Special Issue "Precipitation: Measurement and Modeling"

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

Deadline for manuscript submissions: closed (15 July 2018)

Special Issue Editor

Guest Editor
Prof. Dr. Francisco J. Tapiador

University of Castilla-La Mancha. Department of Environmental Sciences. Earth and Space Sciences (ess) Research Group
Website 1 | Website 2 | E-Mail
Interests: precipitation; remote sensing; drop size distribution modeling; maximum entropy

Special Issue Information

Dear Colleagues,

The Special Issue aims to gather good-quality, timely research on precipitation from a broad perspective, in order to inform on the current state-of-the-art in the field, and to identify the key groups working on precipitation internationally. Apart from regular papers, local/regional studies of precipitation, negative results (such as models performing poorly when compared with observations), short papers and discussions/position papers are welcomed -if in doubt about the suitability of the research for the SI, potential authors are invited to discuss the idea with the Guest Editor before preparing the paper.

We invite papers on the following topics:

-Validation/Verification of precipitation estimates from NWP models, RCMs, GCMs and ESMs.

-Precipitation microphysics, including mp description, verification, comparison, and case studies.

-Satellite precipitation algorithms.

-Database descriptions.

-Seasonal forecast of precipitation.

-Ensemble techniques.

-Particle and Drop Size Distribution (PSD, DSD) research.

-Computing approaches (HPC, Cloud, etc.)

-Uncertainties in measuring precipitation at ground (gauges, disdrometers, radars)

-Instrumental biases.

-Spatial variability of precipitation, at any scales.

-Assimilation of precipitation in numerical models.

-Latent heat studies.

-Precipitation in hurricanes.

-Monsoons.

-Campaigns results.

-Hydrological applications.

-IPWG activities.

-TRMM and GPM studies.

-Megha-Tropiques results.

-Precipitation from sounders.

-New observational concepts (including Geostationary sounders)

-Projects results or preliminary advances (CMIP5/6, HyMEX, CORDEX, CLIVAR, etc.)

-Precipitation climatologies, from local to global.

-Applications (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, including Climate Variability.

-Precipitation in future climates as featuring in models.

Prof. Dr. Francisco J. Tapiador  
Guest Editor

Manuscript Submission Information

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Published Papers (18 papers)

