Hi everyone,
Can you help me to understand the quarterly categorization of bioclim data? The bioclim data has periods on coldest, warmest and so on. But, which months are coldest or warmest? Is it uniform all over the world? I mean, the months, which are driest in USA, is same in Bangladesh?
Thanks in advance.
Dear Kazi,
The following link contains the Worldclim database that you can download to get the bioclimatic variables during 1950-2000. The categorization of bioclim data is specific for each region (country).
The variables included in the website are:
Bioclimatic variables
Bioclimatic variables are derived from the monthly temperature and rainfall values in order to generate more biologically meaningful variables. These are often used in species distribution modeling and related ecological modeling techniques. The bioclimatic variables represent annual trends (e.g., mean annual temperature, annual precipitation) seasonality (e.g., annual range in temperature and precipitation) and extreme or limiting environmental factors (e.g., temperature of the coldest and warmest month, and precipitation of the wet and dry quarters). A quarter is a period of three months (1/4 of the year).
They are coded as follows:
BIO1 = Annual Mean Temperature
BIO2 = Mean Diurnal Range (Mean of monthly (max temp - min temp))
BIO3 = Isothermality (BIO2/BIO7) (* 100)
BIO4 = Temperature Seasonality (standard deviation *100)
BIO5 = Max Temperature of Warmest Month
BIO6 = Min Temperature of Coldest Month
BIO7 = Temperature Annual Range (BIO5-BIO6)
BIO8 = Mean Temperature of Wettest Quarter
BIO9 = Mean Temperature of Driest Quarter
BIO10 = Mean Temperature of Warmest Quarter
BIO11 = Mean Temperature of Coldest Quarter
BIO12 = Annual Precipitation
BIO13 = Precipitation of Wettest Month
BIO14 = Precipitation of Driest Month
BIO15 = Precipitation Seasonality (Coefficient of Variation)
BIO16 = Precipitation of Wettest Quarter
BIO17 = Precipitation of Driest Quarter
BIO18 = Precipitation of Warmest Quarter
BIO19 = Precipitation of Coldest Quarter
This scheme follows that of ANUCLIM, except that for temperature seasonality the standard deviation was used because a coefficient of variation does not make sense with temperatures between -1 and 1).
http://www.worldclim.org/bioclim
You may also use Worldwide Bioclimatic Classification System link in which you can search by country. The categorization of the summer, winter and etc. for each country is specific:
Using this web you can get the following parameters:
Country name, station location and elevation, station name
The length of the observation period for temperature and precipitation respectively
Annual average of temperature and annual precipitation sum
(red) Temperature curve
(blue) Precipitation time series
Indication of frost periods
Mean daily max. temperature for the warmest month
Mean daily min. temperature for the coldest month
http://www.globalbioclimatics.org/form/web.htm
Hoping this will be helpful,
Rafik
Dear Rafik,
Your post is extremely helpful! Thank you so much! I am really so much glad to have the above links. You are great!
Thanking you,
Kazi
Dear Kazi,
The periods (month/quarter) that bioclimatic variables are depending on are calculated for all the locations/points/raster cells separately. Hence, these periods are not connected to administrative units, such as countries.
It is true for databases WorldClim and CliMond, and is true if you calculate bioclimatic variables using function biovars() of package 'dismo' in R statistical environment. As far as I know, it is the same for ANUCLIM, DIVA GIS, GRASS GIS (r.bioclim addon) and the AML macro of Robert Hijmans written for ESRI ArcGIS. If you want to calculate and fix the period for a certain region, e.g. a country, you should use your own script.
HTH,
Ákos
Dear Akos, thanks. I will make further exploration as per your recommendation.
Dear Kazi Masel Ullah , this paper is highly relevant for you:
Article The way bioclimatic variables are calculated has impact on p...
It is about the alternative ways the month/quarter can be selected for bioclimatic variables, and whether the selected method has impact on the species distribution models and predictions made by them.
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