My favourite software tool for time series analysis is the R package 'TSA' available from 'http://homepage.stat.uiowa.edu/~kchan/TSA.htm'. This package was developed as part of the book 'Time Series Analysis' by Cryer and Chan (Springer 2008). Both the book and the R package are highly recommended.

Very well David...will check them up to see the way out. thank you sir

My favourite software tool for time series analysis is the R package 'TSA' available from 'http://homepage.stat.uiowa.edu/~kchan/TSA.htm'. This package was developed as part of the book 'Time Series Analysis' by Cryer and Chan (Springer 2008). Both the book and the R package are highly recommended.

Other software maybe interest you, is the LARS-WG stochastic weather generator. This software is available on http://www.rothamsted.ac.uk/mas-models/larswg.php.

LARS-WG is a model simulating time-series of daily weather at a single site. It can be used: 1) to generate long time-series suitable for the assessment of agricultural and hydrological risk; 2) to provide the means of extending the simulation of weather to unobserved locations; and 3) to serve as a computationally inexpensive tool to produce daily site-specific climate scenarios for impact assessments of climate change.

It depends very much on what kind of analysis you want to perform, but for a complete spectral analysis you could use the ssa-mtm toolkit (http://www.atmos.ucla.edu/tcd/ssa/)

In order to visualize and interpret meteorological data you might use either the Climate Consultant software (free download is available from: http://climate-consultant.software.informer.com/5.4/) or Meteonorm software (http://meteonorm.com/download/software/). The latter can also be used to produce climate data for any region in the world. The demo version of Meteonorm is only restricted to 5 specific regions in the world and you have to buy the full-version for application in other areas.

Maybe the main difference between the packages in R and Timesat is that Timesat was developped to deal with high temporal resolution imagery (e.g. MODIS vegetation indices), so it works with images (can be any kind of time series images). I do not know the packages in R but I feel that there deal with no spatillay data (spreadsheets). Please somebody correct me if I am wrong.

Good luck

Many thanks fellow researchers for the wonderful ideas and comments. I will work them out to see.

I found a XL program name MAKESENS 1.0. Please check it and easy to use. You can download it.

We are most enthusiastic about the climate explorer - which is used worldwide -not only by dendrochronologists and contains besides extensive climate datasets a package of TSA tools. Please find more info in this presentation http://www.knmi.nl/publications/fulltexts/the_climate_explorer.pdf

Success!

NCL (http://www.ncl.ucar.edu/) is a great tool for analysing or plotting all types of meteorological data. Look in their example page for code samples.

You might also want to check out pandas (http://pandas.pydata.org), which is a general purpose Python data analysis package that has good time series support and is pretty fast. Nothing specific for meteorology, though.

Extending the answer from @Martin you could check out

- Iris (A Python library for Meteorology and Climatology)

http://scitools.org.uk/iris/

- Ulmo (Ulmo is a python library for clean, simple and fast access to public hydrology and climatology data)

https://github.com/twdb/ulmo/

- Earthpy (EarthPy is a collection of IPython notebooks with examples of Earth Science related Python code)

http://earthpy.org/

If you are using R and your data is in NetCDF format you can also find an R package to help you read files (RNetCDF).

I think R is most useful for time series data analysis and plotting. Like others mentioned, R have several packages to handle such analysis.

I used Statgraphics is a good software

Today there is a dominating FREE software in this area. R: http://www.r-project.org/

For specific time series analyses just look for "time series analysis r to be addressed to many tutorials. These introductions to time series analysis with R can be useful:

http://www.statoek.wiso.uni-goettingen.de/veranstaltungen/zeitreihen/sommer03/ts_r_intro.pdf

http://www.stats.uwo.ca/faculty/aim/tsar/tsar.pdf

Matlab also has time series tools. I also can recommend Climate Data Operation (CDO) which contain time series operations (eg. filtering, detrend etc.). It is freely available from http://code.zmaw.de/projects/cdo

GrAds ( Grid Analysis and Display System (GrADS) is an excellent tools for meteorological data analysis:

http://iges.org/grads/

Dear John

you can use R programing software

this language has many package for your purpose

cran.r-project.org

RClim software may also be a useful tool for climate analysis.

If the data also have a spatial component, you could look into Earth Trends Modeler, an extension of the Idrisi Selva GIS package. It's put out by Clark Labs and oriented to research applications.

I have used AnClim. Google it. The developer Stepnak will have to provide extra rights to use extra features. I found it userfriendly.

On open-source/"free" side R is always a good way to go. But I guess eViews is big commercial provider here (although I am a bit older and so only have experience of RATS a forerunner to eViews.

I found the following lecture course quite useful: http://www.ltrr.arizona.edu/~dmeko/geos585a.html

It contains very well documented notes and tutorial material to understand the underlying mathematical methods. It requires Matlab and a few toolboxes though.

As some people suggested already, R is a free and open source software package. Some useful sites to start with:

http://www.statmethods.net/

http://www.cookbook-r.com/

Like a lot of programmed, opposed to menu driven, software it seems simply things like getting the data read in, getting a simple plot, are a bit of drag. But once you are swimming with it R in particular is extremely powerful (and free!). This makes it a winner in my own (not very expert) view.

Hi,

you can use,

NCL http://www.ncl.ucar.edu/Download/macosx.shtml

GrADS http://www.iges.org/grads/

There is a good tool to work with homogenization of time series:

http://webs.ono.com/climatol/climatol.html

I think the GRADS tool may be easy to use

AnClim is a good tool for climate data.

Like many of the others here I would recommend using R. For your application, I would use the Openair package for R. It's quite easy to use and is well-built for time series analyses.

Try AnClim and Toolkit (Trend) software. These are equally powerful and user friendly.

R is a  good choice

I could download a software (Makesens 1.0) which can be used to trend analysis. You can download the instructions too. Check the attached program.

I'm dealing with gridded time series of RS data for my study.

If you deal with gridded time series, It would be useful TIMESAT and IDRISI selva software, I think. You can easily find and download them on the Internet. Good luck!

Many thanks fellows for your ideas. I appreciate it very much

you may use forecast package of r  best one for any type time series analysis

Application for analysis of climatic series (only Portuguese and Spanish to version 3.0). Only Windows.

Download:

Portugueses: https://drive.google.com/open?id=0ByVe4I3-KfAhSlI0WU5YVG84dzg

Spanish: https://drive.google.com/open?id=0ByVe4I3-KfAhaVZYOERqanB3SjA

Manual: https://drive.google.com/open?id=0ByVe4I3-KfAhM1hqWEQzU1hSWnc

https://drive.google.com/open?id=0ByVe4I3-KfAhSlI0WU5YVG84dzg

https://drive.google.com/open?id=0ByVe4I3-KfAhaVZYOERqanB3SjA

https://drive.google.com/open?id=0ByVe4I3-KfAhM1hqWEQzU1hSWnc

Of recent R seems to work well, it will even assist you beyond what you actually aiming at currently. The advantage with the others is that they are also ad-ins that work well with EXCEL. Regarding "R" prepare to do some prior-training. Good luck

I think you can use MATLAB. Hope this might be of some help http://in.mathworks.com/help/ident/time-series-model-identification.html?requestedDomain=in.mathworks.com

Matlab will be OK for you.

Hi,

These all softwares are good for time series analysis but depend on their availability. R is freely available and with updated packages. I will recommend R for your analysis. May guys mentioned R's packages above.

See https://www.esrl.noaa.gov/psd/data/writ/

You can upload your own time-series to the time-series page. It looks at monthly time series. It can do trends, basic statistics, comparisons to other time-series, different types of plots, autocorrelations, and wavelets.