netcdf

I used the paleoview software to download some variables from past climate, including the mean temperature from 15000BP-10000BP (I could upload a file on request but its a GB at least). The main problem is that when I read the raster, it contains only positive latitude and positive longitude. I know from the article that this has a 2.5*2.5 resolution. Using Raster I loaded both the raster and ncdf4 libraries to read it using raster library(raster) library(ncdf4) When I read it using the following code r <- raster("mean_temperature-15000BP-10000BP.nc", varname = "14000BP-13000BP/13300BP") I get

My NetCDF file has 4 dimensions (longitude, latitude, time, level pressure) and several variables. I want to replace the longitude data which is [340 342 344 ... 360 0 2 4 ... 18 20] by [-20 -18 -16 ... -2 0 2 4 ... 18 20]. In fact the longitude is counted from 0° to 360° but I need to have it from -180° to 180°. I have found some ideas on Internet but I don't know how to apply them. Here an explanation: "Some netcdf files contain strictly positive values [0,360] which are not compatible with the way gdal/QGis treat longitude values - they do not wrap around the dateline. This also causes

I have a NetCDF file of a probability surface. It's a 30x30 grid of 0.25 degree lat/lon intervals with a probability surface described in the z dimension. I can easily import this into Panoply, a NetCDF viewer: And it's then a breeze (checking one box) to interpolate/smooth the raw data to a finer grid size: However, I don't just want to visualize the data, I want to plot it in R along with bathymetry and point data. That all is no problem, but I have not found a straightforward way to interpolate the gridded data in R. Here's the code I use to import and plot the data: library(RNetCDF) nc <-

I am trying to combine multiple netCDF files with the same dimensions, their dimensions are as follows: OrderedDict([(u'lat', <type 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 720 ), (u'lon', <type 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 1440 ), (u'time', <type 'netCDF4._netCDF4.Dimension'>: name = 'time', size = 96 ), (u'nv', <type 'netCDF4._netCDF4.Dimension'>: name = 'nv', size = 2 )]) OrderedDict([(u'lat', <type 'netCDF4._netCDF4.Dimension'>: name = 'lat', size = 720 ), (u'lon', <type 'netCDF4._netCDF4.Dimension'>: name = 'lon', size = 1440 ), (u'time', <type 'netCDF4.

I have a global data at 0.25 degree resolution that I'd like to mask so that it only contains data values over land. The data covers full 360 degrees in the lon dimension and from -60 to 60 degrees in the lat dimension. The file header, as well as summary lat and lon coordinate values, are listed below: netcdf cmorph_global_daily { dimensions: lat = UNLIMITED ; // (480 currently) lon = 1440 ; time = 7305 ; variables: float lat(lat) ; lat:units = "degrees_north" ; lat:long_name = "Latitude" ; float lon(lon) ; lon:units = "degrees_east" ; lon:long_name = "Longitude" ; float prcp(lat, lon, time)

I want to use netCDF formats in a C project using Visual Studio Express 2013 on a Windows 64bit. I've downloaded the installation file from the official website and executed the .exe. Then, I've looked into this post to see how I should do the linking etc. More specifically, in my project in Visual Studio, I did the following: Put #include < netcdf.h > in VC++ Directories, Library directories, I added C:\Program Files (x86)\netCDF 4.3.3.1\lib; C:\Program Files (x86)\netCDF 4.3.3.1\bin; in VC++ Directories, Include directories, I added C:\Program Files (x86)\netCDF 4.3.3.1\include; C:\Program

I am learning how to use netCDF4 using Pyhton module in Anaconda. I am trying to append values to two variables I have created time and field : from netCDF4 import Dataset import numpy as np root_grp = Dataset('py_netcdf4.nc', 'w', format='NETCDF4') root_grp.description = 'Example simulation data' ndim = 128 # Size of the matrix ndim*ndim xdimension = 0.75 ydimension = 0.75 # dimensions root_grp.createDimension('time', None) root_grp.createDimension('x', ndim) root_grp.createDimension('y', ndim) # variables time = root_grp.createVariable('time', 'f8', ('time',)) x = root_grp.createVariable('x'