scholarly journals Nature of extreme precipitation over Ukraine in the 21st century

2018 ◽  
pp. 36-45
Author(s):  
V. F. Martazinova ◽  
O. Shchehlov
Keyword(s):  
Comparative Analysis ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Human Life ◽  
Precipitation Amount ◽  
Precipitation Rate ◽  
Monthly Precipitation ◽  
Threshold Values ◽  
Precipitation Regime ◽  
Carpathian Region

The article examines the state of precipitation over the territory of Ukraine over recent decades. Through the example of central months of the seasons differences in monthly and average daily precipitation amounts for the period of 2000-2014 are shown. Within the most territory of Ukraine summer precipitation is almost twice as high as spring and autumn one. During all seasons the greatest amount of precipitation is observed in the Carpathian region. Distribution of average long-term precipitation values over the rest of the territory coincides in spring, summer and autumn: the highest precipitation values are observed in the western and north-western parts and decrease to the south-east. The article studies a yearly precipitation rate at low-land and mountain meteorological stations. It proposes to separate criteria of precipitation extremality depending on the regions. All extreme daily precipitation can be divided into the following categories: > 20-30 mm / day, > 30-50 mm / day, > 50 mm / day. Each category of extreme precipitation has its a certain economic risk, but the third class can cause not only economic risks, but also risks associated with human life and activities. The distinct feature of the present-day precipitation consists in redistribution of precipitation in the middle of the months, when a daily precipitation rate increases together with intervals between heavy rains. In order to analyze the changes of precipitation regime, the approach of dividing the rates of monthly precipitation amount by the rates of extreme and non-extreme precipitation is proposed. A comparative analysis of daily precipitation in different seasons and over different climatic periods was also carried out. The article studies the proportion of daily precipitation of up to 15 mm and the one exceeding 15 mm forming a part of monthly rates of precipitation over the territory of Ukraine. In January, rainfalls exceeding 15 mm make up from 5-10 % of the total amount of monthly precipitation, except the Carpathian region and the southwestern regions of Ukraine where those exceed 20-25 %. In spring, the amount of rainfalls increases and its percentage of the monthly precipitation amount is around 20 % over most of the regions. Until summer, the amount of rainfalls increases and in July its percentage is 50-70 %. Until autumn, the amount of those starts decreasing, however, the percentage of rainfalls is almost twice as high as in spring, and for most of the regions it is about 30-40 %. Such breakdown of the monthly precipitation rates into two components allows determination during a period in question of precipitation amounts we have each month. The maximum daily precipitation amounts serve as an important indicator of the precipitation regime which shows the potential danger from extreme precipitation. For different regions the threshold values of the upper limit of rainfalls taken as a maximum daily value for the period of 2000-2014 differ. In winter and spring time, the limit of rainfalls amount per day usually hits 20-30 mm for the most territory of the country. At the same time there are certain areas where the limit values of the daily rainfalls rate reach 40-50 mm. The most significant rainfalls are observed in summer. Despite the fact that the territory of such rainfalls is quite patchy, nevertheless, those areas where precipitation rate over one day may reach 70 mm are the most vulnerable and have high risks for human life and activities. In autumn, the threshold values are 30-40 mm. The breakdown of the rates of monthly precipitation amount into extreme and non-extreme ones allows determination in future of whether the precipitation regime changes because of extreme or non-extreme values. Also, in the long run, a comparative analysis of the rates of showers and weak rainfalls in the late 20th and early 21st centuries can be carried out and a tendency of precipitation regime seasonal change over the next decade can be obtained which will help us to identify vulnerable regions suffering from extreme precipitation rates.

Evaluation of High-Resolution Precipitation Products over Southwest China

2020 ◽  
Vol 21 (11) ◽  
pp. 2691-2712
Author(s):  
Yanbo Nie ◽  
Jianqi Sun
Keyword(s):  
High Resolution ◽  
Root Mean Square ◽  
Extreme Precipitation ◽  
Southwest China ◽  
Daily Precipitation ◽  
The Other ◽  
Future Research ◽  
Monthly Precipitation ◽  
Mean Square ◽  
Mean Square Errors

