scholarly journals Characteristics and Changes of Extreme Precipitation in the Yellow–Huaihe and Yangtze–Huaihe Rivers Basins, China

2011 ◽  
Vol 24 (14) ◽  
pp. 3781-3795 ◽  
Author(s):  
Quan Dong ◽  
Xing Chen ◽  
Tiexi Chen
Keyword(s):  
Monte Carlo ◽  
Spatial Distribution ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Poyang Lake ◽  
Yellow River ◽  
Statistical Significance ◽  
Monte Carlo Experiment ◽  
Huaihe River ◽  
Daily Precipitation Data

Abstract Many works suggest that the intensity of extreme precipitation might be changing under the background of global warming. Because of the importance of extreme precipitation in the Yellow–Huaihe and Yangtze–Huaihe River basins of China and to compare the spatial difference, the generalized Pareto distribution (GPD) function is used to fit the daily precipitation series in these basins and an estimate of the extreme precipitation spatial distribution is presented. At the same time, its long-term trends are estimated for the period between 1951 and 2004 by using a generalized linear model (GLM), which is based on GPD. High quality daily precipitation data from 215 observation stations over the area are used in this study. The statistical significance of the trend fields is tested with a Monte Carlo experiment based on a two-dimensional Hurst coefficient, H2. The spatial distribution of the shape parameter of GPD indicates that the upper reaches of the Huaihe River (HuR) basin have the largest probability of extreme rainfall events, which is consistent with most historical flood records in this region. Spatial variations in extreme precipitation trends are found and show significant positive trends in the upper reaches of Poyang Lake in the Yangtze River (YaR) basin and a significant negative trend in the mid- to lower reaches of the Yellow River (YeR) and Haihe River (HaR) basins. The trends in the HuR basin and the lower reaches of Poyang Lake in the YaR basin are nearly neutral. All trend fields are significant at the 5% level of significance from the Monte Carlo experiments.

scholarly journals Spatial distribution of extreme precipitation in the Tibetan Plateau and effects of external forcing factors based on Generalized Pareto distribution

2020 ◽  
Author(s):  
Jiajia Gao ◽  
Jun Du ◽  
Xiaoqing Huang
Keyword(s):  
Spatial Distribution ◽  
Extreme Precipitation ◽  
Pareto Distribution ◽  
Daily Precipitation ◽  
Generalized Pareto Distribution ◽  
The Tibetan Plateau ◽  
External Forcing ◽  
Maximum Rainfall ◽  
Flood Season ◽  
Generalized Pareto

Abstract The daily precipitation data of the years 1955–2017 from May to September were retrieved; then a Generalized Pareto Distribution (GPD) and maximum likelihood methods were adopted to understand trends and calculate the reappearance period of heavy precipitation in the Tibetan Plateau (TP). The daily precipitation values at 22 stations in the TP were found to conform to the model, and theoretical and measured frequencies were consistent. According to the spatial distribution of the maximum precipitation value, the extreme values of Shigatse and Lhasa showed large fluctuations, and the probability of record-breaking precipitation events was low. In the western part of Nagqu, the probability of extreme precipitation was relatively low, and that of record-breaking precipitation was relatively high. The peak values of extreme precipitation in the flood season in the TP generally exhibited a decreasing trend from southeast to northwest, and the extreme value of the flood season that reappeared in the southeast region was approximatelytwice that of the northwest region. The maximum rainfall in most areas will exceed 20 mm in the next 5–10 years, and the maximum rainfall in Shigatse will reach 52.7 mm. After 15 years of recurrence in various regions, the peak rainfall in the flood season has become low. Most of the regions in the model have different responses to ENSO and Indian Ocean monsoon indices with external forcing factors.

scholarly journals Bias Correction of Zero-Inflated RCM Precipitation Fields: A Copula-Based Scheme for Both Mean and Extreme Conditions

2019 ◽  
Vol 20 (4) ◽  
pp. 595-611 ◽  
Author(s):  
Rajib Maity ◽  
Mayank Suman ◽  
Patrick Laux ◽  
Harald Kunstmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Extreme Precipitation ◽  
Joint Distribution ◽  
Daily Precipitation ◽  
Extreme Values ◽  
Entire Study ◽  
Daily Precipitation Data ◽  
Zero Values ◽  
The Mean

