[R-sig-Geo] Climate data in R

Wed Aug 3 00:52:07 CEST 2016

I also recommended browsing through NOAA PSD curated catalog. I believe 
it's up-to-date and provide useful metadata and links to original sources:

http://www.esrl.noaa.gov/psd/data/

--Mel.

On 8/2/2016 5:34 PM, Tom Philippi wrote:
> Without knowing what part of the globe you need climate data for, nor what
> data you need (30 year "normals", bioclim parameters, monthly values,
> daily, extremes?), I can't give a useful specific answer.
>
> What follows is an initial draft of a web page on climate data in R.  It's
> somewhat US and North America centric.
>
> The number of APIs providing climate data is growing rapidly.  The downside
> is that most data providers are region/continent specific.  NOAA NDCD,
> ACIS, Mesowest, PRISM, SNOTEL, SNODAS, and others are North America or
> CONUS, there are different APIs and packages for EU, UK, NZ, and Canadian
> climate.  The few worldwide services tend to have lower station densities
> than region-specific services, especially for older dates.
>
> Some APIs and overviews:
> ACIS (NOAA):  http://www.rcc-acis.org/docs_webservices.html
> NOAA Co-ops: http://tidesandcurrents.noaa.gov/api/
> PRISM http://www.prism.oregonstate.edu/index.phtml
> MesoWest: http://www.rcc-acis.org/docs_webservices.html
> http://synopticlabs.org/api/
> http://www.esrl.noaa.gov/psd/data/gridded/
> https://climatedataguide.ucar.edu/climate-data/global-temperature-data-sets-overview-comparison-table
> http://www.cgiar-csi.org/data/uea-cru-ts-v3-10-01-historic-climate-database
>
> All of those APIs can be hit from R; some have R packages available to make
> it easier.  [And, more importantly for my use cases, those packages isolate
> my code that hits the package functions from changes in the underlying
> API.  Instead of each of us having to keep up with changing APIs and fixing
> our broken code every 6-12 months, package maintainers put out new versions
> that work with the new APIs but use the same parameters and return the same
> objects.  If my code from last year fails to fetch data this year, I
> usually can simply update the package.  Thanks, maintainers!]
>
> For R packages, start with https://github.com/ropensci/opendata#climate and
> http://ropensci.org/packages/
>
> Most non-raster APIs have 2 steps: a station finder that you query by name
> or location, then a data fetcher pulling data from the found stations.
>
> Raster datasets tend to be huge, and tend to be organized as 1 file per
> date.  There's a PRISM API that lets you select locations and retrieve data
> for a range of dates for requested rectangular AOAs.
>
>
> My 2 lessons learned as an ecologist using climate data (not a real
> climatologist) are:
>
> 1: Spatial interpolation is non-trivial.  PRISM uses not just distances
> from stations of record, but also topography: elevation for temperatures
> and precipitation and side of the mountain (very important for
> precipitation).  Don't just use the nearest station or inverse-distance
> krige unless you are in a broad flat plain or steppe.  [Sorry, Ed!]  There
> are a couple of raster products for daily data (not just the monthly
> PRISM), but they tend to be available a few weeks after the fact.
>
> 2: Station records are instrumentation values, not actual temperatures &
> precipitation amounts.  Almost all climate data providers QA and filter the
> values, because sensors drift and fail.  However, the appropriate amount of
> filtering is dependent on your use.  Some blips in the raw data are
> instrumentation errors, some are short extreme events; some are of a
> magnitude & duration where it can't be determined which of those they are.
> The appropriate or optimal amount of filtering for uses such as crop
> production models is much greater than the appropriate amount for some
