Full article
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