scholarly journals Uncertainty Assessment in Drought Severities for the Cheongmicheon Watershed Using Multiple GCMs and the Reliability Ensemble Averaging Method

2019 ◽  
Vol 11 (16) ◽  
pp. 4283 ◽  
Author(s):  
Patricia Jitta Abdulai ◽  
Eun-Sung Chung
Keyword(s):  
General Circulation ◽  
Standardized Precipitation Index ◽  
Model Performance ◽  
Coupled Model ◽  
General Circulation Models ◽  
Future Climate Change ◽  
Drought Indices ◽  
Ensemble Averaging ◽  
Total Uncertainty ◽  
Uncertainty Range

The consequence of climate variations on hydrology remains the greatest challenging aspect of managing water resources. This research focused on the quantitative approach of the uncertainty in variations of climate influence on drought pattern of the Cheongmicheon watershed by assigning weights to General Circulation Models (GCMs) based on model performances. Three drought indices, Standardized Precipitation Evapotranspiration Index (SPEI), Standardized Precipitation Index (SPI) and Streamflow Drought Index (SDI) are used for three durations 3-, 6- and 9-months. This study included 27 GCMs from Coupled Model Intercomparison Project 5 (CMIP5) and considered three future periods (2011–2040, 2041–2070 and 2071–2100) of the concentration scenario of Representation Concentration Pathway (RCP) 4.5. Compared to SPEI and SDI, SPI identified more droughts in severe or extreme categories of shorter time scales than SPEI or SDI. The results suggested that the discrepancy in temperature plays a significant part in characterizing droughts. The Reliability Ensemble Averaging (REA) technique was used to give a mathematical approximation of associated uncertainty range and reliability of future climate change predictions. The uncertainty range and reliability of Root Mean Square Error (RMSE) varied among GCMs and total uncertainty ranges were between 50% and 200%. This study provides the approach for realistic projections by incorporating model performance ensemble averaging based on weights from RMSE.

scholarly journals Comparison of Projection in Meteorological and Hydrological Droughts in the Cheongmicheon Watershed for RCP4.5 and SSP2-4.5

2021 ◽  
Vol 13 (4) ◽  
pp. 2066
Author(s):  
Jin Hyuck Kim ◽  
Jang Hyun Sung ◽  
Eun-Sung Chung ◽  
Sang Ug Kim ◽  
Minwoo Son ◽  
...  
Keyword(s):  
General Circulation ◽  
Drought Index ◽  
Standardized Precipitation Index ◽  
Coupled Model ◽  
Meteorological Drought ◽  
General Circulation Models ◽  
Hydrological Drought ◽  
Drought Indices ◽  
Drought Period ◽  
Drought Characteristics

Due to the recent appearance of shares socioeconomic pathway (SSP) scenarios, there have been many studies that compare the results between Coupled Model Intercomparison Project (CMIP)5 and CMIP6 general circulation models (GCMs). This study attempted to project future drought characteristics in the Cheongmicheon watershed using SSP2-4.5 of Australian Community Climate and Earth System Simulator-coupled model (ACCESS-CM2) in addition to Representative Concentration Pathway (RCP) 4.5 of ACCESS 1-3 of the same institute. The historical precipitation and temperature data of ACCESS-CM2 were generated better than those of ACCESS 1-3. Two meteorological drought indices, namely, Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) were used to project meteorological drought while a hydrological drought index, Standardized Streamflow Index (SDI), was used to project the hydrological drought characteristics. The metrological data of GCMs were bias-corrected using quantile mapping method and the streamflow was obtained using Soil and Water Assessment Tool (SWAT) and bias-corrected meteorological data. As a result, there were large differences of drought occurrences and severities between RCP4.5 and SSP2-4.5 for the values of SPI, SPEI, and SDI. The differences in the minimum values of drought index between near (2021–2060) and far futures (2061–2100) were very small in SSP2-4.5, while those in RCP4.5 were very large. In addition, the longest drought period from SDI was the largest because the variation in precipitation usually affects the streamflow with a lag. Therefore, it was concluded that it is important to consider both CMIP5 and CMIP6 GCMs in establishing the drought countermeasures for the future period.

scholarly journals PLASIM-ENTSem: a spatio-temporal emulator of future climate change for impacts assessment

2013 ◽  
Vol 6 (2) ◽  
pp. 3349-3380 ◽  
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.

