Special Issue "From Local to Global Precipitation Dynamics and Climate Interaction"

A special issue of Climate (ISSN 2225-1154).

Deadline for manuscript submissions: closed (31 January 2020).

Special Issue Editors

Prof. Dr. Rui A. P. Perdigão
Website SciProfiles
Guest Editor
Meteoceanics Interdisciplinary Centre for Complex System Science & CE3C, University of Lisbon, Portugal
Interests: physics of complex systems; information theory; nonlinear statistical physics; nonlinear dynamics; nonlinear statistics; fluid dynamical systems; climate dynamics; earth system dynamics; nonlinear geophysics; atmospheric physics
Prof. Dr. Naresh Devineni
Website
Guest Editor
City University of New York, Department of Civil Engineering, New York, United States
Interests: hydroclimate; precipitation extremes; spatial scaling; flood risk; climate tele-connections; bayesian learning; non-parametric models; persistent floods; reservoir management; land-atmoshpere processes

Special Issue Information

Dear Colleagues,

The Special Issue welcomes research on theoretical and applied aspects pertaining to the dynamics of precipitation and climate interactions, along with dynamical co-evolution, feedbacks, and synergies among underlying earth system processes across spatio–temporal scales.

The Special Issue further encourages discussion on transdisciplinary methods in mathematical, statistical, and computational physics, with applications to data analysis and dynamic modeling, in order to shed light on precipitation complexity and predictability, along with underlying geophysical mechanisms.

Works that focus on investigating physical causality and inference of regional precipitation regimes, transitions, extremes, and their climate interactions using statistical and dynamical frameworks are also welcome.

The methodological debate may range from traditional, nonlinear, dynamic, stochastic–dynamic, kinematic–geometric, and information–theoretical developments to emerging frameworks in mathematical physics addressing non-ergodic, thermodynamically unstable processes and interactions.

Contributions are welcome from a diverse community in meteorology, climatology, hydrology, and the broader physical geosciences, working with diverse approaches, ranging from dynamical modeling to data mining and analysis, with physical understanding in mind.

Prof. Dr. Rui A. P. Perdigão
Prof. Dr. Naresh Devineni
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 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

  • precipitation
  • climate dynamics
  • atmospheric physics
  • complex systems
  • information theory
  • nonlinear dynamics
  • nonlinear statistics
  • stochastic–dynamic modeling
  • scaling and fractals
  • extreme events

Published Papers (8 papers)

