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 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.

Do CMIP5 models hint at a warmer and wetter India in the 21st century?

2015 ◽  
Vol 7 (2) ◽  
pp. 280-295 ◽  
Author(s):  
Rajib Maity ◽  
Ankit Aggarwal ◽  
Kironmala Chanda
Keyword(s):  
General Circulation ◽  
Winter Season ◽  
Coupled Model ◽  
General Circulation Models ◽  
Cmip5 Models ◽  
Historical Period ◽  
The North ◽  
North Eastern ◽  
Spatio Temporal ◽  
Projected Changes

This study diagnoses the spatio-temporal variation of three major hydroclimatic variables (temperature, precipitation and evaporation) estimated from four general circulation models participating in the Fifth Phase of the Coupled Model Intercomparision Project (CMIP5). Changes in climate regime are analyzed across India for the historical scenario (1850–2005) and for the RCP8.5 scenario (2006–2100). The study provides a relative assessment of projected changes in climatic pattern over different zones in India, broadly divided as southern, Eastern, Western, Central, North-Eastern and Himalayan regions. Monthly data for both the scenarios were obtained, and all the data were re-gridded to a common resolution. All the models show a stronger warming in the future as compared to the historical period. The North-Eastern, Northern and Himalayan regions are likely to be severely affected. Though inconsistencies have been observed among the models, the majority of them predict an increase in precipitation in future, with a major increment in southern cities. The Himalayan belt is expected to receive heavy rainfall in the summer season, with little change in the winter season. Most of the regions are not expected to experience change in evaporation in pre-monsoonal months, but substantial change is expected in some regions during monsoonal and post-monsoonal months.

scholarly journals Precipitation in the Amazon and its relationship with moisture transport and tropical Pacific and Atlantic SST from the CMIP5 simulation

2015 ◽  
Vol 12 (1) ◽  
pp. 671-704 ◽  
Author(s):  
G. Martins ◽  
C. von Randow ◽  
G. Sampaio ◽  
A. J. Dolman
Keyword(s):  
Moisture Transport ◽  
General Circulation ◽  
Regional Analysis ◽  
Coupled Model ◽  
General Circulation Models ◽  
Moisture Convergence ◽  
Cmip5 Models ◽  
Wet Season ◽  
The Pacific ◽  
Eastern Edge

Abstract. Studies on numerical modeling in Amazonia show that the models fail to capture important aspects of climate variability in this region and it is important to understand the reasons that cause this drawback. Here, we study how the general circulation models of the Coupled Model Intercomparison Project Phase 5 (CMIP5) simulate the inter-relations between regional precipitation, moisture convergence and Sea Surface Temperature (SST) in the adjacent oceans, to assess how flaws in the representation of these processes can translate into biases in simulated rainfall in Amazonia. Using observational data (GPCP, CMAP, ERSST.v3, ERAI and evapotranspiration) and 21 numerical simulations from CMIP5 during the present climate (1979–2005) in June, July and August (JJA) and December, January and February (DJF), respectively, to represent dry and wet season characteristics, we evaluate how the models simulate precipitation, moisture transport and convergence, and pressure velocity (omega) in different regions of Amazonia. Thus, it is possible to identify areas of Amazonia that are more or less influenced by adjacent ocean SSTs. Our results showed that most of the CMIP5 models have poor skill in adequately representing the observed data. The regional analysis of the variables used showed that the underestimation in the dry season (JJA) was twice in relation to rainy season as quantified by the Standard Error of the Mean (SEM). It was found that Atlantic and Pacific SSTs modulate the northern sector of Amazonia during JJA, while in DJF Pacific SST only influences the eastern sector of the region. The analysis of moisture transport in JJA showed that moisture preferentially enters Amazonia via its eastern edge. In DJF this occurs both via its northern and eastern edge. The moisture balance is always positive, which indicates that Amazonia is a source of moisture to the atmosphere. Additionally, our results showed that during DJF the simulations in northeast sector of Amazonia have a strong bias in precipitation and an underestimation of moisture convergence due to the higher influence of biases in the Pacific SST. During JJA, a strong precipitation bias was observed in the southwest sector associated, also with a negative bias of moisture convergence, but with weaker influence of SSTs of adjacent oceans. The poor representation of precipitation-producing systems in Amazonia by the models and the difficulty of adequately representing the variability of SSTs in the Pacific and Atlantic oceans may be responsible for these underestimates in Amazonia.

