I have made several updates to RClimate tools for do-it-yourself climate scientists. The downloadable monthly climate trends file (link to csv file) now includes the 5 major global land-ocean temperature anomaly time series (GISS, HAD, NOAA, RSS, UAH) as well as PDO, AMO and NINI34 indexes. Stay tuned, I plan to add several more series in the next few weeks. Do you have any suggestions?
I have also added several functions to my on-line RClimate.txt file to help DIY citizen climate scientists to quickly and easily retrieve up to date climate trend data so that they can spend their time analyzing the temperature anomaly and climate oscillation trends rather than slugging through data downloads and reformatting.
Introduction
Climate trend analysis involves a number of steps that can present challenges to do-it-yourself (DIY) citizen climate scientists (C2S). There are 3 basic steps even before you can start analyzing your data:
- You need to find the data source(s)
- You need to retrieve/ download the data file(s)
- You need to reformat/ manipulate the data file(s) to suitable format for your intended analysis
Suppose you want to compare NOAA anomaly trends with PDO and Nino 34 indexes. You would need to download and reformat/ merge 3 files or just use the RClimate monthly trends file. As a user of my own file, I can tell you first hand that it is much easier and more fun to use my consolidated file.
Having spent more time than I want to admit working my way through these preliminary steps, I want to make it as easy as possible for others to be able to get their hands on the data in Excel or R as quickly as possible.
For those new to RClimate, here are links to several previous posts on these free, open source climate data tools:
- RClimate Introduction
- RClimate Scripts
- Do It Yourself Climate Trend Analysis
- RClimate Tools for Do It Yourself Climate Trend Analysis
I now have 14 functions in my RClimate.txt file, 9 climate data retrieval and reformatting functions , an easy to use plot_series(“?”) and 4 data support functions. There’s more on the way. Do you have any suggestions? Do you have R scripts you’d like to contribute?
Looking for Partners
There are an incredible amount of climate data series available on the web in a multitude of formats. I see a real need for a citizen based cooperative effort to consolidate and repackage this valuable data into usable formats for citizen climate scientists on an on-going basis. I’d welcome your ideas, thoughts, suggestions and help to make this valuable climate trend data more accessible to existing and future citizen climate scientists.
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Firstly thank you for making your scripts available: it has significantly helped me to gain access to R. I have modified one of the scripts to gain access to tidal data from particular sites from http://www.psmsl.org/data/obtaining/ and produce graphs and if appropriate regression data. This led me to think whether the generally perceived increase in mean tidal height is uniform across the world. Given the stated errors in the data, have you looked at this previously? Thank you again for your help.
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Hi
Have you considered adding the global temperature series of the Japanese Meteorological Agency to your file?
Data can be downloaded here:
http://ds.data.jma.go.jp/tcc/tcc/products/gwp/temp/map/download.html
The data are given on a 5 by 5 degree grid so to create a global dataset one needs to weight with area of each cell and then average.
I have tried to do this but so far with no success.
I can mail you my script (in Scilab) if you want.
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