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Precipitation Measurement Instruments: Calibration, Accuracy and Performance

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A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (15 April 2021) | Viewed by 18529

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Special Issue Editor

Prof. Dr. Luca Giovanni Lanza

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Guest Editor

Department of Civil, Chemical and Environmental Engineering (DICCA), University of Genova, 1 Montallegro, 16145 Genova GE, Italy
Interests: hydrology; precipitation; measurement; green roofs; nature-based solutions; sustainable urban drainage
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Precipitation is one of the most challenging among environmental measurements, since accurate determination of the amount of water that would ultimately land on a well-defined portion of the ground surface in undisturbed conditions is a difficult task. This is the aim of so-called in situ measurements at the ground, with the instrument located precisely where the information is sought, therefore at one single location, immersed in the precipitation process. In situ precipitation gauges provide the only direct measurements of precipitation at the ground and are usually referred to as the “ground truth” in precipitation monitoring.

Many types of instruments and measurement techniques are developed and in operational use. Most of these techniques are well described and understood, but new instruments are appearing (especially noncatching instruments), which still need deeper testing and investigation. All instruments are subject to both systematic (bias) and random measurement errors, depending on the construction of the device, the measuring principle, the algorithms used for data interpretation and correction, installation issues, environmental factors, etc.

This Special Issue will focus on the science of precipitation measurements, the measuring principles, new or improved technologies, the assessment of measurement accuracy and performance and the uncertainty budget, calibration methods and laboratory testing, comparison of instruments, and field measurement campaigns. Review papers on the state-of-the-art as well as new research and innovative studies are encouraged.

Prof. Luca G. Lanza
Guest Editor

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Keywords

atmospheric precipitation measurements
measuring principles
technology
intercomparison
measurement accuracy
calibration
uncertainty

Published Papers (7 papers)

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Editorial

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5 pages, 174 KiB

Open AccessEditorial

Precipitation Measurement Instruments: Calibration, Accuracy and Performance

by Luca G. Lanza and Arianna Cauteruccio

Water 2022, 14(5), 811; https://0-doi-org.brum.beds.ac.uk/10.3390/w14050811 - 04 Mar 2022

Cited by 1 | Viewed by 2045

Abstract

Though ranking high among the relevant environmental variables (due to the well-known significant interactions with the everyday human life and economic activities), atmospheric precipitation is not yet measured operationally with neither the degree of accuracy that would meet the most demanding applications nor [...] Read more.

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

Research

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13 pages, 2813 KiB

Open AccessArticle

Differences in the Ice Particle Shattering Impact on the CIP Measurements in the Stratiform Cloud Region and the Embedded Convection Region

by Minsong Huang

Water 2021, 13(17), 2322; https://0-doi-org.brum.beds.ac.uk/10.3390/w13172322 - 25 Aug 2021

Cited by 2 | Viewed by 1575

Abstract

Stratiform clouds with embedded convective cells is an important precipitation system. Precise knowledge of the cloud’s microphysical structure can be useful for the development of a numerical weather prediction model and precipitation enhancement. Airborne measurement is one of the important ways for determining the microphysical structure of clouds. However, cloud particle shattering during measurement poses a serious problem to the measured microphysical characterization of clouds. In order to study the different influences of the shattered ice particles on the standard cloud imaging probe (CIP) measurement in the stratiform cloud region and the convective cloud region, a time-variant threshold method to identify the shattered fragments is presented. After application of this algorithm, the shattered fragments were recognized and their impacts on the particle size distribution (PSD), particle number concentration and ice water content measurement were analyzed. It was found that the shattering effect on the PSD decreases with the increasing size of less than 400 μm, fluctuates between 400 μm and 1000 μm and slightly increases with the increasing size of larger than 1000 μm on average in a stratiform region and a convective region. However, the average ratio of PSD uncorrected to that corrected for shattering events using the presented algorithm in convective clouds is larger than that in the stratiform regions in the whole size, and nearly twice that in the size of less than 1000 μm. The measured number concentration can be overestimated by up to a factor of 3.9 on average in a stratiform region, while in a convective region, it is 7.7, nearly twice that of a stratiform region. The ice water content in a stratiform region can be overestimated by 29.5% on average, but by 60.7% in a convective region. These findings can be helpful for the cloud physics community to use the airborne CIP measurement data for numerical weather and climate models. Full article