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Research

Open AccessArticle Influence of Disdrometer Type on Weather Radar Algorithms from Measured DSD: Application to Italian Climatology
Atmosphere 2018, 9(9), 360; https://doi.org/10.3390/atmos9090360
Received: 24 July 2018 / Revised: 11 September 2018 / Accepted: 14 September 2018 / Published: 18 September 2018
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Abstract
Relations for retrieving precipitation and attenuation information from radar measurements play a key role in radar meteorology. The uncertainty in such relations highly affects the precipitation and attenuation estimates. Weather radar algorithms are often derived by applying regression methods to precipitation measurements and
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Relations for retrieving precipitation and attenuation information from radar measurements play a key role in radar meteorology. The uncertainty in such relations highly affects the precipitation and attenuation estimates. Weather radar algorithms are often derived by applying regression methods to precipitation measurements and radar observables simulated from datasets of drop size distributions (DSD) using microphysical and electromagnetic assumptions. DSD datasets can be derived from theoretical considerations or obtained from experimental measurements collected throughout the years by disdrometers. Although the relations obtained from experimental disdrometer datasets can be generally considered more representative of a specific climatology, the measuring errors, which depend on the specific type of disdrometer used, introduce an element of uncertainty to the final retrieval algorithms. Eventually, data quality checks and filtering procedures applied to disdrometer measurements play an important role. In this study, we pursue two main goals: (i) evaluate two different techniques for establishing weather radar algorithms from measured DSD, and (ii) investigate to what extent dual-polarization radar algorithms derived from experimental DSD datasets are influenced by the different error structures introduced by the various disdrometer types (namely 2D video disdrometer, first and second generation of OTT Parsivel disdrometer, and Thies Clima disdrometer) used to collect the data. Furthermore, weather radar algorithms optimized for Italian climatology are presented and discussed. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Dynamic Ensemble Analysis of Frontal Placement Impacts in the Presence of Elevated Thunderstorms during PRECIP Events
Atmosphere 2018, 9(9), 339; https://doi.org/10.3390/atmos9090339
Received: 30 May 2018 / Revised: 17 August 2018 / Accepted: 26 August 2018 / Published: 29 August 2018
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Abstract
The Program for Research on Elevated Convection with Intense Precipitation (PRECIP) field campaign sampled 10 cases of elevated convection during 2014 and 2015. These intense observing periods (IOP) mostly featured well-defined stationary or warm frontal zones, over whose inversion elevated convection would form.
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The Program for Research on Elevated Convection with Intense Precipitation (PRECIP) field campaign sampled 10 cases of elevated convection during 2014 and 2015. These intense observing periods (IOP) mostly featured well-defined stationary or warm frontal zones, over whose inversion elevated convection would form. However, not all frontal zones translated as expected, with some poleward motions being arrested and even returning equatorward. Prior analyses of the observed data highlighted the downdrafts in these events, especially diagnostics for their behavior: the downdraft convective available potential energy (DCAPE) and the downdraft convective inhibition (DCIN). With the current study, the DCAPE and DCIN are examined for four cases: two where frontal motion proceeded poleward, as expected, and two where the frontal motions were slowed significantly or stalled altogether. Using the Weather Research and Forecasting (WRF) model, a multi-model ensemble was created for each of the four cases, and the best performing members were selected for additional deterministic examination. Analyses of frontal motions and surface cold pools are explored in the context of DCAPE and DCIN. These analyses further establish the DCAPE and DCIN, not only as a means to classify elevated convection, but also to aid in explaining frontal motions in the presence of elevated convection. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Numerical Simulation of a Heavy Precipitation Event in the Vicinity of Madrid-Barajas International Airport: Sensitivity to Initial Conditions, Domain Resolution, and Microphysics Parameterizations
Atmosphere 2018, 9(9), 329; https://doi.org/10.3390/atmos9090329
Received: 2 July 2018 / Revised: 3 August 2018 / Accepted: 18 August 2018 / Published: 22 August 2018
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Abstract
Deep convection is a threat to many human activities, with a great impact on aviation safety. On 7 July 2017, a widespread torrential precipitation event (associated with a cut-off low at mid-levels) was registered in the vicinity of Madrid, causing serious flight disruptions.
