• Cynthia Evangeline Sellinger added an answer:
    What is the best programming language for solar radiation data processing?

    I just programmed macros in Excel, but I realize that sometimes (when the databases are very large and I would like to calculate many specific variables ) consumes many resources and computing time. I hear of people using Python, Fortran, C++, etc., but what is the best?

    Cynthia Evangeline Sellinger

    Interactive Data Language (IDL) works great for programming large data sets.  Not only can you use the built-in statistical packages, but this language handles a large, matrix of information with ease.

  • Uttam Ghimire added an answer:
    Can anyone suggest software for performing statistical downscaling on climate data?
    I'm looking for a step-by-step description for statistical downscaling.
    Uttam Ghimire

    For CMIP3 models, SDSM can be regarded as one of the easiest methods. However for CMIP5 models adopted in IPCC AR5, you cannot use that. 

  • Amrit Thapa added an answer:
    Do anyone have R code for distributing Temperature and Precipitation to each grid in DEM?

    I am trying to distribute temperature and precipitation data in mountainous catchment. I have a data of one of the station within the catchment and want to distribute on each grid of the DEM using lapse rate and vertical gradient. I am planning to use R software to do so. How can i do this?

    Amrit Thapa

    Dear Achut Parajuli,

    Thank you for your suggestions.

  • Michel M. Verstraete added an answer:
    Where can I get the FLUXNET tower data for India to measure the exchanges of carbon dioxide (CO2) between terrestrial ecosystems and the atmosphere?

    How much FLUXNET tower is installed in  India? How and where do I get the tower data for NPP model validation? 

    Michel M. Verstraete

    Dear Srikanta,

    Please visit the main web site of the FLUXNET programme at

    to find information on the locations, time periods and variables available through this initiative.

    According to the map of available sites

    there is only one FLUXNET station in India, located at the Central Rice Research Institute (CRRI):

    and this site has published data only in 2010, 2011 and 2012.

    In order to validate an NPP model, you will probably want to use data from other sites, with much longer time series.

    I hope this helps. Cheers, Michel.

  • Mark Žagar added an answer:
    Which GCM result is best for wind resources downscaling in complex rerrain like Nepal?

    I am currently doing thesis on "Impact of Climate Change on energy Generation from Wind Resources". 

    Mark Žagar

    Wind resource estimates in complex terrain require a forcing dataset, and a mesoscale/microscale model for downscaling. A forcing dataset will typically be one of the multi-decade atmospheric reanalyses (NCAR, ERA Interim, etc.) or a similarly long series of operational atmospheric analyses (e.g. publicly available NOAA GFS analyses). All of these can be used to drive a mesoscale model, like WRF, down to a resolution of a few kilometres. Subsequent downscaling can be then performed on limited areas using a CFD model, for example.

    In the same way as using past analyses for estimating the wind resources, one can use the climate prediction models to investigate future climate change impact on wind resources in complex terrain. The results will reflect changes in global/regional circulation patterns, but not the local features like forestation, glacier melting, etc., unless these surface characteristics are also being changed in the downscaling model according to the future predictions.

    As the previous posters have said, the resolution of the nowadays' regional climate models is perhaps still too low to provide reliable information about future wind resources in complex terrain. This is why I would propose the method described above in the meantime.

  • Kenneth M Towe added an answer:
    Is there any scientific community (even informal) especially dedicated to the climatology of small oceanic islands?

    I would greatly appreciate having feedback from scientists/groups specifically dedicated to the climatology of small oceanic islands worldwide (Including issues related with  as climate change, water, etc), having  information about their work, publications, etc.

  • Anice Garcia added an answer:
    Does anyone know a recent study addressing the spatialisation of temperature/precipitation/drought extreme events for the last 30 years?

    Hello, I have been searching for a study addressing climatic extreme events. However I could not find a study covering the last decades (especially from 1980 till now) at a global level. I do not mean I am looking for a a extreme event with a global impact, but the spatial distribution of different extreme events across time.


    Anice Garcia

    M.K.V. Sivakumar, R.P. Motha and H. Das (eds.) Natural Disasters and Extreme Events in Agriculture, Springer, Berlin (2005) 23–37.

  • Andreas Will added an answer:
    Is there any recent regional climate model for Africa?

