Global climate model evaluation and selection using the interactive tool GCMeval

2020 ◽  
Author(s):  
Kajsa Parding ◽  
Oskar A. Landgren ◽  
Andreas Dobler ◽  
Carol F. McSweeney ◽  
Rasmus E. Benestad ◽  
...  
Keyword(s):  
Model Selection ◽  
Web Application ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Performance ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Services ◽  
Skill Scores

<p>We present the interactive web application GCMeval, available at https://gcmeval.met.no. The tool is a useful resource for climate services by illustrating how model selection affects representation of future climate change. GCMeval was developed in a co-design process engaging users. Based on a thorough analysis of user demands, needs and capabilities, two different user groups were defined: Data users with lots of experience with data processing and Product users with a strong focus on information products. The available data, information, and user interface in GCMeval are tailored to the requirements of the data users.</p><p>In the tool, the user can select all or a subset of models from the CMIP5 and CMIP6 ensembles and assign weights to different regions, seasons, climate variables, and skill scores. The tool provides visualizations of the spread of future changes in temperature and precipitation which allows the user to study how the sub-ensemble fits in relation to the full multi-model ensemble and to compare climate model results for different regions of the world. A ranking of individual model performance for recent past climate is also provided. The tool can be used to aid in model selection for climate or impact studies, or to illustrate how an already existing selection represents the range of possible future climate outcomes.</p>

Evaluation of Climate Change Impact on Sustainability of Tailan Underground Reservoir in China

2013 ◽  
Vol 726-731 ◽  
pp. 3249-3255
Author(s):  
Emmanuel Kwame Appiah-Adjei ◽  
Long Cang Shu ◽  
Kwaku Amaning Adjei ◽  
Cheng Peng Lu
Keyword(s):  
Climate Change ◽  
Water Balance ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Future Climate ◽  
Future Climate Change ◽  
Research Station ◽  
Recharge Sources ◽  
Underground Reservoir

In order to ensure availability of water throughout the year in the Tailan River basin of northwestern China, an underground reservoir has been constructed in the basin to augment the groundwater resource and efficiently utilize it. This study investigates the potential impact of future climate change on the reservoir by assessing its influence on sustainability of recharge sources to the reservoir. The methods employed involved using a combined Statistical Downscaling Model (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG) to downscale the climate variations of the basin from a global climate model and applying them through a simple soil water balance to quantify their impact on recharge to the reservoir. The results predict the current mean monthly temperature of the basin to increase by 2.01°C and 2.84°C for the future periods 2040-2069 and 2070-2099, respectively, while the precipitations are to decrease by 25% and 36% over the same periods. Consequently, the water balance analyses project the recharge to the reservoir to decrease by 37% and 49% for the periods 2040-2069 and 2070-2099, respectively. Thus the study provides useful information for sustainable management of the reservoir against potential future climate changes.

scholarly journals The Impact of Climate Change on Meningitis in Northwest Nigeria: An Assessment Using CMIP5 Climate Model Simulations

2014 ◽  
Vol 6 (3) ◽  
pp. 371-379 ◽  
Author(s):  
Auwal F. Abdussalam ◽  
Andrew J. Monaghan ◽  
Daniel F. Steinhoff ◽  
Vanja M. Dukic ◽  
Mary H. Hayden ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Treatment Strategies ◽  
Coupled Model ◽  
Annual Incidence ◽  
Future Climate ◽  
Future Climate Change ◽  
The Impact

Abstract Meningitis remains a major health burden throughout Sahelian Africa, especially in heavily populated northwest Nigeria with an annual incidence rate ranging from 18 to 200 per 100 000 people for 2000–11. Several studies have established that cases exhibit sensitivity to intra- and interannual climate variability, peaking during the hot and dry boreal spring months, raising concern that future climate change may increase the incidence of meningitis in the region. The impact of future climate change on meningitis risk in northwest Nigeria is assessed by forcing an empirical model of meningitis with monthly simulations of seven meteorological variables from an ensemble of 13 statistically downscaled global climate model projections from phase 5 of the Coupled Model Intercomparison Experiment (CMIP5) for representative concentration pathway (RCP) 2.6, 6.0, and 8.5 scenarios, with the numbers representing the globally averaged top-of-the-atmosphere radiative imbalance (in W m−2) in 2100. The results suggest future temperature increases due to climate change have the potential to significantly increase meningitis cases in both the early (2020–35) and late (2060–75) twenty-first century, and for the seasonal onset of meningitis to begin about a month earlier on average by late century, in October rather than November. Annual incidence may increase by 47% ± 8%, 64% ± 9%, and 99% ± 12% for the RCP 2.6, 6.0, and 8.5 scenarios, respectively, in 2060–75 with respect to 1990–2005. It is noteworthy that these results represent the climatological potential for increased cases due to climate change, as it is assumed that current prevention and treatment strategies will remain similar in the future.

