<p>Google Earth Engine's <a href="https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30_ENSEMBLE_STATS" rel="nofollow noreferrer">NASA NEX dataset</a> (or <a href="https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-GDDP" rel="nofollow noreferrer">this</a>) might be of interest to you. It is an online repository, where you can do your analysis using the GEE platform without having the need to download to local machine.</p>

CC BY-SA 4.0
2018-12-05T07:36:42.447Z
2018-12-05T07:36:42.447Z
shahryar
<p>Besides the Google Earth application suggested by <code>shahryar</code> I'm not aware of an online tool that could do the job you are looking for.</p>

<p>What I would do is to download the files and operate with a NCO or CDO to select the domain you are after (so that you can get rid of the "big" file immediately after and save disk space).</p>

<p>If you are working on a windows machine and cannot use NCO or CDO, a way to automatize at least the downloading procedure would be a script in R.
Something like this:</p>

<pre><code>library(RCurl)
opts = curlOptions(proxy='my_proxy', userpwd = "mypassword", netrc = TRUE) ##you need to get the credentials beforehand

var = c("pr","tasmax","tasmin") # put variables here
rcp = c("rcp45", "rcp85") #put the Climate scenarios here
mod= c("CCSM4", "GFDL-CM3", "IPSL-CM5A-MR", "MIROC5",  "inmcm4") #put the GCM models you want here
year=c(seq(2036,2050,1), seq(2086,2100,1)) ##here you can select the years you are looking for

for (v in var) {
  for (r in rcp) {
    url&lt;- paste0( 'ftp://ftp.nccs.nasa.gov/BCSD/', r, '/day/atmos/', v, '/r1i1p1/v1.0/', sep='')
    for (m in mod) {
      for (y in year) {
        nfile&lt;- paste0(v,'_day_BCSD_',r,"_r1i1p1_",m,'_',y,'.nc', sep='')
        url1&lt;- paste0(url,nfile, sep='')
        destfile&lt;-paste0('your_destination_path_NASA_NEX/',r,'/',v,'/',nfile, sep='')
        bin &lt;- getBinaryURL(url1, .opts = opts)
        writeBin(bin, destfile)
        Sys.sleep(1)
        gc()
      }
    }
  }
}
</code></pre>

<p>In the middle of the loop, using <code>ncdf4</code> (give a look <a href="https://stackoverflow.com/questions/21280104/how-to-take-a-subset-from-a-netcdf-file-using-latitude-longitude-boundaries-in-r">here</a>) you can nest few lines to pick the portion of the data covering your domain, store it, and get rid of the original file you just downloaded.
This is time consuming though. Surely it would be more efficient to use a combination of <code>wget</code> (as explained <a href="https://nex.nasa.gov/nex/resources/366/" rel="nofollow noreferrer">here by NASA</a>) and then <code>NCO</code> or <code>CDO</code>.</p>

CC BY-SA 4.0
2018-12-05T09:22:35.390Z
2018-12-05T09:49:53.203Z
2018-12-05T09:49:53.203Z
Nemesi
<p>I'm looking to download a small geographic area of the CMIP5 models part of NASA-NEX dataset. Previously I relied on the Planet OS OpenNEX GDDP website which had a great tool for selecting geographic areas, models and time periods, saving in this way a large amount of downloading time and disk space. The problem is that OpenNEX is gone and I haven't been able to find a similar tool.</p>

<p>Is there another tool/website/script that can be used similarly?</p>

<climate-change><climate><climate-models><gis><nasa>
where to download NASA-NEX daily downscaled datasets?
Guillermo.D
# where to download NASA-NEX daily downscaled datasets?

(Asked by: username_0 on 2018-12-04)

I'm looking to download a small geographic area of the CMIP5 models part of NASA-NEX dataset. Previously I relied on the Planet OS OpenNEX GDDP website which had a great tool for selecting geographic areas, models and time periods, saving in this way a large amount of downloading time and disk space. The problem is that OpenNEX is gone and I haven't been able to find a similar tool.

Is there another tool/website/script that can be used similarly?

**Tags:** climate-change, climate, climate-models, gis, nasa


---

## 2 answers

### Answer by username_1 on 2018-12-05. Score: 2 | Accepted answer

Google Earth Engine's [NASA NEX dataset](https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-DCP30_ENSEMBLE_STATS) (or [this](https://developers.google.com/earth-engine/datasets/catalog/NASA_NEX-GDDP)) might be of interest to you. It is an online repository, where you can do your analysis using the GEE platform without having the need to download to local machine.


---

### Answer by username_2 on 2018-12-05. Score: 0

Besides the Google Earth application suggested by `username_1` I'm not aware of an online tool that could do the job you are looking for.

What I would do is to download the files and operate with a NCO or CDO to select the domain you are after (so that you can get rid of the "big" file immediately after and save disk space).

If you are working on a windows machine and cannot use NCO or CDO, a way to automatize at least the downloading procedure would be a script in R.
Something like this:

```
library(RCurl)
opts = curlOptions(proxy='my_proxy', userpwd = "mypassword", netrc = TRUE) ##you need to get the credentials beforehand

var = c("pr","tasmax","tasmin") # put variables here
rcp = c("rcp45", "rcp85") #put the Climate scenarios here
mod= c("CCSM4", "GFDL-CM3", "IPSL-CM5A-MR", "MIROC5",  "inmcm4") #put the GCM models you want here
year=c(seq(2036,2050,1), seq(2086,2100,1)) ##here you can select the years you are looking for

for (v in var) {
  for (r in rcp) {
    url<- paste0( 'ftp://ftp.nccs.nasa.gov/BCSD/', r, '/day/atmos/', v, '/r1i1p1/v1.0/', sep='')
    for (m in mod) {
      for (y in year) {
        nfile<- paste0(v,'_day_BCSD_',r,"_r1i1p1_",m,'_',y,'.nc', sep='')
        url1<- paste0(url,nfile, sep='')
        destfile<-paste0('your_destination_path_NASA_NEX/',r,'/',v,'/',nfile, sep='')
        bin <- getBinaryURL(url1, .opts = opts)
        writeBin(bin, destfile)
        Sys.sleep(1)
        gc()
      }
    }
  }
}

```

In the middle of the loop, using `ncdf4` (give a look [here](https://stackoverflow.com/questions/21280104/how-to-take-a-subset-from-a-netcdf-file-using-latitude-longitude-boundaries-in-r)) you can nest few lines to pick the portion of the data covering your domain, store it, and get rid of the original file you just downloaded.
This is time consuming though. Surely it would be more efficient to use a combination of `wget` (as explained [here by NASA](https://nex.nasa.gov/nex/resources/366/)) and then `NCO` or `CDO`.


---

