ClimateNA version history
ClimateNA v6.30 (May 25, 2020)
Historical monthly data for 2019 has been added using our new data.
ClimateNA v6.22 (April 22, 2020)
- An error was discovered and fixed in downscaling the HadGEM-ES GCMs. It also affected the multiple GCMs’ ensembles, but not to a significant extent (<1% on average).
- The name of selected GCM was missing in the default output path for “Future years” in ASC output mode. It has been fixed.
ClimateNA v6.21 (November 01, 2019)
- A bug was identified and fixed in generating historical monthly PAS (precipitation as snow) for August-December (PAS_08 – PAS_12) for individual years. It does not affect PAS in normal and decadal periods.
ClimateNA v6.20 (September 30, 2019)
- Historical monthly anomaly data from Climate Research Unit (CRU ts4.02) have all been replaced with our own data for improved accuracies. The replaced data include monthly anomaly data for the years 1901-2018, all decadal and normal anomaly data except the reference normal period 1961-1990, which are based on PRISM and WorldClim data.
ClimateNA v6.11 (July 14, 2019)
A bug in solar radiation (RAD) data for 2017 and 2018 has been identified and fixed. No RAD data is available for these years, but some values were passed to these two years by mistake.
ClimateNA v6.10 (June 24, 2019)
Historical monthly data for 2018 has been added using our new data.
The maximum number of rows/cols of an ascii input file has been from 32,767 to unlimited.
ClimateNA v6.00 (March 20, 2019)
A new feature has been added that enables the program directly read digital elevation model (DEM) raster (ASC) files and output climate variables in raster format for mapping. The spatial resolution of the raster files is up to user’s preference.
RCP 2.6 of the included GCMs have been added for being relevant to the Paris agreement, which requires the increase of global temperature being controlled below 2°C.
- Steps visible on high-resolution maps (<100m x 100m) are removed through bilinear interpolaiton of the lapse rates dynamically estimated for each grid of the baseline data across the two neighbouring grids.
ClimateNA v5.60 (August 31, 2018)
- Historical monthly data from the Climate Research Unit (CRU ts4.01) for the years 1999-2016 have been replaced by our newly developed dataset with improved accuracy.
- Historical monthly data for the year 2017 has been added using our new data.
- Improvements were made to better handle errors in the input data.
ClimateNA v5.51 (May 02, 2018)
- “Divided by zero” error in some occasions for future time-series causing the program to crash.
- Errors in Radiation (RAD) for future time-series.
ClimateNA v5.50 (December 2017)
- Climate data for historical years and periods updated from CRU ts3.24 to CRU ts4.01. The period extended from 1901-2015 to 1901-2016.
- Some missing values for CRU data (for individual historical years) at some edges of the coverage are fixed.
- PAS_at for individual years was calculated based on previous year’s data. Fixed. This bug does not affect users using
normal or decadal climate data.
ClimateNA v5.41 (June 2017)
· GCM climate data missing at some edges.
New GCM time series
· Five individual runs for each of the following two GCMs and two RCPs have been added into the package. The two GCMs include “CanESM2” and “CSIRO-Mk3-6-0”, and the two RCPs are RCP 4.5 and RCP 8.5.
ClimateNA v5.40 (December 2016)
· Climate data for historical years and periods updated from CRU ts3.23 to CRU ts3.24. The period extended from 1901-2014 to 1901-2015.
ClimateNA v5.31 (July 2016)
- An error in retrieving historical (CRU) data from the previous year in calculating winter variables and PAS for September – December. This bug only affects the historical time-series climate data.
ClimateNA v5.30 (May 2016)
- Monthly future projections for years of 2011-2100 for RCP4.5 and RCP8.5 of six GCMs with time-series function available;
- Monthly paleoclimate data for three paleo periods for four GCMs and one ensemble;
- Allowing users to add future time series data for additional GCMs into the program at the user end;
- Allowing users to choose multiple GCMs and time periods for a single run;
· Climate data for historical years updated from CRU ts3.22 to CRU ts3.23 and extended to 2014;
· Free from dependence on VB library files.
