scholarly journals STUDY ON THE FLOOD AND DROUGHT RISK AS OF GLOBAL WARMING BY REGIONAL CLIMATE MODEL

2005 ◽  
Vol 49 ◽  
pp. 493-498 ◽  
Author(s):  
Kazunori Wada ◽  
Masahiko Murase ◽  
Yosuke Tomizawa
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Drought Risk

Impacts of global warming of 1.5 °C and 2.0 °C on precipitation patterns in China by regional climate model (COSMO-CLM)

2018 ◽  
Vol 203 ◽  
pp. 83-94 ◽  
Author(s):  
Hemin Sun ◽  
Anqian Wang ◽  
Jianqing Zhai ◽  
Jinlong Huang ◽  
Yanjun Wang ◽  
...  
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Precipitation Patterns

scholarly journals Weather extremes over Europe under 1.5 and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2021 ◽  
Vol 12 (2) ◽  
pp. 457-468
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Climate Indices ◽  
Weather Extremes ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel dataset of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. This is a unique and physically consistent dataset, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100×10-year simulations and 25×10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. To demonstrate how adaptation-relevant information can be derived from the HAPPI dataset, changes in four climate indices for periods with 1.5 and 2.0 ∘C global warming are quantified. These indices include number of days per year with daily mean near-surface apparent temperature of >28 ∘C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-year return period (RI50yr); and the annual consecutive dry days (CDDs). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature-related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 ∘C.

scholarly journals Projection of Climatic Change over Japan Due to Global Warming by High-Resolution Regional Climate Model in MRI

SOLA ◽  
2005 ◽  
Vol 1 (0) ◽  
pp. 97-100 ◽  
Author(s):  
Kazuo Kurihara ◽  
Koji Ishihara ◽  
Hidetaka Sasaki ◽  
Yukio Fukuyama ◽  
Hitomi Saitou ◽  
...  
Keyword(s):  
Global Warming ◽  
High Resolution ◽  
Regional Climate Model ◽  
Climatic Change ◽  
Climate Model ◽  
Regional Climate

scholarly journals Agricultural Adaptation to Global Warming in the Tibetan Plateau

2019 ◽  
Vol 16 (19) ◽  
pp. 3686
Author(s):  
Yanling Song ◽  
Chunyi Wang ◽  
Hans W. Linderholm ◽  
Jinfeng Tian ◽  
Ying Shi ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Tibetan Plateau ◽  
Winter Wheat ◽  
Regional Climate Model ◽  
Spring Wheat ◽  
Climate Model ◽  
Regional Climate ◽  
The Tibetan Plateau ◽  
Agricultural Adaptation

The Tibetan plateau is one of the most sensitive areas in China and has been significantly affected by global warming. From 1961 to 2017, the annual air temperature increased by 0.32 °C/decade over the Tibetan Plateau, which is the highest in the whole of China. Furthermore, this is a trend that is projected to continue by 0.30 °C/decade from 2018 to 2050 due to global warming using the Regional Climate Model version 4 (RegCM4). The increased temperature trend in recent decades has been highest in winter, which has been positive for the safe dormancy of winter wheat. In order to investigate agricultural adaptation to climate change in the Tibetan plateau, we used the World Food Studies (WOFOST) cropping systems model and weather data from the regional climate model RegCM4, to simulate winter wheat production in Guide county between 2018 and 2050. The simulated winter wheat potential yields amounted to 6698.3 kg/ha from 2018 to 2050, which showed the wheat yields would increase by 81%, if winter wheat was planted instead of spring wheat in the Tibetan Plateau with the correct amount of irrigation water. These results indicate that there are not only risks to crop yields from climate change, but also potential benefits. Global warming introduced the possibility to plant winter wheat instead of spring wheat over the Tibetan Plateau. These findings are very important for farmers and government agencies dealing with agricultural adaptation in a warmer climate.

scholarly journals Weather extremes over Europe under 1.5 °C and 2.0 °C global warming from HAPPI regional climate ensemble simulations

2020 ◽  
Author(s):  
Kevin Sieck ◽  
Christine Nam ◽  
Laurens M. Bouwer ◽  
Diana Rechid ◽  
Daniela Jacob
Keyword(s):  
Global Warming ◽  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Apparent Temperature ◽  
Weather Extremes ◽  
Data Set ◽  
Near Surface ◽  
Model Simulations ◽  
Climate Model Simulations

Abstract. This paper presents a novel data set of regional climate model simulations over Europe that significantly improves our ability to detect changes in weather extremes under low and moderate levels of global warming. The data set provides a unique and physically consistent data set, as it is derived from a large ensemble of regional climate model simulations. These simulations were driven by two global climate models from the international HAPPI consortium. The set consists of 100 × 10-year simulations and 25 × 10-year simulations, respectively. These large ensembles allow for regional climate change and weather extremes to be investigated with an improved signal-to-noise ratio compared to previous climate simulations. The changes in four climate indices for temperature targets of 1.5 °C and 2.0 °C global warming are quantified: number of days per year with daily mean near-surface apparent temperature of > 28 °C (ATG28); the yearly maximum 5-day sum of precipitation (RX5day); the daily precipitation intensity of the 50-yr return period (RI50yr); and the annual Consecutive Dry Days (CDD). This work shows that even for a small signal in projected global mean temperature, changes of extreme temperature and precipitation indices can be robustly estimated. For temperature related indices changes in percentiles can also be estimated with high confidence. Such data can form the basis for tailor-made climate information that can aid adaptive measures at a policy-relevant scales, indicating potential impacts at low levels of global warming at steps of 0.5 °C.

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