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Remote Sensing
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Remote Sensing of Rainfall and Snowfall - Recent Advances
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Remote Sensing of Rainfall and Snowfall - Recent Advances

A special issue of Remote Sensing (ISSN 2072-4292).

Deadline for manuscript submissions: closed (21 October 2019) | Viewed by 11123

Special Issue Editors

Dr. Anoop Kumar Mishra

E-Mail Website
Guest Editor
Centre for Remote Sensing and Geoinformatics, Sathyabama Institute of Science and Technology, Chennai 600119, India
Interests: satellite remote sensing; climate change studies; Indian summer monsoon
Dr. Akhilesh Mishra

E-Mail Website
Guest Editor
1. Amity Centre for Atmospheric & Science Technology, Amity University Rajasthan, Jaipur 303002, India
2. The Florida State University’s Center for Ocean-Atmospheric Studies in Tallahassee, FL, USA
Interests: numerical modeling of weather and climate; season predictability and climate variability; satellite remote sensing
Dr. Satya Prakash

E-Mail Website
Guest Editor
Research Scientist, NOAA-CREST/NYCCT, City University of New York, New York, NY 11201, USA
Interests: remote sensing of precipitation; uncertainty estimation in precipitation estimates; South Asian monsoon rainfall; microwave land surface emissivity

Special Issue Information

Dear Colleagues,

Precipitation information at various temporal and spatial scales has numerous applications in hydrology, hydrometeorology, and climate change studies. Over vast regions of the globe, including ocean and land, however, reliable precipitation information from ground-based rain gauges and radar is available for very limited areas. Space-based measurement using remote sensing techniques offer the only realistic means for monitoring global precipitation and its variability. Precipitation measurement from satellite data is dependent on observations in infrared, visible, and microwave frequencies. Precipitation can also be monitored by integrating observations from these frequencies. Techniques have been developed to remove the errors in precipitation measurement. Over the past few decades, a number of advanced weather satellites have been launched to monitor global precipitation. Remote sensing techniques to monitor precipitation have been revolutionized with the launch of Tropical Rainfall Measuring Mission (TRMM), Megha-Tropiques, and Global Precipitation Measurement (GPM) missions. There have been advances in techniques to monitor precipitation with the launch of these satellites. Furthermore, advanced polarimetric radars have been installed to differentiate between precipitation types. Advanced techniques have been proposed to monitor precipitation precisely. In this context, this Special Issue has been proposed. Articles covering but not limited to recent research on the following topics are invited to this Special Issue:

  • Precipitation monitoring using IR/VIS/MW observations
  • Recent satellite missions and advances in sensors for precipitation measurements
  • Advances in precipitation measurement from radar/rain gauge observations
  • Improved precipitation over orographic regions
  • Variability of precipitation using remote sensing data
  • Nowcasting precipitation and flash flood studies using remote sensing observations

Dr. Anoop Kumar Mishra
Dr. Akhilesh Mishra
Dr. Satya Prakash
Guest Editors

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 submissions that pass pre-check are 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 2700 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.

Keywords

  • Satellite remote sensing
  • precipitation
  • radar meteorology
  • retrieval and validation

Published Papers (2 papers)

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28 pages, 23414 KiB  
Article
Development and Evaluation of a New “Snow Water Index (SWI)” for Accurate Snow Cover Delineation
by Abhilasha Dixit, Ajanta Goswami and Sanjay Jain
Remote Sens. 2019, 11(23), 2774; https://doi.org/10.3390/rs11232774 - 25 Nov 2019
Cited by 26 | Viewed by 6894
Abstract
The current study started by examining the three most established snow indices, namely the NDSI (normalized difference snow index), S3, and NDSII-1 (normalized difference snow and ice index), based on their capabilities to differentiate snow pixels from cloud, debris, vegetation, and water pixels. [...] Read more.
The current study started by examining the three most established snow indices, namely the NDSI (normalized difference snow index), S3, and NDSII-1 (normalized difference snow and ice index), based on their capabilities to differentiate snow pixels from cloud, debris, vegetation, and water pixels. Furthermore, considering the limitations of these indices, a new spectral index called the snow water index (SWI) is proposed. SWI uses spectral characteristics of the visible, SWIR (shortwave infrared), and NIR (near infrared) bands to achieve significant contrast between snow/ice pixels and other pixels including water bodies. A three-step accuracy assessment technique established the dominance of SWI over NDSI, S3, and NDSII-1. In the first step, image thresholding using standard value (>0), individual index theory (fixed threshold), histogram, and GCPs (ground control points) derived threshold were used to assess the performance of the selected indices. In the second step, comparisons of the spectral separation of features in the individual band were made from the field spectral observations collected using a spectroradiometer. In the third step, GCPs collected using field surveys were used to derive the user’s accuracy, producer’s accuracy, overall accuracy, and kappa coefficient for each index. The SWI threshold varied between 0.21 to 0.25 in all of the selected observations from both ablation and accumulation time. Spectral separability plots justify the SWI’s capability of extraction and removal of the most critical water pixels in integration with other impure classes from snow/ice pixels. GCP enabled accuracy assessment resulted in a maximum overall accuracy (0.93) and kappa statistics (0.947) value for the SWI. Thus, the results of the accuracy assessment justified the supremacy of the SWI over other indices. The study revealed that SWI demonstrates a considerably higher correlation with actual snow/ice cover and is prominent for spatio-temporal snow cover studies globally. Full article
(This article belongs to the Special Issue Remote Sensing of Rainfall and Snowfall - Recent Advances)
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8 pages, 1960 KiB  
Technical Note
Monitoring the Indian Summer Monsoon Evolution at the Granularity of the Indian Meteorological Sub-divisions using Remotely Sensed Rainfall Products
by Amit Bhardwaj and Vasubandhu Misra
Remote Sens. 2019, 11(9), 1080; https://doi.org/10.3390/rs11091080 - 7 May 2019
Cited by 6 | Viewed by 3205
Abstract
We make use of satellite-based rainfall products from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to objectively define local onset and demise of the Indian Summer Monsoon (ISM) at the spatial resolution of the meteorological subdivisions defined by the Indian [...] Read more.
We make use of satellite-based rainfall products from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) to objectively define local onset and demise of the Indian Summer Monsoon (ISM) at the spatial resolution of the meteorological subdivisions defined by the Indian Meteorological Department (IMD). These meteorological sub-divisions are the operational spatial scales for official forecasts issued by the IMD. Therefore, there is a direct practical utility to target these spatial scales for monitoring the evolution of the ISM. We find that the diagnosis of the climatological onset and demise dates and its variations from the TMPA product is quite similar to the rain gauge based analysis of the IMD, despite the differences in the duration of the two datasets. This study shows that the onset date variations of the ISM have a significant impact on the variations of the seasonal length and seasonal rainfall anomalies in many of the meteorological sub-divisions: for example, the early or later onset of the ISM is associated with longer and wetter or shorter and drier ISM seasons, respectively. It is shown that TMPA dataset (and therefore its follow up Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG)) could be usefully adopted for monitoring the onset of the ISM and therefore extend its use to anticipate the potential anomalies of the seasonal length and seasonal rainfall anomalies of the ISM in many of the Indian meteorological sub-divisions. Full article
(This article belongs to the Special Issue Remote Sensing of Rainfall and Snowfall - Recent Advances)
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