Evaluation of the CMIP5 general circulation models for simulating the precipitation and temperature of the Koshi River Basin in Nepal

Abstract This study evaluates the performance of 12 different general circulation models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5) to simulate precipitation and temperature in the Koshi River Basin, Nepal. Four statistical performance indicators: correlation coefficient, normalised root-mean-square deviation (NMRSD), absolute NMRSD, and average absolute relative deviation are considered to evaluate the GCMs using historical observations. Seven different climate indices: consecutive dry days, consecutive wet days, cold spell duration index, warm spell duration index, frost days, very wet days, and simple daily intensity index are considered to identify the most suitable models for the basin and future climate impact assessment studies. Weights for each performance indicator are determined using the entropy method, with compromise programming applied to rank the GCMs based on the Euclidian distant technique. The results suggest that CanESM2 and CSIRO-MK3.6.0 are the most suitable for predicting extreme precipitation events, and BCC-CSM 1.1, CanESM2, NorESM1-M, and CNRM-CM5 for extreme temperature events in Himalayan river basins. Overall, IPSL-CM5A-MR, CanESM2, CNRM-CM5, BCC-CSM 1.1, NorESM1-M, and CSIRO-Mk3.6.0 are deemed suitable models for predicting precipitation and temperature in the Koshi River Basin, Nepal.

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Representative general circulation models selection and downscaling of climate data for the transboundary Koshi river basin in China and Nepal

International Journal of Climatology ◽

10.1002/joc.6447 ◽

2020 ◽

Vol 40 (9) ◽

pp. 4131-4149

Author(s):

Santosh Kaini ◽

Santosh Nepal ◽

Saurav Pradhananga ◽

Ted Gardner ◽

Ashok K. Sharma

Keyword(s):

River Basin ◽

General Circulation ◽

General Circulation Models ◽

Climate Data ◽

Koshi River Basin

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Simulation of Extreme Precipitation in Four Climate Regions in China by General Circulation Models (GCMs): Performance and Projections

Water ◽

10.3390/w13111509 ◽

2021 ◽

Vol 13 (11) ◽

pp. 1509

Author(s):

Mengru Zhang ◽

Xiaoli Yang ◽

Liliang Ren ◽

Ming Pan ◽

Shanhu Jiang ◽

...

Keyword(s):

Extreme Precipitation ◽

General Circulation ◽

Global Climate ◽

Summer Precipitation ◽

General Circulation Models ◽

Cumulative Distribution ◽

Extreme Precipitation Events ◽

Increasing Trend ◽

The Future ◽

Semi Arid

In the context of global climate change, it is important to monitor abnormal changes in extreme precipitation events that lead to frequent floods. This research used precipitation indices to describe variations in extreme precipitation and analyzed the characteristics of extreme precipitation in four climatic (arid, semi-arid, semi-humid and humid) regions across China. The equidistant cumulative distribution function (EDCDF) method was used to downscale and bias-correct daily precipitation in eight Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs). From 1961 to 2005, the humid region had stronger and longer extreme precipitation compared with the other regions. In the future, the projected extreme precipitation is mainly concentrated in summer, and there will be large areas with substantial changes in maximum consecutive 5-day precipitation (Rx5) and precipitation intensity (SDII). The greatest differences between two scenarios (RCP4.5 and RCP8.5) are in semi-arid and semi-humid areas for summer precipitation anomalies. However, the area of the four regions with an increasing trend of extreme precipitation is larger under the RCP8.5 scenario than that under the RCP4.5 scenario. The increasing trend of extreme precipitation in the future is relatively pronounced, especially in humid areas, implying a potential heightened flood risk in these areas.

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Selection and downscaling of general circulation model datasets and extreme climate indices analysis - Manual

10.53055/icimod.4 ◽

2020 ◽

Author(s):

Saurav Pradhananga ◽

Arthur Lutz ◽

Archana Shrestha ◽

Indira Kadel ◽

Bikash Nepal ◽

...

