ClimateAP Map Version


Tongli Wang

Centre for Forest ConservationGenetics (CFCG)

Department of Forest Science, University of British Columbia



May 25, 2014



About this program.. 1

Features. 2

How to use. 3

Climate variables. 3

How to refer. 4

Acknowledgements. 5


About this program


ClimateAP_Map is a Google map based version of the standalone MS Windows ClimateAP v1.00. It extracts and downscales PRISM (Daly et al. 2002) and ANUSPLINE 1961-1990 monthly normal data (2.5 x 2.5 arcmin) to scale-free point data and calculates seasonal and annual climate variables for specific locations based on latitude, longitude and elevation (optional). The coverage of ClimateAP includes most part of the Asia Pacific region (Figure 1).

The program uses the scale-free data as baseline in combination with monthly anomaly data of individual years to downscale (Delta method) and calculate historical monthly, seasonal and annual climate variables for individual years and periods (decadal and normal periods) for 1901 - 2012. The monthly anomaly data were calculated based the dataset from Climate Research Unit (CRU) (Mitchell and Jones 2005) (version ts3.21). A time-series function allows users to obtain climate data for multiple years in a single run. With the same approach, ClimateAP also downscales and integrates future climate datasets for 2020s (2011-2040), 2050s (2041-70) and 2080s (2071-2100) generated by various global circulation models from the IPCC Fifth Assessment (AR5). A time-series of annual projections is also available for the years between 2011-2100. The output of the program includes both directly calculated and derived climate variables.

Downscaling of PRISM monthly data including bilinear interpolation and elevation adjustment, and calculations of climate variables and estimation of derived climate variables are described in Wang et al. (2012). For predictions of multiple locations and for more GCMs, we recommend you to download the standalone version at http://climateap.forestry.ubc.ca/downloads/index.html.


Figure 1. The coverage of ClimateAP



1.      Obtain coordinates of a location by clicking on the map. The values of latitude, longitude and elevation are generated by Google Map geo-positioning system and Google Elevation Service. Alternatively, latitude, longitude and elevation can also be input manually.

2.      Navigate the map with overlays to identify the locations of interest.

3.      Include historical years and periods between 1901- 2012 and future periods (2020s, 2050s and 2080s). A large number of climate variables (see below) can be generated for either a historical period (a year or a period) or future periods with different climate change scenarios.

4.      Save outputs for multiple locations to a file on your local computer.


How to use

Please check the Quick Tutorial.


Climate variables

1)      Annual variables:

Directly calculated variables:

MAT mean annual temperature (C),

MWMT mean warmest month temperature (C),

MCMT mean coldest month temperature (C),

TD temperature difference between MWMT and MCMT, or continentality (C),

MAP mean annual precipitation (mm),

MSP mean summer (May to Sept.) precipitation (mm),

AHM annual heat:moisture index (MAT+10)/(MAP/1000))

Derived variables:

DD<0 (DD_0) degree-days below 0C, chilling degree-days

DD>5 (DD5) degree-days above 5C, growing degree-days

DD<18 (DD_18) degree-days below 18C, heating degree-days

DD>18 (DD18) degree-days above 18C, cooling degree-days

NFFD the number of frost-free days

PAS precipitation as snow (mm) between August in previous year and July in current year

EMT extreme minimum temperature over 30 years. For an individual year, the EMT is estimated for the 30-year normal period where the individual year is centred.

EXT extreme maximum temperature over 30 years. For an individual year, the EXT is estimated for the 30-year normal period where the individual year is centred.

Eref Hargreaves reference evaporation

CMD Hargreaves climatic moisture deficit


2) Seasonal variables:

Tave_DJF winter (Dec.(prev. yr) - Feb.) mean temperature (C)

Tave_MAM spring (Mar. - May) mean temperature (C)

Tave_JJA summer (Jun. - Aug.) mean temperature (C)

Tave_SON autumn (Sep. - Nov.) mean temperature (C)

Tmax_DJF winter mean maximum temperature (C)

Tmax_MAM spring mean maximum temperature (C)

Tmax_JJA summer mean maximum temperature (C)

Tmax_SON autumn mean maximum temperature (C)


Tmin_DJF winter mean minimum temperature (C)

Tmin_MAM spring mean minimum temperature (C)

Tmin_JJA summer mean minimum temperature (C)

Tmin_SON autumn mean minimum temperature (C)

PPT_DJF winter precipitation (mm)

PPT_MAM spring precipitation (mm)

PPT_JJA summer precipitation (mm)

PPT_SON autumn precipitation (mm)


3) Monthly variables

Tave01 Tave12 January - December mean temperatures (C)

Tmax1 Tmax12 January - December maximum mean temperatures (C)

Tmin01 Tmin12 January - December minimum mean temperatures (C)

PPT01 PPT12 January - December precipitation (mm)

DD_0_01 DD_0_12 January - December degree-days below 0C

DD5_01 DD5_12 January - December degree-days above 5C

DD_18_01 DD_18_12 January - December degree-days below 18C

DD18_01 DD18_12 January - December degree-days above 18C

NFFD01 NFFD12 January - December number of frost-free days

PAS01 PAS12 January December precipitation as snow

Eref01 Eref12 January December Hargreaves reference evaporation

CMD01 CMD12 January December Hargreaves climatic moisture deficit



How to refer


Wang, T., A. Hamann, D. L. Spittlehouse, and T. Murdock. 2012. ClimateWNA - High-Resolution Spatial Climate Data for Western North America. Journal of Applied Meteorology and Climatology 51: 16-29 (to be updated)




Funding for this study was provided by the APFNet (www.apfnet.cn).