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8

There are a number of sites which provide varying ranges of climatic data at a broad range of spatial scales. I often use WorldClim for global data and if I need higher resolution data for the USA I use data from the PRISM group. You could also look at MODIS data, which is very detailed, with many derivative datasets generated for ease of use. I am not ...


8

Weather Underground users can now access daily weather conditions dating back six years in most cities around the world. Historical weather information such as maximum and minimum temperatures, precipitation, humidity and winds are available for use by researchers, travelers, event planners and weather buffs free of charge. The databank was ...


6

Would your map be better than using the average temperature for the whole area? Unless you know that there is a physical reason why temperature differences occur I would use the average value everywhere, and not make an interpolation. It may well be that the prediction is more accurate if you do that than if you use an interpolated map. Local differences may ...


6

I doubt that you'll find a free database for climatic data, which contains literately every point in the world. I assume that even the most exact climate data is usually computed from models and already interpolated. For instance: How do you plan to get exact climate information for locations somewhere in central Africa? In places where there has never ...


5

I would write an R script that worked as a client, but will run on the database server. This will save the complication of trying to hook into PostGIS's backend and using PL/R (as I said in comments). The script will look something like this (which is practically pseudo-code here): > con = dbConnect(PG,"localhost","weather") # connect to local DB ...


5

I have written an R function that performs a robust regression (least absolute deviation method) against a DEM to up-sample climate variables. It works quite well for smaller areas where the gradient in the [X,Y] domain does not effect the estimates and is quite superior to resampling and interpolation techniques. It is a loose implementation of Nick ...


5

The PRISM Climate Group's precipitation raster below is at an 800 m scale. They also have 2 km and 4 km climate products. Climate source uses both 400 m and 2 km grids for their precipitation products. A description of the PRISM methods can be found here. A study area, for example, in the Rocky Mountains would benefit from a greater resolution, while a ...


5

For only 3 points, a simple linear interpolation for each date might be suitable. You just need to compute the equation of the plane defined by your three points. See here, section "define a plane through three points". However, any kind of interpolation on 3 points will provide only a very schematized trend of the temperature variation over space. ...


4

A quick Google has turned up MODIS Snow and Ice Project, which appears to give resolutions of 500m. You could also look at Landsat data. Due to the high albedo of snow, it should be a fairly easy process to threshold highly reflective values, then average them out by collecting a time-series of images and applying map algebra. Alternatively, you could ...


4

A very simple approach which springs to mind is to export the tiff to an ascii grid format such as ESRI's .asc file. You will then have a space delimited plain text file. It will have a few header lines which describe the origin, resolution and NoData values etc and you can easily skip over these for the sake of you calculations. You can do the ...


4

Take a look at: http://www.cgiar-csi.org/data/uea-cru-ts-v3-10-01-historic-climate-database Quote: "In January 2010, the University of East Anglia officially released the CRU-TS 3.0 Climate Database (See the official data release at http://badc.nerc.ac.uk/data/cru). This new version of database covers from 1901 to 2006*, globally at 0.5 degree spatial ...


4

You can likely get a reasonable interpolation using a linear regression (assuming your 30 weather stations are a representative sample) using elevation, latitude and distance from the coast as independent variables with the day as a factor. I've done this using ArcGIS and R previously. Daily 9am and 3pm temperatures over 10 days in 2003 from weather ...


3

Check the website climate.gov from NOAA (http://www.climate.gov/#dataServices). These are the available datasets for the world: http://www.climate.gov/#dataServices/mapServices_global Includes: Global Hourly Surface Data (*) Global Hourly Summaries (*) Global Summary of the Day (GSOD) (*) GHCN-Daily Data (*) GHCN-D ...


3

For the United States, National Snow Analyses. For global try Rutger's Global Snow Lab These were the top results for a Google search for "snow cover" and "global snow cover", respectively. You'll have to come up with a quantitative definition of what you're looking for (e.g. has snow cover of depth x over period y) and apply it to the data. Map algebra ...