Keyword(s):

River Basin ◽

General Circulation ◽

Climate Models ◽

Circulation Model ◽

Climate Extremes ◽

Climate Indices ◽

Climate Change Scenarios ◽

Sacred Landscape ◽

Kailash Sacred Landscape ◽

Selection Of

A supplement to the Climate Change Scenarios for Nepal report published by the Ministry of Forests and Environment for the National Adaptation Plan (NAP) Process, this manual provides detailed information about the processes through which the assessment highlighted in the report can be carried out. They include – selection of the general circulation/climate models (GCMs), downscaling of the GCM dataset, assessment of changes in precipitation and temperature, and assessment of change in climate extremes. The manual downscales climate datasets for the Koshi River basin, the Kabul River basin, and the Kailash Sacred Landscape to analyse future scenarios in these basins and the landscape.

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An Investigation into the Future Changes in Onset and Cessation of Rain and Their Variability over the Aswa Catchment, Uganda

Climate ◽

10.3390/cli8060067 ◽

2020 ◽

Vol 8 (6) ◽

pp. 67

Author(s):

Michael Iwadra ◽

P. T. Odirile ◽

B. P. Parida ◽

D. B. Moalafhi

Keyword(s):

General Circulation ◽

Rainfall Variability ◽

Standardized Precipitation Index ◽

Tropical Rainfall Measuring Mission ◽

Kendall Test ◽

Close Correlation ◽

General Circulation Models ◽

Extreme Precipitation Events ◽

Future Global Warming ◽

The Future

Future global warming may result in extreme precipitation events leading to crop, environment and infrastructure damage. Rainfall is a major input for the livelihood of peasant farmers in the Aswa catchment where the future rainfall variability, onset and cessation are also likely to be affected. The Aswa catchment has limited rainfall data; therefore, use of secondary datasets from Tropical Rainfall Measuring Mission (TRMM) is considered in this study, based on the close correlation of the recorded and TRMM rainfall. The latter was used to calibrate the statistical downscaling model for downscaling of two general circulation models to simulate future changes in rainfall. These data were analyzed for trends, wet and dry conditions/variability; onset and cessations of rain using the Mann–Kendall test, Standardized Precipitation Index (SPI) and the cumulative percentage mean rainfall method, respectively. Results show future rainfall is likely to increase, accompanied by increasing variability reaching as high as 118.5%. The frequency of SPI values above 2 (extreme wetness) is to increase above current level during mid and end of the century. The highest rainfall variability is expected especially during the onset and cessation months, which are generally expected to come earlier and later, by up to four and five weeks, respectively. The reliability worsens from the midterm (2036–2065) to long term (2066–2099). These likely changes in rainfall quantities, variability, onset and cessation months are some of the key rainfall dynamics that have implications for future arable agriculture, environment and water resource availability and planning over the Aswa catchment, as is increasingly the case elsewhere.

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Advanced risk-based event attribution for heavy regional rainfall events

npj Climate and Atmospheric Science ◽

10.1038/s41612-020-00141-y ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Yukiko Imada ◽

Hiroaki Kawase ◽

Masahiro Watanabe ◽

Miki Arai ◽

Hideo Shiogama ◽

...

Keyword(s):

General Circulation ◽

Heavy Rainfall ◽

Static Pressure ◽

Heat Waves ◽

Extreme Temperature ◽

General Circulation Models ◽

Rainfall Events ◽

Pressure Pattern ◽

Ensemble Simulations ◽

Event Attribution

Abstract Risk-based event attribution (EA) science involves probabilistically estimating alterations of the likelihoods of particular weather events, such as heat waves and heavy rainfall, owing to global warming, and has been considered as an effective approach with regard to climate change adaptation. However, risk-based EA for heavy rain events remains challenging because, unlike extreme temperature events, which often have a scale of thousands of kilometres, heavy rainfall occurrences depend on mesoscale rainfall systems and regional geographies that cannot be resolved using general circulation models (GCMs) that are currently employed for risk-based EA. Herein, we use GCM large-ensemble simulations and high-resolution downscaled products with a 20-km non-hydrostatic regional climate model (RCM), whose boundary conditions are obtained from all available GCM ensemble simulations, to show that anthropogenic warming increased the risk of two record-breaking regional heavy rainfall events in 2017 and 2018 over western Japan. The events are examined from the perspective of rainfall statistics simulated by the RCM and from the perspective of background large-scale circulation fields simulated by the GCM. In the 2017 case, precipitous terrain and a static pressure pattern in the synoptic field helped reduce uncertainty in the dynamical components, whereas in the 2018 case, a static pressure pattern in the synoptic field provided favourable conditions for event occurrence through a moisture increase under warmer climate. These findings show that successful risk-based EA for regional extreme rainfall relies on the degree to which uncertainty induced by the dynamic components is reduced by background conditioning.