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Deep convection is a threat to many human activities, with a great impact on aviation safety. On 7 July 2017, a widespread torrential precipitation event (associated with a cut-off low at mid-levels) was registered in the vicinity of Madrid, causing serious flight disruptions. During this type of episode, accurate short-term forecasts are key to minimizing risks to aviation. The aim of this research is to improve early warning systems by obtaining the best WRF model setup. In this paper, the aforementioned event was simulated. Various model configurations were produced using four different physics parameterizations, 3-km and 1-km domain resolutions, and 0.25° and 1° initial condition resolutions. Simulations were validated using data from 17 rain gauge stations. Two validation indices are proposed, accounting for the temporal behaviour of the model. Results show significant differences between microphysics parameterizations. Validation of domain resolution shows that improvement from 3 to 1 km is negligible. Interestingly, the 0.25° resolution for initial conditions produced poor results compared with 1°. This may be linked to a timing error, because precipitation was simulated further east than observed. The use of ensembles generated by combining different WRF model configurations produced reliable precipitation estimates. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Observed Response of the Raindrop Size Distribution to Changes in the Melting Layer
Atmosphere 2018, 9(8), 319; https://doi.org/10.3390/atmos9080319
Received: 15 July 2018 / Revised: 8 August 2018 / Accepted: 10 August 2018 / Published: 18 August 2018
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Abstract
Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the
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Vertical variability in the raindrop size distribution (RSD) can disrupt the basic assumption of a constant rain profile that is customarily parameterized in radar-based quantitative precipitation estimation (QPE) techniques. This study investigates the utility of melting layer (ML) characteristics to help prescribe the RSD, in particular the mass-weighted mean diameter (Dm), of stratiform rainfall. We utilize ground-based polarimetric radar to map the ML and compare it with Dm observations from the ground upwards to the bottom of the ML. The results show definitive proof that a thickening, and to a lesser extent a lowering, of the ML causes an increase in raindrop diameter below the ML that extends to the surface. The connection between rainfall at the ground and the overlying microphysics in the column provide a means for improving radar QPE at far distances from a ground-based radar or close to the ground where satellite-based radar rainfall retrievals can be ill-defined. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Identification and Characterization of an Anomaly in Two-Dimensional Video Disdrometer Data
Atmosphere 2018, 9(8), 315; https://doi.org/10.3390/atmos9080315
Received: 20 June 2018 / Revised: 30 July 2018 / Accepted: 8 August 2018 / Published: 13 August 2018
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Abstract
The two-dimensional video distrometer (2DVD) is a well known ground based point-monitoring precipitation gauge, often used as a ground truth instrument to validate radar or satellite rainfall retrieval algorithms. This instrument records a number of variables for each detected hydrometeor, including the detected
[...] Read more.
The two-dimensional video distrometer (2DVD) is a well known ground based point-monitoring precipitation gauge, often used as a ground truth instrument to validate radar or satellite rainfall retrieval algorithms. This instrument records a number of variables for each detected hydrometeor, including the detected position within the sample area of the instrument. Careful analyses of real 2DVD data reveal an artifact—there are time periods where hydrometeor detections within parts of the sample area are artificially enhanced or diminished. Here, we (i) illustrate this anomaly with an exemplary 2DVD data set, (ii) describe the origin of this anomaly, (iii) develop and present an algorithm to help flag data potentially partially corrupted by this anomaly, and (iv) explore the prevalence and quantitative impact of this anomaly. Although the anomaly is seen in every major rain event studied and by every 2DVD the authors have examined, the anomaly artificially induces less than 3% of all detected drops and typically alters estimates of rain rates and accumulations by less than 2%. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Trends, Variability, and Seasonality of Maximum Annual Daily Precipitation in the Upper Vistula Basin, Poland
Atmosphere 2018, 9(8), 313; https://doi.org/10.3390/atmos9080313
Received: 29 June 2018 / Revised: 2 August 2018 / Accepted: 9 August 2018 / Published: 10 August 2018
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Abstract
The aim of this study was to detect trends in maximum annual daily precipitation in the Upper Vistula Basin. We analyzed data from 51 weather stations between 1971 and 2014. Then we used the Mann–Kendall test to detect monotonical trends of the precipitation