Abstract Changes in extreme precipitation due to climate change often require the application of methods to bias correct simulated atmospheric fields, including extremes. Most existing bias correction techniques (i) only focus on the bias in the mean value or on the extreme values separately, and (ii) exclude zero values from analysis, even though their presence is significant in daily precipitation. We developed a copula-based bias correction scheme that is suitable for zero-inflated daily precipitation data to correct the bias in mean as well as in extreme precipitation at any specific statistical quantile. In considering the whole of Germany as a test bed, the proposed scheme is found to work well across the entire study area, including the German Alpine regions. The joint distribution between observed and regional climate model (RCM)-derived precipitation is developed through copulas. In particular, the joint distribution is modified to make it discrete at zero in order to account for zero values. The benefit of considering zero precipitation values is revealed through the improved performance of bias correction both in the mean and extreme values. Second, the quantile that best captures the bias (whether in the mean or any extreme value) is determined for a specific location and varies spatially and seasonally. This relaxation in selecting the location-specific optimal quantile renders the proposed methodology spatially transferable. By acknowledging possible changes in extreme precipitation due to climate change, the proposed scheme is expected to be suitable for climate change impact assessments for extreme events worldwide.

scholarly journals Identifying hydro-meteorological events from precipitation extremes indices and other sources over northern Namibia, Cuvelai Basin

2015 ◽  
Vol 7 (1) ◽  
Author(s):  
Frans C. Persendt ◽  
Christopher Gomez ◽  
Peyman Zawar-Reza
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Economic Losses ◽  
Precipitation Data ◽  
Rainfall Station ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Dry Spell ◽  
Flood Disasters ◽  
Precipitation Indices

Worldwide, more than 40% of all natural hazards and about half of all deaths are the result of flood disasters. In northern Namibia flood disasters have increased dramatically over the past half-century, along with associated economic losses and fatalities. There is a growing concern to identify these extreme precipitation events that result in many hydro-meteorological disasters. This study presents an up to date and broad analysis of the trends of hydrometeorological events using extreme daily precipitation indices, daily precipitation data from the Grootfontein rainfall station (1917–present), regionally averaged climatologies from the gauged gridded Climate Research Unit (CRU) product, archived disasters by global disaster databases, published disaster events in literature as well as events listed by Mendelsohn, Jarvis and Robertson (2013) for the data-sparse Cuvelai river basin (CRB). The listed events that have many missing data gaps were used to reference and validate results obtained from other sources in this study. A suite of ten climate change extreme precipitation indices derived from daily precipitation data (Grootfontein rainfall station), were calculated and analysed. The results in this study highlighted years that had major hydro-meteorological events during periods where no data are available. Furthermore, the results underlined decrease in both the annual precipitation as well as the annual total wet days of precipitation, whilst it found increases in the longest annual dry spell indicating more extreme dry seasons. These findings can help to improve flood risk management policies by providing timely information on historic hydro-meteorological hazard events that are essential for early warning and forecasting.

scholarly journals Annual and Seasonal Precipitation and Their Extremes over the Tibetan Plateau and Its Surroundings in 1963–2015

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 620
Author(s):  
Jin Ding ◽  
Lan Cuo ◽  
Yongxin Zhang ◽  
Cunjie Zhang ◽  
Liqiao Liang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The Tibetan Plateau ◽  
Opposite Pattern ◽  
Westerly Jet ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Moisture Transports ◽  
Precipitation Events

Based on daily precipitation data from 115 climate stations, seasonal and annual precipitation and their extremes over the Tibetan Plateau and its surroundings (TPS) in 1963–2015 are investigated. There exists a clear southeast-northwest gradient in precipitation and extreme daily precipitation but an opposite pattern for the consecutive dry days (CDDs). The wet southeast is trending dry while the dry center and northwest are trending wet in 1963–2015. Correspondingly, there is a drying tendency over the wet basins in the southeast and a wetting tendency over the dry and semi-dry basins in the center and northwest in summer, which will affect the water resources in the corresponding areas. The increase (decrease) in precipitation tends to correspond to the increase (decrease) in maximum daily precipitation but the decrease (increase) in CDDs. Extreme precipitation events with 20-year, 50-year, 100-year, and 200-year recurrence occurred frequently in the past decades especially in the 1980s. The greatest extreme precipitation events tend to occur after the late 1990s and in the southeastern TPS. The ERA5 reanalysis and climate system indices reveal that (1) decreased moisture transports to the southeast in summer due to the weakening of the summer monsoons and the East Asian westerly jet; (2) increased moisture transports to the center in winter due to the strengthening of the winter westerly jet and north Atlantic oscillation; and (3) decreased instability over the southeast thus suppressing precipitation and increased instability over the northwest thus promoting precipitation. All these are conducive to the drying trends in the southeast and the wetting trends in the center.

