scholarly journals Performance of Global Climate Model (GCMs) for Wind Data Analysis

2019 ◽  
Vol 117 ◽  
pp. 00006
Author(s):  
Chutipat Foyhirun ◽  
Duangrudee K. Kongkitkul ◽  
Chaiwat Ekkawatpanit
Keyword(s):  
Wind Speed ◽  
Wave Height ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Andaman Sea ◽  
Future Climate Change ◽  
Observation Data ◽  
Efficiency Coefficient ◽  
Wind Speed Data

The surface wind speed is an important climate variable for study of ocean wave energy and coastal erosion. The wind speed and wave height variations are caused by global warming. In the future, climate change impacts on changes of direction and wind speed which affect on wave height and wave period. The global climate model (GCMs) were developed by various institutions so each GCM has different GCM output. Then, the aim of this study is to evaluation the performance of GCMs for wind speed analysis in the area of Gulf of Thailand and Andaman Sea. In this study, the daily wind speed data was analyzed with a total of 15 GCMs and daily wind speed data of NCEP-NCAR was used as observation data to compare with wind speed data from GCMs over the period 1986-2005 (20 years). Moreover, the wind speed data was evaluated by efficiency coefficient which are root mean square error (RMSE) and mean absolute error (MAE). It was found tht MRI-CGCM3, GFDL-ESM2M, IPSL-CM5A-LR, and IPSL-CM5A-MR are consistent with the most of observation data from NCEP-NCAR.

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 APPLICABILITY OF D4PDF DATASET TO GLOBAL STOCHASTIC TROPICAL CYCLONE MODEL

2020 ◽  
pp. 26
Author(s):  
Sota Nakajo ◽  
Jinji Umeda ◽  
Nobuhito Mori
Keyword(s):  
Tropical Cyclone ◽  
Climate Model ◽  
Model Simulation ◽  
Global Climate ◽  
Global Climate Model ◽  
Observation Data ◽  
Change Rate ◽  
Regional Area ◽  
Global Climate Model Simulation ◽  
Disaster Event

Disaster damage caused by tropical cyclone has grown every year. However, our experience of tropical cyclone is not enough to evaluate very low frequent and catastrophic disaster event. Stochastic tropical cyclone model has been used for assessment of tropical cyclone disaster. Global stochastic model was improved by using a lot of ensemble Global Climate Model simulation data (d4PDF) instead of limited number of observation data. The model bias included d4PDF was corrected by each regional grid by simple statistical method and interpolation. The accuracy of new model was verified at representative regional area in different basins. Generally, the improvement is remarkable where tropical cyclones rarely passed. The variation of joint PDF of tropical cyclone change rate between previous model and present model agree with model improvement. As an example of application, the frequencies of strong tropical cyclone events of two cases were estimated.

scholarly journals Future ecosystem changes in the Northeast Atlantic: a comparison between a global and a regional model system

2018 ◽  
Vol 75 (7) ◽  
pp. 2355-2369 ◽  
Author(s):  
Morten D Skogen ◽  
Solfrid S Hjøllo ◽  
Anne Britt Sandø ◽  
Jerry Tjiputra
Keyword(s):  
Climate Model ◽  
Spring Bloom ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Scale ◽  
Regional Model ◽  
Global Model ◽  
Future Climate Change ◽  
Co2 Uptake ◽  
The Future

Abstract The biogeochemistry from a global climate model (Norwegian Earth System Model) has been compared with results from a regional model (NORWECOM.E2E), where the regional model is forced by downscaled physics from the global model. The study should both be regarded as a direct comparison between a regional and its driving global model to investigate at what extent a global climate model can be used for regional studies, and a study of the future climate change in the Nordic and Barents Seas. The study concludes that the global and regional model compare well on trends, but many details are lost when a coarse resolution global model is used to assess climate impact on regional scale. The main difference between the two models is the timing of the spring bloom, and a non-exhaustive nutrient consumption in the global model in summer. The global model has a cold (in summer) and saline bias compared with climatology. This is both due to poorly resolved physical processes and oversimplified ecosystem parameterization. Through the downscaling the regional model is to some extent able to alleviate the bias in the physical fields, and the timing of the spring bloom is close to observations. The summer nutrient minimum is one month early. There is no trend in future primary production in any of the models, and the trends in modelled pH and ΩAr are also the same in both models. The largest discrepancy in the future projection is in the development of the CO2 uptake, where the regional suggests a slightly reduced uptake in the future.

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>

scholarly journals Similarities within a multi-model ensemble: functional data analysis framework

2019 ◽  
Vol 12 (2) ◽  
pp. 735-747 ◽  
Author(s):  
Eva Holtanová ◽  
Thomas Mendlik ◽  
Jan Koláček ◽  
Ivanka Horová ◽  
Jiří Mikšovský
Keyword(s):  
Time Series ◽  
Data Analysis ◽  
Functional Data Analysis ◽  
Functional Data ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Future Climate Change ◽  
Model Ensembles

Abstract. Despite the abundance of available global climate model (GCM) and regional climate model (RCM) outputs, their use for evaluation of past and future climate change is often complicated by substantial differences between individual simulations and the resulting uncertainties. In this study, we present a methodological framework for the analysis of multi-model ensembles based on a functional data analysis approach. A set of two metrics that generalize the concept of similarity based on the behavior of entire simulated climatic time series, encompassing both past and future periods, is introduced. To our knowledge, our method is the first to quantitatively assess similarities between model simulations based on the temporal evolution of simulated values. To evaluate mutual distances of the time series, we used two semimetrics based on Euclidean distances between the simulated trajectories and based on differences in their first derivatives. Further, we introduce an innovative way of visualizing climate model similarities based on a network spatialization algorithm. Using the layout graphs, the data are ordered on a two-dimensional plane which enables an unambiguous interpretation of the results. The method is demonstrated using two illustrative cases of air temperature over the British Isles (BI) and precipitation in central Europe, simulated by an ensemble of EURO-CORDEX RCMs and their driving GCMs over the 1971–2098 period. In addition to the sample results, interpretational aspects of the applied methodology and its possible extensions are also discussed.

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 Non-linear intensification of Sahel rainfall as a possible dynamic response to future warming

2017 ◽  
Vol 8 (3) ◽  
pp. 495-505 ◽  
Author(s):  
Jacob Schewe ◽  
Anders Levermann
Keyword(s):  
Climate Model ◽  
Climate Modeling ◽  
Global Climate ◽  
Global Climate Model ◽  
West African Monsoon ◽  
Future Climate Change ◽  
Source Regions ◽  
Future Global Warming ◽  
Sahel Rainfall ◽  
Climate Model Simulations

Abstract. Projections of the response of Sahel rainfall to future global warming diverge significantly. Meanwhile, paleoclimatic records suggest that Sahel rainfall is capable of abrupt transitions in response to gradual forcing. Here we present climate modeling evidence for the possibility of an abrupt intensification of Sahel rainfall under future climate change. Analyzing 30 coupled global climate model simulations, we identify seven models where central Sahel rainfall increases by 40 to 300 % over the 21st century, owing to a northward expansion of the West African monsoon domain. Rainfall in these models is non-linearly related to sea surface temperature (SST) in the tropical Atlantic and Mediterranean moisture source regions, intensifying abruptly beyond a certain SST warming level. We argue that this behavior is consistent with a self-amplifying dynamic–thermodynamical feedback, implying that the gradual increase in oceanic moisture availability under warming could trigger a sudden intensification of monsoon rainfall far inland of today's core monsoon region.

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