• Arash Malekian added an answer:
    What do these error messages concerning gridded Green and Ampt infiltration in HEC-HMS mean?

    I am trying to set up a model in HEC-HMS using gidded Green and Ampt Infiltration as the loss method and ModClark for transformation but when I try to run it I get the following error messages: 

    ERROR 44850: Loss method "Gridded Green Ampt" is invalid for grid cells.
    ERROR 40501: An error occurred while initializing grid cell data for subbasin "W90". Parameter grid is missing or incomplete.
    ERROR 40441: Subbasin "W90" could not be initialized because the grid cells were missing or parameter data was invalid.

     I created a grid cell file using HecGeoHMS and I followed the instructions of the GeoHMS User Manual in order to create an ascii- file in the same coordinate system (SHG100) and then used this file as a mask to create all the gridded parameter information I need (Impervious area, initial water content, etc.) I also used this file to get my gridded precipitation data in the same resolution and the same extent as the grid cell file... 

    Then I transformed all these ascii-grids to dss files using the asc2dssGrid utility. 

    In case it is of importance: Before the error messages I also got those warnings:

    NOTE 40552: Grid cell file contained 4 invalid cells for subbasin "W140". Lost area equals 0.00008
    NOTE 40552: Grid cell file contained 3 invalid cells for subbasin "W90". Lost area equals 0.00003
    NOTE 40552: Grid cell file contained 2 invalid cells for subbasin "W80". Lost area equals 0.00006

  • Claire Harnett added an answer:
    How can I read GHCN precipitation daily files (format .dly) with MATLAB or R?

    I have downloaded daily climatological data from the Global Historical Climatology Network (GHCN), but it is provided in a not very common format such as .dly. I have found some R packages related to this, but apparently they are aimed at retrieving temperature measures. Any suggestions?

    Claire Harnett

    For any future confused people who stumble across this thread, I also found a toolbox here:

    It is open access and runs in matlab, letting you import your variables without actually writing any of your own script. Good user interface and would highly recommend!

  • Irfan Shakir added an answer:
    Can someone suggest an article on statistical downscaling of Global Precipitation Measuring Mission?

    Hi friends

    I am searching articles on statistical downscaling of Global Precipitation Measuring Mission.

    Irfan Shakir

    Thank you Mohammad

  • Jeremy Leung added an answer:
    Is there any work ranking the Madden-Julian Oscillation events in the past decades?

    The Madden-Julian Oscillation (MJO) event occurring earlier this year (2015) was said to be the strongest ever, based on its RMM index. I wonder if there is anyone ranking all the MJO events based on whatever criteria (e.g. RMM index, precipitation).

    Jeremy Leung

    That's a good idea Yi.

  • Sergey Victorovich Simonenko added an answer:
    What is the most accepted criterion to classify positive and negative Indian Ocean Dipole events?

    Indian Ocean Dipole (IOD) is commonly depicted by Dipole Mode Index (DMI). Most of the published research work relay on DMI to define IOD. But there are many disagreements in classification of IOD events among these publications. 

    What are the most accepted criterion of IOD events? Is there any source that provides a list of recent IOD events?

    Sergey Victorovich Simonenko

    .....Solar System.

  • Isaac Mugume added an answer:
    What is the suitability of NWP model in East Africa?

    I'm customizing WRF for operational prediction in East Africa. A recent suggestion is to compare with other models possibly UK's unified model, COSMO and AROME with WRF. Is this suggestion appropriate for a Ph.D study?

    Isaac Mugume

    Thank you Lech for the constructive advise.

  • 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.

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.

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