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The aim of this study was to detect trends in maximum annual daily precipitation in the Upper Vistula Basin. We analyzed data from 51 weather stations between 1971 and 2014. Then we used the Mann–Kendall test to detect monotonical trends of the precipitation for three significance levels: 1, 5, and 10%. Our analysis of weather conditions helped us describe the mechanism behind the formation of maximum annual daily precipitation. To analyze precipitation seasonality, we also used Colwell indices. Our study identified a significant trend of the highest daily precipitation for the assumed significance levels (0.01, 0.05, 0.1) for 22% of the investigated weather stations at different elevations. The significant trends found were positive and an increase in precipitation is expected. From 1971 to 2014, the maximum daily total precipitation most often occurred in the summer half-year, i.e., from May until September. These months included a total of 88% of days with the highest daily precipitation. The predictability index for the highest total precipitation within the area was high and exceeded 5%. It was markedly affected by the coefficient of constancy (C) and to a lesser degree by the seasonality index (M). Our analysis demonstrated a convergence of the Colwell indices and frequency of cyclonic situation and, therefore, confirmed their usability in the analysis of precipitation seasonality. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Using the Weather Research and Forecasting (WRF) Model for Precipitation Forecasting in an Andean Region with Complex Topography
Atmosphere 2018, 9(8), 304; https://doi.org/10.3390/atmos9080304
Received: 14 June 2018 / Revised: 26 July 2018 / Accepted: 30 July 2018 / Published: 2 August 2018
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Abstract
The Weather Research and Forecasting (WRF) model has been successfully used in weather prediction, but its ability to simulate precipitation over areas with complex topography is not optimal. Consequently, WRF has problems forecasting rainfall events over Chilean mountainous terrain and foothills, where some
[...] Read more.
The Weather Research and Forecasting (WRF) model has been successfully used in weather prediction, but its ability to simulate precipitation over areas with complex topography is not optimal. Consequently, WRF has problems forecasting rainfall events over Chilean mountainous terrain and foothills, where some of the main cities are located, and where intense rainfall occurs due to cutoff lows. This work analyzes an ensemble of microphysics schemes to enhance initial forecasts made by the Chilean Weather Agency in the front range of Santiago. We first tested different vertical levels resolution, land use and land surface models, as well as meteorological forcing (GFS/FNL). The final ensemble configuration considered three microphysics schemes and lead times over three rainfall events between 2015 and 2017. Cutoff low complex meteorological characteristics impede the temporal simulation of rainfall properties. With three days of lead time, WRF properly forecasts the rainiest N-hours and temperatures during the event, although more accuracy is obtained when the rainfall is caused by a meteorological frontal system. Finally, the WSM6 microphysics option had the best performance, although further analysis using other storms and locations in the area are needed to strengthen this result. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Characteristics of the Underestimation Error of Annual Maximum Rainfall Depth Due to Coarse Temporal Aggregation
Atmosphere 2018, 9(8), 303; https://doi.org/10.3390/atmos9080303
Received: 5 July 2018 / Revised: 26 July 2018 / Accepted: 30 July 2018 / Published: 2 August 2018
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Abstract
This study analyzed all characteristics of the error committed in evaluating annual maximum rainfall depth, Hd, associated with a given duration, d, when data with coarse temporal aggregation, ta, were used. It is well known that when t
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This study analyzed all characteristics of the error committed in evaluating annual maximum rainfall depth, Hd, associated with a given duration, d, when data with coarse temporal aggregation, ta, were used. It is well known that when ta = 1 min, this error is practically negligible while coarser temporal aggregations can determine underestimation for a single Hd up to 50% and for the average value of sufficiently numerous series of Hd up to 16.67%. By using a mathematical relation between average underestimation error and the ratio ta/d, each Hd value belonging to a specific series could be corrected through deterministic or stochastic approaches. With a deterministic approach, an average correction was identically applied to all Hd values with the same ta and d while, for a stochastic correction, a thorough knowledge of the statistical characteristics of the underestimation error was required. Accordingly, in this work, rainfall data derived from many stations in central Italy were analyzed and it was assessed that single and average errors, which were both assumed as random variables, followed exponential and normal distributions, respectively. Furthermore, the single underestimation error was also found inversely correlated to the corresponding annual maximum rainfall depth. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Lagrangian Cloud Tracking and the Precipitation-Column Humidity Relationship