    There are a number of regional climate models for different regions. I am interested to downscale global climate models based on regional climate mode for dynamical downscaling. Any suggestion is appreciated.

    Andreas Will

    Of course, there are many models and a broad band of evaluation results exhibiting a substantial spread.

    If you are not familiar with a mesoscale model, I cannot recommend conducting own simulations without an experienced cooperation partner. It's easy to produce numbers which don't describe the nature in an acceptable way.

    Using the CORDEX results first is strongly recommended.

    You find all models and the reference configuration for Africa on the CORDEX-AFRICA webpage. However, there are several attempts to simulate parts of Africa at higher resolutions by different groups. If you are interested in that, you probably need a non-hydrostatic model system like COSMO-CLM or WRF. E.g. at the CLM-Community webpage you may find a contact person who can answer your detailed questions.

    Good Luck, Andreas Will

  • Ji Qing Tan added an answer:
    Why do many researchers insist on using the Safir-Simpson hurricane scale to gauge the intensity of a tropical cyclone?

    The Safir-Simpson hurricane scale is a classification method to identify the intensity of a tropical cyclone by civil engineer Herbert Saffir and meteorologist Bob (Robert) Simpson, but this method proved to be useless due to its failures to identify the two thirds of the top 156 deadliest hurricanes from 1851 to 1996. I found the overgeneralization problem caused this.

    I developed a new classification method to deal with this problem, but many reviewers and editors told me that even though what you said is correct, we still insist on using SSHS, and your paper can't be published at least in the journals of USA due to common people accepting SSHS. I really don't know why this thing could happen in scientific world, any people know the true reason?

    Ji Qing Tan

    one year ago , I found it , and downlaod from the official weasite. But I don't know why they disaperar recently, if you want , I would forward the data which I download one year ago.

  • Brij Kishor Pandey added an answer:
    How do I get the no.of regression parameters /coefficient for GCM models ?

    I need the number of parameters of the IPCC AR4 GCM models for evaluation of model performance. Is there any representative equation or no. of parameters available for GCM models ?

    Brij Kishor Pandey

    Thanks Vishal ...

  • Vladimir E Kostylev added an answer:
    This is a great summary map, used by many. Could you advise on the availability of more recent/high resolution maps of sensitivity to sea level rise?
    Possibly new storm surge models can be used to generate these.
    Vladimir E Kostylev

    An excellent assessment of the SLR impacts is published by Withey et al (2015) based on Shaw (1998) work. They estimate that over 2009–2054 period the coastal adaptation to SLR could cost Canada in the range of  $53.7 and $108.7 billion in present value GDP.

  • Farhad Ashkani added an answer:
    Does anyone know some native experimental methods for predicting drought?

    Due to low rainfall, people in central Iran have some amazing ways.
    These methods have been developed over several thousand years and may have a higher accuracy than the current academic methods.

    For example, in some days of September and October, they put cotton on their roofs in order to check weight change due to wetting. They use this method to determine whether the current year is going to be dry or wet.

    Farhad Ashkani

    One of the most ingenious methods that Iranians used in past was Kariz or Qanat in order to have fresh water without using any pump or doing any over-extraction.

    The other useful methods have been in ancient architecture of Iran. The materials and the methods that they used made their houses cooler in summer and less depended to extra devices to cool them. The cooling system was a part of body of the building.

    Best regards,


  • Aidan Farrow asked a question:
    How can I run GEOS-Chem for 1990 using GEOS-4 data and 2010 using GEOS-5 data so that the output is comparable?

    I am running a long time series simulation with GEOS-Chem starting in 1986 and running to the present day. How can I make the simulations directly comparable when some years are forced with GEOS-4, GEOS-5 and current GEOS data? It seems like there is a step change in the emissions input data between GEOS-4 and GEOS-5 (See attached image of global mean NOx from 1986-2010).

  • Closed account added an answer:
    What are the most reliable ways of determining the paleoclimate during the Pennsylvanian (ex Upper Carboniferous) and Permian?

    We know that there were great paleoclimatic changes during the Pennsylvanian and Permian. the Pennsylvanian in Euramerica is characterized by great peat (coal) swamps, widespread changes in sea level occurred during the Pennsylvanian, continental glaciation during both periods, and great aridity particularly in the Permian.


    Dear Paul,

    I have posted those texts within my profile, so you can reach them also here.


