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Special Issue "Retrieval of Cloud and Precipitation by Ground-Based Radar and In Situ Observations: Application to Atmospheric and Volcanic Ash Clouds"

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

Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 8590

Special Issue Editors

Dr. Mario Montopoli
E-Mail Website
Guest Editor
National Research Council of Italy - Institute of Atmospheric Sciences and Climate (CNR - ISAC), 00133 Rome, Italy
Interests: radar remote sensing; Doppler analysis and wind reconstruction; solid precipitation
Special Issues, Collections and Topics in MDPI journals
Dr. Gianfranco Vulpiani
E-Mail Website
Guest Editor
Civil Protection Department, The Council of Ministers, 00193 Rome, Italy
Interests: operational QPE; deep convection; neural networks; data fusion
Special Issues, Collections and Topics in MDPI journals
Dr. Elisa Adirosi
E-Mail Website
Guest Editor
National Research Council of Italy - Institute of Atmospheric Sciences and Climate (CNR - ISAC)
Interests: ground validation studies of precipitation; disdrometers and particle size distributions; retrieval techniques from radar and in situ devices
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Remote Sensing dedicates this Special Issue to the ground-based techniques for the estimation of cloud and precipitation parameters. Precipitation is a key element in the water cycle, which is essential for delivering and sustaining the supplies of freshwater. Climate change is modifying the frequency and intensity of severe precipitation events and this has a critical impact on hydrogeological and hydraulic risk management. The increase of urbanization has exacerbated such risks with profound socio-economic and civil protection implications. Clouds play an important role in the planet’s energy budget thanks to their great influence on the solar and infrared radiation that flows through the atmosphere. The mechanisms of energy balance variations are complex and not entirely understood and they potentially have a role in the climate modifications. For these reasons, it is essential to have information about the distribution and variability of the clouds and precipitation properties all over the Earth on a long-term basis.

In this respect ground-based networks (e.g., weather radars, cloud profiling radars) and in situ devices (e.g., rain/snow gauges, distrometers, cameras) tailored for observing clouds and precipitation play a great role

  • in enhancing the quality and reliability of ground-based derived products to improve early warning tools;
  • in determining the variability of precipitation characteristics on different time and space scales;
  • in developing validation studies of current and new space programs for precipitation estimation worldwide.

Clouds are not just the result of atmospheric processes, but they can be originated by volcanic emissions. Volcanic emissions can have a great impact on climate and represent a hazard for air traffic and civil protection risk management. Contributions that include ground-based radar and in situ observations of volcanic clouds are also welcome.

This Special Issue has the ambition to collect multidisciplinary initiatives in the fields of heterogeneous clouds and precipitation using ground-based sensors. A non-exhaustive list of potential thematic tracks could be: rain/solid precipitation microphysical parameter estimation, severe storm processes analysis and nowcasting, satellite and ground based multi-sensors data fusion, data assimilation, radar and in situ networking at regional, national and continental level, urban scale monitoring and early warning tools, winter storms, description of ground-based climate records and observatories, algorithm innovations, validation studies, volcanic clouds observations from ground based sensors.

Dr. Mario Montopoli
Dr. Gianfranco Vulpiani
Dr. Elisa Adirosi
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 2500 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 vs. Ground validation studies
  • Severe storms analysis, interpretation and nowcasting
  • liquid/solid precipitation microphysical parameter estimation
  • Quantitative precipitation estimation
  • Early warning tools
  • Volcanic clouds observations
  • Data Quality
  • Data assimilation
  • Data fusion
  • Climate records
  • Urban scale monitoring
  • Sensor networking
  • AI and multi-sensor big data approaches

Published Papers (4 papers)