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

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13 pages, 4276 KiB

Open AccessFeature PaperEditor’s ChoiceArticle

On Neglecting Free-Stream Turbulence in Numerical Simulation of the Wind-Induced Bias of Snow Gauges

by Arianna Cauteruccio, Matteo Colli and Luca G. Lanza

Water 2021, 13(3), 363; https://0-doi-org.brum.beds.ac.uk/10.3390/w13030363 - 31 Jan 2021

Cited by 4 | Viewed by 2175

Abstract

Numerical studies of the wind-induced bias of precipitation measurements assume that turbulence is generated by the interaction of the airflow with the gauge body, while steady and uniform free-stream conditions are imposed. However, wind is turbulent in nature due to the roughness of the site and the presence of obstacles, therefore precipitation gauges are immersed in a turbulent flow. Further to the turbulence generated by the flow-gauge interaction, we investigated the natural free-stream turbulence and its influence on precipitation measurement biases. Realistic turbulence intensity values at the gauge collector height were derived from 3D sonic anemometer measurements. Large Eddy Simulations of the turbulent flow around a chimney-shaped gauge were performed under uniform and turbulent free-stream conditions, using geometrical obstacles upstream of the gauge to provide the desired turbulence intensity. Catch ratios for dry snow particles were obtained using a Lagrangian particle tracking model, and the collection efficiency was calculated based on a suitable particle size distribution. The collection efficiency in turbulent conditions showed stronger undercatch at the investigated wind velocity and snowfall intensity below 10 mm h⁻¹, demonstrating that adjustment curves based on the simplifying assumption of uniform free-stream conditions do not accurately portray the wind-induced bias of snow measurements. Full article

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

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15 pages, 5370 KiB

Open AccessFeature PaperArticle

Parameterization of the Collection Efficiency of a Cylindrical Catching-Type Rain Gauge Based on Rainfall Intensity

by Arianna Cauteruccio and Luca G. Lanza

Water 2020, 12(12), 3431; https://0-doi-org.brum.beds.ac.uk/10.3390/w12123431 - 06 Dec 2020

Cited by 17 | Viewed by 2337

Abstract

Despite the numerous contributions available in the literature about the wind-induced bias of rainfall intensity measurements, adjustments based on collection efficiency curves are rarely applied operationally to rain records obtained from catching-type rain gauges. The many influencing variables involved and the variability of the results of field experiments do not facilitate the widespread application of adjustment algorithms. In this paper, a Lagrangian particle tracking model is applied to the results of computational fluid dynamic simulations of the airflow field surrounding a rain gauge to derive a simple formulation of the collection efficiency curves as a function of wind speed. A new parameterization of the influence of rainfall intensity is proposed. The methodology was applied to a cylindrical gauge, which has the typical outer shape of tipping-bucket rain gauges, as a representative specimen of most operational measurement instruments. The wind velocity is the only ancillary variable required to calculate the adjustment, together with the measured rainfall intensity. Since wind is commonly measured by operational weather stations, its use adds no relevant burden to the cost of meteo-hydrological networks. Full article

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

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20 pages, 3698 KiB

Open AccessEditor’s ChoiceArticle

Comparison Study of Multiple Precipitation Forcing Data on Hydrological Modeling and Projection in the Qujiang River Basin

by Yongyu Song, Jing Zhang, Xianyong Meng, Yuyan Zhou, Yuequn Lai and Yang Cao

Water 2020, 12(9), 2626; https://0-doi-org.brum.beds.ac.uk/10.3390/w12092626 - 19 Sep 2020