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Research

Open AccessArticle
Robustness of the Link between Precipitation in North Africa and Standard Modes of Atmospheric Variability during the Last Millennium
Climate 2020, 8(5), 62; https://doi.org/10.3390/cli8050062 - 06 May 2020
Abstract
Drought is a recurring phenomenon in North Africa, and extended dry periods can have a serious impact on economic and social structures, as well as the natural environment. Consequently, understanding the mechanisms that underlie precipitation variability in the region is a key driver [...] Read more.
Drought is a recurring phenomenon in North Africa, and extended dry periods can have a serious impact on economic and social structures, as well as the natural environment. Consequently, understanding the mechanisms that underlie precipitation variability in the region is a key driver of sustainable economic growth in activities such as agriculture, manufacturing, energy, and transport. North Africa’s climate differs significantly between coastal and inland areas. The region has a Mediterranean climate along the coast, characterized by mild, wet winters and warm, dry summers with reasonable rainfall of around 400 to 600 mm per year. The link between winter precipitation variability in this region and atmospheric patterns is assessed here using several gridded datasets of observations and reanalysis as well as model simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5) and the third phase of the Paleoclimate Modelling Intercomparison Project (PMIP) covering the last millennium. Results show that the link between the zonal wind index at 850 hPa (U850) and winter precipitation is stronger and more robust over time than the link with some well-known modes of variability, such as the North Atlantic Oscillation (NAO), Mediterranean Oscillation (MO), and Western Mediterranean Oscillation (WeMO). U850 better explains the interannual changes in winter precipitation variability in North Africa for the past decades as well as the last millennium. Both winter precipitation and U850 simulated time series present significant decreasing trends, associated with drier conditions, starting in the 19th century. This is in agreement with the reconstructed and simulated Palmer Drought Severity Index (PDSI), which shows a decreasing trend toward drying conditions in North Africa. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
A Subregional Model of System Dynamics Research on Surface Water Resource Assessment for Paddy Rice Production under Climate Change in the Vietnamese Mekong Delta
Climate 2020, 8(3), 41; https://doi.org/10.3390/cli8030041 - 12 Mar 2020
Abstract
Effective water management plays an important role in socioeconomic development in the Vietnamese Mekong Delta (VMD). The impacts of climate change and human activities (that is, domestic consumption and industrial and agricultural activities) vary in different subregions of the delta. In order to [...] Read more.
Effective water management plays an important role in socioeconomic development in the Vietnamese Mekong Delta (VMD). The impacts of climate change and human activities (that is, domestic consumption and industrial and agricultural activities) vary in different subregions of the delta. In order to provide intersectoral data for determining the significantly impacted subregions of the VMD, the present study simulated interactions between local climatic patterns, human activities, and water resources using a system dynamics modeling (SDM) approach with each subregion as an agent of the developed model. The average rainfall and temperature of 121 subregions in the VMD were collected during 1982–2012, and the future changes of climate by provinces were based on the Representative Concentration Pathways (RCP) scenarios (RCP4.5 and RCP8.5) by the end of 21st century. The assessment was based on the levels of impact of various factors, including (1) water consumption, (2) differences between evapotranspiration and rainfall, and (3) spatial distribution of salinity intrusion over the delta scale. In the coastal areas, as well as the central and upstream areas, water resources were projected to be affected by environmental changes, whereas the former, characterized by the lack of surface freshwater, would be affected at a greater scale during the dry season. Besides, the sea level rise would lead to an increase in negative impacts in the eastern coastal areas, suggesting that water-saving techniques should be applied not only for agriculture, but also for industry and domestic water consumption during the dry season. In addition, the south subregions (that is, the western subregions of the Hau River except for An Giang) were likely to be flooded due to the simulated high rainfall and seasonal rises of sea level during the wet season. Therefore, the alternative forms of settlement and livelihood should be considered toward balance management with changing delta dynamics. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
Change of the Rainfall Seasonality Over Central Peruvian Andes: Onset, End, Duration and Its Relationship With Large-Scale Atmospheric Circulation
Climate 2020, 8(2), 23; https://doi.org/10.3390/cli8020023 - 28 Jan 2020
Abstract
Changes of the onset dates, end dates, and duration of the rainy season over central Peruvian Andes (Mantaro river basin, MRB) could severely affect water resources management and the main economic activities (e.g., rainfed agriculture, raising cattle, among others). Nonetheless, these changes have [...] Read more.