  • Kenneth M Towe added an answer:
    What are people's opinions of research on anthrogenic Carbon Emissions and their contribution to Global Warming?
    Specifically how reliable is the science? It seems to me the empirical evidence is nowhere near what is required for cause & effect making this a statistical study of trends and potential causes.
  • Molulaqhooa Maoyi added an answer:
    Does anyone know how to convert the Joint Typhoon Warning Centre Lat Lon to normal Lat and Lon that can be plotted on a map?

    The problem I am having is that the lat and lon values are out of range for normal map coordinates i.e -90:90 S/N   -180:180 W/S

    Example of JTWC Track Data :

    SH, 01, 1999121300, , BEST, 0, 124S, 1042E, 50, 0,

    Molulaqhooa Maoyi

    Thanks Guys, your comments helped a lot.

  • Frank Veroustraete added an answer:
    How can I detect desertification by remote sensing?
    Which image product is best suited for this purpose and how can I download that product?
    Frank Veroustraete

    Hi Behrooz,

    I made a study of desertification in the Xinjiang province (North- Western China) lately, using a  multi-temporal series of 50 years Corona and Landsat imagery. The LUCC is enormous over that time lapse in the Xinjiang province. It led to increased desertification in originally natural landscapes. In short, an originally natural landscape  with gallery forests along the Tarim river and its tributaries changed into a patchy landscape with irrigated agriculture plots on the one hand and sandy deserts on the other hand. This LUCC had a fundamntal impact on regional hydrology. The Tarim river in the 50 years mentioned retracted by more than 200 km from its original Gobi desert ending.  If you want to know more, then read the paper available on ResearchGate:

    I think that the Xinjiang province gives a fairly good example of what large scale desertification is all about e.g., humans changing natural landscapes - in equilibrium with regional hydrology - replaced by desert and irrigated cropland (mainly cotton for export to SoutWestern China sweatshops). In fact the original water resources in the new landscape has been focussed on irrigated agriculture and the original natural landscape  degraded into sandy desert. Another large scale example exists in Kazakhstan (Aral Sea), not that far Norrth from the Xinjiang province, with the difference that the Aral Sea has almost vanished into pure desert. Al fishing activities in the Aral Sea have stopped and people had to move or die.



    • Source
      [Show abstract] [Hide abstract]
      ABSTRACT: It is only by using the first collection of intelligence satellite imagery acquired by CORONA, that time series of NDVI imagery can go back for a time period of nearly 50 years, based on diachronic mapping. This is an exceptionally long time period if not the longest, for which remote sensing imagery is available to estimate land use change for specific regions on the globe. The P.R. of China and the former USSR can be documented to nearly 50 years back in time, using CORONA satellite imagery. Typically – for many regions of the globe – is that a 50 year time span represents the principal time period in which many anthropogenic land use changes have taken place. In this paper, an account is given of the land use change which took place over the last 44 years in the Chinese province of Xinjiang, located in the North-west of the country. Declassified CORONA imagery was used, as well as LANDSAT MSS and ETM+ imagery. The Xinjiang province has one of the largest inland water basins on the globe, e.g. that of the Tarim river. Moreover, the province has grown into a major cotton and fruit producer in China. Based on diachronic mapping with CORONA and LANDSAT imagery, we can illustrate that over the last 44 years the Tarim river basin has undergone drastic land use changes, e.g., from nonfragmented landscapes of natural vegetation to fragmented mosaics of agrcicultural plots and desert. The region of interest in this study is the downstream area of the Tarim basin in the province of Xinjiang in the P.R. of China. A transfer function was established between canopy panchromatic reflectance (pc,pan) and canopy NDVI (NDVIc). This allows to reach the objective to increase the back casting time period of land use change observations based on satellite observations. To this end, a coupled PROSPECT-SAIL radiative transfer modelling approach was applied. Our approach elicited that the relationship between NDVI and ppan at leaf level, converges to a single relationship depending on leaf structure. The canopy level transfer function used to convert pc,pan into NDVIc was established using different chlorophyll contents, LAI values and a bright soil in the PROSPECT/SAIL radiative transfer models. A main result is that for a time lapse of 44 years, a drastic change in land use took place in the downstream reaches of the Tarim river basin. In many places natural vegetation has converted into high productivity irrigated agricultural plots. On the other hand natural vegetation also degraded into desert and semi-desert areas of very low to zero level productivity. A relatively small area (13%) of the Tarim downstream area has remained unchanged during the course of 44 years. Typically, the radiation regime and especially the hydrology of the the Xinjiang province has changed significantly over the last 44 years due to this drastic land use change. During this period the Tarim river retracted upstream, several hundreds of km, leaving behind desert land inapt for agricultural production and hence inapt to sustain human life.
      Sensors 11/2011; 1(4):194 - 210. DOI:10.5640/insc.0104194
  • Shahzad Sultan added an answer:
    What are the available methods for precipitation estimation in remote areas?