Estimation of hydrological response to future climate change in a cold watershed

2018 ◽  
Vol 10 (1) ◽  
pp. 78-88 ◽  
Author(s):  
Jian Sha ◽  
Zhong-Liang Wang ◽  
Yue Zhao ◽  
Yan-Xue Xu ◽  
Xue Li
Keyword(s):  
Climate Change ◽  
General Circulation ◽  
Water System ◽  
Coupled Model ◽  
Weather Conditions ◽  
General Circulation Models ◽  
Future Climate ◽  
Future Climate Change ◽  
Research Station ◽  
Hydrological Process

Abstract The vulnerability of the natural water system in cold areas to future climate change is of great concern. A coupled model approach was applied in the headwater watershed area of Yalu River in the northeastern part of China to estimate the response of hydrological processes to future climate change with moderate data. The stochastic Long Ashton Research Station Weather Generator was used to downscale the results of general circulation models to generate synthetic daily weather series in the 2050s and 2080s under various projected scenarios, which were applied as input data of the Generalized Watershed Loading Functions hydrological model for future hydrological process estimations. The results showed that future wetter and hotter weather conditions would have positive impacts on the watershed runoff yields but negative impacts on the watershed groundwater flow yields. The freezing period in winter would be shortened with earlier snowmelt peaks in spring. These would result in less snow cover in winter and shift the monthly allocations of streamflow with more yields in March but less in April and May, which should be of great concern for future local management. The proposed approach of the coupled model application is effective and can be used in other similar areas.

Evaluating parametric sensitivity of climate feedbacks in CNRM-CM6

2021 ◽  
Author(s):  
Saloua Peatier ◽  
Benjamin Sanderson ◽  
Laurent Terray
Keyword(s):  
Climate Sensitivity ◽  
General Circulation ◽  
Temperature Response ◽  
Coupled Model ◽  
General Circulation Models ◽  
Future Climate Change ◽  
Climate Feedbacks ◽  
Geophysical Research ◽  
Physics Ensemble ◽  
Earth’S Climate

<p>The global surface temperature response to CO2 doubling (Equilibrium Climate Sensitivity or ECS) is a key uncertain parameter determining the extent of future climate change. Sherwood et al. (2020) estimated the ECS to be within [2.6K - 4.5K], but in the Coupled Model Intercomparison Project phase 6 (CMIP6), 1/3 of the General Circulation Models (GCMs) show ECS exceeding 4.5K (Zelinka et al., 2020). CNRM-CM6-1 is one of these models, with an ECS of 4.9K. In this paper, we sampled 30 atmospheric parameters of CNRM-CM6-1 and produced a Perturbed Physics Ensemble (PPE) of atmospheric-only simulations to explore the feedback parameters diversity and the climatological plausibility of the members. This PPE showed a comparable  range of feedback parameters to the multi-model archive, from 0.8 W.m-2/K to 1.8 W.m-2/K. Emulators of climatological performance and feedback parameters were used together with  observational datasets to search for optimal model configurations conditional on different net climate feedbacks. The climatological constraints considered here did not themselves rule out the higher end ECS values of 5K and above. An optimal subset of parameter configurations were chosen to sample the range of ECS allowing the assessment of feedback constraints in future fully coupled experiments.</p><p> </p><p><strong>References :</strong></p><p>Sherwood, S. C., Webb, M. J., Annan, J. D., Armour, K. C., Forster, P. M., Hargreaves, J. C., ... & Zelinka, M. D. (2020). An assessment of Earth's climate sensitivity using multiple lines of evidence. Reviews of Geophysics, 58(4), e2019RG000678.</p><p>Zelinka, M. D., Myers, T. A., McCoy, D. T., Po‐Chedley, S., Caldwell, P. M., Ceppi, P., ... & Taylor, K. E. (2020). Causes of higher climate sensitivity in CMIP6 models. Geophysical Research Letters, 47(1), e2019GL085782.</p><p><br><br></p>

Assessing the spatio-temporal uncertainties in future meteorological droughts from CMIP5 models, emission scenarios and bias corrections

2020 ◽  
pp. 1-58
Author(s):  
Chuanhao Wu ◽  
Pat J.-F. Yeh ◽  
Jiali Ju ◽  
Yi-Ying Chen ◽  
Kai Xu ◽  
...  
Keyword(s):  
General Circulation ◽  
Standardized Precipitation Index ◽  
Coupled Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Northern Asia ◽  
Drought Characteristics ◽  
Uncertainty Sources ◽  
Spatio Temporal ◽  
The Standardized Precipitation Index