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Research

Article
Quantitative Precipitation Estimation over Antarctica Using Different Ze-SR Relationships Based on Snowfall Classification Combining Ground Observations
Remote Sens. 2022, 14(1), 82; https://doi.org/10.3390/rs14010082 - 24 Dec 2021
Cited by 6 | Viewed by 3176
Abstract
Snow plays a crucial role in the hydrological cycle and energy budget of the Earth, and remote sensing instruments with the necessary spatial coverage, resolution, and temporal sampling are essential for snowfall monitoring. Among such instruments, ground-radars have scanning capability and a resolution [...] Read more.
Snow plays a crucial role in the hydrological cycle and energy budget of the Earth, and remote sensing instruments with the necessary spatial coverage, resolution, and temporal sampling are essential for snowfall monitoring. Among such instruments, ground-radars have scanning capability and a resolution that make it possible to obtain a 3D structure of precipitating systems or vertical profiles when used in profiling mode. Radars from space have a lower spatial resolution, but they provide a global view. However, radar-based quantitative estimates of solid precipitation are still a challenge due to the variability of the microphysical, geometrical, and electrical features of snow particles. Estimations of snowfall rate are usually accomplished using empirical, long-term relationships between the equivalent radar reflectivity factor (Ze) and the liquid-equivalent snowfall rate (SR). Nevertheless, very few relationships take advantage of the direct estimation of the microphysical characteristics of snowflakes. In this work, we used a K-band vertically pointing radar collocated with a laser disdrometer to develop Ze-SR relationships as a function of snow classification. The two instruments were located at the Italian Antarctic Station Mario Zucchelli. The K-band radar probes the low-level atmospheric layers, recording power spectra at 32 vertical range gates. It was set at a high vertical resolution (35 m), with the first trusted range gate at a height of only 100 m. The disdrometer was able to provide information on the particle size distribution just below the trusted radar gate. Snow particles were classified into six categories (aggregate, dendrite aggregate, plate aggregate, pristine, dendrite pristine, plate pristine). The method was applied to the snowfall events of the Antarctic summer seasons of 2018–2019 and 2019–2020, with a total of 23,566 min of precipitation, 15.3% of which was recognized as showing aggregate features, 33.3% dendrite aggregate, 7.3% plates aggregate, 12.5% pristine, 24% dendrite pristine, and 7.6% plate pristine. Applying the appropriate Ze-SR relationship in each snow category, we calculated a total of 87 mm water equivalent, differing from the total found by applying a unique Ze-SR. Our estimates were also benchmarked against a colocated Alter-shielded weighing gauge, resulting in a difference of 3% in the analyzed periods. Full article
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Article
Effects of Variable Eruption Source Parameters on Volcanic Plume Transport: Example of the 23 November 2013 Paroxysm of Etna
Remote Sens. 2021, 13(20), 4037; https://doi.org/10.3390/rs13204037 - 09 Oct 2021
Cited by 2 | Viewed by 1111
Abstract
The purpose of the present paper is to investigate the effects of variable eruption source parameters on volcanic plume transport in the Mediterranean basin after the paroxysm of Mount Etna on 23 November 2013. This paroxysm was characterized by a north-east transport of [...] Read more.
The purpose of the present paper is to investigate the effects of variable eruption source parameters on volcanic plume transport in the Mediterranean basin after the paroxysm of Mount Etna on 23 November 2013. This paroxysm was characterized by a north-east transport of ash and gas, caused by a low-pressure system in northern Italy. It is evaluated here in a joint approach considering the WRF-Chem model configured with eruption source parameters (ESPs) obtained elaborating the raw data from the VOLDORAD-2B (V2B) Doppler radar system. This allows the inclusion of the transient and fluctuating nature of the volcanic emissions to accurately model the atmospheric dispersion of ash and gas. Two model configurations were considered: the first with the climax values for the ESP and the second with the time-varying ESP according to the time profiles of the mass eruption rate recorded by the V2B radar. It is demonstrated that the second configuration produces a considerably better comparison with satellite retrievals from different sensors platforms (Ozone Mapping and Profiler Suite, Meteosat Second-Generation Spinning Enhanced Visible and Infrared Imager, and Visible Infrared Imaging Radiometer Suite). In the context of volcanic ash transport dispersion modeling, our results indicate the need for (i) the use of time-varying ESP, and (ii) a joint approach between an online coupled chemical transport model like WRF-Chem and direct near-source measurements, such as those carried out by the V2B Doppler radar system. Full article