AbstractThe evaluation of gridded high-resolution precipitation products (HRPPs) is important in areas with complex topography, because rain gauges that are unevenly and sparsely distributed over an area cannot effectively reflect the spatial variabilities of the precipitation and related extremes in detail. In this study, the applicability of six satellite-based precipitation products (TMPA 3B42V7, IMERG, GSMaP-Gauge, CMORPH-CRT, PERSIANN-CDR, and GPCP) and five gauge-based precipitation products (APHRODITE, CN05.1, GPCC-D, GPCC-M, and CRU) over southwest China from 1998 to 2016 is evaluated by performing a comparison with meteorological station observations. The results show that GPCC-M exhibits the best performances for annual, seasonal, and monthly precipitation, which is supported by the lowest root-mean-square errors (RMSEs) for annual and seasonal precipitation and the lowest normalized root-mean-square error (NRMSE) for monthly precipitation. According to the NRMSE and critical success index (CSI), CN05.1 outperforms the other HRPPs at detecting daily precipitation; however, CN05.1 tends to overestimate the frequencies of light precipitation and underestimate the frequencies of heavy precipitation, which is reflected by the probability density function (PDF) for daily precipitation. The bias ratio (BIAS) and extreme precipitation indices show that IMERG shows numerous advantages over the other HRPPs in detecting extreme precipitation and estimating the precipitation intensity. Such results are helpful for future research on precipitation/extremes and related hydrometeorological disasters that occur throughout southwest China.

scholarly journals Evaluation of Precipitation Estimation Accuracy in Reanalyses, Satellite Products, and an Ensemble Method for Regions in Australia and South and East Asia

2013 ◽  
Vol 14 (4) ◽  
pp. 1323-1333 ◽  
Author(s):  
Jorge L. Peña-Arancibia ◽  
Albert I. J. M. van Dijk ◽  
Luigi J. Renzullo ◽  
Mark Mulligan
Keyword(s):  
East Asia ◽  
Precipitation Amount ◽  
Department Of Energy ◽  
Estimation Accuracy ◽  
Monthly Precipitation ◽  
Precipitation Regime ◽  
Monsoon Period ◽  
Ensemble Mean ◽  
Precipitation Estimation ◽  
Precipitation Estimates

Abstract Precipitation estimates from reanalyses and satellite observations are routinely used in hydrologic applications, but their accuracy is seldom systematically evaluated. This study used high-resolution gauge-only daily precipitation analyses for Australia (SILO) and South and East Asia [Asian Precipitation—Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE)] to calculate the daily detection and accuracy metrics for three reanalyses [ECMWF Re-Analysis Interim (ERA-Interim), Japanese 25-yr Reanalysis (JRA-25), and NCEP–Department of Energy (DOE) Global Reanalysis 2] and three satellite-based precipitation products [Tropical Rainfall Measuring Mission (TRMM) 3B42V6, Climate Prediction Center morphing technique (CMORPH), and Precipitation Estimation from Remotely Sensed Imagery Using Artificial Neural Networks (PERSIANN)]. A depth-frequency-adjusted ensemble mean of the reanalyses and satellite products was also evaluated. Reanalyses precipitation from ERA-Interim in southern Australia (SAu) and northern Australasia (NAu) showed higher detection performance. JRA-25 had a better performance in South and East Asia (SEA) except for the monsoon period, in which satellite estimates from TRMM and CMORPH outperformed the reanalyses. In terms of accuracy metrics (correlation coefficient, root-mean-square difference, and a precipitation intensity proxy, which is the ratio of monthly precipitation amount to total days with precipitation) and over the three subdomains, the depth-frequency-adjusted ensemble mean generally outperformed or was nearly as good as any of the single members. The results of the ensemble show that additional information is captured from the different precipitation products. This finding suggests that, depending on precipitation regime and location, combining (re)analysis and satellite products can lead to better precipitation estimates and, thus, more accurate hydrological applications than selecting any single product.

scholarly journals Seasonality of runoff and precipitation regimes along transects in Peru and Austria

2017 ◽  
Vol 65 (4) ◽  
pp. 347-358 ◽  
Author(s):  
Maria M. Cárdenas Gaudry ◽  
Dieter Gutknecht ◽  
Juraj Parajka ◽  
Rui A.P. Perdigão ◽  
Günter Blöschl
Keyword(s):  
Spatial Variation ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Circular Statistics ◽  
Monthly Precipitation ◽  
Annual Maximum ◽  
Discharge Data ◽  
Precipitation Regimes ◽  
Daily Precipitation Data ◽  
Monthly Runoff