Changes of the onset dates, end dates, and duration of the rainy season over central Peruvian Andes (Mantaro river basin, MRB) could severely affect water resources management and the main economic activities (e.g., rainfed agriculture, raising cattle, among others). Nonetheless, these changes have not been documented for the Tropical Andes. To asses that, we used daily datasets of observed rainfall during the 1965–2013 period. For this period, the average onset (end) date of the rainy season over the MRB occurs in the pentad 17 (19–23 September) [pentad 57 (7–11 April)]. The duration of the rainy season mainly is modulated by the onset dates due to it has higher variability than end dates. There is a reduction of 3 days/decade in the duration of wet season over the MRB for the last four decades due to the delay of the onset days. Furthermore, El Niño favors late-onset and early end of the rainy season, while La Niña favors early onset and late end of the rainy season in the MRB. Onset dates are related to the propagation of the convective region of the South American Monsoon System (SAMS), from the Caribbean region toward the central Amazon basin. Early (late)-onset days are associated with a southward (northward) shift of the South Atlantic Convergence Zone (SACZ) and weak (strong) convection over equatorial Atlantic that induces the southernmost propagation (eastward shift) of the SAMS. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
Toward a Regional-Scale Seasonal Climate Prediction System over Central Italy Based on Dynamical Downscaling
Climate 2019, 7(10), 120; https://doi.org/10.3390/cli7100120 - 05 Oct 2019
Cited by 1
Abstract
Anticipating seasonal climate anomalies is essential for defining short-term adaptation measures. To be actionable, many stakeholders require seasonal forecasts at the regional scale to be properly coupled to region-specific vulnerabilities. In this study, we present and preliminarily evaluate a regional-scale Seasonal Forecast System [...] Read more.
Anticipating seasonal climate anomalies is essential for defining short-term adaptation measures. To be actionable, many stakeholders require seasonal forecasts at the regional scale to be properly coupled to region-specific vulnerabilities. In this study, we present and preliminarily evaluate a regional-scale Seasonal Forecast System (SFS) over Central Italy. This system relies on a double dynamical downscaling performed through the Regional-scale Climate Model (RCM) RegCM4.1. A twelve-member ensemble of the NCEP-CFSv2 provides driving fields for the RegCM. In the first step, the RegCM dynamically downscales NCEP-CFSv2 predictions from a resolution of 100 to 60 km over Europe (RegCM-d1). This first downscaling drives a second downscaling over Central Italy at 12 km (RegCM-d2). To investigate the added value of the downscaled forecasts compared to the driving NCEP-CFSv2, we evaluate the driving CFS, and the two downscaled SFSs over the same (inner) domain. Evaluation involves winter temperatures and precipitations over a climatological period (1982–2003). Evaluation for mean bias, statistical distribution, inter-annual anomaly variability, and hit-rate of anomalous seasons are shown and discussed. Results highlight temperature physical values reproduction benefiting from the downscaling. Downscaled inter-annual variability and probabilistic metrics show improvement mainly at forecast lead-time 1. Downscaled precipitation shows an improved spatial distribution with an undegraded but not improved seasonal forecast quality. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
Precipitation Trends over the Indus Basin
Climate 2019, 7(10), 116; https://doi.org/10.3390/cli7100116 - 26 Sep 2019
Cited by 5
Abstract
A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with [...] Read more.
A large population relies on water input to the Indus basin, yet basinwide precipitation amounts and trends are not well quantified. Gridded precipitation data sets covering different time periods and based on either station observations, satellite remote sensing, or reanalysis were compared with available station observations and analyzed for basinwide precipitation trends. Compared to observations, some data sets tended to greatly underestimate precipitation, while others overestimate it. Additionally, the discrepancies between data set and station precipitation showed significant time trends in many cases, suggesting that the precipitation trends of those data sets were not consistent with station data. Among the data sets considered, the station-based Global Precipitation Climatology Centre (GPCC) gridded data set showed good agreement with observations in terms of mean amount, trend, and spatial and temporal pattern. GPCC had average precipitation of about 500 mm per year over the basin and an increase in mean precipitation of about 15% between 1891 and 2016. For the more recent past, since 1958 or 1979, no significant precipitation trend was seen. Among the remote sensing based data sets, the Tropical Rainfall Measuring Mission Multi-Satellite Precipitation Analysis (TMPA) compared best to station observations and, though available for a shorter time period than station-based data sets such as GPCC, may be especially valuable for parts of the basin without station data. The reanalyses tended to have substantial biases in precipitation mean amount or trend relative to the station data. This assessment of precipitation data set quality and precipitation trends over the Indus basin may be helpful for water planning and management. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
An Unusual Cold February 2019 in Saskatchewan—A Case Study Using NCEP Reanalysis Datasets
Climate 2019, 7(7), 87; https://doi.org/10.3390/cli7070087 - 03 Jul 2019
Abstract
In February 2019, central Canada, and especially the province of Saskatchewan, experienced extreme cold weather. It was the coldest February in 82 years and the second coldest in 115 years. In this study, we examine National Centers for Environmental Prediction (NCEP)/National Center for [...] Read more.