scholarly journals Assessing mean climate change signals in the global CORDEX-CORE ensemble

2020 ◽  
Author(s):  
Claas Teichmann ◽  
Daniela Jacob ◽  
Armelle Reca Remedio ◽  
Thomas Remke ◽  
Lars Buntemeyer ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Future Climate Change ◽  
Climate Services ◽  
Climate Change Information ◽  
Mean Climate

<p>The Coordinated Output for Regional Evaluations (CORE) simulation ensemble is an effort of the WCRP CORDEX community to provide high resolution regional climate change information for the major inhabited areas of the world and thus to generate the solid scientific basis for further research related to vulnerability, impact, adaptation and climate services (VIACS). This is especially important in those areas in which so far only few high-resolution simulations or only global comparatively coarse simulations were available. The driving simulations were selected to cover the spread of high, medium and low climate sensitivity at a global scale. Initially, the two RCMs REMO and RegCM4 were used to downscale these data global climate model output to a resolution of 0.22° (about 25km) while it is intended that the CORDEX CORE ensemble can then be extended by additional regional simulations to further increase the ensemble size and thus the representation of possible future climate change pathways.</p> <p>The aim of this study is to investigate and document the climate change information provided by the current CORDEX CORE ensemble with respect to mean climate change in different regions and in comparison to previously existing global climate information, especially those global climate simulations used as boundary forcing for CORDEX CORE, but also in comparison to the entire AR5-GCM ensemble. The analysis focuses on the representation of the AR5-GCM range of climate change signals by the CORDEX CORE ensemble with respect to mean temperature and precipitation changes and corresponding shifts in the annual cycles in the new AR6 IPCC physical reference regions. This also provides an indication for CORDEX CORE suitability for VIACS applications in each region.</p>

Evaluation of CMIP6 Models Toward Dynamical Downscaling Over Eight CORDEX Domains

2021 ◽  
Author(s):  
Meng-Zhuo Zhang ◽  
Zhongfeng Xu ◽  
Ying Han ◽  
Weidong Guo
Keyword(s):  
Model Selection ◽  
Large Scale ◽  
Evaluation Method ◽  
Climate Model ◽  
Dynamical Downscaling ◽  
Global Climate ◽  
Global Climate Model ◽  
Model Performance ◽  
Uncertainty Range ◽  
Multiple Variables

Abstract Both reliability and independence of global climate model (GCM) simulation are essential for model selection to generate a reasonable uncertainty range of dynamical downscaling simulations. In this study, we evaluate the performance and interdependency of 37 GCMs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) in terms of seven key large-scale driving fields over eight CORDEX domains. A multivariable integrated evaluation method is used to evaluate and rank the models’ ability to simulate multiple variables in terms of their climatological mean and interannual variability. The results suggest that the model performance varies considerably with seasons, domains, and variables evaluated, and no model outperforms in all aspects. However, the multi-model ensemble mean performs much better than any individual model. Among 37 CMIP6 models, the MPI-ESM1-2-HR, FIO-ESM-2-0, and MPI-ESM1-2-LR rank top three due to their overall good performance across all domains. To measure the model interdependency in terms of multiple fields, we define the similarity of multivariate error fields between pairwise models. Our results indicate that the dependence exists between most of the CMIP6 models, and the models sharing the same idea or/and concept generally show less independence. Furthermore, we hierarchically cluster the top 15 models based on the similarity of multivariate error fields to facilitate the model selection. Our evaluation can provide useful guidance on the selection of CMIP6 models based on their performance and relative independence, which helps to generate a more reliable ensemble of dynamical downscaling simulations with reasonable inter-model spread.

scholarly journals Trends in projections of standardized precipitation indices in a future climate in Poland

2016 ◽  
Vol 20 (5) ◽  
pp. 1947-1969 ◽  
Author(s):  
Marzena Osuch ◽  
Renata J. Romanowicz ◽  
Deborah Lawrence ◽  
Wai K. Wong
Keyword(s):  
Bias Correction ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Standardized Precipitation Index ◽  
Future Climate ◽  
Future Climate Change ◽  
Climate Projections ◽  
Monthly Precipitation

Abstract. Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann–Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons.

scholarly journals Future Climate Change and Its Impact on Runoff Generation from the Debris-Covered Inylchek Glaciers, Central Tian Shan, Kyrgyzstan

Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1513 ◽  
Author(s):  
Wilfried Hagg ◽  
Elisabeth Mayr ◽  
Birgit Mannig ◽  
Mark Reyers ◽  
David Schubert ◽  
...  
Keyword(s):  
Mass Balance ◽  
Hydrological Model ◽  
Climate Model ◽  
Global Climate Model ◽  
Future Climate ◽  
Fine Tuning ◽  
Future Climate Change ◽  
Tarim River ◽  
Glacier Mass Balance ◽  
Tian Shan

The heavily debris-covered Inylchek glaciers in the central Tian Shan are the largest glacier system in the Tarim catchment. It is assumed that almost 50% of the discharge of Tarim River are provided by glaciers. For this reason, climatic changes, and thus changes in glacier mass balance and glacier discharge are of high impact for the whole region. In this study, a conceptual hydrological model able to incorporate discharge from debris-covered glacier areas is presented. To simulate glacier melt and subsequent runoff in the past (1970/1971–1999/2000) and future (2070/2071–2099/2100), meteorological input data were generated based on ECHAM5/MPI-OM1 global climate model projections. The hydrological model HBV-LMU was calibrated by an automatic calibration algorithm using runoff and snow cover information as objective functions. Manual fine-tuning was performed to avoid unrealistic results for glacier mass balance. The simulations show that annual runoff sums will increase significantly under future climate conditions. A sensitivity analysis revealed that total runoff does not decrease until the glacier area is reduced by 43%. Ice melt is the major runoff source in the recent past, and its contribution will even increase in the coming decades. Seasonal changes reveal a trend towards enhanced melt in spring, but a change from a glacial-nival to a nival-pluvial runoff regime will not be reached until the end of this century.

Heavy Rain and Drought Conditions in Thailand under Global Warming

2015 ◽  
Vol 804 ◽  
pp. 235-238
Author(s):  
Sunisa Saiuparad
Keyword(s):  
Global Warming ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Heavy Rain ◽  
Future Climate ◽  
Present Climate ◽  
Drought Conditions ◽  
Global Warming Scenario ◽  
Environmental Prediction

Thailand is an agricultural country. Most farmers still depend on rainfall for cultivation. Global warming may result in changes in the amount and distribution of rainfall both in space and time. This could impact the occurrence of heavy rain and drought in the country. Thus, it is necessary to analyze heavy rain and drought conditions in Thailand under global warming for the purpose of preparedness and impact mitigation. The data used in this study consist of present climate and future climate. The data for present climate are from the National Centers for Environmental Prediction (NCEP) and the Thai Meteorological Department (TMD). The data for future climate are from the Educational Global Climate Model (EdGCM). The results are risk maps of heavy rain and drought in Thailand during the years 2046-2065 and 2081-2099 under a global warming scenario.

Building synergies in regional climate services for Southeast Asia: The ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series.

2020 ◽  
Author(s):  
Gerald Lim ◽  
Aurel Moise ◽  
Raizan Rahmat ◽  
Bertrand Timbal
Keyword(s):  
Climate Change ◽  
Data Analysis ◽  
Southeast Asia ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Early Warning Systems ◽  
Climate Data ◽  
Climate Services

<p>Southeast Asia (SEA) is a rapidly developing and densely populated region that is home to over 600 million people. This, together with the region’s high sensitivity, exposure and low adaptive capacities, makes it particularly vulnerable to climate change and extremes such as floods, droughts and tropical cyclones. While the last decade saw some countries in SEA develop their own climate change projections, studies were largely uncoordinated and most countries still lack the capability to independently produce robust future climate information. Following a proposal from the World Meteorological Organisation (WMO) Regional Association (RA) V working group on climate services, the ASEAN Regional Climate Data, Analysis and Projections (ARCDAP) workshop series was conceived in 2017 to bridge these gaps in regional synergies. The ARCDAP series has been organised annually since 2018 by the ASEAN Specialised Meteorological Centre (hosted by Meteorological Service Singapore) with support from WMO through the Canada-funded Climate Risk and Early Warning Systems (Canada-CREWS) initiative.</p><p>This presentation will cover the activities and outcomes from the first two workshops, as well as the third which will be held in February 2020. The ARCDAP series has so far brought together representatives from ASEAN National Meteorological and Hydrological Services (NMHSs), climate scientists and end-users from policy-making and a variety of vulnerability and impact assessment (VIA) sectors, to discuss and identify best practices regarding the delivery of climate change information, data usage and management, advancing the science etc. Notable outputs include two comprehensive workshop reports and a significant regional contribution to the HadEX3 global land in-situ-based dataset of temperature and precipitation extremes, motivated by work done with the ClimPACT2 software.</p><p>The upcoming third workshop will endeavour to encourage the uptake of the latest ensemble of climate simulations from the Coupled Model Intercomparison Project (CMIP6) using CMIP-endorsed tools such as ESMValTool. This will address the need for ASEAN climate change practitioners to upgrade their knowledge of the latest global climate model database. It is anticipated that with continued support from WMO, the series will continue with the Fourth workshop targeting the assessment of downscaling experiments in 2021.</p>

scholarly journals Geographic distribution of Desmodus rotundus in Mexico under current and future climate change scenarios: Implications for bovine paralytic rabies infection