AbstractDrought projections are accompanied with large uncertainties due to varying estimates of future warming scenarios from different modelling and forcing data. Using the Standardized Precipitation Index (SPI), this study presents a global assessment of uncertainties in drought characteristics (severity S and frequency Df) projections based on the simulations of 28 general circulation models (GCMs) from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). A hierarchical framework incorporating a variance–based global sensitivity analysis was developed to quantify the uncertainties in drought characteristics projections at various spatial (global and regional) and temporal (decadal and 30-yr) scales due to 28 GCMs, 3 Representative Concentration Pathway scenarios (RCP2.6, RCP4.5, RCP8.5), and 2 bias-correction (BC) methods. The results indicated that the largest uncertainty contribution in the globally projected S and Df is from the GCM (>60%), followed by BC (<35%) and RCP (<16%). Spatially, BC reduces the spreads among GCMs particularly in Northern Hemisphere (NH), leading to smaller GCM uncertainty in NH than Southern Hemisphere (SH). In contrast, the BC and RCP uncertainties are larger in NH than SH, and the BC uncertainty can be larger than GCM uncertainty for some regions (e.g., southwest Asia). At the decadal and 30-yr timescales, the contributions for 3 uncertainty sources show larger variability in S than Df projections, especially in SH. The GCM and BC uncertainties show overall decreasing trends with time, while the RCP uncertainty is expected to increase over time and even can be larger than BC uncertainty for some regions (e.g., northern Asia) by the end of this century.

scholarly journals PLASIM-ENTSem v1.0: a spatio-temporal emulator of future climate change for impacts assessment

2014 ◽  
Vol 7 (1) ◽  
pp. 433-451 ◽  
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 (Planet Simulator coupled with the efficient numerical terrestrial scheme). 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 non-CO2 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, the validation of the simulator (with respect to empirical data) and the validation of the emulator (with respect to high-complexity models). We also demonstrate the application to estimates of sea-level rise and associated uncertainty.

scholarly journals A multi-diagnostic approach to cloud evaluation

2017 ◽  
Vol 10 (7) ◽  
pp. 2547-2566 ◽  
Author(s):  
Keith D. Williams ◽  
Alejandro Bodas-Salcedo
Keyword(s):  
General Circulation ◽  
Model Development ◽  
Model Performance ◽  
Coupled Model ◽  
Cloud Amount ◽  
General Circulation Models ◽  
Diagnostic Techniques ◽  
Model Errors ◽  
Intercomparison Project ◽  
Model Development Process

Abstract. Most studies evaluating cloud in general circulation models present new diagnostic techniques or observational datasets, or apply a limited set of existing diagnostics to a number of models. In this study, we use a range of diagnostic techniques and observational datasets to provide a thorough evaluation of cloud, such as might be carried out during a model development process. The methodology is illustrated by analysing two configurations of the Met Office Unified Model – the currently operational configuration at the time of undertaking the study (Global Atmosphere 6, GA6), and the configuration which will underpin the United Kingdom's Earth System Model for CMIP6 (Coupled Model Intercomparison Project 6; GA7). By undertaking a more comprehensive analysis which includes compositing techniques, comparing against a set of quite different observational instruments and evaluating the model across a range of timescales, the risks of drawing the wrong conclusions due to compensating model errors are minimized and a more accurate overall picture of model performance can be drawn. Overall the two configurations analysed perform well, especially in terms of cloud amount. GA6 has excessive thin cirrus which is removed in GA7. The primary remaining errors in both configurations are the in-cloud albedos which are too high in most Northern Hemisphere cloud types and sub-tropical stratocumulus, whilst the stratocumulus on the cold-air side of Southern Hemisphere cyclones has in-cloud albedos which are too low.

scholarly journals Twenty-First Century Drought Analysis Across China using CMIP6 Under Climate Change

2021 ◽  
Author(s):  
Gengxi Zhang ◽  
Thian Yew Gan ◽  
Xiaoling Su
Keyword(s):  
Soil Moisture ◽  
General Circulation ◽  
Coupled Model ◽  
Severity Index ◽  
General Circulation Models ◽  
Mitigation Strategies ◽  
Drought Indices ◽  
Drought Severity ◽  
Moisture Index ◽  
Arid Northwestern China

Abstract Under global warming, according to results obtained from offline drought indices driven by projections of general circulation models (GCMs), future droughts in China will worsen but the results are not consistent. We analyzed changes in droughts covering the entire hydrologic cycle using outputs of GCMs of the 6th Coupled Model Intercomparison Project (CMIP6) for SSP2-4.5 and SSP5-8.5 climate scenarios, and compared the results with that of popular, offline drought indices (the self-calibrating Palmer Drought Severity Index (scPDSI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Precipitation Actual Evapotranspiration Index (SPAEI)). Among meteorological, agricultural, and hydrological drought indices tested under both SSP scenarios, the results obtained from SPAEI and scPDSI agree better with univariate drought indices than SPEI. scPDSI generally agrees well with agricultural droughts (Standardized Soil Moisture Index with the surface soil moisture content; SSIS). Future droughts estimated using soil moisture analysis are more widespread than that from precipitation and runoff analysis in humid regions of South China by the end of the 21st century. In arid northwestern China and Inner Mongolia, drought areas and severity based on scPDSI and SSIS forced with the SSP scenarios show obvious decreasing trends, in contrast to increasing trends projected in humid regions. Trends projected using SPEI contradict those projected by other drought indices in non-humid regions. Therefore, selecting appropriate drought indices are crucial in project representative future droughts and meaningful information needed to achieve effective regional drought mitigation strategies under climate warming impact.