Atmosphere 2018, 9(8), 289; https://doi.org/10.3390/atmos9080289
Received: 5 June 2018 / Revised: 11 July 2018 / Accepted: 19 July 2018 / Published: 26 July 2018
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Abstract
The tropical, oceanic mean relationship between column relative humidity and precipitation is highly non-linear. Mean precipitation remains weak until it rapidly picks up and grows at high column humidity. To investigate the origin of this relationship, a Lagrangian cloud tracking code, RAMStracks, is
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The tropical, oceanic mean relationship between column relative humidity and precipitation is highly non-linear. Mean precipitation remains weak until it rapidly picks up and grows at high column humidity. To investigate the origin of this relationship, a Lagrangian cloud tracking code, RAMStracks, is developed, which can follow the evolution of clouds. RAMStracks can record the morphological properties of convective clouds, the meteorological environment of clouds, and their effects. RAMStracks is applied to a large-domain radiative convective equilibrium simulation, which produces a complex population of convective clouds. RAMStracks records the lifecycle of 501 clouds through growth, splits, mergers, and decay. The mean evolution of all these clouds is examined. It is shown that the column humidity evolves non-monotonically, but that lower-level and upper-level contributions to total moisture do evolve monotonically. The precipitation efficiency of tropical storms tends to increase with cloud age. This is confirmed using a prototype testing method. The same method reveals that different tracked clouds with similar initial conditions evolve in very different ways. This makes drawing general conclusions from individual storms difficult. Finally, the causality of the precipitation-column humidity relationship is examined. A Granger Causality test, as well as regressions, suggest that moisture and precipitation are causally linked, but that the direction of causality is ambiguous. Much of this link appears to come from the lower-level moisture’s contribution to column humidity. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Rainfall Detection and Rainfall Rate Estimation Using Microwave Attenuation
Atmosphere 2018, 9(8), 287; https://doi.org/10.3390/atmos9080287
Received: 8 February 2018 / Revised: 6 July 2018 / Accepted: 20 July 2018 / Published: 24 July 2018
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Abstract
Eight microwave links operating at frequencies ranging from 6 to 8 GHz and with path lengths ranging from 5.7 to 37.4 km traversing the city of Seoul, Korea are used to detect rainfall and estimate path-averaged rainfall rates. Rainfall detection using rain-induced attenuation
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Eight microwave links operating at frequencies ranging from 6 to 8 GHz and with path lengths ranging from 5.7 to 37.4 km traversing the city of Seoul, Korea are used to detect rainfall and estimate path-averaged rainfall rates. Rainfall detection using rain-induced attenuation (dB) was validated by rain detectors installed at automatic weather stations, and the results confirmed that microwave links can be used to detect rainfall with an accuracy ≥80%. The power-law R-k relationships between rain-induced specific attenuation, k (dB km−1), and the rainfall rate, R (mm h−1), were established and cross-validated by estimating the path-averaged rainfall rate. The mean bias of the path-averaged rainfall rate, as compared to the rainfall rate from ground rain gauges, was between −3 and 1 mm h−1. The improved accuracy of rainfall detection led to the improved accuracy of the path-averaged rainfall rate. Hence, it was confirmed that microwave links, used for broadcasting and media communications, can identify rainy or dry periods (rain spells or dry spells) in a way comparable to rain detectors and provide high time-resolution rainfall rates in real time. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Subpixel-Based Precipitation Nowcasting with the Pyramid Lucas–Kanade Optical Flow Technique
Atmosphere 2018, 9(7), 260; https://doi.org/10.3390/atmos9070260
Received: 16 April 2018 / Revised: 25 June 2018 / Accepted: 6 July 2018 / Published: 12 July 2018
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Abstract
Short-term high-resolution quantitative precipitation forecasting (QPF) is very important for flash-flood warning, navigation safety, and other hydrological applications. This paper proposes a subpixel-based QPF algorithm using a pyramid Lucas–Kanade optical flow technique (SPLK) for short-time rainfall forecast. The SPLK tracks the storm on
[...] Read more.
