scholarly journals A Projection of Extreme Precipitation Based on a Selection of CMIP5 GCMs over North Korea

2019 ◽  
Vol 11 (7) ◽  
pp. 1976 ◽  
Author(s):  
Jang Sung ◽  
Minsung Kwon ◽  
Jong-June Jeon ◽  
Seung Seo
Keyword(s):  
Climate Change ◽  
Extreme Precipitation ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Daily Maximum ◽  
Climate Change Scenarios ◽  
Model Ensemble ◽  
Model Variability ◽  
Cmip5 Gcms ◽  
Selection Of

The numerous choices between climate change scenarios makes decision-making difficult for the assessment of climate change impacts. Previous studies have used climate models to compare performance in terms of simulating observed climates or preserving model variability among scenarios. In this study, the Katsavounidis-Kuo-Zhang algorithm was applied to select representative climate change scenarios (RCCS) that preserve the variability among all climate change scenarios (CCS). The performance of multi-model ensemble of RCCS was evaluated for reference and future climates. It was found that RCCS was well suited for observations and multi model ensemble of all CCS. Using the RCCS under RCP (Representative Concentration Pathway) 8.5, the future extreme precipitation was projected. As a result, the magnitude and frequency of extreme precipitation increased towards the farther future. Especially, extreme precipitation (daily maximum precipitation of 20-year return-period) during 2070-2099, was projected to occur once every 8.3-year. The RCCS employed in this study is able to successfully represent the performance of all CCS, therefore, this approach can give opportunities managing water resources efficiently for assessment of climate change impacts.

scholarly journals ELPIS-JP: a dataset of local-scale daily climate change scenarios for Japan

2012 ◽  
Vol 370 (1962) ◽  
pp. 1121-1139 ◽  
Author(s):  
Toshichika Iizumi ◽  
Mikhail A. Semenov ◽  
Motoki Nishimori ◽  
Yasushi Ishigooka ◽  
Tsuneo Kuwagata
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Regional Climate Models ◽  
Local Scale ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Emission Scenarios ◽  
Model Ensemble ◽  
Daily Weather Data

We developed a dataset of local-scale daily climate change scenarios for Japan (called ELPIS-JP) using the stochastic weather generators (WGs) LARS-WG and, in part, WXGEN. The ELPIS-JP dataset is based on the observed (or estimated) daily weather data for seven climatic variables (daily mean, maximum and minimum temperatures; precipitation; solar radiation; relative humidity; and wind speed) at 938 sites in Japan and climate projections from the multi-model ensemble of global climate models (GCMs) used in the coupled model intercomparison project (CMIP3) and multi-model ensemble of regional climate models form the Japanese downscaling project (called S-5-3). The capability of the WGs to reproduce the statistical features of the observed data for the period 1981–2000 is assessed using several statistical tests and quantile–quantile plots. Overall performance of the WGs was good. The ELPIS-JP dataset consists of two types of daily data: (i) the transient scenarios throughout the twenty-first century using projections from 10 CMIP3 GCMs under three emission scenarios (A1B, A2 and B1) and (ii) the time-slice scenarios for the period 2081–2100 using projections from three S-5-3 regional climate models. The ELPIS-JP dataset is designed to be used in conjunction with process-based impact models (e.g. crop models) for assessment, not only the impacts of mean climate change but also the impacts of changes in climate variability, wet/dry spells and extreme events, as well as the uncertainty of future impacts associated with climate models and emission scenarios. The ELPIS-JP offers an excellent platform for probabilistic assessment of climate change impacts and potential adaptation at a local scale in Japan.