scholarly journals Emulating atmosphere-ocean and carbon cycle models with a simpler model, MAGICC6 – Part 2: Applications

2011 ◽  
Vol 11 (4) ◽  
pp. 1457-1471 ◽  
Author(s):  
M. Meinshausen ◽  
T. M. L. Wigley ◽  
S. C. B. Raper
Keyword(s):  
Carbon Cycle ◽  
21St Century ◽  
General Circulation ◽  
Climate Model ◽  
Coupled Model ◽  
General Circulation Models ◽  
Rcp Scenarios ◽  
Carbon Cycle Model ◽  
Uncertainty Range ◽  
Ipcc Ar4

Abstract. Intercomparisons of coupled atmosphere-ocean general circulation models (AOGCMs) and carbon cycle models are important for galvanizing our current scientific knowledge to project future climate. Interpreting such intercomparisons faces major challenges, not least because different models have been forced with different sets of forcing agents. Here, we show how an emulation approach with MAGICC6 can address such problems. In a companion paper (Meinshausen et al., 2011a), we show how the lower complexity carbon cycle-climate model MAGICC6 can be calibrated to emulate, with considerable accuracy, globally aggregated characteristics of these more complex models. Building on that, we examine here the Coupled Model Intercomparison Project's Phase 3 results (CMIP3). If forcing agents missed by individual AOGCMs in CMIP3 are considered, this reduces ensemble average temperature change from pre-industrial times to 2100 under SRES A1B by 0.4 °C. Differences in the results from the 1980 to 1999 base period (as reported in IPCC AR4) to 2100 are negligible, however, although there are some differences in the trajectories over the 21st century. In a second part of this study, we consider the new RCP scenarios that are to be investigated under the forthcoming CMIP5 intercomparison for the IPCC Fifth Assessment Report. For the highest scenario, RCP8.5, relative to pre-industrial levels, we project a median warming of around 4.6 °C by 2100 and more than 7 °C by 2300. For the lowest RCP scenario, RCP3-PD, the corresponding warming is around 1.5 °C by 2100, decreasing to around 1.1 °C by 2300 based on our AOGCM and carbon cycle model emulations. Implied cumulative CO2 emissions over the 21st century for RCP8.5 and RCP3-PD are 1881 GtC (1697 to 2034 GtC, 80% uncertainty range) and 381 GtC (334 to 488 GtC), when prescribing CO2 concentrations and accounting for uncertainty in the carbon cycle. Lastly, we assess the reasons why a previous MAGICC version (4.2) used in IPCC AR4 gave roughly 10% larger warmings over the 21st century compared to the CMIP3 average. We find that forcing differences and the use of slightly too high climate sensitivities inferred from idealized high-forcing runs were the major reasons for this difference.

scholarly journals Modified Approach to Reduce GCM Bias in Downscaled Precipitation: A Study in Ganga River Basin

Water ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 2097 ◽  
Author(s):  
Sharma ◽  
Ojha ◽  
Shukla ◽  
Pham ◽  
Linh ◽  
...  
Keyword(s):  
River Basin ◽  
General Circulation ◽  
Model Performance ◽  
Coupled Model ◽  
General Circulation Models ◽  
Skill Score ◽  
Reanalysis Data ◽  
Ganga River ◽  
Large Variability ◽  
Forest Regions

Reanalysis data is widely used to develop predictor-predictand models, which are further used to downscale coarse gridded general circulation models (GCM) data at a local scale. However, large variability in the downscaled product using different GCMs is still a big challenge. The first objective of this study was to assess the performance of reanalysis data to downscale precipitation using different GCMs. High bias in downscaled precipitation was observed using different GCMs, so a different downscaling approach is proposed in which historical data of GCM was used to develop a predictor-predictand model. The earlier approach is termed “Re-Obs” and the proposed approach as “GCM-Obs”. Both models were assessed using mathematical derivation and generated synthetic series. The intermodal bias in different GCMs downscaled precipitation using Re-Obs and GCM-Obs model was also checked. Coupled Model Inter-comparison Project-5 (CMIP5) data of ten different GCMs was used to downscale precipitation in different urbanized, rural, and forest regions in the Ganga river basin. Different measures were used to represent the relative performances of one downscaling approach over other approach in terms of closeness of downscaled precipitation with observed precipitation and reduction of bias using different GCMs. The effect of GCM spatial resolution in downscaling was also checked. The model performance, convergence, and skill score were computed to assess the ability of GCM-Obs and Re-Obs models. The proposed GCM-Obs model was found better than Re-Obs model to statistically downscale GCM. It was observed that GCM-Obs model was able to reduce GCM-Observed and GCM-GCM bias in the downscaled precipitation in the Ganga river basin.

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