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Article
Influence of Wind-Induced Effects on Laser Disdrometer Measurements: Analysis and Compensation Strategies
Remote Sens. 2021, 13(15), 3028; https://doi.org/10.3390/rs13153028 - 02 Aug 2021
Cited by 6 | Viewed by 1316
Abstract
Nowadays, laser disdrometers constitute a very appealing tool for measuring surface precipitation properties, by virtue of their capability to estimate not only the rainfall amount and intensity, but also the number, the size and the velocity of falling drops. However, disdrometric measures are [...] Read more.
Nowadays, laser disdrometers constitute a very appealing tool for measuring surface precipitation properties, by virtue of their capability to estimate not only the rainfall amount and intensity, but also the number, the size and the velocity of falling drops. However, disdrometric measures are affected by various sources of error being some of them related to environmental conditions. This work presents an assessment of Thies Clima laser disdrometer performance with a focus on the relationship between wind and the accuracy of the disdrometer output products. The 10-min average rainfall rate and total rainfall accumulation obtained by the disdrometer are systematically compared with the collocated measures of a standard tipping bucket rain gauge, the FAK010AA sensor, in terms of familiar statistical scores. A total of 42 rainy events, collected in a mountainous site of Southern Italy (Montevergine observatory), are used to support our analysis. The results show that the introduction of a new adaptive filtering in the disdrometric data processing can reduce the impact of sampling errors due to strong winds and heavy rain conditions. From a quantitative perspective, the novel filtering procedure improves by 8% the precipitation estimates with respect to the standard approach widely used in the literature. A deeper examination revealed that the signature of wind speed on raw velocity-diameter spectrographs gradually emerges with the rise of wind strength, thus causing a progressive increase of the wrongly allocated hydrometeors (which reaches 70% for wind speed greater than 8 m s−1). With the aid of reference rain-gauge rainfall data, we designed a second simple methodology that makes use of a correction factor to mitigate the wind-induced bias in disdrometric rainfall estimates. The resulting correction factor could be applied as an alternative to the adaptive filtering suggested by this study and may be of practical use when dealing with disdrometric data processing. Full article
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Article
Validation of GPM Rainfall and Drop Size Distribution Products through Disdrometers in Italy
Remote Sens. 2021, 13(11), 2081; https://doi.org/10.3390/rs13112081 - 25 May 2021
Cited by 10 | Viewed by 1892
Abstract
The high relevance of satellites for collecting information regarding precipitation at global scale implies the need of a continuous validation of satellite products to ensure good data quality over time and to provide feedback for updating and improving retrieval algorithms. However, validating satellite [...] Read more.
The high relevance of satellites for collecting information regarding precipitation at global scale implies the need of a continuous validation of satellite products to ensure good data quality over time and to provide feedback for updating and improving retrieval algorithms. However, validating satellite products using measurements collected by sensors at ground is still a challenging task. To date, the Dual-frequency Precipitation Radar (DPR) aboard the Core Satellite of the Global Precipitation Measurement (GPM) mission is the only active sensor able to provide, at global scale, vertical profiles of rainfall rate, radar reflectivity, and Drop Size Distribution (DSD) parameters from space. In this study, we compare near surface GPM retrievals with long time series of measurements collected by seven laser disdrometers in Italy since the launch of the GPM mission. The comparison shows limited differences in the performances of the different GPM algorithms, be they dual- or single-frequency, although in most cases, the dual-frequency algorithms present the better performances. Furthermore, the agreement between satellite and ground-based estimates depends on the considered precipitation variable. The agreement is very promising for rain rate, reflectivity factor, and the mass-weighted mean diameter (Dm), while the satellite retrievals need to be improved for the normalized gamma DSD intercept parameter (Nw). Full article
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