Representative general circulation models selection and downscaling of climate data for the transboundary Koshi river basin in China and 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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PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

Geoscientific Model Development Discussions ◽

10.5194/gmdd-6-3349-2013 ◽

2013 ◽

Vol 6 (2) ◽

pp. 3349-3380 ◽

Cited By ~ 5

Author(s):

P. B. Holden ◽

N. R. Edwards ◽

P. H. Garthwaite ◽

K. Fraedrich ◽

F. Lunkeit ◽

...

Keyword(s):

Radiative Forcing ◽

General Circulation ◽

Coupled Model ◽

Co2 Concentration ◽

General Circulation Models ◽

Climate Impacts ◽

Future Climate ◽

Future Climate Change ◽

Climate Data ◽

Spatio Temporal

Abstract. Many applications in the evaluation of climate impacts and environmental policy require detailed spatio-temporal projections of future climate. To capture feedbacks from impacted natural or socio-economic systems requires interactive two-way coupling but this is generally computationally infeasible with even moderately complex general circulation models (GCMs). Dimension reduction using emulation is one solution to this problem, demonstrated here with the GCM PLASIM-ENTS. Our approach generates temporally evolving spatial patterns of climate variables, considering multiple modes of variability in order to capture non-linear feedbacks. The emulator provides a 188-member ensemble of decadally and spatially resolved (~ 5° resolution) seasonal climate data in response to an arbitrary future CO2 concentration and radiative forcing scenario. We present the PLASIM-ENTS coupled model, the construction of its emulator from an ensemble of transient future simulations, an application of the emulator methodology to produce heating and cooling degree-day projections, and the validation of the results against empirical data and higher-complexity models. We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

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Understanding the past to interpret the future: comparison of simulated groundwater recharge in the upper Colorado River basin (USA) using observed and general-circulation-model historical climate data

Hydrogeology Journal ◽

10.1007/s10040-016-1481-0 ◽

2016 ◽

Vol 25 (2) ◽

pp. 347-358 ◽

Cited By ~ 6

Author(s):

Fred D Tillman ◽

Subhrendu Gangopadhyay ◽

Tom Pruitt

Keyword(s):

Groundwater Recharge ◽

General Circulation Model ◽

River Basin ◽

General Circulation ◽

Colorado River ◽

Circulation Model ◽

Climate Data ◽

The Past ◽

Upper Colorado River Basin ◽

Simulated Groundwater

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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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Beneficial impacts of climate change on pastoral and broadacre agriculture in cool-temperate Tasmania

Crop and Pasture Science ◽

10.1071/cp12425 ◽

2014 ◽

Vol 65 (2) ◽

pp. 194 ◽

Cited By ~ 5

Author(s):

D. C. Phelan ◽

D. Parsons ◽

S. N. Lisson ◽

G. K. Holz ◽

N. D. MacLeod

Keyword(s):

Climate Change ◽

General Circulation ◽

General Circulation Models ◽

Annual Rainfall ◽

Wheat Crop ◽

Daily Maximum ◽

Climate Data ◽

Diverse Range ◽

Wheat Production ◽

Elevated Atmospheric Co2

Although geographically small, Tasmania has a diverse range of regional climates that are affected by different synoptic influences. Consequently, changes in climate variables and climate-change impacts will likely vary in different regions of the state. This study aims to quantify the regional effects of projected climate change on the productivity of rainfed pastoral and wheat crop systems at five sites across Tasmania. Projected climate data for each site were obtained from the Climate Futures for Tasmania project (CFT). Six General Circulation Models were dynamically downscaled to ~10-km grid cells using the CSIRO Conformal Cubic Atmospheric Model under the A2 emissions scenario for the period 1961–2100. Mean daily maximum and minimum temperatures at each site are projected to increase from a baseline period (1981–2010) to 2085 (2071–2100) by 2.3–2.7°C. Mean annual rainfall is projected to increase slightly at all sites. Impacts on pasture and wheat production were simulated for each site using the projected CFT climate data. Mean annual pasture yields are projected to increase from the baseline to 2085 largely due to an increase in spring pasture growth. However, summer growth of temperate pasture species may become limited by 2085 due to greater soil moisture deficits. Wheat yields are also projected to increase, particularly at sites presently temperature-limited. This study suggests that increased temperatures and elevated atmospheric CO2 concentrations are likely to increase regional rainfed pasture and wheat production in the absence of any significant changes in rainfall patterns.