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.

scholarly journals The Climatology of the Atmospheric Boundary Layer in Contemporary Global Climate Models

2018 ◽  
Vol 31 (22) ◽  
pp. 9151-9173 ◽  
Author(s):  
Richard Davy
Keyword(s):  
Boundary Layer ◽  
General Circulation ◽  
Climate Models ◽  
Global Climate ◽  
Coupled Model ◽  
General Circulation Models ◽  
Global Climate Models ◽  
Cmip5 Models ◽  
Seasonal Cycles ◽  
Layer Depth

Here, we present the climatology of the planetary boundary layer depth in 18 contemporary general circulation models (GCMs) in simulations of the late-twentieth-century climate that were part of phase 5 of the Coupled Model Intercomparison Project (CMIP5). We used a bulk Richardson methodology to establish the boundary layer depth from the 6-hourly synoptic-snapshot data available in the CMIP5 archives. We present an ensemble analysis of the climatological mean, diurnal cycle, and seasonal cycle of the boundary layer depth in these models and compare it to the climatologies from the ECMWF ERA-Interim reanalysis. Overall, we find that the CMIP5 models do a reasonably good job of reproducing the distribution of mean boundary layer depth, although the geographical patterns vary considerably between models. However, the models are biased toward weaker diurnal and seasonal cycles in the boundary layer depth and generally produce much deeper boundary layers at night and during the winter than are found in the reanalysis. These biases are likely to reduce the ability of these models to accurately represent other properties of the diurnal and seasonal cycles, and the sensitivity of these cycles to climate change.

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.

Arctic amplification as a rapid response to increased CO2

2021 ◽  
Author(s):  
Tyler Janoski ◽  
Michael Previdi ◽  
Gabriel Chiodo ◽  
Karen Smith ◽  
Lorenzo Polvani
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
Coupled Model ◽  
General Circulation Models ◽  
Forced Response ◽  
Arctic Sea Ice ◽  
Lapse Rate ◽  
The Arctic ◽  
Cmip5 Models ◽  
Arctic Amplification

&lt;p&gt;Arctic amplification (AA), or enhanced surface warming of the Arctic, is ubiquitous in observations, and in model simulations subjected to increased greenhouse gas (GHG) forcing. Despite its importance, the mechanisms driving AA are not entirely understood. Here, we show that in CMIP5 (Coupled Model Intercomparison Project 5) general circulation models (GCMs), AA develops within a few months following an instantaneous quadrupling of atmospheric CO&lt;sub&gt;2&lt;/sub&gt;. We find that this rapid AA response can be attributed to the lapse rate feedback, which acts to disproportionately warm the Arctic, even before any significant changes in Arctic sea ice occur. Only on longer timescales (beyond the first few months) does the decrease in sea ice become an important contributor to AA via the albedo feedback and increased ocean-to-atmosphere heat flux. An important limitation of our CMIP5 analysis is that internal climate variability is large on the short time scales considered. To overcome this limitation &amp;#8211; and thus better isolate the GHG-forced response &amp;#8211; we produced a large ensemble (100 members) of instantaneous CO&lt;sub&gt;2&lt;/sub&gt;-quadrupling simulations using a single GCM, the NCAR Community Earth System Model (CESM1). In our new CESM1 ensemble we find the same rapid AA response seen in the CMIP5 models, confirming that AA ultimately owes its existence to fast atmospheric processes.&lt;/p&gt;

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.

Evaluation of future runoff variations in the north–south transect of eastern China: effects of CMIP5 models outputs uncertainty

2019 ◽  
Vol 11 (4) ◽  
pp. 1355-1369 ◽  
Author(s):  
Guodong Sun ◽  
Fei Peng
Keyword(s):  
General Circulation ◽  
Eastern China ◽  
Coupled Model ◽  
General Circulation Models ◽  
Annual Runoff ◽  
Actual Evapotranspiration ◽  
Cmip5 Models ◽  
Climate Projections ◽  
Uncertainty Range ◽  
The North

Abstract Runoff is an important water flux that is difficult to simulate and predict due to lacking observation. Meteorological forcing data are a key factor in causing the uncertainty of predicted runoff. In this study, climate projections from ten general circulation models of the Coupled Model Intercomparison Project 5 (CMIP5) with high resolution under the Representative Concentration Pathway (RCP) 4.5 scenario are employed to estimate the future uncertainty range of predicted runoff in the North–South Transect of Eastern China (NSTEC) from 2011 to 2100. It is found that the range of future annual runoff is from 268.9 mm (Meteorological Research Institute coupled GCM, MRI-CGCM3) to 544.2 mm (Model for Interdisciplinary Research on Climate, MIROC5). The precipitation and the annual actual evapotranspiration are two key factors that affect the variation of runoff. The low annual runoff for the MRI-CGCM3 model may be caused by low precipitation and high annual actual evapotranspiration (466.9 mm). However, the high annual runoff for the MIROC5 may be caused by the high precipitation, although there is high annual actual evapotranspiration (544.2 mm). The above results imply that the forcing data and the model physics are important factors in the numerical simulation and prediction about runoff.

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