3

Im no expert in interpolation, but surely 3 points is too little? Creating a layer from these 3 points will unlikely be that spatially realistic to the real world? That aside, you have what you have. Perhaps an Inverse Distance Weighting interpolation, setting the max search radius to be the max distance between any two of the points. (You dont mention a ...


3

Perhaps this website would be useful for future climate data to meet your specific needs: http://www.ccafs-climate.org/ I haven't downloaded data from here yet, but it does appear to have the very latest available data.


3

The PRISM Climate Group's data is exceptional. Their raster products include precipitation, max temp, min temp, dewpoint and historic data. NASA's MODIS site has a wealth of data as does this USGS site. You will find a wide range of products there from vegetation indices to emissivity and burn data.


3

The WorldClim dataset has a lot of the data you want. It is free for non-commercial use and has interpolated 1 km resolution data on: average monthly mean temperature (°C * 10) average monthly minimum temperature (°C * 10) average monthly maximum temperature (°C * 10) average monthly precipitation (mm)


3

for rainfall you can download the TRMM datasets: http://trmm.gsfc.nasa.gov/


3

The available free gridded global data mostly relates to near-surface wind speed and direction over global oceans. Free global land surface wind speed datasets are few. None that I know come in GIS format, as each cell has two data values, one for speed and one for vector - but more digging might provide disaggregation and the possibility of mapping at ...


2

Microsoft Research provides an interactive web interface FetchClimate and an associated API interface for use with C, C#, and other .NET frameworks.


2

After some more digging, I found that NOAA and NCDC keep a respectable number of freely available datasets detailing just the kind of information I'm looking for. I was able to find shapefiles for: 1. Average Mean Temperature 2. Mean Number of Days with Temperature 32 degrees Farenheit or below 3. Mean Number of Days with Snow Depth >= 1, 5, or 10 inches. I ...


2

European Reanalysis Interim (ERA-Interim) | European Centre for Medium-Range Weather Forecasts State-of-the-art 3rd generation reanalysis (1979-present) with robust physics and data assimilation.0.75°x0.75° global grid with 60 vertical levels. Well suited for climate study within the satellite era. European Reanalysis 40-year (ERA-40) | European ...


2

Yes, it is appropriate. Prediction by kriging can theoretically only get better when you bring in more correlated information, and that is what you do when moving from kriging to co-kriging. In practice, the gain can be disappointing, considering the effort it takes. There can also be other reasons to favor co-kriging. An example is when you need the ...


2

Oddly enough, I had a chat last night with a fellow from the National Renewable Energy Lab (NREL) here in Denver. He said they are doing work in India on wind / renewables but the Indian Gov't will not release the data they need for their work! Just thought I'd share that since I saw this post and had this discussion last night...


1

You won't improve much on WORLDCLIM if the input observations are not better. There are much more observations for European area than were included in Worldclim - but these may not be widely available to the public. Reanalysis products from even regional modeling systems are too coarse for your needs and themselves require validation. I am working on ...


1

An interesting dataset is European Climate Assessment and Dataset (ECA&D, http://www.ecad.eu/) which is offered at approx 25km spatial resolution and daily temporal resolution. The daily maps if temperature (min, mean, max), precipitation sum and pressure are provided as GIS layers. We used them in a series of scientific projects. Sample analysis: ...


1

Please read this link http://nsidc.org/data/modis/data_versions.html#temporal . It says MOD10A2 V5 has temporal coverage from 2002 to present. MODIS/Terra MOD10A2 Version 3 (V003) : 2000-10-31 to 2002-12-31 Version 4 (V004) : 2000-02-24 to 2007-01-03 Version 5 (V005) : 2000-02-24 to present


1

You will find a lot of open data using our free Ocean Data tool http://marinexplore.com/explore/ You can select area by location name and narrow selection by polygon tool if need. After previewing data online you will be able to generate a download with CSV file for in-situ measurements and NetCDF file for gridded data.


1

Most of the available gridded dataset that includes your data is in this list: http://www.esrl.noaa.gov/psd/data/gridded/



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