Investigation of the Effect of Climate Change on Extreme Precipitation: Capital Ankara Case

Abstract. The climate change impact on mean and extreme precipitation events in the northern Mediterranean region is assessed using high-resolution EuroCORDEX and MedCORDEX simulations. The focus is made on three regions, Lez and Aude located in France, and Muga located in northeastern Spain, and eight pairs of global and regional climate models are analyzed with respect to the SAFRAN product. First the model skills are evaluated in terms of bias for the precipitation annual cycle over historical period. Then future changes in extreme precipitation, under two emission scenarios, are estimated through the computation of past/future change coefficients of quantile-ranked model precipitation outputs. Over the 1981–2010 period, the cumulative precipitation is overestimated for most models over the mountainous regions and underestimated over the coastal regions in autumn and higher-order quantile. The ensemble mean and the spread for future period remain unchanged under RCP4.5 scenario and decrease under RCP8.5 scenario. Extreme precipitation events are intensified over the three catchments with a smaller ensemble spread under RCP8.5 revealing more evident changes, especially in the later part of the 21st century.

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The effect of climate change on urban drainage: an evaluation based on regional climate model simulations

Water Science & Technology ◽

10.2166/wst.2006.592 ◽

2006 ◽

Vol 54 (6-7) ◽

pp. 9-15 ◽

Cited By ~ 41

Author(s):

M. Grum ◽

A.T. Jørgensen ◽

R.M. Johansen ◽

J.J. Linde

Keyword(s):

Climate Change ◽

Extreme Precipitation ◽

Climate Model ◽

Regional Climate ◽

Rain Gauge ◽

Urban Drainage ◽

Extreme Precipitation Events ◽

Rainfall Extremes ◽

The Future ◽

Precipitation Events

That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 × 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at time-scales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.

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Comparative Analysis or Precipitation Variation Characteristics between Subtropical Monsoon Climate and Temperate Monsoon Climate-Take Changsha and Chengde for Example

Tobacco Regulatory Science ◽

10.18001/trs.7.5.29 ◽

2021 ◽

Vol 7 (5) ◽

pp. 1113-1122

Author(s):

Bo Chen ◽

Shi-jun Xu ◽

Xin-ping Zhang ◽

Yi Xie

Keyword(s):

Climate Change ◽

Extreme Precipitation ◽

Precipitation Intensity ◽

Annual Precipitation ◽

Wet Season ◽

Precipitation Frequency ◽

Extreme Precipitation Events ◽

Average Precipitation ◽

Autumn And Winter ◽

Average Annual Precipitation

Using the methods of literature review, regression analysis and moving average, this paper selects the daily precipitation of Changsha and Chengde from 1951 to 1986 as samples, and analyzes the average precipitation, precipitation frequency, precipitation intensity, extreme precipitation time and other indicators of Changsha and Chengde from the perspective of interannual and seasonal changes Trends. The researches show that: the average precipitation of Changsha in the 36 years is 1151.2mm, spring is the wet season, autumn and winter are the dry seasons, and the maximum average precipitation is in spring; the average annual precipitation, precipitation frequency in spring, summer and winter, annual precipitation frequency, annual precipitation intensity and extreme precipitation events show a decreasing trend. The average annual precipitation of Chengde city is 454.1 mm, wet season in summer and dry season in spring, autumn and winter; the average annual precipitation, precipitation in four seasons, annual precipitation frequency, precipitation frequency in spring, autumn and winter, annual precipitation intensity and extreme precipitation events show a decreasing trend, while the precipitation frequency in summer shows an increasing trend. The study of regional climate change based on the time series data of this stage is of great significance to comprehensively understand the law of regional climate change and predict the future trend of climate change.

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Temporal variation of extreme precipitation events in Lithuania**The study was supported by the Lithuanian State Science and Studies Foundation and by the BSR Interreg IVB Project ‘Climate Change: Impacts, Costs and Adaptation in the Baltic Sea Region (BaltCICA)’.

Oceanologia ◽

10.5697/oc.53-1-ti.259 ◽

2011 ◽

Vol 53 ◽

pp. 259-277 ◽

Cited By ~ 18

Author(s):

Egidijus Rimkus ◽

Justas Kažys ◽

Arūnas Bukantis ◽

Aleksandras Krotovas

Keyword(s):

Climate Change ◽

Temporal Variation ◽

Extreme Precipitation ◽

Climate Change Impacts ◽

The Baltic Sea ◽

Extreme Precipitation Events ◽

Baltic Sea Region ◽

The Baltic ◽

Project Climate Change ◽

Precipitation Events

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Downscaling future precipitation extremes to urban hydrology scales using a spatio-temporal Neyman–Scott weather generator

Hydrology and Earth System Sciences ◽

10.5194/hess-20-1387-2016 ◽

2016 ◽

Vol 20 (4) ◽

pp. 1387-1403 ◽

Cited By ~ 14

Author(s):

Hjalte Jomo Danielsen Sørup ◽

Ole Bøssing Christensen ◽

Karsten Arnbjerg-Nielsen ◽

Peter Steen Mikkelsen

Keyword(s):