Short-term high-resolution quantitative precipitation forecasting (QPF) is very important for flash-flood warning, navigation safety, and other hydrological applications. This paper proposes a subpixel-based QPF algorithm using a pyramid Lucas–Kanade optical flow technique (SPLK) for short-time rainfall forecast. The SPLK tracks the storm on the subpixel level by using the optical flow technique and then extrapolates the precipitation using a linear method through redistribution and interpolation. The SPLK compares with object-based and pixel-based nowcasting algorithms using eight thunderstorm events to assess its performance. The results suggest that the SPLK can perform better nowcasting of precipitation than the object-based and pixel-based algorithms with higher adequacy in tracking and predicting severe storms in 0–2 h lead-time forecasting. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle An Ensemble Mean and Evaluation of Third Generation Global Climate Reanalysis Models
Atmosphere 2018, 9(6), 236; https://doi.org/10.3390/atmos9060236
Received: 9 February 2018 / Revised: 14 June 2018 / Accepted: 16 June 2018 / Published: 19 June 2018
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Abstract
We have produced a global ensemble mean of the four third-generation climate reanalysis models for the years 1981–2010. The reanalysis system models used in this study are National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather
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We have produced a global ensemble mean of the four third-generation climate reanalysis models for the years 1981–2010. The reanalysis system models used in this study are National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis Interim (ERA-I), Japan Meteorological Agency (JMA) 55-year Reanalysis (JRA-55), and National Aeronautics and Space Administration (NASA) Modern-Era Retrospective Analysis for Research and Applications (MERRA). Two gridded datasets are used as a baseline, for temperature the Global Historical Climatology Network (GHCN), and for precipitation the Global Precipitation Climatology Centre (GPCC). The reanalysis ensemble mean is used here as a comparison tool of the four reanalysis members. Meteorological fields investigated within the reanalysis models include 2-m air temperature, precipitation, and 500-hPa geopotential heights. Comparing the individual reanalysis models to the ensemble mean, we find that each perform similarly over large domains but exhibit significant differences over particular regions. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle East Asian Summer Monsoon Representation in Re-Analysis Datasets
Atmosphere 2018, 9(6), 235; https://doi.org/10.3390/atmos9060235
Received: 23 May 2018 / Revised: 11 June 2018 / Accepted: 14 June 2018 / Published: 16 June 2018
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Abstract
Eight current re-analyses—NCEP/NCAR Re-analysis (NCEPI), NCEP/DOE Re-analysis (NCEPII), NCEP Climate Forecast System Re-analysis (CFSR), ECMWF Interim Re-analysis (ERA-Interim), Japanese 55-year Re-analysis (JRA-55), NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA), NOAA Twentieth Century Re-analysis (20CR), and ECMWF’s first atmospheric re-analysis of the
[...] Read more.
Eight current re-analyses—NCEP/NCAR Re-analysis (NCEPI), NCEP/DOE Re-analysis (NCEPII), NCEP Climate Forecast System Re-analysis (CFSR), ECMWF Interim Re-analysis (ERA-Interim), Japanese 55-year Re-analysis (JRA-55), NASA Modern-Era Retrospective Analysis for Research and Applications (MERRA), NOAA Twentieth Century Re-analysis (20CR), and ECMWF’s first atmospheric re-analysis of the 20th century (ERA-20C)—are assessed to clarify their quality in capturing the East Asian summer monsoon (EASM) rainfall structure and its associated general circulation. They are found to present similar rainfall structures in East Asia, whereas they illustrate some differences in rainfall intensity, especially at lower latitudes. The third generation of re-analysis shows a better estimate of rainfall structure than that in the first and extended generation of re-analysis. Given the fact that the rainfall is ingested by the data assimilation system, the re-analysis cannot improve its production of rainfall quality. The mean sea level pressure is generated by re-analysis, showing a significant uncertainty over the Tibetan Plateau and its surrounding area. In that region, the JRA-55 and MERRA have a negative bias (BIAS), while the other six re-analyses present a positive BIAS to the observed mean sea level pressure. The 20CR and the ERA-20C are ancillary datasets to analyse the EASM due to the fact that they only apply limit observations into the data assimilation system. These two re-analyses demonstrate a prominent difference from the observed winds in the upper-air. Although the upper level winds exhibit difference, the EASM index is consistent in the eight re-analyses, which are based upon the zonal wind over 850 hPa. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle An Uncertainty Investigation of RCM Downscaling Ratios in Nonstationary Extreme Rainfall IDF Curves
Atmosphere 2018, 9(4), 151; https://doi.org/10.3390/atmos9040151
Received: 16 March 2018 / Revised: 6 April 2018 / Accepted: 16 April 2018 / Published: 18 April 2018
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Abstract