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The Arctic and Antarctic Sea-Ice Area Index Records versus Measured and Modeled Temperature Data

Advances in Meteorology ◽

10.1155/2015/481834 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 1

Author(s):

Nicola Scafetta ◽

Adriano Mazzarella

Keyword(s):

Sea Ice ◽

General Circulation ◽

General Circulation Models ◽

Arctic Sea Ice ◽

The Arctic ◽

Climate Indices ◽

Area Index ◽

Antarctic Sea Ice ◽

Arctic Sea ◽

The Antarctic

Here we study the Arctic and Antarctic sea-ice area records provided by the National Snow and Ice Data Center (NSIDC). These records reveal an opposite climatic behavior: since 1978 the Arctic sea-ice area index decreased, that is, the region has warmed, while the Antarctic sea-ice area index increased, that is, the region has cooled. During the last 7 years the Arctic sea-ice area has stabilized while the Antarctic sea-ice area has increased at a rate significantly higher than during the previous decades; that is, the sea-ice area of both regions has experienced a positive acceleration. This result is quite robust because it is confirmed by alternative temperature climate indices of the same regions. We also found that a significant 4-5-year natural oscillation characterizes the climate of these sea-ice polar areas. On the contrary, we found that the CMIP5 general circulation models have predicted significant warming in both polar sea regions and failed to reproduce the strong 4-5-year oscillation. Because the CMIP5 GCM simulations are inconsistent with the observations, we suggest that important natural mechanisms of climate change are missing in the models.

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Comparison of Statistical Downscaling Methods for Monthly Total Precipitation: Case Study for the Paute River Basin in Southern Ecuador

Advances in Meteorology ◽

10.1155/2016/6526341 ◽

2016 ◽

Vol 2016 ◽

pp. 1-13 ◽

Cited By ~ 20

Author(s):

L. Campozano ◽

D. Tenelanda ◽

E. Sanchez ◽

E. Samaniego ◽

J. Feyen

Keyword(s):

River Basin ◽

Statistical Downscaling ◽

General Circulation ◽

General Circulation Models ◽

Support Vector ◽

Monthly Precipitation ◽

Local Conditions ◽

Southern Ecuador ◽

Monthly Total Precipitation ◽

Precipitation Estimates

Downscaling improves considerably the results of General Circulation Models (GCMs). However, little information is available on the performance of downscaling methods in the Andean mountain region. The paper presents the downscaling of monthly precipitation estimates of the NCEP/NCAR reanalysis 1 applying the statistical downscaling model (SDSM), artificial neural networks (ANNs), and the least squares support vector machines (LS-SVM) approach. Downscaled monthly precipitation estimates after bias and variance correction were compared to the median and variance of the 30-year observations of 5 climate stations in the Paute River basin in southern Ecuador, one of Ecuador’s main river basins. A preliminary comparison revealed that both artificial intelligence methods, ANN and LS-SVM, performed equally. Results disclosed that ANN and LS-SVM methods depict, in general, better skills in comparison to SDSM. However, in some months, SDSM estimates matched the median and variance of the observed monthly precipitation depths better. Since synoptic variables do not always present local conditions, particularly in the period going from September to December, it is recommended for future studies to refine estimates of downscaling, for example, by combining dynamic and statistical methods, or to select sets of synoptic predictors for specific months or seasons.