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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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High-resolution isotopic simulations from ECHAM6-wiso nudged with ERA5 reanalyses: new products for isotopic model-data comparisons

10.5194/egusphere-egu2020-12319 ◽

2020 ◽

Author(s):

Alexandre Cauquoin ◽

Martin Werner

Keyword(s):

General Circulation ◽

Ice Cores ◽

General Circulation Models ◽

Global Network ◽

Climate Data ◽

Isotopic Data ◽

Surrounding Water ◽

Weather Forecasts ◽

The Impact ◽

Water Isotope

For several decades, the comparison of climate data with results from water isotope-enabled Atmosphere General Circulation Models (AGCMs) significantly helped to a better understanding of the processes ruling the water cycle, which is one of the main drivers of the climate variability. For the modern period, the use of AGCMs nudged with weather forecasts reanalyses is a powerful way to obtain model outputs under the same weather conditions than at the sampling time of the observations.Here we present new isotopic simulations results from ECHAM6-wiso [1] nudged with the last reanalyses dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF), ERA5 [2], at different spatial resolutions over the period 1979-2018. Model results are evaluated against isotopic data compilations, including GNIP (Global Network of Isotopes in Precipitation [3]), speleothems [4], ice cores datasets and water vapor measurements. To quantify the impact of these reanalyses on our simulations, we also performed nudged simulations with the previous model version ECHAM5-wiso [5] by using ERA5 data and its predecessor ERA-Interim [6].These new simulation products could be a useful contribution to the isotopic data community for the interpretation of their water isotope records and for the exploration of the mechanisms controlling the variability of the surrounding water isotopic composition.&#160;[1] Cauquoin et al., Clim. Past, 15, 1913&#8211;1937, https://doi.org/10.5194/cp-15-1913-2019, 2019.[2] Copernicus Climate Change Service (C3S), 2017.[3] IAEA, the GNIP Database, available at: https://nucleus.iaea.org/wiser.[4] Comas-Bru et al., Clim. Past, 15, 1557&#8211;1579, https://doi.org/10.5194/cp-15-1557-2019, 2019.[5] Werner et al., Geosci. Model Dev., 9, 647&#8211;670, https://doi.org/10.5194/gmd-9-647-2016, 2016.[6] Dee et al., Q. J. R. Meteorol. Soc., 137, 553&#8211;597, https://doi.org/10.1002/qj.828, 2011.

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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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The ability of a GCM-forced hydrological model to reproduce global discharge variability

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-7-687-2010 ◽

2010 ◽

Vol 7 (1) ◽

pp. 687-724 ◽

Cited By ~ 3

Author(s):

F. C. Sperna Weiland ◽

L. P. H. van Beek ◽

J. C. J. Kwadijk ◽

M. F. P. Bierkens

Keyword(s):

General Circulation ◽

Hydrological Model ◽

General Circulation Models ◽

The Arctic ◽

Climate Data ◽

Mean Values ◽

Ensemble Mean ◽

Runoff Variability ◽

Abstract Data ◽

Impacts Of Climate Change

Abstract. Data from General Circulation Models (GCMs) are often used in studies investigating hydrological impacts of climate change. However GCM data are known to have large biases, especially for precipitation. In this study the usefulness of GCM data for hydrological studies was tested by applying bias-corrected daily climate data of the 20CM3 control experiment from an ensemble of twelve GCMs as input to the global hydrological model PCR-GLOBWB. Results are compared with discharges calculated from a model run based on a reference meteorological dataset constructed from the CRU TS2.1 data and ERA-40 reanalysis time-series. Bias-correction was limited to monthly mean values as our focus was on the reproduction of runoff variability. The bias-corrected GCM based runs resemble the reference run reasonably well, especially for rivers with strong seasonal patterns. However, GCM derived discharge quantities are overall too low. Furthermore, from the arctic regimes it can be seen that a few deviating GCMs can bias the ensemble mean. Moreover, the GCMs do not well represent intra- and inter-year variability as exemplified by a limited persistence. This makes them less suitable for the projection of future runoff extremes.

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Estimation of Runoff under changed climatic scenario of a Meso Scale River by Neural Network Based Gridded Model Approach

10.21203/rs.3.rs-223790/v1 ◽

2021 ◽

Author(s):

Debajit Das ◽

Tilottama Chakraborty ◽

Mrinmoy Majumder ◽

Tarun Kanti Bandyopadhyay

Keyword(s):

Climate Change ◽

River Basin ◽

General Circulation ◽

General Circulation Models ◽

Group Method ◽

North East India ◽

North East ◽

Hadley Centre ◽

Gomati River ◽

The Impact

Abstract As climate change is linked with changes in precipitation, evapotranspiration and changes in other climatological parameters, these changes will be affected runoff of a river basin. Gomati River basin is the largest river basin among all the river basin of Tripura. Due to the increase in settlement in the Gomati river basin and climate change may threaten natural flow patterns that endure its diversity. This study assesses the impact of climate change on total flow of a catchment in North East India (Gomati River catchment). For this assessment, the Group Method of Data Handling Modeling System (GMDH) model was used to simulate the rainfall-runoff relationship of the catchment, with respect to the observed data during the period of 2008–2009. The statistically downscaled outputs of HadGEM2-ES (Hadley Centre Global Environment Model version 2), general circulation models (GCMs) scenario was used to assess the impacts of climate change on the Gomati River Basin. Future projections were developed for the 2030s, 2040s and 2050s projections, respectively. The results from the present study can contribute to the development of adaptive strategies and future policies for the sustainable management of water resources in North East, Tripura.

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