scholarly journals PROJECTING CLIMATE VARIABILITY IN THE PURVIEW OF FUTURE CLIMATE PROJECTIONS FOR SHOLA FOREST OF NILGIRIS, WESTERN GHAT IN SOUTH INDIA.

2019 ◽  
Vol 7 (1) ◽  
pp. 876-883
Author(s):  
Tabassum IshrathFathima ◽  
◽  
Somashekar RK ◽  
Mohammed AhmedJ ◽  
◽  
...  
Keyword(s):  
Climate Variability ◽  
South India ◽  
Future Climate ◽  
Western Ghat ◽  
Climate Projections ◽  
Future Climate Projections

Realised added value in dynamical downscaling of Australian climate change

2021 ◽  
Author(s):  
Giovanni Di Virgilio ◽  
Jason P. Evans ◽  
Alejandro Di Luca ◽  
Michael R. Grose ◽  
Vanessa Round ◽  
...  
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Adaptation ◽  
Regional Climate ◽  
Future Climate ◽  
Added Value ◽  
Climate Projections ◽  
Eastern Australia ◽  
Australian Alps ◽  
Future Climate Projections

<p>Coarse resolution global climate models (GCM) cannot resolve fine-scale drivers of regional climate, which is the scale where climate adaptation decisions are made. Regional climate models (RCMs) generate high-resolution projections by dynamically downscaling GCM outputs. However, evidence of where and when downscaling provides new information about both the current climate (added value, AV) and projected climate change signals, relative to driving data, is lacking. Seasons and locations where CORDEX-Australasia ERA-Interim and GCM-driven RCMs show AV for mean and extreme precipitation and temperature are identified. A new concept is introduced, ‘realised added value’, that identifies where and when RCMs simultaneously add value in the present climate and project a different climate change signal, thus suggesting plausible improvements in future climate projections by RCMs. ERA-Interim-driven RCMs add value to the simulation of summer-time mean precipitation, especially over northern and eastern Australia. GCM-driven RCMs show AV for precipitation over complex orography in south-eastern Australia during winter and widespread AV for mean and extreme minimum temperature during both seasons, especially over coastal and high-altitude areas. RCM projections of decreased winter rainfall over the Australian Alps and decreased summer rainfall over northern Australia are collocated with notable realised added value. Realised added value averaged across models, variables, seasons and statistics is evident across the majority of Australia and shows where plausible improvements in future climate projections are conferred by RCMs. This assessment of varying RCM capabilities to provide realised added value to GCM projections can be applied globally to inform climate adaptation and model development.</p>

scholarly journals Responses of runoff to historical and future climate variability over China

2017 ◽  
Author(s):  
Chuanhao Wu ◽  
Bill X. Hu ◽  
Guoru Huang ◽  
Peng Wang ◽  
Kai Xu
Keyword(s):  
Climate Variability ◽  
Arid Regions ◽  
Southern China ◽  
Aridity Index ◽  
Global Climate Models ◽  
Future Climate ◽  
Western China ◽  
Climate Projections ◽  
Positive Contribution ◽  
The Mean

Abstract. China has suffered some of the effects of global warming, and one of the potential implications of climate warming is the alteration of the temporal-spatial patterns of water resources. Based on the long-term (1960–2012) water budget data and climate projections from 28 Global Climate Models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5), this study investigated the responses of runoff (R) to historical and future climate variability in China at both grid and catchment scales using the Budyko-based elasticity method. Results show that there is a large spatial variation in precipitation (P) elasticity (from 1.2 to 3.3) and potential evaporation (PET) elasticity (from −2.3 to −0.2) across China. The P elasticity is larger in northeast and western China than in southern China, while the opposite occurs for PET elasticity. The catchment properties elasticity of R appears to have a strong non-linear relationship with the mean annual aridity index and tends to be more significant in more arid regions. For the period 1960–2012, the climate contribution to R ranges from −2.4 % a−1 to 3.3 % a−1 across China, with the negative contribution in the North China plain and the positive contribution in western China and some parts of the southwest. The results of climate projections indicate that although there is large uncertainty involved in the 28 GCMs, most project a consistent change in P (or PET) in China at the annual scale. For the period 2071–2100, the mean annual P will likely increase in most parts of China, especially the western regions, while the mean annual PET will likely increase in all of China, particularly the southern regions. Furthermore, greater increases are projected for higher emission scenarios. Overall, due to climate change, the arid regions and humid regions of China will likely become wetter and drier in the period 2071–2100, respectively (relative to the baseline 1971–2000).

Future Climate Projections

2013 ◽  
pp. 53-118 ◽  
Author(s):  
Silvio Gualdi ◽  
Samuel Somot ◽  
Wilhelm May ◽  
Sergio Castellari ◽  
Michel Déqué ◽  
...  
Keyword(s):  
Future Climate ◽  
Climate Projections ◽  
Future Climate Projections

Drought risk assessment for future climate projections in the Nakdong River Basin, Korea

2020 ◽  
Vol 40 (10) ◽  
pp. 4528-4540 ◽  
Author(s):  
Jong‐Suk Kim ◽  
Seo‐Yeon Park ◽  
Hyun‐Pyo Hong ◽  
Jie Chen ◽  
Si‐Jung Choi ◽  
...  
Keyword(s):  
Risk Assessment ◽  
River Basin ◽  
Future Climate ◽  
Climate Projections ◽  
Drought Risk ◽  
Nakdong River ◽  
Nakdong River Basin ◽  
The Nakdong River ◽  
Future Climate Projections
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