Tropical cyclones in a regional climate change projection with RegCM4 over the CORDEX Central America domain

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.

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Fire hazard forecast by the regional climate change projection using the ETA model: a case study in Bahia, Brazil

Territorium Revista Portuguesa de riscos prevenção e segurança ◽

10.14195/1647-7723_29-1_5 ◽

2021 ◽

pp. 59-66

Author(s):

Rodrigo Rudge Ramos Ribeiro ◽

Miguel Angel Trejo-Rangel ◽

Samia Nascimento Sulaiman

Keyword(s):

Climate Change ◽

Fire Hazard ◽

Meteorological Data ◽

Regional Climate ◽

Regional Climate Change ◽

Weather Forecast ◽

Maximum Temperature ◽

Fire Occurrence ◽

Climate Change Projection ◽

Eta Model

This article proposes a method for predicting fire occurrence, considering regional climate change projection using the Eta model, with a 20 km resolution, for the RCP4.5 and RCP8.5 scenarios. Fire occurrence in the state of Bahia was calculated as a function of the three main sensitivity factors on a daily time-scale: days without precipitation, precipitation, and maximum temperature. Historical fire occurrences from 1998 to 2018 and meteorological data from 1960 to 2018 were obtained from official institutes, and weather forecast parameters from 2018 to 2050 were downscaled from the web platform PROJETA. The correlations between the meteorological factors and fire occurrence were calculated for the historical data and a weight factor corresponding to a control simulation. Afterwards, a correction factor was determined, based on the historical fire occurrence data used for the forecast in the two scenarios. The results indicate that between 2018 and 2050, risk of fire will have an average increase of 27% at the RCP4.5 and 38% at the RCP8.5 scenario.

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GPS Time Series as Proxies for Regional Climate Change

Proceedings of the 31st International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2018) ◽

10.33012/2018.16088 ◽

2018 ◽

Author(s):

Shimon Wdowinski

Keyword(s):

Climate Change ◽

Time Series ◽

Regional Climate ◽

Regional Climate Change ◽

Gps Time Series

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

npj Climate and Atmospheric Science ◽

10.1038/s41612-020-00159-2 ◽

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.

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Regional Climate Change Competitiveness—Modelling Approach

Energies ◽

10.3390/en14123704 ◽

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.

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Tropical cyclones cumulatively control regional carbon fluxes in Everglades mangrove wetlands (Florida, USA)

Scientific Reports ◽

10.1038/s41598-021-92899-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Xiaochen Zhao ◽

Victor H. Rivera-Monroy ◽

Luis M. Farfán ◽

Henry Briceño ◽

Edward Castañeda-Moya ◽

...

Keyword(s):

Tropical Cyclones ◽

Functional Role ◽

Net Primary Productivity ◽

Dissolved Inorganic Carbon ◽

Regional Climate ◽

Regional Climate Change ◽

Neotropical Region ◽

Limited Information ◽

Organic C ◽

Wide Range

AbstractMangroves are the most blue-carbon rich coastal wetlands contributing to the reduction of atmospheric CO2 through photosynthesis (sequestration) and high soil organic carbon (C) storage. Globally, mangroves are increasingly impacted by human and natural disturbances under climate warming, including pervasive pulsing tropical cyclones. However, there is limited information assessing cyclone’s functional role in regulating wetlands carbon cycling from annual to decadal scales. Here we show how cyclones with a wide range of integrated kinetic energy (IKE) impact C fluxes in the Everglades, a neotropical region with high cyclone landing frequency. Using long-term mangrove Net Primary Productivity (Litterfall, NPPL) data (2001–2018), we estimated cyclone-induced litterfall particulate organic C (litter-POC) export from mangroves to estuarine waters. Our analysis revealed that this lateral litter-POC flux (71–205 g C m−2 year−1)—currently unaccounted in global C budgets—is similar to C burial rates (69–157 g C m−2 year−1) and dissolved inorganic carbon (DIC, 61–229 g C m−2 year−1) export. We proposed a statistical model (PULITER) between IKE-based pulse index and NPPL to determine cyclone’s impact on mangrove role as C sink or source. Including the cyclone’s functional role in regulating mangrove C fluxes is critical to developing local and regional climate change mitigation plans.

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