scholarly journals Comparison of CMIP5 and CMIP6 Multi-Model Ensemble for Precipitation Downscaling Results and Observational Data: The Case of Hanjiang River Basin

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 867
Author(s):  
Dong Wang ◽  
Jiahong Liu ◽  
Weiwei Shao ◽  
Chao Mei ◽  
Xin Su ◽  
...  
Keyword(s):  
River Basin ◽  
Seasonal Variations ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Poor Performance ◽  
Model Ensemble ◽  
Downscaling Method ◽  
Simulated Precipitation ◽  
Hanjiang River

Evaluating global climate model (GCM) outputs is essential for accurately simulating future hydrological cycles using hydrological models. The GCM multi-model ensemble (MME) precipitation simulations of the Climate Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6, respectively) were spatially and temporally downscaled according to a multi-site statistical downscaling method for the Hanjiang River Basin (HRB), China. Downscaled precipitation accuracy was assessed using data collected from 14 meteorological stations in the HRB. The spatial performances, temporal performances, and seasonal variations of the downscaled CMIP5-MME and CMIP6-MME were evaluated and compared with observed data from 1970–2005. We found that the multi-site downscaling method accurately downscaled the CMIP5-MME and CMIP6-MME precipitation simulations. The downscaled precipitation of CMIP5-MME and CMIP6-MME captured the spatial pattern, temporal pattern, and seasonal variations; however, precipitation was slightly overestimated in the western and central HRB and precipitation was underestimated in the eastern HRB. The precipitation simulation ability of the downscaled CMIP6-MME relative to the downscaled CMIP5-MME improved because of reduced biases. The downscaled CMIP6-MME better simulated precipitation for most stations compared to the downscaled CMIP5-MME in all seasons except for summer. Both the downscaled CMIP5-MME and CMIP6-MME exhibit poor performance in simulating rainy days in the HRB.

scholarly journals Evaluating Hydroclimatic Change Signals from Statistically and Dynamically Downscaled GCMs and Hydrologic Models

2014 ◽  
Vol 15 (2) ◽  
pp. 844-860 ◽  
Author(s):  
Rajesh R. Shrestha ◽  
Markus A. Schnorbus ◽  
Arelia T. Werner ◽  
Francis W. Zwiers
Keyword(s):  
River Basin ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Global Climate Models ◽  
Peace River ◽  
Simulated Precipitation ◽  
Basin Scale ◽  
Hydroclimatic Change

Abstract This study analyzed potential hydroclimatic change in the Peace River basin in the province of British Columbia, Canada, based on two structurally different approaches: (i) statistically downscaled global climate models (GCMs) using the bias-corrected spatial disaggregation (BCSD) and (ii) dynamically downscaled GCM with the Canadian Regional Climate Model (CRCM). Additionally, simulated hydrologic changes from the GCM–BCSD-driven Variable Infiltration Capacity (VIC) model were compared to the CRCM integrated Canadian Land Surface Scheme (CLASS) output. The results show good agreements of the GCM–BCSD–VIC simulated precipitation, temperature, and runoff with observations, while the CRCM-simulated results differ substantially from observations. Nevertheless, differences (between the 2050s and 1970s) obtained from the two approaches are qualitatively similar for precipitation and temperature, although they are substantially different for snow water equivalent and runoff. The results obtained from the five Coupled Global Climate Model, version 3, (CGCM3)-driven CRCM runs are similar, suggesting that the multidecadal internal variability is not a large source of uncertainty for the Peace River basin. Overall, the GCM–BCSD–VIC approach, for now, remains the preferred approach for projecting basin-scale future hydrologic changes, provided that it explicitly accounts for the biases and includes plausible snow and runoff parameterizations. However, even with the GCM–BCSD–VIC approach, projections differ considerably depending on which of an ensemble of eight GCMs is used. Such differences reemphasize the uncertain nature of future hydroclimatic projections.

scholarly journals Detection and Attribution of Streamflow Timing Changes to Climate Change in the Western United States

2009 ◽  
Vol 22 (13) ◽  
pp. 3838-3855 ◽  
Author(s):  
H. G. Hidalgo ◽  
T. Das ◽  
M. D. Dettinger ◽  
D. R. Cayan ◽  
D. W. Pierce ◽  
...  
Keyword(s):  
Climate Change ◽  
United States ◽  
Greenhouse Gases ◽  
River Basin ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Hydrologic Model ◽  
Western United States ◽  
Detection And Attribution

