The tenth IMSC, Beijing, China, 2007 - International Meetings on ...
The tenth IMSC, Beijing, China, 2007 - International Meetings on ...
The tenth IMSC, Beijing, China, 2007 - International Meetings on ...
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Tropical cycl<strong>on</strong>es have their origins from areas of low atmospheric pressure over warm<br />
waters in the tropics or subtropics. We have carefully studied the interc<strong>on</strong>necti<strong>on</strong> between the<br />
West African Weather Systems (WAWS) and their subsequent development into Tropical<br />
Cycl<strong>on</strong>es.<br />
Between 2004 and 2005, we studied the interc<strong>on</strong>necti<strong>on</strong> and the telec<strong>on</strong>necti<strong>on</strong> between<br />
the WAWS and the various occurrences of Tropical Cycl<strong>on</strong>es and their eventual development<br />
into Hurricanes. We noted that critical synoptic characteristic and the envir<strong>on</strong>mental properties<br />
of the Systems; the thermodynamic c<strong>on</strong>diti<strong>on</strong>s of the storms trajectory and the c<strong>on</strong>diti<strong>on</strong>s of<br />
the ocean are all closely linked. It is therefore believed that proper understanding and<br />
m<strong>on</strong>itoring of these systems will play a very vital role in early detecti<strong>on</strong> of potential WAWS that<br />
may develop into Tropical Cycl<strong>on</strong>es and even Hurricanes. More practical issues will be<br />
presented.<br />
It was recorded that over the period 1992-2001, weather and climate-related disasters<br />
especially those of Tropical Cycl<strong>on</strong>es origin killed about 622 000 people, affected more than<br />
two billi<strong>on</strong>, left milli<strong>on</strong>s more homeless, devastated arable land and spread diseases.<br />
Intense Precipitati<strong>on</strong> Events in the Reanalysis Datasets over the Asia<br />
Kiyotoshi Takahashi<br />
Meteorological Research Institute, JMA<br />
ktakahas@mri-jma.go.jp<br />
Nobuo Yamazaki<br />
Meteorological Colledge, JMA<br />
Masaru Chiba<br />
Meteorological Research Institute, JMA<br />
Hirotaka Kamahori<br />
Japan Meteorological Agency<br />
Recently, many studies for occurrance trends of intense precipitati<strong>on</strong> have been<br />
c<strong>on</strong>ducted based <strong>on</strong> both observati<strong>on</strong>al data analysis and model simulati<strong>on</strong> in associati<strong>on</strong> with<br />
the global warming. Basically detecti<strong>on</strong> of such trends should be based <strong>on</strong> the l<strong>on</strong>g-term<br />
surface observati<strong>on</strong>, but there is a problem that its distributi<strong>on</strong> is not homogeneous and<br />
localized geographically. On the other hand, estimati<strong>on</strong> based <strong>on</strong> satellite observati<strong>on</strong> is<br />
homogenous spatially. However, its temporal coverage is limited for just recent ten years for<br />
daily base products. As another available data sources, there are atmospheric reanalysis<br />
datasets, which are useful because they provide not <strong>on</strong>ly precipitati<strong>on</strong> but also other quantities<br />
with spatial homogeneity and physical c<strong>on</strong>sistency although reanalysis datasets may suffer<br />
from artificial trends due to changes in observati<strong>on</strong>al input data.In this study, statistical<br />
characteristics of intense precipitati<strong>on</strong> events in reanalysis datasets are examined by<br />
comparis<strong>on</strong> with newly produced observati<strong>on</strong>al gridded precipitati<strong>on</strong> data for India and<br />
<str<strong>on</strong>g>China</str<strong>on</strong>g>.<str<strong>on</strong>g>The</str<strong>on</strong>g> annual index for intense precipitati<strong>on</strong> used in Takahashi, K. et al (2006) as well as<br />
annual precipitati<strong>on</strong> calculated from each reanalysis dataset, especially the latest product<br />
JRA-25, shows significant correlati<strong>on</strong> with observati<strong>on</strong> at <strong>on</strong>e percent level.<br />
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