AbstractThe aim of this study is to understand the seasonalities of runoff and precipitation and their controls along two transects in Peru and one transect in Austria. The analysis is based on daily precipitation data at 111 and 61 stations in Peru and Austria, respectively, and daily discharge data at 51 and 110 stations. The maximum Pardé coefficient is used to quantify the strength of the seasonalities of monthly precipitation and runoff. Circular statistics are used to quantify the seasonalities of annual maximum daily precipitation and annual maximum daily runoff. The results suggest that much larger spatial variation in seasonality in Peru is because of the large diversity in climate and topography. In the dry Peruvian lowlands of the North, the strength of the monthly runoff seasonality is smaller than that of precipitation due to a relatively short rainy period from January to March, catchment storage and the effect of upstream runoff contributions that are more uniform within the year. In the Peruvian highlands in the South, the strength of the monthly runoff seasonality is greater than that of precipitation, or similar, due to relatively little annual precipitation and rather uniform evaporation within the year. In the Austrian transect, the strength of the runoff seasonality is greater than that of precipitation due to the influence of snowmelt in April to June. The strength of monthly regime of precipitation and runoff controls the concentration of floods and extreme precipitation in Peruvian transects. The regions with strong monthly seasonality of runoff have also extreme events concentrated along the same time of the year and the occurrence of floods is mainly controlled by the seasonality of precipitation. In Austria, the monthly runoff maxima and floods occur in the same season in the Alps. In the lowlands, the flood seasonality is controlled mainly by summer extreme precipitation and its interplay with larger soil moisture. The analyses of precipitation and runoff data along topographic gradients in Peru and Austria showed that, overall, in Peru the spatial variation in seasonality is much larger than in Austria. This is because of the larger diversity in climate and topography.

Daily precipitation characteristics of RegCM4 and WRF in China and their interannual variations

2020 ◽  
Vol 82 ◽  
pp. 97-115
Author(s):  
X Kong ◽  
A Wang ◽  
X Bi ◽  
J Wei
Keyword(s):  
Extreme Precipitation ◽  
Climate Models ◽  
Daily Precipitation ◽  
Regional Climate ◽  
Precipitation Amount ◽  
Extreme Rainfall ◽  
Horizontal Resolution ◽  
Interannual Variations ◽  
Precipitation Frequency ◽  
Precipitation Characteristics

To evaluate and clarify the daily precipitation characteristics (i.e. amount, frequency and intensity) of the regional climate models (RCMs) in China, long-term simulations were carried out using RegCM4.5 and Weather Research and Forecasting model (WRF), which were nested within the European Centre for Medium-Range Weather Forecasts (ECMWF)’s 20th century reanalysis (ERA-20C) between 1901 and 2010. The 2 RCMs were initially run at a resolution of 50 km. Analyses mainly compared the model-simulated climatic means and interannual variations of precipitation characteristics with those of dense and high-quality station observations (STN) from 1961-2010. Both models satisfactorily reproduced the seasonal mean precipitation amount, but they overestimated its frequency and underestimated its intensity. Extreme rainfall frequency was also underestimated by both RCMs. In winter (DJF), the interannual variabilities in dry days, light precipitation and moderate precipitation were well represented by both models. However, they poorly reproduced the counterparts of extreme precipitation in winter. In summer (JJA), the 2 RCMs performed well in simulating the interannual variability of extreme precipitation. Comparably, RegCM outperformed WRF in reproducing the spatial patterns of precipitation amount, interannual variations in extreme precipitation and rain events. By contrast, WRF better represented precipitation frequency in different sub-regions overall. Moreover, when the horizontal resolution of RegCM was increased from 50 to 25 km, there was a slight improvement in the representation of precipitation amount and intensity. Our results show that RCMs perform well in reproducing actual climatic means and interannual variations of daily precipitation characteristics in China, and that high-resolution RCM simulations can produce improved results for precipitation amount and intensity.

scholarly journals Assessment of GPM-Era Satellite Products’ (IMERG and GSMaP) Ability to Detect Precipitation Extremes over Mountainous Country Nepal

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 254
Author(s):  
Bikash Nepal ◽  
Dibas Shrestha ◽  
Shankar Sharma ◽  
Mandira Singh Shrestha ◽  
Deepak Aryal ◽  
...  
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Probability Of Detection ◽  
Precipitation Extremes ◽  
Extreme Precipitation Events ◽  
Precipitation Measurement ◽  
Global Precipitation Measurement ◽  
Global Precipitation ◽  
Precipitation Events