Partnerships to Visualize Climate Change Futures in Tampa Bay, Florida

2019 ◽  
Vol 41 (3) ◽  
pp. 42-47
Author(s):  
Rebecca K. Zarger ◽  
Gina Larsen ◽  
Alexis Winter ◽  
Libby Carnahan ◽  
Ramona Madhosingh-Hector ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Global Climate ◽  
Climate Change Impacts ◽  
Tampa Bay ◽  
Global Climate Models ◽  
Extension Agents ◽  
Climate Change Scenarios ◽  
Local Climate ◽  
The Public

Abstract Our project investigates public perceptions of climate change risk and vulnerability in the Tampa Bay, Florida, region, specifically focused on how climate change is likely to impact water infrastructure in the area. As part of the project, our research team of anthropologists and environmentally-focused state extension agents collaboratively developed public workshops to promote more dialogue on local climate change impacts. The anthropologists developed localized climate change scenarios based on global climate models, Florida-centric models, and input from key informants. Extension agents brought expertise in climate and sustainability science and facilitating educational programming and dialogue. We documented residents' concerns and views on climate change, how local scenarios are received by the public, and how scenarios can be communicated to the public through narrative and visual formats. We consider the roles of anthropologist-extension agent partnerships in creating new spaces for dialogue on climate change futures.

scholarly journals A new dataset for systematic assessments of climate change impacts as a function of global warming

2012 ◽  
Vol 5 (4) ◽  
pp. 3533-3572 ◽  
Author(s):  
J. Heinke ◽  
S. Ostberg ◽  
S. Schaphoff ◽  
K. Frieler ◽  
C. Müller ◽  
...  
Keyword(s):  
Climate Change ◽  
Temperature Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Climate Change Scenarios ◽  
Political Debate ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
Global Mean

Abstract. In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalized patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 AOGCMs. The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilize a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

scholarly journals Climate change and hydrological extremes in Belgian catchments

2010 ◽  
Vol 7 (4) ◽  
pp. 5033-5078 ◽  
Author(s):  
P. Baguis ◽  
E. Roulin ◽  
P. Willems ◽  
V. Ntegeka
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Potential Evapotranspiration ◽  
Hydrological Regime ◽  
Climate Change Impacts ◽  
Delta Method ◽  
Climate Change Signal ◽  
Climate Change Scenarios ◽  
Hydrological Extremes ◽  
Current Century

Abstract. In this study we focus our attention on the climate change impacts on the hydrological balance in Belgium. There are two main rivers in the country, the Scheldt and the Meuse, supplied with water almost exclusively by precipitation. With the climate change projected by climate models for the end of the current century, one would expect that the hydrological regime of the rivers may be affected mainly through the changes in precipitation patterns and the increased potential evapotranspiration (PET) due to increased temperature throughout the year. We examine the hydrology of two important tributaries of the rivers Scheldt and Meuse, the Gete and the Ourthe, respectively. Our analysis is based on simulations with the SCHEME hydrological model and on climate change data from the European PRUDENCE project. Two emission scenarios are considered, the SRES A2 and B2 scenarios, and the perturbation (or delta) method is used in order to assess the climate change signal at monthly time scale and provide appropriate input time series for the hydrological simulations. The ensemble of climate change scenarios used allows us to estimate the combined model and scenario uncertainty in the streamflow calculations, inherent to this kind of analysis. In this context, we also analyze extreme river flows using two probability distribution families, allowing us to quantify the shift of the extremes under climate change conditions.

A Weather Generator-Based Statistical Downscaling Tool for Site-Specific Assessment of Climate Change Impacts

2018 ◽  
Vol 61 (3) ◽  
pp. 977-993 ◽  
Author(s):  
Jie Chen ◽  
Xunchang John Zhang ◽  
Xiangquan Li
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Statistical Downscaling ◽  
Climate Models ◽  
Climate Change Impacts ◽  
Weather Generator ◽  
Climate Change Scenarios ◽  
Widespread Application ◽  
Site Specific ◽  
Downscaling Method