2017 ◽  
Vol 4 (3) ◽  
Author(s):  
Heliot Zarza ◽  
Enrique Martínez-Meyer ◽  
Gerardo Suzán ◽  
Gerardo Ceballos
Keyword(s):  
Climate Change ◽  
Geographic Distribution ◽  
Current Distribution ◽  
Climate Model ◽  
Global Climate Model ◽  
Future Climate ◽  
Epidemiological Surveillance ◽  
Future Climate Change ◽  
Climate Change Scenarios ◽  
Desmodus Rotundus

Veterinaria México OA ISSN: 2448-6760Cite this as:Zarza H, Martínez-Meyer E, Suzán G, Ceballos G. Geographic distribution of Desmodus rotundus in Mexico under current and future climate change scenarios: Implications for bovine paralytic rabies infection. Veterinaria México OA. 2017;4(3). doi: 10.21753/vmoa.4.3.390.Climate change may modify the spatial distribution of reservoirs hosting emerging and reemerging zoonotic pathogens, and forecasting these changes is essential for developing prevention and adaptation strategies. The most important reservoir of bovine paralytic rabies in tropical countries, is the vampire bat (Desmodus rotundus). In Mexico, the cattle industry loses more than $2.6 million US dollar, annually to this infectious disease. Therefore, we predicted the change in the distribution of D. rotundus due to future climate change scenarios, and examined the likely effect that the change in its distribution will have on paralytic rabies infections in Mexico. We used the correlative maximum entropy based model algorithm to predict the potential distribution of D. rotundus. Consistent with the literature, our results showed that temperature was the variable most highly associated with the current distribution of vampire bats. The highest concentration of bovine rabies was in Central and Southeastern Mexico, regions that also have high cattle population densities. Furthermore, our climatic envelope models predicted that by 2050–2070, D. rotundus will lose 20 % of its current distribution while the northern and central regions of Mexico will become suitable habitats for D. rotundus. Together, our study provides an advanced notice of the likely change in spatial patterns of D. rotundus and bovine paralytic rabies, and presents an important tool for strengthening the National Epidemiological Surveillance System and Monitoring programmes, useful for establishing holistic, long-term strategies to control this disease in Mexico.Figure 4. Modelled suitability for future distribution of Desmodus rotundus according to Global Climate Model GFDL-CM3 for two time periods (2050 and 2070), and two Representative Concentration Pathways (RCP 4.5 and 8.5). Left-hand column shows suitability values, with blue indicating more suitable conditions.

scholarly journals The simultaneous occurrence of surge and discharge extremes for the Rhine delta

2013 ◽  
Vol 13 (8) ◽  
pp. 2017-2029 ◽  
Author(s):  
S. F. Kew ◽  
F. M. Selten ◽  
G. Lenderink ◽  
W. Hazeleger
Keyword(s):  
North Sea ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Storm Surges ◽  
Future Climate ◽  
Simultaneous Occurrence ◽  
Rhine River ◽  
The North ◽  
The North Sea

Abstract. The low-lying Netherlands is at risk from multiple threats of sea level rise, storm surges and extreme river discharges. Should these occur simultaneously, a catastrophe will be at hand. Knowledge about the likelihood of simultaneous occurrence or the so-called "compound effect" of such threats is essential to provide guidance on legislation for dike heights, flood barrier design and water management in general. In this study, we explore the simultaneous threats of North Sea storm surges and extreme Rhine river discharge for the current and future climate in a large 17-member global climate model ensemble. We use a simple approach, taking proxies of north-northwesterly winds over the North Sea and multiple~day precipitation averaged over the Rhine basin for storm surge and discharge respectively, so that a sensitivity analysis is straightforward to apply. By investigating soft extremes, we circumvent the need to extrapolate the data and thereby permit the model's synoptic development of the extreme events to be inspected. Our principle finding based on the climate model data is that, for the current climate, the probability of extreme surge conditions following extreme 20-day precipitation sums is around 3 times higher than that estimated from treating extreme surge and discharge probabilities as independent, as previously assumed. For the future climate (2070–2100), the assumption of independence cannot be rejected, at least not for precipitation sums exceeding 7 days.

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