scholarly journals Climate Change Hotspots Identification in China through the CMIP5 Global Climate Model Ensemble

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Huanghe Gu ◽  
Zhongbo Yu ◽  
Jigan Wang ◽  
Qin Ju ◽  
Chuanguo Yang ◽  
...  
Keyword(s):  
Climate Change ◽  
21St Century ◽  
Climate Model ◽  
Greenhouse Gas Emission ◽  
Global Climate Model ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Seasonal Temperature ◽  
Climate Variables ◽  
Model Ensemble

China is one of the countries vulnerable to adverse climate changes. The potential climate change hotspots in China throughout the 21st century are identified in this study by using a multimodel, multiscenario climate model ensemble that includes Phase Five of the Coupled Model Intercomparison Project (CMIP5) atmosphere-ocean general circulation models. Both high (RCP8.5) and low (RCP4.5) greenhouse gas emission trajectories are tested, and both the mean and extreme seasonal temperature and precipitation are considered in identifying regional climate change hotspots. Tarim basin and Tibetan Plateau in West China are identified as persistent regional climate change hotspots in both the RCP4.5 and RCP8.5 scenarios. The aggregate impacts of climate change increase throughout the 21st century and are more significant in RCP8.5 than in RCP4.5. Extreme hot event and mean temperature are two climate variables that greatly contribute to the hotspots calculation in all regions. The contribution of other climate variables exhibits a notable subregional variability. South China is identified as another hotspot based on the change of extreme dry event, especially in SON and DJF, which indicates that such event will frequently occur in the future. Our results can contribute to the designing of national and cross-national adaptation and mitigation policies.

scholarly journals Early emergence in a butterfly causally linked to anthropogenic warming

2010 ◽  
Vol 6 (5) ◽  
pp. 674-677 ◽  
Author(s):  
Michael R. Kearney ◽  
Natalie J. Briscoe ◽  
David J. Karoly ◽  
Warren P. Porter ◽  
Melanie Norgate ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Change ◽  
Future Climate Change ◽  
Climate Data ◽  
Regional Warming

There is strong correlative evidence that human-induced climate warming is contributing to changes in the timing of natural events. Firm attribution, however, requires cause-and-effect links between observed climate change and altered phenology, together with statistical confidence that observed regional climate change is anthropogenic. We provide evidence for phenological shifts in the butterfly Heteronympha merope in response to regional warming in the southeast Australian city of Melbourne. The mean emergence date for H. merope has shifted −1.5 days per decade over a 65-year period with a concurrent increase in local air temperatures of approximately 0.16°C per decade. We used a physiologically based model of climatic influences on development, together with statistical analyses of climate data and global climate model projections, to attribute the response of H. merope to anthropogenic warming. Such mechanistic analyses of phenological responses to climate improve our ability to forecast future climate change impacts on biodiversity.

An assessment of global and regional climate change based on the EH5OM climate model ensemble

2009 ◽  
Vol 98 (1-2) ◽  
pp. 21-49 ◽  
Author(s):  
Čedo Branković ◽  
Lidija Srnec ◽  
Mirta Patarčić
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Model Ensemble

scholarly journals Incorrect Asian aerosols affecting the attribution and projection of regional climate change in CMIP6 models

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Zhili Wang ◽  
Lei Lin ◽  
Yangyang Xu ◽  
Huizheng Che ◽  
Xiaoye Zhang ◽  
...  
Keyword(s):  
Climate Change ◽  
Radiative Forcing ◽  
Impact Analysis ◽  
Climate Model ◽  
Regional Climate ◽  
Eastern China ◽  
Coupled Model ◽  
Regional Climate Change ◽  
Anthropogenic Aerosol ◽  
Wide Range

AbstractAnthropogenic aerosol (AA) forcing has been shown as a critical driver of climate change over Asia since the mid-20th century. Here we show that almost all Coupled Model Intercomparison Project Phase 6 (CMIP6) models fail to capture the observed dipole pattern of aerosol optical depth (AOD) trends over Asia during 2006–2014, last decade of CMIP6 historical simulation, due to an opposite trend over eastern China compared with observations. The incorrect AOD trend over China is attributed to problematic AA emissions adopted by CMIP6. There are obvious differences in simulated regional aerosol radiative forcing and temperature responses over Asia when using two different emissions inventories (one adopted by CMIP6; the other from Peking university, a more trustworthy inventory) to driving a global aerosol-climate model separately. We further show that some widely adopted CMIP6 pathways (after 2015) also significantly underestimate the more recent decline in AA emissions over China. These flaws may bring about errors to the CMIP6-based regional climate attribution over Asia for the last two decades and projection for the next few decades, previously anticipated to inform a wide range of impact analysis.

scholarly journals Multi-scenario and multi-model ensemble of regional climate change projections for the plain areas of the Pannonian Basin

Időjárás ◽  
2020 ◽  
Vol 124 (2) ◽  
pp. 157-190
Author(s):  
Anna Kis ◽  
Rita Pongrácz ◽  
Judit Bartholy ◽  
Milan Gocic ◽  
Mladen Milanovic ◽  
...  
Keyword(s):  
Climate Change ◽  
Pannonian Basin ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Model Ensemble ◽  
Climate Change Projections

scholarly journals Downscaling a global climate model to simulate climate change over the US and the implication on regional and urban air quality

2013 ◽  
Vol 6 (5) ◽  
pp. 1429-1445 ◽  
Author(s):  
M. Trail ◽  
A. P. Tsimpidi ◽  
P. Liu ◽  
K. Tsigaridis ◽  
Y. Hu ◽  
...  
Keyword(s):  
Climate Change ◽  
Air Quality ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Climate Conditions ◽  
Southeastern Us ◽  
The Us ◽  
Ozone Levels

