[NARCCAP-discuss] High observed vs. modeled errors for precipitation

Fri Aug 30 12:43:04 MDT 2013

Kelli:
	I would also strongly suggest that you do not select models simply on the
basis of which ones happen to do best for your particular basin or region.
 That does not guarantee that they produce the best climate change for
your region because the change will be affected not only by local factors,
but also by changes in remote influences, which other models might do
better.  In general, unless a model is particularly bad, you should use
the full ensemble.

	Also, it looks like you are using the GCM-driven contemporary simulations
to evaluate the models.  These simulations will have two sources of bias:
GCM bias and the RCM bias.  In general, for an application such as yours,
some degree of bias correction is necessary.  Precipitation also is much
more difficult for models to simulate well than temperature.  I do not
have the appropriate references at hand, but I suggest you look into work
by Dennis Lettenmaier, Eric Wood and colleagues concerning bias
correction, especially for hydrologic applications.

	Finally, is your "observed data" your own, or a community data set?  If
the latter, I would suggest that you do not rely solely on one
observational data set, unless you have compelling reasons to use just one.

Best wishes on your work,
Bill Gutowski
-- 
William J. Gutowski, Jr.

3021 Agronomy Hall
Dept. of Geological & Atmospheric Sciences
Dept. of Agronomy
Iowa State University
Ames, Iowa  50011-1010

Tel:  1-515-294-5632
Fax: 1-515-294-2619
http://www.ge-at.iastate.edu
http://rcmlab.agron.iastate.edu

On 8/30/13 12:47 AM, "jayanti pal" <jiban_samudra18 at yahoo.com> wrote:

>Hello,
>
>Though I am not familier with NARCCAP model I suggest to check the
>precipiation values in the dataset. I found a paper "Evaluation and bias
>correction of Precipitation and Temperature of NARCCAP Regional Climate
>Models over the North Carolina, US" by
>
>Kim, Y.; Band, L. E.  where they used five GCM-RCM model among which in
>the RCM3s, spring and winter
>precipitation are overestimated. I cant open this paper due to
>restriction on this site. I also found another paper, I have attached it
>. Hope it will help you.
>
>With Regards,
>
>
> 
>Jayanti Pal
>Junior Research Fellow
>Department of Atmospheric SCience
>University Of Calcutta
>email-jiban_samudra18 at yahoo.com
>jayantibright at gmail.com
>
>
>________________________________
> From: Kelli Walters <waltersk at onid.orst.edu>
>To: narccap-discuss at mailman.ucar.edu
>Sent: Wednesday, 28 August 2013 5:47 AM
>Subject: [NARCCAP-discuss] High observed vs. modeled errors for
>precipitation
> 
>
>Hello,
>
>I am evaluating which NARCCAP model runs best fit my observed data to
>determine which ones I should use as climate projections in a
>hydrologic model. I am comparing the past data set (1970-2000) from
>the models to observed data for temperature (max and min) and
>precipitation. For temperature, the models seem to accurately reflect
>the observations, with Nash-Sutcliffe efficiencies around 0.5 (r2 of
>0.5-0.6) for daily comparison and in the range of 0.6-0.9 (r2 of about
>0.85) for monthly averages.
>
>However, for precipitation, my errors have been much larger. I am
>getting Nash-Sutcliffe efficiencies of around -0.4 to -1 (r2 of 0.02
>and smaller) for both daily values and monthly averages. What I am
>wondering is: are these error values normal or in the same range as
>other people are getting for precipitation?
>
>Do you have any papers or references that give these error metrics for
>precipitation when comparing the modeled data to observations? I have
>been looking for literature to back up what I am finding, but I can't
>seem to find what values are considered "acceptable" for precipitation
>error. Any help or sources you can provide on this would be much
>appreciated.
>
>Thank you,
>Kelli
>
>
>-- 
>KELLI WALTERS, EIT
>M.S. Candidate
>Civil Engineering | Water Resources
>Oregon State University
>waltersk at onid.orst.edu
>
>
>
>
>
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