Cited by 15 | Viewed by 2914

Abstract

As a key factor in the water cycle and climate change, the quality of precipitation data directly affects the hydrological processes of the river basin. Although many precipitation products with high spatial and temporal resolutions are now widely used, it is meaningful and necessary to investigate and evaluate their merits and demerits in hydrological applications. In this study, two satellite-based precipitation products (Tropical Rainfall Measurement Mission, TRMM; Integrated Multi-satellite Retrievals for GPM, IMERG) and one reanalysis precipitation product (China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model, CMADS) are studied to compare their streamflow simulation performance in the Qujiang River Basin, China, using the SWAT model with gauged rainfall data as a reference. The main conclusions are as follows: (1) CMADS has stronger precipitation detection capabilities compared to gauged rainfall, while TRMM results in the most obvious overestimation in the four sub-basins. (2) In daily and monthly streamflow simulations, CMADS + SWAT mode offers the best performance. CMADS and IMERG can provide high quality precipitation data for data-scarce areas, and IMERG can effectively avoid the overestimation of streamflow caused by TRMM, especially on a daily scale. (3) The runoff projections of the three modes under RCP (Representative Concentration Pathway) 4.5 was higher than that of RCP 8.5 on the whole. IMERG + SWAT overestimates the surface water resources of the basin compared to CMADS + SWAT, while TRMM + SWAT provides the most stable uncertainty. These findings contribute to the comparison of the differences among the three precipitation products and provides a reference for the selection of precipitation data in similar regions. Full article

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

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18 pages, 2346 KiB

Open AccessArticle

A Homogeneous Dataset for Rainfall Trend Analysis in the Calabria Region (Southern Italy)

by Tommaso Caloiero, Eugenio Filice, Roberto Coscarelli and Gaetano Pellicone

Water 2020, 12(9), 2541; https://0-doi-org.brum.beds.ac.uk/10.3390/w12092541 - 11 Sep 2020

Cited by 16 | Viewed by 2606

Abstract

In order to investigate the tendency in rainfall amount in Calabria (southern Italy), in this work, monthly rainfall series were first tested for homogeneity and then a trend analysis was performed. In particular, a homogenization approach based on the Climatol method was applied to homogenize monthly climatological series. Then, the Mann–Kendall non-parametric test and the Theil–Sen estimator were applied to evaluate the presence of trends and their significance in the monthly, seasonal and annual rainfall series. Moreover, the trend slopes were further evaluated with a linear regression analysis. At the annual scale, results evidenced a decreasing trend mainly in the north-eastern part of the region. At the seasonal scale, a spatial distributed negative trend in winter, and a positive trend in summer, mainly localized in the north-western part of the region, were identified. Finally, on a monthly scale negative trends spreading across the region were detected in January and December, with an opposite behavior in July and especially in September, when almost the entire region presented a positive trend. Full article

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

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29 pages, 4763 KiB

Open AccessArticle

Evaluation of Radar-Gauge Merging Techniques to Be Used in Operational Flood Forecasting in Urban Watersheds

by Dayal Wijayarathne, Paulin Coulibaly, Sudesh Boodoo and David Sills

Water 2020, 12(5), 1494; https://0-doi-org.brum.beds.ac.uk/10.3390/w12051494 - 23 May 2020

Cited by 12 | Viewed by 3903

Abstract

Demand for radar Quantitative Precipitation Estimates (QPEs) as precipitation forcing to hydrological models in operational flood forecasting has increased in the recent past. It is practically impossible to get error-free QPEs due to the intrinsic limitations of weather radar as a precipitation measurement tool. Adjusting radar QPEs with gauge observations by combining their advantages while minimizing their weaknesses increases the accuracy and reliability of radar QPEs. This study deploys several techniques to merge two dual-polarized King City radar (WKR) C-band and two KBUF Next-Generation Radar (NEXRAD) S-band operational radar QPEs with rain gauge data for the Humber River (semi-urban) and Don River (urban) watersheds in Ontario, Canada. The relative performances are assessed against an independent gauge network by comparing hourly rainfall events. The Cumulative Distribution Function Matching (CDFM) method performed best, followed by Kriging with Radar-based Error correction (KRE). Although both WKR and NEXRAD radar QPEs improved significantly, NEXRAD Level III Digital Precipitation Array (DPA) provided the best results. All methods performed better for low- to medium-intensity precipitation but deteriorated with the increasing rainfall intensities. All methods outperformed radar only QPEs for all events, but the agreement is best in the summer. Full article

(This article belongs to the Special Issue Precipitation Measurement Instruments: Calibration, Accuracy and Performance)

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