> ecological applications where short intense events can be important.  Even
> within larger agencies like NOAA, different regional climatologists filter
> the data to different extents.  To do valid science, if extreme events
> matter for your use, you need to know the preprocessing on your datastream,
> lest you get fooled into thinking that region-specific filtering is
> climatological signal.
>
> If anyone has comments, additions, or corrections to the above, please send
> them to me!
>
> If the OP has a specific data type in a specific region, I might have a
> specific suggestion.
>
> Tom 2
>
> Tom Philippi
> Quantitative Ecologist & Data Therapist
> Inventory and Monitoring Program
> US National Park Service
>
>
> On Mon, Aug 1, 2016 at 12:49 PM, Isaque Daniel <isaquedanielre at hotmail.com>
> wrote:
>
>> Hi,
>>
>> You can follow the example in:
>> http://stackoverflow.com/questions/34619218/extract-raster-values-from-stack-to-points-in-for-loop
>>
>>
>> Is really simple, using coordinates and extract functions of raster
>> package.
>>
>>
>> Best
>>
>> Isaque
>>
>>
>>
>> ------------------------------------------------------------------------------------------------------------------
>> Eng. Agr. Isaque Daniel Rocha Eberhardt
>> Mestre em Sensoriamento Remoto - Instituto Nacional de Pesquisas Espaciais
>> (INPE)
>> Doutorando em Transportes - Universidade de Bras??lia (UNB)
>> Mobile: +55 (061) 99015658
>>
>> ------------------------------------------------------------------------------------------------------------------
>> Agronomist engineer
>> Master in Remote Sensing - National  Institute for Space Research (INPE) -
>> Brazil
>> PHD Student in Transport - Bras??lia University (UNB)
>>
>>
>> ________________________________
>> De: R-sig-Geo <r-sig-geo-bounces at r-project.org> em nome de Kenny Bell <
>> kmb56 at berkeley.edu>
>> Enviado: segunda-feira, 1 de agosto de 2016 19:47
>> Para: M. Edward (Ed) Borasky
>> Cc: R-sig-geo mailing list
>> Assunto: Re: [R-sig-Geo] Climate data in R
>>
>> See https://cran.r-project.org/web/packages/prism/index.html for
>> CRAN - Package prism<
>> https://cran.r-project.org/web/packages/prism/index.html>
>> cran.r-project.org
>> prism: Access Data from the Oregon State Prism Climate Project. Allows
>> users to access the Oregon State Prism climate data. Using the web service
>> API data can easily ...
>>
>>
>> interpolated US weather data
>>
>> On Mon, Aug 1, 2016 at 12:43 PM, M. Edward (Ed) Borasky <znmeb at znmeb.net>
>> wrote:
>>
>>> I have a similar question. Assume I've downloaded the climate data for
>> all
>>> the stations in the US state of Oregon, including their latitude,
>> longitude
>>> and elevation, using rnoaa. How do I *interpolate* climate values for an
>>> arbitrary latitude / longitude / elevation inside a triangle defined by
>> the
>>> nearest stations?
>>>
>>> On Mon, Aug 1, 2016 at 3:24 AM Miluji Sb <milujisb at gmail.com> wrote:
>>>
>>>> Dear all,
>>>>
>>>> I have a set of coordinates. Is it possible to extract climate data
>>>> (temperature and precipitation) by coordinates using the R packages
>> such
>>> as
>>>> rnoaa?
>>>>
>>>> For example;
>>>>
>>>> out <- ncdc(datasetid='ANNUAL', stationid='GHCND:USW00014895',
>>>> datatypeid='TEMP')
>>>>
>>>> But instead of stationid can I pass a list of coordinates through it?
>>>> Thanks a lot!
>>>>
>>>> Sincerely,
>>>>
>>>> Milu
>>>>
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>>> --
>>> How many people can stand on the shoulders of a giant before the giant
>>> collapses?
>>>
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>>
>>
>> --
>> Kendon Bell
>> Email: kmb56 at berkeley.edu
>> Phone: (510) 612-3375
>>
>> Ph.D. Candidate
>> Department of Agricultural & Resource Economics
>> University of California, Berkeley
>>
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