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arrcc_newsletter_0920.pdf

ARRCC newsletter View online version | Share with a friend Asia Regional Resilience to a Changing Climate (ARRCC) Met Office Partnership newsletter September 2020 Welcome Welcome to the latest edition of our ARRCC Met Office Partnership newsletter. This edition covers the period from July

PowerPoint Presentation

and the IRI Map Room: http://iridl.ldeo.columbia.edu/maproom/. * Region usually experiences less than 10mm/month rainfall during the month (dry season). (1) Note: Large variations across the country. (2) Note: Hot in the north, cold in the south. (3) Note: Hot in north and west. (4) Note: Very wet

Microsoft Word - PRECIS validation Christian Seiler v6

% and -36% by 2100. This more intense cycle is also visible in the Sub-Andean mountain range with strongest precipitation decreases around August. In the highlands, this pattern reverses by 2100 with strongest relative precipitation in-and decrease during the dry- and wet season respectively. Because

hydropower-workshop-report-july-2022-final.pdf

season in Nepal. Model evaluation criteria: How well do the climate models capture the large-scale processes in the atmosphere that cause extreme precipitation events? Model assessment criteria: In a south Asian monsoon, how well does the model capture wind speed and direction over the monsoon period

Microsoft Word - EAfrica2019

but probabilities of a wetter season than last year and of 10-year extremes are presented. A wetter season than 2018 is favoured in most boxes east of 30E and between 10N and 10S. Elsewhere a drier season than 2018 is likely in most grid boxes. Probabilities of a season drier than any in the past 10 years (2009

North-east Brazil rainfall

Forecasts for the north-east part of Brazil between 0° S to 10° S and east of 50° W for the February to May wet season.

The wet season is between February and May with considerable year-to-year and decade-to-decade variability. The forecasts are produced using a combination of dynamical forecast models and statistical predictions and include predictions of the most likely of five rainfall categories (very wet, wet

353-369-94.fm

Asia-Pac. J. Atmos. Sci., 52(4), 353-369, 2016 pISSN 1976-7633 / eISSN 1976-7951 DOI:10.1007/s13143-016-0004-1 Climate Change Projections over India by a Downscaling Approach Using PRECIS Prasanta Kumar Bal 1,2 , Andimuthu Ramachandran 1 , Kandasamy Palanivelu 1 , Perumal Thirumurugan 1 , Rajadurai

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