Abstract. Statistical downscaling approaches are usually used to bridge the gap between climate model outputs and data requirements of impact models such as crop and soil erosion models. This study synthesizes, integrates, and standardizes a statistical downscaling method that was initially developed in 2005 and subsequently evaluated and improved during the last decade. A new downscaling software program, Generator for Point Climate Change (GPCC), has been developed to automate and visualize the method to assist end users with detailed technical and user documentation. GPCC readily generates daily time series of climate change scenarios for local and site-specific climate change impact studies using monthly projections from global climate models or regional climate models. The downscaled variables include precipitation and maximum and minimum temperatures. This software provides a simple but effective climate downscaling tool for assessing the impacts of climate change on crop production, soil hydrology, and soil erosion at a field scale. The tool can also provide an alternative downscaling method to facilitate the international collaborative efforts of the Agricultural Model Intercomparison and Improvement Project (AgMIP) for simulation of world food production and food security assessment. The detailed downscaling methods, their scientific bases, and the advantages of GPCC over other commonly used downscaling methods are presented. GPCC is written in the Matlab language, and a standalone version can be run on Windows XP or above without Matlab software. The tool has a graphical user interface that is simple and easy to generate downscaled climates as well as to visualize downscaled outputs. Each interface tab and key button and their functions are described to facilitate its widespread application. Keywords: Agricultural system models, Climate change impacts, Generator for point climate change, Interface, Statistical downscaling, Stochastic weather generator.

Impact of climate change scenarios on Canadian agroclimatic indices

2013 ◽  
Vol 93 (2) ◽  
pp. 243-259 ◽  
Author(s):  
Budong Qian ◽  
Reinder De Jong ◽  
Sam Gameda ◽  
Ted Huffman ◽  
Denise Neilsen ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Warm Season ◽  
Climate Change Impacts ◽  
Growing Season ◽  
Adaptation Strategies ◽  
Climate Change Scenarios ◽  
Climate Scenarios ◽  
Heat Accumulation ◽  
Cool Season

Qian, B., De Jong, R., Gameda, S., Huffman, T., Neilsen, D., Desjardins, R., Wang, H. and McConkey, B. 2013. Impact of climate change scenarios on Canadian agroclimatic indices. Can. J. Soil Sci. 93: 243–259. The Canadian agricultural sector is facing the impacts of climate change. Future scenarios of agroclimatic change provide information for assessing climate change impacts and developing adaptation strategies. The goal of this study was to derive and compare agroclimatic indices based on current and projected future climate scenarios and to discuss the potential implications of climate change impacts on agricultural production and adaptation strategies in Canada. Downscaled daily climate scenarios, including maximum and minimum temperatures and precipitation for a future time period, 2040–2069, were generated using the stochastic weather generator AAFC-WG for Canadian agricultural regions on a 0.5°×0.5° grid. Multiple climate scenarios were developed, based on the results of climate change simulations conducted using two global climate models – CGCM3 and HadGEM1 – forced by IPCC SRES greenhouse gas (GHG) emission scenarios A2, A1B and B1, as well as two regional climate models forced by the A2 emission scenario. The agroclimatic indices that estimate growing season start, end and length, as well as heat accumulations and moisture conditions during the growing season for three types of field crops, cool season, warm season and over-wintering crops, were used to represent agroclimatic conditions. Compared with the baseline period 1961–1990, growing seasons were projected to start earlier, on average 13 d earlier for cool season and over-wintering crops and 11 d earlier for warm season crops. The end of the growing season was projected on average to be 10 and 13 d later for over-wintering and warm season crops, respectively, but 11 d earlier for cool season crops because of the projected high summer temperatures. Two indices quantifying the heat accumulation during the growing season, effective growing degree days (EGDD) and crop heat units (CHU) indicated a notable increase in heat accumulation: on average, EGDD increased by 15, 55 and 34% for cool season, warm season and over-wintering crops, respectively. The magnitudes of the projected changes were highly dependent on the climate models, as well as on the GHG emission scenarios. Some contradictory projections were observed for moisture conditions based on precipitation deficit accumulated over the growing season. This confirmed that the uncertainties in climate projections were large, especially those related to precipitation, and such uncertainties should be taken into account in decision making when adaptation strategies are developed. Nevertheless, the projected changes in indices related to temperature were fairly consistent.

scholarly journals MODELLING SHORELINE EVOLUTION IN RESPONSE TO CLIMATE CHANGE

2011 ◽  
Vol 1 (32) ◽  
pp. 28
Author(s):  
Anna Zacharioudaki ◽  
Dominic E Reeve
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Change Impacts ◽  
Wave Climate ◽  
Climate Change Scenarios ◽  
Physical Processes ◽  
Shoreline Evolution ◽  
The Uk ◽  
A Site