In February 2019, central Canada, and especially the province of Saskatchewan, experienced extreme cold weather. It was the coldest February in 82 years and the second coldest in 115 years. In this study, we examine National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) Reanalysis 1 data to understand the atmospheric processes leading to this cold snap. A detailed investigation of surface air temperature, sea level pressure, surface fluxes, and winds revealed a linkage between the North Pacific storm track and the February cold snap. A shift in the jet stream pattern triggered by the storm activity over the North Pacific caused a high-pressure blocking pattern, which resulted in unusual cold temperatures in Saskatchewan in February. This study demonstrates the potential for extreme cold in a warming climate; weather records in Saskatchewan show an increase in minimum winter temperature by 4–5 °C. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
An Investigation into the Spatial and Temporal Variability of the Meteorological Drought in Jordan
Climate 2019, 7(6), 82; https://doi.org/10.3390/cli7060082 - 11 Jun 2019
Cited by 3
Abstract
Following the impact of droughts witnessed during the last decade there is an urgent need to develop a drought management strategy, policy framework, and action plan for Jordan. This study aims to provide a historical baseline using the standardized precipitation index (SPI) and [...] Read more.
Following the impact of droughts witnessed during the last decade there is an urgent need to develop a drought management strategy, policy framework, and action plan for Jordan. This study aims to provide a historical baseline using the standardized precipitation index (SPI) and meteorological drought maps, and to investigate the spatial and temporal trends using long-term historical precipitation records. Specifically, this study is based on the statistical analysis of 38 years of monthly rainfall data, gathered from all 29 meteorological stations that cover Jordan. The Mann–Kendall test and linear regression analysis were used to uncover evidence of long-term trends in precipitation. Drought indices were used for calculating the meteorological SPI on an annual (SPI12), 6-months (SPI6), and 3-months basis (SPI3). At each level, every drought event was characterized according to its duration, interval, and intensity. Then, drought maps were generated using interpolation kriging to investigate the spatial extent of drought events, while drought patterns were temporally characterized using multilinear regression and spatial grouped using the hierarchical clustering technique. Both annual and monthly trend analyses and the Mann–Kendall test indicated significant reduction of precipitation in time for all weather stations except for Madaba. The rate of decrease is estimated at approximately 1.8 mm/year for the whole country. The spatial SPI krig maps that were generated suggest the presence of two drought types in the spatial dimension: Local and national. Local droughts reveal no actual observed trends or repeatable patterns of occurrence. However, looking at meteorological droughts across all time scales indicated that Jordan is facing an increasing number of local droughts. With a probability of occurrence of once every two years to three years. On the other hand, extreme national droughts occur once every 15 to 20 years and last for two or more consecutive years. Linear trends indicated significant increase in drought magnitude by time with a rate of 0.02 (p < 0.0001). Regression analysis indicated that draught in Jordan is time dependent (p < 0.001) rather than being spatially dependent (p > 0.99). Hierarchical clustering was able to group national draughts into three zones, namely the northern zone, the eastern zone, and the southern zone. This study highlights the urgent need for a monitoring program to investigate local and national drought impacts on all sectors, as well as the development of a set of proactive risk management measures and preparedness plans for various physiographic regions. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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Open AccessArticle
Developing Gridded Climate Data Sets of Precipitation for Greece Based on Homogenized Time Series
Climate 2019, 7(5), 68; https://doi.org/10.3390/cli7050068 - 16 May 2019
Cited by 3
Abstract
The creation of realistic gridded precipitation fields improves our understanding of the observed climate and is necessary for validating climate model output for a wide range of applications. The challenge in trying to represent the highly variable nature of precipitation is to overcome [...] Read more.
The creation of realistic gridded precipitation fields improves our understanding of the observed climate and is necessary for validating climate model output for a wide range of applications. The challenge in trying to represent the highly variable nature of precipitation is to overcome the lack of density of observations in both time and space. Data sets of mean monthly and annual precipitations were developed for Greece in gridded format with an analysis of 30 arcsec (∼800 m) based on data from 1971 to 2000. One hundred and fifty-seven surface stations from two different observation networks were used to cover a satisfactory range of elevations. Station data were homogenized and subjected to quality control to represent changes in meteorological conditions rather than changes in the conditions under which the observations were made. The Meteorological Interpolation based on Surface Homogenized Data Basis (MISH) interpolation method was used to develop data sets that reproduce, as closely as possible, the spatial climate patterns over the region of interest. The main geophysical factors considered for the interpolation of mean monthly precipitation fields were elevation, latitude, incoming solar irradiance, Euclidian distance from the coastline, and land-to-sea percentage. Low precipitation interpolation uncertainties estimated with the cross-validation method provided confidence in the interpolation method. The resulting high-resolution maps give an overall realistic representation of precipitation, especially in fall and winter, with a clear longitudinal dependence on precipitation decreasing from western to eastern continental Greece. Full article
(This article belongs to the Special Issue From Local to Global Precipitation Dynamics and Climate Interaction)
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