[NARCCAP-discuss] why 50km x 50km
Jianhua Huang
jh.eco.cas at gmail.com
Wed May 29 12:44:09 MDT 2013
Gutowski:
Thanks again for the detailed information. It is really helpful
Jianhua
-----Original Message-----
From: narccap-discuss-bounces at mailman.ucar.edu
[mailto:narccap-discuss-bounces at mailman.ucar.edu] On Behalf Of Gutowski,
William J [GE AT]
Sent: Tuesday, May 28, 2013 3:02 PM
To: Discussion of NARCCAP data - uses and questions
Subject: Re: [NARCCAP-discuss] why 50km x 50km
Jianhua:
The answer to that question will depend on what field you are
considering. The scales in the atmosphere with the most energy, mass and
momentum tend to be the synoptic scales and larger, suggesting that an RCM
at 50 km should resolve these scales well and, presumably, their climate
change. In specific locations, finer scales can be important (one example
is the circulation in mesoscale convective systems), so to some extent, the
answer to your question depends on the physical processes you are targeting.
Your question is a good one, and there may be some work out there on
it, but I'm not sure how much or where. There would have been some
consideration of subgrid variability in papers on internal variability by
René Laprise and colleagues and in papers looking at how best to handle
subgrid variability in the surface of a model grid box. I did a paper on
one aspect of the latter several years ago (Gutowski et al. 1998, Monthly
Weather Review), but there are many others from around that period.
Bill
--
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 5/25/13 7:38 PM, "Huang Jianhua" <jh.eco.cas at gmail.com> wrote:
>Thanks Gutowski and Oleksandr for the detailed inputs, which solved my
>first question very well. Another question is whether 50 km x 50 km
>resolution good enough to catch the pattern of climate variation? In
>other words, is the intra-grid variation negligible compared with the
>inter-grid variation? Is it verified in any publication?
>
>Thanks for any suggestion.
>
>Jianhua
>
>
>On Fri, May 24, 2013 at 11:35 AM, Oleksandr Huziy
><guziy.sasha at gmail.com>wrote:
>
>> Hello,
>>
>> since nobody has answered this, I could try to suggest these reasons:
>> 1. The resolution is limited by the computational cost, when you
>>decrease gridsize, you'll have to decrease the time step (this
>>increases integration times enormously, talking from experience,
>>since we're not yet parallelizing in time) and when you decrease the
>>grid spacing the number of points will increase, since you would
>>still want to cover the same region (North America). For example from
>>200x200 points domain with 50km spacing you would get 1000x1000 with
>>10 km spacing and as far as I know these sizes are not available for
>>all institutions (even for the operational tasks (i.e short periods)
>>they have become available only recetly)... It'll take a lot of time
>>to run, and a lot of space to store...
>> 2. The model parameterizations were developed for the rough
>>resolutions and not all the models can be easily changed to the
>>higher resolution.
>> 3. I would even say that the analysis of the 1000x1000 grid over 30
>>years, with daily resolution is not an easy task...
>>
>> Cheers
>>
>> --
>> Oleksandr (Sasha) Huziy
>>
>>
>>
>> 2013/5/23 Jianhua Huang <jianhua.huangsdu at gmail.com>
>>
>> > Dear all:
>> >
>> >
>> >
>> > Anyone knows why the NARCCAP models choose the 50km x 50km resolution?
>> This
>> > looks a naïve question, but I was asked in a recent presentation. I
>> checked
>> > the NARCCAP website thoroughly, but found no answer. Why the
>>resolution
>> is
>> > 50km x 50km, why not 10km x 10 km? Is 50 km resolution good enough
>> > to
>> catch
>> > the spatial heterogeneity of climate change in the United States?
>> >
>> >
>> >
>> > Thanks for any clue or suggestion.
>> >
>> >
>> >
>> > Jianhua
>> >
>> > _______________________________________________
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>> >
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