In this paper we examine the evidence for detectable climate change impacts on shoreline evolution. In a sequentially linked set of models, climate change scenarios are taken from atmospheric climate models and used to generate time slices of deepwater wave climate, nearshore wave climate and shoreline evolution. The models used are simple, containing the key physical processes only. Results are based on a hypothetical case which has some similarities to a site on the south coast of the UK. Output from the model is analysed using a robust statistical methodology to determine the evidence for statistically significant differences between beach behaviour under current conditions and several future scenarios. Statistically significant differences vary with season and also with the combination of climate model outputs used for input. Summers are the only season for which all models showed significant changes, corresponding to an increase in the net eastward littoral transport.

scholarly journals Projecting heat-related excess mortality under climate change scenarios in China

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Jun Yang ◽  
Maigeng Zhou ◽  
Zhoupeng Ren ◽  
Mengmeng Li ◽  
Boguang Wang ◽  
...  
Keyword(s):  
Climate Change ◽  
Excess Mortality ◽  
Climate Models ◽  
Global Climate ◽  
Specific Effect ◽  
Northern China ◽  
The Elderly ◽  
Population Ageing ◽  
Global Climate Models ◽  
Climate Change Scenarios

AbstractRecent studies have reported a variety of health consequences of climate change. However, the vulnerability of individuals and cities to climate change remains to be evaluated. We project the excess cause-, age-, region-, and education-specific mortality attributable to future high temperatures in 161 Chinese districts/counties using 28 global climate models (GCMs) under two representative concentration pathways (RCPs). To assess the influence of population ageing on the projection of future heat-related mortality, we further project the age-specific effect estimates under five shared socioeconomic pathways (SSPs). Heat-related excess mortality is projected to increase from 1.9% (95% eCI: 0.2–3.3%) in the 2010s to 2.4% (0.4–4.1%) in the 2030 s and 5.5% (0.5–9.9%) in the 2090 s under RCP8.5, with corresponding relative changes of 0.5% (0.0–1.2%) and 3.6% (−0.5–7.5%). The projected slopes are steeper in southern, eastern, central and northern China. People with cardiorespiratory diseases, females, the elderly and those with low educational attainment could be more affected. Population ageing amplifies future heat-related excess deaths 2.3- to 5.8-fold under different SSPs, particularly for the northeast region. Our findings can help guide public health responses to ameliorate the risk of climate change.

scholarly journals Water Budgets of Managed Forests in Northeast Germany under Climate Change—Results from a Model Study on Forest Monitoring Sites

2021 ◽  
Vol 11 (5) ◽  
pp. 2403
Author(s):  
Daniel Ziche ◽  
Winfried Riek ◽  
Alexander Russ ◽  
Rainer Hentschel ◽  
Jan Martin
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Coupled Model ◽  
Regional Climate Models ◽  
Realistic Model ◽  
Forest Monitoring ◽  
Climate Change Scenarios ◽  
Historical Time ◽  
Time Period

To develop measures to reduce the vulnerability of forests to drought, it is necessary to estimate specific water balances in sites and to estimate their development with climate change scenarios. We quantified the water balance of seven forest monitoring sites in northeast Germany for the historical time period 1961–2019, and for climate change projections for the time period 2010–2100. We used the LWF-BROOK90 hydrological model forced with historical data, and bias-adjusted data from two models of the fifth phase of the Coupled Model Intercomparison Project (CMIP5) downscaled with regional climate models under the representative concentration pathways (RCPs) 2.6 and 8.5. Site-specific monitoring data were used to give a realistic model input and to calibrate and validate the model. The results revealed significant trends (evapotranspiration, dry days (actual/potential transpiration < 0.7)) toward drier conditions within the historical time period and demonstrate the extreme conditions of 2018 and 2019. Under RCP8.5, both models simulate an increase in evapotranspiration and dry days. The response of precipitation to climate change is ambiguous, with increasing precipitation with one model. Under RCP2.6, both models do not reveal an increase in drought in 2071–2100 compared to 1990–2019. The current temperature increase fits RCP8.5 simulations, suggesting that this scenario is more realistic than RCP2.6.

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