Climate Change ◽

Time Series ◽

Extreme Precipitation ◽

Climate Models ◽

Regional Climate ◽

Weather Generator ◽

Spatial Extent ◽

Urban Hydrology ◽

Precipitation Time Series ◽

Spatio Temporal

Abstract. Spatio-temporal precipitation is modelled for urban application at 1 h temporal resolution on a 2 km grid using a spatio-temporal Neyman–Scott rectangular pulses weather generator (WG). Precipitation time series used as input to the WG are obtained from a network of 60 tipping-bucket rain gauges irregularly placed in a 40 km  ×  60 km model domain. The WG simulates precipitation time series that are comparable to the observations with respect to extreme precipitation statistics. The WG is used for downscaling climate change signals from regional climate models (RCMs) with spatial resolutions of 25 and 8 km, respectively. Six different RCM simulation pairs are used to perturb the WG with climate change signals resulting in six very different perturbation schemes. All perturbed WGs result in more extreme precipitation at the sub-daily to multi-daily level and these extremes exhibit a much more realistic spatial pattern than what is observed in RCM precipitation output. The WG seems to correlate increased extreme intensities with an increased spatial extent of the extremes meaning that the climate-change-perturbed extremes have a larger spatial extent than those of the present climate. Overall, the WG produces robust results and is seen as a reliable procedure for downscaling RCM precipitation output for use in urban hydrology.

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Will Climate Change Exacerbate the Economic Damage of Flood to Agricultural Production? A Case Study of Rice in Ha Tinh Province, Vietnam

Frontiers in Environmental Science ◽

10.3389/fenvs.2021.643947 ◽

2021 ◽

Vol 9 ◽

Author(s):

Pham Quy Giang ◽

Tran Trung Vy

Keyword(s):

Climate Change ◽

Extreme Precipitation ◽

Agricultural Production ◽

Climate Change Impacts ◽

Economic Loss ◽

Baseline Period ◽

Rice Production ◽

Generalized Extreme Value Distribution ◽

Economic Damage

In developing countries in general and in Vietnam in particular, flood induced economic loss of agriculture is a serious concern since the livelihood of large populations depends on agricultural production. The objective of this study was to examine if climate change would exacerbate flood damage to agricultural production with a case study of rice production in Huong Son District of Ha Tinh Province, North-central Vietnam. The study applied a modeling approach for the prediction. Extreme precipitation and its return periods were calculated by the Generalized Extreme Value distribution method using historical daily observations and output of the MRI-CGCM3 climate model. The projected extreme precipitation data was then employed as an input of the Mike Flood model for flood modeling. Finally, an integrated approach employing flood depth and duration and crop calendar was used for the prediction of potential economic loss of rice production. Results of the study show that in comparison with the baseline period, an increase of 49.14% in the intensity of extreme precipitation was expected, while the frequency would increase 5 times by 2050s. As a result, the seriousness of floods would increase under climate change impacts as they would become more intensified, deeper and longer, and consequently the economic loss of rice production would increase significantly. While the level of peak flow was projected to rise nearly 1 m, leading the area of rice inundated to increase by 12.61%, the value of damage would rise by over 21% by 2050s compared to the baseline period. The findings of the present study are useful for long-term agricultural and infrastructural planning in order to tackle potential flooding threats to agricultural production under climate change impacts.

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Comparing soil carbon loss through respiration and leaching under extreme precipitation events in arid and semi-arid grasslands

10.5194/bg-2017-264 ◽

2017 ◽

Author(s):

Ting Liu ◽

Liang Wang ◽

Xiaojuan Feng ◽

Jinbo Zhang ◽

Tian Ma ◽

...

Keyword(s):

Climate Change ◽

Soil Carbon ◽

Extreme Precipitation ◽

Dissolved Inorganic Carbon ◽

Precipitation Event ◽

Carbon Loss ◽

Research Attention ◽

Extreme Precipitation Events ◽

Leaching Loss ◽

Arid And Semiarid

Abstract. Respiration and leaching are two main processes responsible for soil carbon loss. While the former has received considerable research attention, studies examining leaching processes are limited especially in semiarid grasslands due to low precipitation. Climate change may increase the extreme precipitation event (EPE) frequency in arid and semiarid regions, potentially enhancing soil carbon loss through leaching and respiration. Here we incubated soil columns of three typical grassland soils from Inner Mongolia and Qinghai-Tibetan Plateau and examined the effect of simulated EPEs on soil carbon loss through respiration and leaching. EPEs induced transient increase of soil respiration, equivalent to 32 % and 72 % of the net ecosystem productivity (NEP) in the temperate grasslands (Xilinhot and Keqi) and 7 % in the alpine grasslands (Gangcha). By comparison, leaching loss of soil carbon accounted for 290 %, 120 % and 15 % of NEP at the corresponding sites, respectively, with dissolved inorganic carbon (DIC) as the main form of carbon loss in the alkaline soils. Moreover, DIC loss increased with re-occuring EPEs in the soil with the highest pH due to increased dissolution of soil carbonates and elevated contribution of dissolved CO2 from organic carbon degradation (indicated by DIC-δ13C). These results highlight that leaching loss of soil carbon (particularly DIC) is important in the regional carbon budget of arid and semiarid grasslands. With a projected increase of EPEs under climate change, soil carbon leaching processes and its influencing factors warrant better understanding and should be incorporated into soil carbon models when estimating carbon balance in grassland ecosystems.

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