Spatial uncertainty to determine reliable daily precipitation maps
Current time: 02-20-2018, 02:58 AM
Users browsing this thread: 1 Guest(s)
Author: asim99
Last Post: asim99
Replies 0
Views 867

Spatial uncertainty to determine reliable daily precipitation maps
#1
Spatial uncertainty to determine reliable daily precipitation maps

Author: Adrian Chappell, Luigi Renzullo, and Malcolm Haylock | Size: 6.5 MB | Format: PDF | Quality: Unspecified | Publisher: Wiley | Year: 2012 | pages: 14


[Image: info.png]

Daily precipitation observations are commonly used with related variables to make
estimates at unsampled locations to provide maps and gridded data for hydrological and
climate model applications. Uncertainty in the way gridded data (maps) are prepared, given
the available information, is rarely considered. Over a study period of one year, we used
conditional simulations to produce multiple equally likely realizations of Australian
precipitation per day. Together those realizations represented an ensemble measure of
spatial uncertainty for rainfall for a given day. An independent gauge data set had values
within the 5th–95th percentile uncertainty range 94% of the time. Combined with other
measures they confirmed the reliability of the ensemble spatial uncertainty ranges. We
compared several established mapping techniques to an independent gauge data set using
local error statistics and to the spatial uncertainty maps. Those statistics showed little
difference between the mapping techniques and overall assessment of performance was
largely dependent on skill scores. However, the mapping techniques were different when
compared to the spatial uncertainty ranges. These findings support the assertion that
assessment of mapping techniques using local error statistics is insensitive to the
uncertainty in producing the maps as a whole. We conclude that uncertainty information in
precipitation estimates should not be overlooked when comparing precipitation estimation
techniques. The focus of performance assessment is traditionally on local error estimates,
and this tradition diverts attention away from the issues of uncertainty and reliability.
Reliable uncertainty characterization is necessary for the rigorous detection of spatial
patterns and longer time series trends in precipitation

[Image: download.png]
***************************************
Content of this section is hidden, You must be registered and activate your account to see this content. See this link to read how you can remove this limitation:

http://forum.civilea.com/thread-27464.html
***************************************



a- Follow the Forum Rules.
b- Use Search function before asking question, requesting or posting.
c- Use THANKS button if you like someone's post.
d- If you like abook/software then please buy the original. Encourage the writer/developer to continue their good work.
[-] The following 3 users say Thank You to asim99 for this post:
  • kowheng, ska51, Mohammad6299
Reply


Possibly Related Threads...
Thread Author Replies Views Last Post
A comparison of geostatistical procedures for spatial analysis of precipitation in mo arshiakh 0 1,007 04-25-2013, 08:31 PM
Last Post: arshiakh
Temporal-spatial variation and the influence factors of precipitation in Sichuan Prov arshiakh 0 907 04-08-2013, 07:12 PM
Last Post: arshiakh
Spatial interpolation of precipitation in a dense gauge network for monsoon storm eve asim99 0 884 03-27-2013, 07:06 AM
Last Post: asim99



Users browsing this thread: 1 Guest(s)