Designed for rainstorms and flooding, hydrosystems are largely based on local rainfall Intensity–Duration–Frequency (IDF) curves which include nonstationary components accounting for climate variability. IDF curves are commonly calculated using downscaling outputs from General Circulation Models (GCMs) or Regional Circulation Models (RCMs). However, the
[...] Read more.
Designed for rainstorms and flooding, hydrosystems are largely based on local rainfall Intensity–Duration–Frequency (IDF) curves which include nonstationary components accounting for climate variability. IDF curves are commonly calculated using downscaling outputs from General Circulation Models (GCMs) or Regional Circulation Models (RCMs). However, the downscaling procedures used in most studies are based on one specific time scale (e.g., 1 h) and generally ignore scale-driven uncertainty. This study analyzes the uncertainties in IDF curves stemming from RCM downscaling ratios for four representative weather stations in the United Kingdom. We constructed a series of IDF curves using distribution-based scaling bias-correction technology and a statistical downscaling method to explore the scale-driven uncertainty of IDF curves. The results revealed considerable scale-induced uncertainty of IDF curves for short durations and long return periods; however, there was no clear correlation with the mean storm intensity of the IDF curves of different RCM ensemble members for each duration and return period. The scale-driven uncertainty of IDF curves, which may be propagated or enhanced through hydrometeorological applications, is critical and cannot be ignored in the hydrosystem design process; therefore, a multi-scale method to derive IDF curves must be developed. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Precipitation Preventing a Deficit of Readily Available Soil Water in Arable Soils in Poland
Atmosphere 2018, 9(4), 121; https://doi.org/10.3390/atmos9040121
Received: 27 February 2018 / Revised: 19 March 2018 / Accepted: 21 March 2018 / Published: 23 March 2018
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Abstract
Plants grown in arable soils mainly use rainwater stored in the soil at matric potential between −10 kPa and −100 kPa, which corresponds to the readily available soil water (RASW). RASW in the 100-cm soil layer of Polish arable soils is relatively low
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Plants grown in arable soils mainly use rainwater stored in the soil at matric potential between −10 kPa and −100 kPa, which corresponds to the readily available soil water (RASW). RASW in the 100-cm soil layer of Polish arable soils is relatively low and ranges from about 12 mm in mountain clay soils up to 75 mm in black earths, which, at an average daily evapotranspiration of 3.8 mm·day−1 and spatio—temporal variability of precipitation, determines water scarcity of crop plants. The aim of the study is to estimate the values and the frequency of critical rainfall which ensures that soil water is kept in the range of readily available to plants and prevents water shortages for plants in arable soils. In order to meet this condition, the decade (10-day) sums of this precipitation, included in the ranges 16–27, 22–31, 26–35 and 33–39 mm, occur in 20.8, 13.4, 11.3 and 5.9%, respectively, of the decades of the vegetation period (April to September). Maps of critical rainfall spatial diversity in the background of the actual soil cover in Poland were generated. They may be useful for preliminary, estimated operational planning of irrigation needs. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Verification of High-Resolution Medium-Range Precipitation Forecasts from Global Environmental Multiscale Model over China during 2009–2013
Atmosphere 2018, 9(3), 104; https://doi.org/10.3390/atmos9030104
Received: 9 December 2017 / Revised: 15 February 2018 / Accepted: 3 March 2018 / Published: 13 March 2018
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Abstract
Accurate and timely precipitation forecasts are a key factor for improving hydrological forecasts. Therefore, it is fundamental to evaluate the skill of Numerical Weather Prediction (NWP) for precipitation forecasting. In this study, the Global Environmental Multi-scale (GEM) model, which is widely used around
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Accurate and timely precipitation forecasts are a key factor for improving hydrological forecasts. Therefore, it is fundamental to evaluate the skill of Numerical Weather Prediction (NWP) for precipitation forecasting. In this study, the Global Environmental Multi-scale (GEM) model, which is widely used around Canada, was chosen as the high-resolution medium-term prediction model. Based on the forecast precipitation with the resolution of 0.24° and taking regional differences into consideration, the study explored the forecasting skill of GEM in nine drought sub-regions around China. Spatially, GEM performs better in East and South China than in the inland areas. Temporally, the model is able to produce more precise precipitation during flood periods (summer and autumn) compared with the non-flood season (winter and spring). The forecasting skill variability differs with regions, lead time and season. For different precipitation categories, GEM for trace rainfall and little rainfall performs much better than moderate rainfall and above. Overall, compared with other prediction systems, GEM is applicable for the 0–96 h forecast, especially for the East and South China in flood season, but improvement for the prediction of heavy and storm rainfall and for the inland areas should be focused on as well. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Stable Isotopic Characteristics and Influencing Factors in Precipitation in the Monsoon Marginal Region of Northern China
