Selection of climate information for regional climate change assessments using regionalization techniques: an example for the Upper Great Lakes Region, USA

2014 ◽  
Vol 35 (6) ◽  
pp. 1027-1040 ◽  
Author(s):  
Perdinan ◽  
Julie A. Winkler
Keyword(s):  
Climate Change ◽  
Great Lakes ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Great Lakes Region ◽  
Climate Information ◽  
Upper Great Lakes ◽  
Selection Of

Regional climate change projections for Chicago and the US Great Lakes

2010 ◽  
Vol 36 ◽  
pp. 7-21 ◽  
Author(s):  
Katharine Hayhoe ◽  
Jeff VanDorn ◽  
Thomas Croley ◽  
Nicole Schlegal ◽  
Donald Wuebbles
Keyword(s):  
Climate Change ◽  
Great Lakes ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Climate Change Projections ◽  
The Us

scholarly journals Optimization Assessment of Projection Methods of Climate Change for Discrepancies between North and South China

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3106
Author(s):  
Yurui Lun ◽  
Liu Liu ◽  
Ruotong Wang ◽  
Guanhua Huang
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Statistical Downscaling ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Climate Zones ◽  
Climate Change Projection ◽  
The North ◽  
North And South ◽  
Selection Of

Downscaling methods have been widely used due to the coarse and biased outputs of general circulation models (GCMs), which cannot be applied directly in regional climate change projection. Hence, appropriate selection of GCMs and downscaling methods is important for assessing the impacts of climate change. To explicitly explore the influences of multi-GCMs and different downscaling methods on climate change projection in various climate zones, the Heihe River Basin (HRB) and the Zhanghe River Basin (ZRB) were selected in this study to represent the north arid region and the south humid region in China, respectively. We first evaluated the performance of multi-GCMs derived from Coupled Model Inter-comparison Project Phase 5 (CMIP5) in the two regions based on in-situ measurements and the 40 year European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) data. Subsequently, to construct appropriate climate change projection techniques, comparative analysis using two statistical downscaling methods was performed with consideration of the significant north–south meteorological discrepancies. Consequently, specific projections of future climate change for 2021–2050 under three representative concentration pathway (RCP) scenarios (RCP2.6, RCP4.5, and RCP8.5) were completed for the HRB and ZRB, including daily precipitation, maximum air temperature, and minimum air temperature. The results demonstrated that the score-based method with multiple criteria for performance evaluation of multiple GCMs more accurately captured the spatio-temporal characteristics of the regional climate. The two statistical downscaling methods showed respective advantages in arid and humid regions. The statistical downscaling model (SDSM) showed more accurate prediction capacities for air temperature in the arid-climate HRB, whereas model output statistics (MOS) better captured the probability distribution of precipitation in the ZRB, which is characterized by a humid climate. According to the results obtained in this study, the selection of appropriate GCMs and downscaling methods for specific climate zones with different meteorological features significantly impact regional climate change projection. The statistical downscaling models developed and recommended for the north and south of China in this study provide scientific reference for sustainable water resource management subject to climate change.

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 Regional Climate Change Competitiveness—Modelling Approach

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3704
Author(s):  
Agnieszka Karman ◽  
Andrzej Miszczuk ◽  
Urszula Bronisz
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Regional Climate Change ◽  
Measurement Scale ◽  
Practical Application ◽  
Adaptation To Climate Change ◽  
Regional Competitiveness ◽  
The Face ◽  
Competitiveness Index ◽  
Modelling Approach

The article deals with the competitiveness of regions in the face of climate change. The aim was to present the concept of measuring the Regional Climate Change Competitiveness Index. We used a comparative and logical analysis of the concept of regional competitiveness and heuristic conceptual methods to construct the index and measurement scale. The structure of the index includes six broad sub-indexes: Basic, Natural, Efficiency, Innovation, Sectoral, Social, and 89 indicators. A practical application of the model was presented for the Mazowieckie province in Poland. This allowed the region’s performance in the context of climate change to be presented, and regional weaknesses in the process of adaptation to climate change to be identified. The conclusions of the research confirm the possibility of applying the Regional Climate Change Competitiveness Index in the economic analysis and strategic planning. The presented model constitutes one of the earliest tools for the evaluation of climate change competitiveness at a regional level.

scholarly journals Turn down the heat: regional climate change impacts on development

2017 ◽  
Vol 17 (6) ◽  
pp. 1563-1568 ◽  
Author(s):  
Christopher P. O. Reyer ◽  
Kanta Kumari Rigaud ◽  
Erick Fernandes ◽  
William Hare ◽  
Olivia Serdeczny ◽  
...  
Keyword(s):  
Climate Change ◽  
Regional Climate ◽  
Climate Change Impacts ◽  
Regional Climate Change
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