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Special Issue "Precipitation and Water Cycle Measurements using Remote Sensing"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing of the Water Cycle".

Deadline for manuscript submissions: 4 April 2020

Special Issue Editor

Guest Editor
Prof. Francisco J. Tapiador

Head of the Earth and Space Sciences (ess) Research Group, Dean of Enviromental Sciences and Biochemistry (2012-2019), University of Castilla-La Mancha (UCLM), Avda. Carlos III s/n, E-45071 Toledo, Spain
Website | E-Mail
Phone: (+34) 925 268 800 ext. 5762
Interests: precipitation; remote sensing; climate; social sciences

Special Issue Information

Dear Colleagues,

The Special Issue aims to publish remote sensing research on precipitation and the water cycle from a broad perspective, from tropical to polar research and from solid precipitation to humidity and microphysics. Local/regional studies, negative results (such as retrievals performing poorly when compared with observations), short papers and discussion/position papers are welcomed. Case studies and the analysis of single events/observations are also suitable for this Special Issue.

We invite papers on the following topics:

  • GPM studies.
  • Megha-Tropiques studies.
  • CloudSat studies.
  • FY studies.
  • TRMM studies.
  • Grace studies.
  • Passive microwave retrievals (SSMI/S, AMSU, AMSR, etc.)
  • ATBDs. This Special Issue is an opportunity to disseminate your algorithm theoretical basis description through an international journal.
  • IPWG activities.
  • Precipitation estimation using infrared and visible wavelengths.
  • Hydrological applications.
  • Precipitation estimation from microwave links.
  • Precipitation estimation from GPS measurements.
  • Satellite algorithms: description, case-studies, full validations.
  • Validation/verification of precipitation estimates from NWP models, RCMs, GCMs and ESMs.
  • Precipitation microphysics, including description, verification, comparison, and case studies.
  • Database descriptions.
  • Particle and drop size distribution (PSD, DSD) research.
  • Computing approaches (HPC, cloud, etc.) to improve the remote sensing of precipitation and the water cycle.
  • Uncertainties in the remote measurement of precipitation at ground (disdrometers, radars, etc.)
  • Instrumental biases affecting remote sensing measurements.
  • Spatial variability of precipitation, at any scale.
  • Beam filling issues.
  • Assimilation of satellite precipitation in numerical models.
  • Latent heat studies.
  • Precipitation in hurricanes.
  • Monsoons.
  • Validation of campaign results.
  • Precipitation from sounders.
  • New observational concepts (including geostationary sounders)
  • Projects results or preliminary advances (CMIP5/6, HyMEX, CORDEX, CLIVAR, etc.)
  • Satellite precipitation climatologies, from local to global.
  • Applications of precipitation (hydropower, insurance, agriculture, hazards, etc.)
  • Case studies focused on precipitation processes and/or uncertainties.
  • Precipitation estimates for biogeography.
  • Coupling of precipitation from observations and models with hydrological models.
  • Data fusion techniques (neural networks, etc.)
  • Precipitation trends and analysis of series.
  • Temporal variability of precipitation from satellites, including climate variability.
  • Precipitation in future climates as featured in models.

Prof. Francisco J. Tapiador
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.


  • Precipitation
  • Rainfall
  • Humidity
  • Ice
  • Hail
  • Hydrology

Published Papers (1 paper)

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Open AccessArticle
Evaluation of the Performance of SM2RAIN-Derived Rainfall Products over Brazil
Remote Sens. 2019, 11(9), 1113; https://doi.org/10.3390/rs11091113
Received: 30 March 2019 / Revised: 27 April 2019 / Accepted: 7 May 2019 / Published: 9 May 2019
PDF Full-text (14797 KB) | HTML Full-text | XML Full-text
Microwave-based satellite soil moisture products enable an innovative way of estimating rainfall using soil moisture observations with a bottom-up approach based on the inversion of the soil water balance Equation (SM2RAIN). In this work, the SM2RAIN-CCI (SM2RAIN-ASCAT) rainfall data obtained from the inversion [...] Read more.
Microwave-based satellite soil moisture products enable an innovative way of estimating rainfall using soil moisture observations with a bottom-up approach based on the inversion of the soil water balance Equation (SM2RAIN). In this work, the SM2RAIN-CCI (SM2RAIN-ASCAT) rainfall data obtained from the inversion of the microwave-based satellite soil moisture (SM) observations derived from the European Space Agency (ESA) Climate Change Initiative (CCI) (from the Advanced SCATterometer (ASCAT) soil moisture data) were evaluated against in situ rainfall observations under different bioclimatic conditions in Brazil. The research V7 version of the Tropical Rainfall Measurement Mission Multi-satellite Precipitation Analysis (TRMM TMPA) was also used as a state-of-the-art rainfall product with an up-bottom approach. Comparisons were made at daily and 0.25° scales, during the time-span of 2007–2015. The SM2RAIN-CCI, SM2RAIN-ASCAT, and TRMM TMPA products showed relatively good Pearson correlation values (R) with the gauge-based observations, mainly in the Caatinga (CAAT) and Cerrado (CER) biomes (R median > 0.55). SM2RAIN-ASCAT largely underestimated rainfall across the country, particularly over the CAAT and CER biomes (bias median < −16.05%), while SM2RAIN-CCI is characterized by providing rainfall estimates with only a slight bias (bias median: −0.20%), and TRMM TMPA tended to overestimate the amount of rainfall (bias median: 7.82%). All products exhibited the highest values of unbiased root mean square error (ubRMSE) in winter (DJF) when heavy rainfall events tend to occur more frequently, whereas the lowest values are observed in summer (JJA) with light rainfall events. The SM2RAIN-based products showed larger contribution of systematic error components than random error components, while the opposite was observed for TRMM TMPA. In general, both SM2RAIN-based rainfall products can be effectively used for some operational purposes on a daily scale, such as water resources management and agriculture, whether the bias is previously adjusted. Full article
(This article belongs to the Special Issue Precipitation and Water Cycle Measurements using Remote Sensing)

Graphical abstract

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