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Trends in temperature and precipitation extremes in historical (1961–1990) and projected (2061–2090) periods in a data scarce mountain basin, northern Pakistan

Stochastic Environmental Research and Risk Assessment ◽

10.1007/s00477-020-01829-6 ◽

2020 ◽

Vol 34 (10) ◽

pp. 1441-1455 ◽

Cited By ~ 1

Author(s):

Naeem Saddique ◽

Abdul Khaliq ◽

Christian Bernhofer

Keyword(s):

General Circulation ◽

Heavy Precipitation ◽

General Circulation Models ◽

Climate Extreme ◽

Adaptation Measures ◽

Significance Level ◽

Mitigation And Adaptation ◽

The Future ◽

Increasing Trends ◽

Precipitation And Temperature

Abstract This study investigates the trends of precipitation and temperature extremes for the historical observations (1961–1990) and future period (2061–2090) in the Jhelum River Basin. Future trends are estimated by using ensemble mean of three general circulation models under RCP4.5 and RCP8.5. Therefore, statistical downscaling model has been used to downscale the future precipitation and temperature. A total of 15 precipitation and temperature indices were calculated using the RClimdex package. Man-Kendall and Sen’s slope tests were used to detect the trends in climate extreme indices. Overall, the results of study indicate that there were significant changes in precipitation and temperature patterns as well as in the climate extremes in the basin for both observed as well as projected climate. Generally, more warming and increase in precipitation were observed, which increases from RCP4.5 to RCP8.5. For all the stations, increasing trends were found for both precipitation and temperature for twenty-first century at a 95% significance level. The frequency of warm days (TX90p), warm nights (TN90p), and summer days (SU25) showed significant increasing trends, alternatively the number of cold nights (TN10p) and cold days (TX10p) exhibited opposite behaviors. In addition, an increasing trend of warmest day (TXx) and coldest day (TNn) was observed. Our analysis also reveals that the number of very wet days (R90p) and heavy precipitation days (R10 mm) will likely increase in the future. Meanwhile, the Max 1-day (RX1-day) and 5-day (RX5-day) precipitation indices showed increasing trends at most of the stations of basin. The results of the study is of potential benefit for decision-makers to develop basin wide appropriate mitigation and adaptation measures to combat climate change and its consequences.

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EVALUATION OF GENERAL CIRCULATION MODELS IN PREDICTING MONTHLY RAINFALL FOR THE SANFRANCISCO RIVER BASIN

10.3850/38wc092019-1479 ◽

2019 ◽

Author(s):

EDUARDO E. DE FIGUEIREDO ◽

RICARDO DE ARAGÃO ◽

MARCOS A. S. CRUZ ◽

ANDRÉ Q ALMEIDA ◽

VAJAPEYAM S SRINIVASAN

Keyword(s):

River Basin ◽

General Circulation ◽

General Circulation Models ◽

Monthly Rainfall

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Impact of Climate Change on Water Balance Components and Droughts in the Guajoyo River Basin (El Salvador)

Water ◽

10.3390/w11112360 ◽

2019 ◽

Vol 11 (11) ◽

pp. 2360 ◽

Cited By ~ 5

Author(s):

Pablo Blanco-Gómez ◽

Patricia Jimeno-Sáez ◽

Javier Senent-Aparicio ◽

Julio Pérez-Sánchez

Keyword(s):

Climate Change ◽

El Salvador ◽

River Basin ◽

General Circulation ◽

Goodness Of Fit ◽

General Circulation Models ◽

Future Climate ◽

Future Climate Change ◽

Climate Change Scenarios ◽

Historical Series

This study assessed how changes in terms of temperature and precipitation might translate into changes in water availability and droughts in an area in a developing country with environmental interest. The hydrological model Soil and Water Assessment Tool (SWAT) was applied to analyze the impacts of climate change on water resources of the Guajoyo River Basin in El Salvador. El Salvador is in one of the most vulnerable regions in Latin America to the effects of climate change. The predicted future climate change by two climate change scenarios (RCP 4.5 and RCP 8.5) and five general circulation models (GCMs) were considered. A statistical analysis was performed to identify which GCM was better in terms of goodness of fit to variation in means and standard deviations of the historical series. A significant decreasing trend in precipitation and a significant increase in annual average temperatures were projected by the middle and the end of the twenty–first century. The results indicated a decreasing trend of the amount of water available and more severe droughts for future climate scenarios with respect to the base period (1975–2004). These findings will provide local water management authorities useful information in the face of climate change to help decision making.

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