    The problem is that I have poor quality of TRMM product of 3B42 v7 of the studied rain storm, which is a rare event. (error value equal to the precipitation rate)

    I do have data of 3 'handmade' rain gauges spread over 850 square kilometers. No civil weather RADAR in the study area.

    Is it useful to interpolate GPCP data over the area? what about REF 2.0? anybody have an experiance with them?

    Shahzad Sultan

    Dear I have compared CMORPH, TRMM and REF2.0 and it is hard to say which is the best but still CMORPH and TRMM outperform but both of them slightly underestimated rainfall at mid-latitude between 25N to 35N but yet TRMM shows better agreement with in-situ data. I have also read somewhere that REF2.0 is good for tropical areas between 0 to 20N. the problems related to comparison between observed and TRMM has also been highlighted by Caniaux.

    I hope it answer your question

  • Ad Stoffelen added an answer:
    Can we calculate the monthly mean rainfall using TRMM data? If so, how?
    By using TRMM data would we be able to calculate the monthly mean rainfall and annual rainfall? If so, could you explain to me how?
    Ad Stoffelen

    Doing the computation is fine of course, but how to judge the credibility of it is another issue. The spatiotemporal representation is an issue as local rain gauges have a different daily rain PDF than a PDF obtained from daily sums from a few TRMM passes. So, the rain rate PDF may be correct over a typical TRMM pixel, but not validate well with a local rain gauge, e.g., in areas with orography. The daily temporal error due to non-uniform TRMM sampling, as compared to the uniform sampling by a rain  gauge will be substantial as well, e.g., daily afternoon rain could be missed by TRMM systematically. An attempt of error analysis is given in: Alemohammad et al., Hydrol. Earth Syst. Sci. Discuss., 12, 2527–2559, 2015

  • Mohammad Azmi added an answer:
    How can I calculate snow cover anomaly?

    I have a time series of daily snow cover area for certain years. How can i calculate daily,monthly and seasonal snow cover anomalies? I want to make histogram of snow cover anomalies vs number of occurrences.

    Mohammad Azmi

    No matter what is your meteor-climatological variable, you can calculate anomalies just by following steps:

    •A measure of distance, in standard units, between a data value and its mean.
    •Removes influences of location and spread from data.
    •Easier to discern normal vs. unusual values.
    •Calculated by subtracting the mean from each observation, then dividing by the standard deviation.
    •Have the following characteristics: mean=0 and standard deviation=1.

  • Mariza Costa-Cabral added an answer:
    How does the El Nino/La Nina events affect groundwater?

    what happens when groundwater and Climate index is anticorrelated?

    Mariza Costa-Cabral

    Instead of trying to correlate the time series of groundwater storage with climate indices, use the time series of groundwater storage CHANGE.  Your original variable (storage) is an integral another time series (storage change).  If you use the original variable (storage) you have a highly auto-correlated series (which may violate the conditions for valid application of your methodology).  Additionally, why would you expect such an integral time series to co-vary with climate indices?  Or are you integrating the indices over time also?

  • Muhammad Ali added an answer:
    How to calculate "Air temperature" from "land surface temperature"?
    Air temperature from LST (day and night).
    Muhammad Ali

    Hi Sally,

    Did you get any solution to your query? Any updates on the topic please??