Atmosphere 2018, 9(3), 97; https://doi.org/10.3390/atmos9030097
Received: 1 January 2018 / Revised: 16 February 2018 / Accepted: 6 March 2018 / Published: 8 March 2018
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Abstract
Based on stable hydrogen and oxygen isotope data (δ18O, δD) and meteorological observation data for complete hydrological annual precipitation from 2016 to 2017 in the monsoon marginal region of northern China (Fengxiang and Ningwu), the isotopic characteristics of precipitation and the
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Based on stable hydrogen and oxygen isotope data (δ18O, δD) and meteorological observation data for complete hydrological annual precipitation from 2016 to 2017 in the monsoon marginal region of northern China (Fengxiang and Ningwu), the isotopic characteristics of precipitation and the sources of water vapor in these two regions combined were studied. The results showed that δ18O and δD values in the wet season (June through September) were higher than in the dry season (October to May of the following year) in Fengxiang and Ningwu. The intercept and slope of the meteoric water line in the two regions were somewhat low, revealing that the water vapor in the rainfall comes mainly from the tropical ocean. On a synoptic scale, significantly positive correlations among dry season precipitation, δ18O, and temperature manifested temperature effects, but in the wet season, the temperature effect was not significant. On a monthly scale, a relationship did not exist between the change in trend of the average value of monthly weighted δ18O in precipitation and the average temperature change value in the two regions. However, in the wet season, significantly negative relationships can be found between the average monthly weighted δ18O in precipitation and rainfall amount, which indicated a remarkable rainout effect. Further investigation revealed that continuous precipitation made the values of δ18O and δD more negative under the same source of water vapor (the rainout effect). Because the annual rainfall in the monsoon marginal region of Northern China is mainly made up of monsoon rainfall, the oxygen isotope index of geological and biological records, such as stalagmites and tree rings, which inherit meteoric water isotope information, can be used to reconstruct past rainfall changes in northern China. Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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Open AccessArticle Modeling the Spatial and Temporal Variability of Precipitation in Northwest Iran
Atmosphere 2017, 8(12), 254; https://doi.org/10.3390/atmos8120254
Received: 10 November 2017 / Revised: 3 December 2017 / Accepted: 13 December 2017 / Published: 17 December 2017
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Abstract
Spatial and temporal variability analysis of precipitation is an important task in water resources planning and management. This study aims to analyze the spatial and temporal variability of precipitation in the northeastern corner of Iran using data from 24 well-distributed weather stations between
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Spatial and temporal variability analysis of precipitation is an important task in water resources planning and management. This study aims to analyze the spatial and temporal variability of precipitation in the northeastern corner of Iran using data from 24 well-distributed weather stations between 1991 and 2015. The mean annual rainfall, precipitation concentration index (PCI), and their coefficients of variation were mapped to examine the spatial variability of rainfall. An artificial neural network (ANN) in association with the inverse distance weighted (IDW) method was proposed as a hybrid interpolation method to map the spatial distribution of the detected trends of mean annual rainfall and PCI over the study region. In addition, principal component analysis (PCA) was applied to annual precipitation time series in order to verify the results of the analysis using the mean annual rainfall and PCI data sets. Results show high variation in inter-annual precipitation in the west, and a moderate to high intra-annual variability over the whole region. Irregular year-to-year precipitation concentration is also observed in the northeastern and northwestern parts. All in all, the highest variations in inter-annual and intra-annual precipitation occurred over the western and northern parts, while the lowest variability was observed in the eastern part (i.e., the coastal region). Full article
(This article belongs to the Special Issue Precipitation: Measurement and Modeling)
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