The reliability of satellite precipitation products is important in climatic and hydro-meteorological studies, which is especially true in mountainous regions because of the lack of observations in these areas. Two recent satellite rainfall estimates (SREs) from Global Precipitation Measurement (GPM)-era—Integrated Multi-Satellite Retrievals for Global Precipitation Measurement (IMERG-V06) and gauge calibrated Global Satellite Mapping of Precipitation (GSMaP-V07) are evaluated for their spatiotemporal accuracy and ability to capture extreme precipitation events using 279 gauge stations from southern slope of central Himalaya, Nepal, between 2014 and 2019. The overall result suggests that both SREs can capture the spatiotemporal precipitation variability, although they both underestimated the observed precipitation amount. Between the two, the IMERG product shows a more consistent performance with a higher correlation coefficient (0.52) and smaller bias (−2.49 mm/day) than the GSMaP product. It is worth mentioning that the monthly gauge-calibrated IMERG product yields better detection capability (higher probability of detection (POD) values) of daily precipitation events than the daily gauge calibrated GSMaP product; however, they both show similar performance in terms of false alarm ratio (FAR) and critical success index (CSI). Assessment based on extreme precipitation indices revealed that the IMERG product outperforms GSMaP in capturing daily precipitation extremes (RX1Day and RX5Day). In contrast, the GSMaP product tends to be more consistent in capturing the duration and threshold-based precipitation extremes (consecutive dry days (CDD), consecutive wet days (CWD), number of heavy precipitation days (R10mm), and number of extreme precipitation days (R25mm)). Therefore, it is suggested that the IMERG product can be a good alternative for monitoring daily extremes; meanwhile, GSMaP could be a better option for duration-based extremes in the mountainous region.

Temporal Changes in the Areal Coverage of Daily Extreme Precipitation in the Northeastern United States Using High-Resolution Gridded Data

2020 ◽  
Vol 59 (3) ◽  
pp. 551-565
Author(s):  
Arthur T. DeGaetano ◽  
Griffin Mooers ◽  
Thomas Favata
Keyword(s):  
United States ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Precipitation Amount ◽  
Heavy Precipitation ◽  
Northeastern United States ◽  
Precipitation Frequency ◽  
Polygon Area ◽  
Areal Precipitation ◽  
Grid Points

AbstractTime-dependent changes in extreme precipitation occurrence across the northeastern United States are evaluated in terms of areal extent. Using gridded precipitation data for the period from 1950 to 2018, polygons are defined that are based on isohyets corresponding to extreme daily precipitation accumulations. Across the region, areal precipitation is characterized on the basis of the annual and seasonal number of extreme precipitation polygons and the area of the polygons. Using the subset of grid points that correspond to station locations in the northeastern United States, gridded precipitation replicates the observed trends in extreme precipitation based on station observations. Although the number of extreme precipitation polygons does not change significantly through time, there is a marked increase in the area covered by the polygons. The median annual polygon area nearly doubles from 1950 to 2013. Consistent results occur for percentiles other than the median and a range of extreme precipitation amount thresholds, with the most pronounced changes observed in spring and summer. Like trends in station data, outside the northeastern United States trends in extreme precipitation polygon area are negative, particularly in the western United States, or they are not statistically significant. Collectively, the results suggest that the increases in heavy precipitation frequency and amount observed at stations in the northeastern United States are a manifestation of an expansion of the spatial area over which extreme precipitation occurs rather than a change in the number of unique extreme precipitation polygons.

Human development in the informational economy: challenges to social policy

2020 ◽  
pp. 13-19
Author(s):  
Lyubov Semiv
Keyword(s):  
Social Policy ◽  
Human Development ◽  
Formal Education ◽  
Human Life ◽  
State Regulation ◽  
Sample Survey ◽  
Internet Services ◽  
Carpathian Region ◽  
Search For Information ◽  
Use Of Internet

The scientific hypothesis about the influence of the components of the informational environment on the expansion of human development is tested. The trends in the Ukrainian information space on the level of implementation of informational technology in human life are revealed. The sample survey about living conditions of households in Ukraine in general and the oblasts of the Carpathian region, in particular, is conducted. The ways of use of Internet services by households for involvement of the population in various spheres of public activity and their influence on human development of the oblasts of the Carpathian region are analyzed. The analysis showed a significant reduction in the share of households by objectives: education and training (formal education in school and higher education, distance education, including online activities); software download. The search for information related to health issues and interaction with public authorities has great potential for human development. The paper concludes that the population of the Carpathian region is insufficiently involved in the use of Internet services. Based on the analysis of indicators of the Global Competitiveness Index, the problems in the field of expanding human development opportunities in Ukraine are described. There is mainly a downward trend in the development of areas involved in expanding human development opportunities in the transition to the information economy - education, health, labor, science and innovation. Relevant guidelines for the implementation of state social policy in this area are identified. Social policy as a direction of state regulation of the economy requires a transition from mostly passive to active and effective state social policy. It is necessary to update the mechanisms for conducting active social policy at the level of the state, various administrative, public organizations, and enterprises. Social policy must be closely linked with the implementation of internal reforms in the country (education, health, pensions, taxes and wages, etc.). Social policy measures should be coordinated with measures of other types of state policy - migration, the formation and development of the middle class, the policy of investing in human capital.