Abstract This article applies formal detection and attribution techniques to investigate the nature of observed shifts in the timing of streamflow in the western United States. Previous studies have shown that the snow hydrology of the western United States has changed in the second half of the twentieth century. Such changes manifest themselves in the form of more rain and less snow, in reductions in the snow water contents, and in earlier snowmelt and associated advances in streamflow “center” timing (the day in the “water-year” on average when half the water-year flow at a point has passed). However, with one exception over a more limited domain, no other study has attempted to formally attribute these changes to anthropogenic increases of greenhouse gases in the atmosphere. Using the observations together with a set of global climate model simulations and a hydrologic model (applied to three major hydrological regions of the western United States—the California region, the upper Colorado River basin, and the Columbia River basin), it is found that the observed trends toward earlier “center” timing of snowmelt-driven streamflows in the western United States since 1950 are detectably different from natural variability (significant at the p < 0.05 level). Furthermore, the nonnatural parts of these changes can be attributed confidently to climate changes induced by anthropogenic greenhouse gases, aerosols, ozone, and land use. The signal from the Columbia dominates the analysis, and it is the only basin that showed a detectable signal when the analysis was performed on individual basins. It should be noted that although climate change is an important signal, other climatic processes have also contributed to the hydrologic variability of large basins in the western United States.

scholarly journals Chaotic Statistical Downscaling (CSD): Application and Comparison in the Bogotá River Basin

10.29007/wkcx ◽  
2018 ◽  
Author(s):  
Freddy Duarte ◽  
Gerald Corzo ◽  
Germán Santos ◽  
Oscar Hernández
Keyword(s):  
Time Delay ◽  
Phase Space ◽  
Predictive Model ◽  
River Basin ◽  
Statistical Downscaling ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Deterministic Chaos ◽  
Climatic Information

This study presents a new statistical downscaling method called Chaotic Statistical Downscaling (CSD). The method is based on three main steps: Phase space reconstruction for different time steps, identification of deterministic chaos and a general synchronization predictive model. The Bogotá river basin was used to test the methodology. Two sources of climatic information are downscaled: the first corresponds to 47 rainfall gauges stations (1970-2016, daily) and the second is derived from the information of the global climate model MPI-ESM-MR with a resolution of 1,875° x 1,875° daily resolution. These time series were used to reconstruct the phase space using the Method of Time-Delay. The Time-Delay method allows us to find the appropriate values of the time delay and the embedding dimension to capture the dynamics of the attractor. This information was used to calculate the exponents of Lyapunov, which shows the existence of deterministic chaos. Subsequently, a predictive model is created based on the general synchronization of two dynamical systems. Finally, the results obtained are compared with other statistical downscaling models for the Bogota River basin using different measures of error which show that the proposed method is able to reproduce reliable rainfall values (RMSE=73.37).

scholarly journals Global Climate Model Ensemble Approaches for Future Projections of Atmospheric Rivers

2019 ◽  
Vol 7 (10) ◽  
pp. 1136-1151 ◽  
Author(s):  
E.C. Massoud ◽  
V. Espinoza ◽  
B. Guan ◽  
D.E. Waliser
Keyword(s):  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Ensemble ◽  
Future Projections ◽  
Atmospheric Rivers

scholarly journals Potential Implications of Future Climate Change And Extremes On Health, Agriculture, Water, And Cryosphere Sectors In The Kabul River Basin

2021 ◽  
Author(s):  
Kabi Raj Khatiwada ◽  
Saurav Pradhananga ◽  
Santosh Nepal
Keyword(s):  
River Basin ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Western Himalaya ◽  
Baseline Period ◽  
Future Climate Change ◽  
Climate Data ◽  
Kabul River ◽  
Extreme Indices

Abstract Increasing temperature and variability in precipitation are affecting different sectors in the Himalayan region. This study aims to quantify the future scenario and related extreme indices in the Kabul River Basin of the western Himalaya using high-resolution climate data sets. We selected the representative global climate model simulations for RCP4.5 and 8.5, based on their abilities to represent the historical climate cycle. By using a three-step methodology, we selected four models for RCP4.5 and four for RCP8.5. The analysis shows that, overall, precipitation will increase by 4 and 12 per cent for RCP4.5 and 8.5 respectively by the end of the 21st century, and the seasonal analysis shows decreasing pattern during the winter and pre-monsoon seasons. However, temperatures will increase consistently by 3OC to 5OC in RCP4.5 and 8.5 scenarios. The extreme indices were calculated based on the selected models. The extremes, like consecutive summer days, warm days, and heatwave will increase, whereas the frost days, cold nights, and cold waves will decrease towards the end of this century. Notably, more warm days and heatwaves than the baseline period are projected in future scenarios. Besides, the extremes are not homogenous in time and space. We also discussed the potential implications of these climatic extremes as related to human health, agricultural productivity, water availability, and the cryosphere. We strongly urge prompt climate actions in order to increase the adaptive capacity against these extreme changes and to build a resilient livelihood in the Kabul River Basin.

scholarly journals Climate change hotspots in the CMIP5 global climate model ensemble

2012 ◽  
Vol 114 (3-4) ◽  
pp. 813-822 ◽  
Author(s):  
Noah S. Diffenbaugh ◽  
Filippo Giorgi
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Ensemble
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