scholarly journals CHARAKTERYSTYKA OPADÓW ATMOSFERYCZNYCH W GORZOWIE WIELKOPOLSKIM W LATACH 1951–2016

1970 ◽  
pp. 133-149
Author(s):  
KATARZYNA SZYGA-PLUTA ◽  
DOMINIKA WOJTKOWIAK
Keyword(s):  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Precipitation Data ◽  
Atmospheric Front ◽  
Precipitation Occurrence ◽  
Daily Precipitation Data ◽  
Synoptic Conditions ◽  
Average Precipitation ◽  
Research Period

The purpose of the work is to characterize the precipitation occurrence and the synoptic conditions of the extreme cases in Gorzów Wielkopolski. In the paper the daily precipitation data from IMGW-PIB for Gorzów Wielkopolski station in years 1951–2016 were used. The average monthly, annual and seasonal sums were calculated and the intensity of precipitation was analyzed. Days without any precipitation were also included. Special attention was paid to extreme precipitation cases and their synoptic conditions. The average precipitation in the research period was 547,1 mm. On average, as much as 80% during the year were days with very low (0.1–1.0 mm) and low (1.1–5.0 mm) precipitation, and 13% with moderate (5.1–10.0 mm). Extreme daily precipitation totals in Gorzów Wielkopolski (95th percentile) occur mainly in summer and spring. They are associated with the transition of the atmospheric front or with the development of convection over heated land.

scholarly journals Assessment of temporal change in the tails of probability distribution of daily precipitation over India due to climatic shift in 1970s

2021 ◽  
Author(s):  
Neha Gupta ◽  
Sagar Rohidas Chavan
Keyword(s):  
Extreme Precipitation ◽  
Temporal Change ◽  
Daily Precipitation ◽  
Tail Behavior ◽  
Water Control ◽  
Error Norm ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data ◽  
Time Periods ◽  
Heavy Tailed

Abstract Daily precipitation extremes are crucial in the hydrological design of major water control structures and are expected to show a changing tendency over time due to climate change. The magnitude and frequency of extreme precipitation can be assessed by studying the upper tail behavior of probability distributions of daily precipitation. Depending on the tail behavior, the distributions can be classified into two categories: heavy-tailed and light-tailed distributions. Heavier tails indicate more frequent occurrences of extreme precipitation events. In this paper, we have analyzed the temporal change in the tail behavior of daily precipitation over India from pre- to post-1970 time periods as per the global climatic shift. A modified Probability Ratio Mean Square Error norm is used to identify the best-fit distribution to the tails of daily precipitation among four theoretical distributions (e.g., Pareto-type II, Lognormal, Weibull, and Gamma distributions). The results indicate that the Lognormal distribution, which is a heavy-tailed distribution, fits the tails of daily precipitation for the majority of the grids. It is inferred from the study that there is an increase in the heaviness of tails of daily precipitation data over India from pre- to post-1970 time periods.

Global scaling of observed sub-daily precipitation extremes to dewpoint temperature

2020 ◽  
Author(s):  
Haider Ali ◽  
Hayley Fowler ◽  
Geert Lenderink ◽  
Elizabeth Lewis
Keyword(s):  
Air Temperature ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
The United States ◽  
Precipitation Extremes ◽  
Precipitation Data ◽  
Lower Altitude ◽  
Dewpoint Temperature ◽  
Extreme Precipitation Events ◽  
Daily Precipitation Data

<p>The intensity and frequency of extreme precipitation events have increased globally and are likely to rise further under the warming climate. The Clausius-Clapeyron (CC) relationship (scaling) provides a physical basis to understand the relationship of precipitation extremes with temperature. Recent studies have used global sub-daily precipitation data from satellite, reanalysis and climate model outputs (due to the limited availability of long term observed sub-daily data at global scales) and have reported a higher sensitivity of sub-daily precipitation extremes to surface air temperature than for daily extremes. Moreover, at higher temperatures, moisture availability becomes the dominant driver of extreme precipitation, therefore, dewpoint temperature can be a better scaling variable to overcome humidity limitations as compared to air temperature. Here, we used hourly precipitation data from the Global Sub-daily Rainfall (GSDR) dataset and daily dewpoint temperature data (DPT) from the Met Office Hadley Centre observations dataset (HadISD) at 6695 locations across the United States of America, Australia, Europe, Japan, India and Malaysia. We found that more than 60% of locations (scaling estimated for individual location) show scaling greater than 7%/K (CC rate). Moreover, more than 55% of locations across Europe, Japan, Australia and Malaysia show scaling greater than 1.5CC. Furthermore, when locations across selected regions are pooled within similar climatic zones (based on Koppen Geiger classification), scaling curves show around 7%/K scaling. The scaling curves for locations at greater altitude (>400m MSL) are flat compared to locations at relatively lower altitude. The difference in scaling rates at-station and for pooled regions highlight the importance of understanding the thermodynamic and dynamic processes governing precipitation extremes at different spatial scales and indicate that local processes are driving the super-CC sensitivities in most regions.</p>

scholarly journals Assessment of the Extreme Precipitation by Satellite Estimates over South America