scholarly journals Different algorithms, different models

2021 ◽  
Author(s):  
Martyna Daria Swiatczak
Keyword(s):  
Comparative Analysis ◽  
Real World ◽  
Qualitative Comparative Analysis ◽  
Comparative Methods ◽  
Data Sets ◽  
Simulation Studies ◽  
Threshold Values ◽  
Real World Data ◽  
Software Packages ◽  
Methodological Approaches

AbstractThis study assesses the extent to which the two main Configurational Comparative Methods (CCMs), i.e. Qualitative Comparative Analysis (QCA) and Coincidence Analysis (CNA), produce different models. It further explains how this non-identity is due to the different algorithms upon which both methods are based, namely QCA’s Quine–McCluskey algorithm and the CNA algorithm. I offer an overview of the fundamental differences between QCA and CNA and demonstrate both underlying algorithms on three data sets of ascending proximity to real-world data. Subsequent simulation studies in scenarios of varying sample sizes and degrees of noise in the data show high overall ratios of non-identity between the QCA parsimonious solution and the CNA atomic solution for varying analytical choices, i.e. different consistency and coverage threshold values and ways to derive QCA’s parsimonious solution. Clarity on the contrasts between the two methods is supposed to enable scholars to make more informed decisions on their methodological approaches, enhance their understanding of what is happening behind the results generated by the software packages, and better navigate the interpretation of results. Clarity on the non-identity between the underlying algorithms and their consequences for the results is supposed to provide a basis for a methodological discussion about which method and which variants thereof are more successful in deriving which search target.

scholarly journals ENSO and Wintertime Extreme Precipitation Events over the Contiguous United States

2008 ◽  
Vol 21 (1) ◽  
pp. 22-39 ◽  
Author(s):  
Siegfried D. Schubert ◽  
Yehui Chang ◽  
Max J. Suarez ◽  
Philip J. Pegion
Keyword(s):  
United States ◽  
West Coast ◽  
Extreme Precipitation ◽  
East Coast ◽  
Daily Precipitation ◽  
Precipitation Variability ◽  
The West ◽  
Extreme Precipitation Events ◽  
The Impact ◽  
Precipitation Events

Abstract In this study the authors examine the impact of El Niño–Southern Oscillation (ENSO) on precipitation events over the continental United States using 49 winters (1949/50–1997/98) of daily precipitation observations and NCEP–NCAR reanalyses. The results are compared with those from an ensemble of nine atmospheric general circulation model (AGCM) simulations forced with observed SST for the same time period. Empirical orthogonal functions (EOFs) of the daily precipitation fields together with compositing techniques are used to identify and characterize the weather systems that dominate the winter precipitation variability. The time series of the principal components (PCs) associated with the leading EOFs are analyzed using generalized extreme value (GEV) distributions to quantify the impact of ENSO on the intensity of extreme precipitation events. The six leading EOFs of the observations are associated with major winter storm systems and account for more than 50% of the daily precipitation variability along the West Coast and over much of the eastern part of the country. Two of the leading EOFs (designated GC for Gulf Coast and EC for East Coast) together represent cyclones that develop in the Gulf of Mexico and occasionally move and/or redevelop along the East Coast producing large amounts of precipitation over much of the southern and eastern United States. Three of the leading EOFs represent storms that hit different sections of the West Coast (designated SW for Southwest coast, WC for the central West Coast, and NW for northwest coast), while another represents storms that affect the Midwest (designated by MW). The winter maxima of several of the leading PCs are significantly impacted by ENSO such that extreme GC, EC, and SW storms that occur on average only once every 20 years (20-yr storms) would occur on average in half that time under sustained El Niño conditions. In contrast, under La Niña conditions, 20-yr GC and EC storms would occur on average about once in 30 years, while there is little impact of La Niña on the intensity of the SW storms. The leading EOFs from the model simulations and their connections to ENSO are for the most part quite realistic. The model, in particular, does very well in simulating the impact of ENSO on the intensity of EC and GC storms. The main model discrepancies are the lack of SW storms and an overall underestimate of the daily precipitation variance.

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