  • Junzeng Xu added an answer:
    Does anyone know how to improve experimental treatments for System of Rice Intensification-SRI?
    System of Rice Intensification (SRI) is meant to produce more crop per drop of water and at reduced costs hence lower the farmers burden on production.
    • Source
      [Show abstract] [Hide abstract]
      ABSTRACT: This study evaluated the System of Rice Intensification (SRI) that involves intermittent wetting and drying of paddies based on specific soil and agronomic management practices in western Kenya irrigation schemes. An experimental field trial was conducted in Ahero rice irrigation site (August-December 2011) to compare the conventional cultivation of paddy and the SRI method. The Ahero site served as a farmers’ demonstration field. Twelve treatment combinations were tested under three distinct irrigation regimes: (i) two rice cultivars (IR2793-80-1 and Basmati 370); (ii) two different crop spacing patterns (25 cm×25 cm and 35 cm×35 cm) for conventional paddy and SRI methods respectively; and (iii) three fertilizer levels (organic, inorganic and combined). The West Kano field trial (October 2011-March 2012) served as a Farmer’s Field School (FFS) and evaluated the two irrigation regimes (conventional paddy and SRI), the two rice cultivars and the two different crop spacing patterns used in Ahero. On the Ahero site SRI significantly increased grain yield of IR2793-80-1 and Basmati 370 rice varieties by 16.2% and 4.6%, respectively, compared to conventional paddy. Whereas different fertilizer types and levels showed no significant effect on yield, grain quality per unit bag (90 kg) increased by 11.8-17.0% on mass basis for SRI compared to conventional paddy. In West Kano site, SRI increased grain yield for IR2793-80-1 and Basmati 370 rice varieties by 33.4 % and 53.3 %, respectively, compared to conventional paddy. Grain quality per bag for SRI increased by up to 2.9% on mass basis compared to conventional paddy. On Ahero site (very wet season), SRI system realized water saving of about 12% compared to the conventional paddy. In West Kano site (dry season), SRI trials realized approximately 64% compared to the conventional paddy. These results show that: (i) SRI realized seed savings of up to 75% compared to conventional paddy; (ii) spacing of 25 cm×25 cm for SRI gives higher yields than 35 cm×35 cm; (iii) the number of weeding sessions increases from 2 times for conventional paddy to 3 times for SRI; (iii) Basmati 370 rice variety-a tall plant rice variety, is not prone to lodging under SRI; (iv) SRI system results in significant increase in profits per growing season of between Ksh 20,000-50,000 per acre compared to conventional paddy. Key words: rice productivity, saving water, food security, Farmers Field Schools, rice cultivars, Ahero, West Kano
      The International Conference on Disaster Risk Reduction, and Conflict Resolution for Sustainable Development (18th—20th July 2012 @ Mmust, Kakamega, Kenya); 07/2012
    Junzeng Xu

    We strongly recommended you talk it with professor Norman Uphoff in Cornell University.

  • Iman Rousta added an answer:
    If i have mean monthly temp value for 30 lat/long pixels for a region over about 20 years how do i go about calculating SST Climatology for my region?

    Can i take average of temperature at each lat/long values for each year for particular month and then calculate average of those  20 yrs values can this be considered as SST climatology for that region

    Iman Rousta

    Dear Deepthi

    i have monthly sst anomali from 1950-2013 in excel format for latitude 0-90N and longitude 40W to 70E.

    I will be happy if i can help you.


  • Frederik Schenk added an answer:
    How can I calculate climatological significance of trends?

    Usually we use Mann-Kendall test for calculate statistical significance of analysed trends. I'm wonder, if exist same method to find out climatological significance.

    Frederik Schenk

    If somebody finds a formal/official definition of climatological significance it would be nice to get a link to that source.

  • Anbarah Belal added an answer:
    How to measure rainfall rate in mm/hours, is there an easy and cheap method?
    Rainfall rate to be measured for rain attenuation calculation for hilly profiles?
    Anbarah Belal

    Actualy, i have a question:

    what is the equation i have to use for calculte the annual rainfall rate?

  • Iinnocent Muhire added an answer:
    Can I use the same baseline value for the first 20 yrs for my temperature data?

    I have temperature data for 29 yrs, using first 20 yrs as baseline period I have calculated anomaly for the rest 9 years, can I use the same baseline value for the first 20 yrs?

    Iinnocent Muhire

    Yeah, it is quite better to continue with the same baseline to evaluate the changes taking place in those other  9 years.

About Climatology

Climatology is the study of climate, scientifically defined as weather conditions averaged over a period of time, and is a branch of the atmospheric sciences.

Topic followers (28,844) See all