2020 ◽  
Vol 12 (13) ◽  
pp. 2085 ◽  
Author(s):  
Rayana Santos Araujo Palharini ◽  
Daniel Alejandro Vila ◽  
Daniele Tôrres Rodrigues ◽  
David Pareja Quispe ◽  
Rodrigo Cassineli Palharini ◽  
...  
Keyword(s):  
South America ◽  
Extreme Precipitation ◽  
Large Scale ◽  
Daily Precipitation ◽  
Extreme Values ◽  
Extreme Event ◽  
Rain Gauge ◽  
Tropical Region ◽  
Spatial Coverage ◽  
Daily Precipitation Data

In developing countries, accurate rainfall estimation with adequate spatial distribution is limited due to sparse rain gauge networks. One way to solve this problem is the use of satellite-based precipitation products. These satellite products have significant spatial coverage of rainfall estimates and it is of fundamental importance to investigate their performance across space–time scales and the factors that affect their uncertainties. In the open literature, some studies have already analyzed the ability of satellite-based rain estimation products to estimate average rainfall values. These investigations have found very close agreement between the estimates and observed data. However, further evaluation of the satellite precipitation products is necessary to improve their reliability to estimate extreme values. In this scenario, the main goal of this work is to evaluate the ability of satellite-based precipitation products to capture the characteristics of extreme precipitation over the tropical region of South America. The products evaluated in this investigation were 3B42 RT v7.0, 3B42 RT v7.0 uncalibrated, CMORPH V1.0 RAW, CMORPH V1.0 CRT, GSMAP-NRT-no gauge v6.0, GSMAP-NRT- gauge v6.0, CHIRP V2.0, CHIRPS V2.0, PERSIANN CDR v1 r1, CoSch and TAPEER v1.5 from Frequent Rainfall Observations on GridS (FROGS) database. Some products considered in this investigation are adjusted with rain gauge values and others only with satellite information. In this study, these two sets of products were considered. In addition, gauge-based daily precipitation data, provided by Brazil’s National Institute for Space Research, were used as reference in the analyses. In order to compare gauge-based daily precipitation and satellite-based data for extreme values, statistical techniques were used to evaluate the performance the selected satellite products over the tropical region of South America. According to the results, the threshold for rain to be considered an extreme event in South America presented high variability, ranging from 20 to 150 mm/day, depending on the region and the percentile threshold chosen for analysis. In addition, the results showed that the ability of the satellite estimates to retrieve rainfall extremes depends on the geographical location and large-scale rainfall regimes.

scholarly journals Patterns of Extreme Precipitation and Characteristics of Related Systems in the Northern Xinjiang Region

Atmosphere ◽  
2021 ◽  
Vol 12 (3) ◽  
pp. 358
Author(s):  
Rui Xu ◽  
Jie Ming
Keyword(s):  
Water Vapor ◽  
Extreme Precipitation ◽  
Daily Precipitation ◽  
Principal Component ◽  
Reanalysis Data ◽  
Water Vapor Transport ◽  
Northern Xinjiang ◽  
The North ◽  
Western Tianshan ◽  
Daily Precipitation Data

Based on 40 years of daily precipitation, 272 extreme precipitation days in the Northern Xinjiang region are defined. Using the daily precipitation data on these days, four precipitation spatial patterns were obtained through principal component analysis. Then, daily-averaged reanalysis data were used to analyze the variations of synoptic systems on extreme precipitation days and the two days before and after. The rainfall centers shifted with the influential systems at 500 hPa. Water vapor of the western Tianshan type (Type WT) and the north of Northern Xinjiang type (Type NN) comes from the west, while vapor of the Central Tianshan type (Type CT) mainly comes from the east. In the east of Northern Xinjiang type (Type EN), water vapor converges from both sides. The centers of the upper-level jets are located west of 80° E in Type WT and CT. However, they are to the east of 80° E in the other types. This article summarizes the variations of the systems at 500 hPa, the South Asia High, the westerly jet, and the water vapor transport between the surface and 500 hPa in four types of patterns, and builds the conceptual model for each type. The models built can be applied to the heavy rainfall forecast of Northern Xinjiang.

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