Abstract. Climate change can exacerbate future regional air pollution events by making conditions more favorable to form high levels of ozone. In this study, we use spectral nudging with the Weather Research and Forecasting (WRF) model to downscale NASA earth system GISS modelE2 results during the years 2006 to 2010 and 2048 to 2052 over the contiguous United States in order to compare the resulting meteorological fields from the air quality perspective during the four seasons of five-year historic and future climatological periods. GISS results are used as initial and boundary conditions by the WRF regional climate model (RCM) to produce hourly meteorological fields. The downscaling technique and choice of physics parameterizations used are evaluated by comparing them with in situ observations. This study investigates changes of similar regional climate conditions down to a 12 km by 12 km resolution, as well as the effect of evolving climate conditions on the air quality at major US cities. The high-resolution simulations produce somewhat different results than the coarse-resolution simulations in some regions. Also, through the analysis of the meteorological variables that most strongly influence air quality, we find consistent changes in regional climate that would enhance ozone levels in four regions of the US during fall (western US, Texas, northeastern, and southeastern US), one region during summer (Texas), and one region where changes potentially would lead to better air quality during spring (Northeast). Changes in regional climate that would enhance ozone levels are increased temperatures and stagnation along with decreased precipitation and ventilation. We also find that daily peak temperatures tend to increase in most major cities in the US, which would increase the risk of health problems associated with heat stress. Future work will address a more comprehensive assessment of emissions and chemistry involved in the formation and removal of air pollutants.

scholarly journals Brief Communication: An update of the article "Modelling flood damages under climate change conditions – a case study for Germany"

2016 ◽  
Vol 16 (7) ◽  
pp. 1617-1622 ◽  
Author(s):  
Fred Fokko Hattermann ◽  
Shaochun Huang ◽  
Olaf Burghoff ◽  
Peter Hoffmann ◽  
Zbigniew W. Kundzewicz
Keyword(s):  
Climate Change ◽  
Large Scale ◽  
Considerable Increase ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Impact Modelling ◽  
Flood Damages

Abstract. In our first study on possible flood damages under climate change in Germany, we reported that a considerable increase in flood-related losses can be expected in a future warmer climate. However, the general significance of the study was limited by the fact that outcome of only one global climate model (GCM) was used as a large-scale climate driver, while many studies report that GCMs are often the largest source of uncertainty in impact modelling. Here we show that a much broader set of global and regional climate model combinations as climate drivers show trends which are in line with the original results and even give a stronger increase of damages.

A Preliminary Study on the Relationship between Vegetation Cover and Regional Climate Change in Jiangsu Area of China

2013 ◽  
Vol 448-453 ◽  
pp. 916-922
Author(s):  
Yan Rong Yang ◽  
Zhe Kong ◽  
Chun Ming Liu
Keyword(s):  
Climate Change ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Amount ◽  
Regional Climate Change ◽  
Research Field ◽  
Research Fields ◽  
The Relationship

The relationship between vegetation cover and climate change is one of the most important research fields in global change. Herein Jiangsu province and thereabout in China is chosen to be the research field. Under the support of observations from normalized differential vegetation index (NDVI) during years from 1998 to 2008 and corresponding benchmark weather stations, the relationship between vegetation and climate change had been analyzed combined with simulations from regional climate model RegCM3, in perspectives of point vegetation cover amount and area vegetation cover type respectively. Conclusions are: (1) Points observations showed that NDVI had positive correlation with annual total precipitation and negative correlation with annual average temperature. (2) Area simulations showed that two different vegetation types in south and north Jiangsu almost had same 8warming value, but the incremental annual precipitation amount is more significant in south Jiangsu.

scholarly journals Quantification of the Expected Changes in Annual Maximum Daily Precipitation Quantiles under Climate Change in the Iberian Peninsula

Proceedings ◽  
2018 ◽  
Vol 7 (1) ◽  
pp. 23 ◽  
Author(s):  
Carlos Garijo ◽  
Luis Mediero
Keyword(s):  
Climate Change ◽  
Iberian Peninsula ◽  
Climate Models ◽  
Climate Model ◽  
Global Climate ◽  
Global Climate Model ◽  
Regional Climate ◽  
Control Period ◽  
Regional Climate Models ◽  
The Future

Climate model projections can be used to assess the expected behaviour of extreme precipitations in the future due to climate change. The European part of the Coordinated Regional Climate Downscalling Experiment (EURO-CORDEX) provides precipitation projections for the future under various representative concentration pathways (RCPs) through regionalised Global Climate Model (GCM) outputs by a set of Regional Climate Models (RCMs). In this work, 12 combinations of GCM and RCM under two scenarios (RCP 4.5 and RCP 8.5) supplied by the EURO-CORDEX are analysed for the Iberian Peninsula. Precipitation quantiles for a set of probabilities of non-exceedance are estimated by using the Generalized Extreme Value (GEV) distribution and L-moments. Precipitation quantiles expected in the future are compared with the precipitation quantiles in the control period for each climate model. An approach based on Monte Carlo simulations is developed in order to assess the uncertainty from the climate model projections. Expected changes in the future are compared with the sampling uncertainty in the control period. Thus, statistically significant changes are identified. The higher the significance threshold, the fewer cells with significant changes are identified. Consequently, a set of maps are obtained in order to assist the decision-making process in subsequent climate change studies.

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