Rainfall data from 172 weather stations in Vietnam

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The rainfall data are obtained from Vietnam's HydroMeteorological Data Center (http://www.hymetdata.gov.vn/), and cover daily observations from 172 weather stations. Most of them were actively operated through out the period 1975-2006. The list of weather stations with GIS coordinates is also provided.

Type: 
Time Series
Topics: 
Climate Change
Economy Coverage: 
Lower Middle Income
Languages Supported: 
English
Number of Economies: 
1
Geographical Coverage: 
Vietnam
Tags: 
Access Options:
Download
Temporal Coverage: 
1975 - 2006

Last Updated

Last Updated: 
July 17, 2017
EXCEL

Dataset

The rainfall data are obtained from Vietnam's HydroMeteorological Data Center (http://www.hymetdata.gov.vn/), and cover daily observations from 172 weather stations. Most of them were actively operated through out the period 1975-2006. The list of weather stations with GIS coordinates is also provided. The data are provided in MS Excel files. Each file contains data from one weather station. Please note: (I) Blank cells in years for which the weather stations were active mean absolute no rainfall. (II) Cells with 0.0 (mm of rainfall) mean that there was some rainfall but it was too little to measure. (III) In years the weather stations were not active or for some reasons the data were not collected, the cells are marked by an X or a note showing that data in those years were not collected. We are revising the data so that errors will be eliminated and the data are better organized. Version 2 is expected to come out by April 15th, 2011. For any inqueries in regards to the use of data, please contact us at: Quy-Toan Do (The World Bank, [email protected]) or Le Dang Trung (Univesity of Copenhagen, [email protected])
Resource Type: Dataset Format: EXCEL
PDF

Working paper

As natural disasters hit with increasing frequency, especially in coastal areas, it is imperative to better understand how much natural disasters affect economies and their people. This requires disaggregated measures of natural disasters that can be reliably linked to households, the first challenge this paper tackles. In particular, a methodology is illustrated to create natural disaster and hazard maps from first hand, geo-referenced meteorological data. In a second step, the repeated cross-sectional national living standard measurement surveys (2002, 2004, and 2006) from Vietnam are augmented with the natural disaster measures derived in the first phase, to estimate the welfare effects associated with natural disasters. The results indicate that short-run losses from natural disasters can be substantial, with riverine floods causing welfare losses of up to 23 percent and hurricanes reducing welfare by up to 52 percent inside cities with a population over 500,000. Households are better able to cope with the short-run effects of droughts, largely due to irrigation. There are also important long-run negative effects, in Vietnam mostly so for droughts, flash floods, and hurricanes. Geographical differentiation in the welfare effects across space and disaster appears partly linked to the functioning of the disaster relief system, which has so far largely eluded households in areas regularly affected by hurricane force winds.

Resource Type: Download Format: PDF

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The rainfall data are obtained from Vietnam's HydroMeteorological Data Center (http://www.hymetdata.gov.vn/), and cover daily observations from 172 weather stations. Most of them were actively operated through out the period 1975-2006. The list of weather stations with GIS coordinates is also provided.

FieldValue
Groups audience
Modified Date
2019-05-04
Release Date
Periodicity
Periodicity not specified
Identifier
f4216c0c-8365-4b2d-bb19-c6071c3473c1
Temporal Coverage

1975 - 2006

License
License Not Specified
Contact Email
Rating: 
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Type: 
Languages Supported: 
Economy Coverage: 
Terms of Use: 
Number of Economies: 
1
Geographical Coverage: 
Data Classification of a Dataset: 
Start Date: 
Wednesday, January 1, 1975
End Date: 
Sunday, December 31, 2006
GSP
Programatic Region: 
Last Updated Date: 
Monday, July 17, 2017
Granularity: 
Modified date: 
17363
Primary Dataset: 
Yes
collection_field: 

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