- An error caused due to multiple parts in ID fields of the input file.
ClimateNA v5.21 (July 05, 2015)
- An error in retrieving historical (CRU) data.
ClimateNA v5.20 (June 20, 2015)
· Climate data for historical years updated from CRU ts3.21 to CRU ts3.22 and extended to 2013.
· Solar radiation data for the baseline (1961-1990) updated to a new version.
- An error caused by handling missing values in historical years.
- Errors in solar radiation data for the baseline (1961-1990)
- An error in incorporating historical solar radiation data.
· Added ensemble averages for 15 systematically selected GCMs.
· Improved the algorithms for estimating DD>5 and DD>18 by separating coastal and interior regions.
· Improved elevation adjustment algorithms. The lapse rates for elevation adjustments estimated from local dynamic regression functions are weighted by R-square values to avoid over-adjustment in some occasions.
· A bug was identified and fixed. It was related to access previous data for adjusting winter seasonal variables when producing climate data for a specific historical year. It did not affect TimeSeries option for getting climate data for individual historical years.
· Improved the data access speed for historical years and periods.
- Set the lapse rate to zero for precipitation and radiation if it is negative. This happens only in rare cases, where the lapse rates are also very small. This change will have almost no effect on the output values, but just to avoid confusion.
- An error was identified and fixed in GCM data.
- Negative values in precipitation in historical data for 2001-2012;
- An error occurs in getting historical data for 2001-2012;
- An error occurs in getting future climate data for “GlobalMean”.
1. The baseline dataset of 1961-1990 PRISM normal data at a spatial resolution of 4,000 x 4,000 m has been updated from to 1971-2000 PRISM normal data at a spatial resolution of 800 x 800 m.
2. Historical monthly data from CRU has been updated from the version ts3.1 (1901-2009) to ts3.21 (1901-2012).
3. Future climate projections have been updated from IPCC AR4 to IPCC AR5 GCMs.
4. Annual projections for the years between 2011 and 2100 from one GCM.
New variables added
Monthly solar radiation data have been added to historical (1948-2010) and the three future periods.
Improvement in downscaling algorithms
The algorithms for elevation adjustment in downscaling monthly climate data have been upgraded from global partial derivative functions to local dynamic regression functions. The new downscaling approach is also applied to monthly precipitation and monthly solar radiation.
1. Errors in reading annual climate data after the year 1999.
2. Return only “0” values in time series if elevation is -9999.
- Anomaly data for historical years 2010 and 2011 have been added.
- The anomaly means for the normal period of 1981-2010 and the decadal period of 2001-2010 have also been added.
- For monthly variable option, in addition to selecting all 144 monthly variables, an option has been added for selecting only primary monthly climate variables, which include monthly minimum, maximum and average temperatures, and monthly precipitation.
4. Derived monthly variables added, including DD<0°C (DD_0), DD>5°C (DD5), DD<18°C (DD_18), DD>18°C (DD18), NFFD, PAS, Eref, and CMD.
5. A new derived annual variable, “Extreme maximum temperature (EXT) over a normal period (30 years)” has been added. For an individual year, EXT is estimated for its corresponding normal period where the individual year is centered. This also applies to EMT (extreme minimum temperature.
6. Options have been added to allow the selection of a different set of climate variables for the “Time Series”.
7. Seven additional climate change scenarios (20 in total) have been included in the package. A CSV file containing coordinates for GCM files is included for users to develop their own GCM files.
8. Climate data for historical years and periods (decades and normals) from Climate Research Unit (CRU) have been updated from CRUTS2.1 to CRU TS3.1 that covers the period of 1901-2009.
1. The estimate of extreme minimum temperature (EMT) for an individual year has been changed to its corresponding normal period where the individual year is centered.
2. The symbols of degree-days (DDs) for multiple location outputs have been changed as follows for easy import to ArcGIS and R.
DD_0 = DD<0; DD5 = DD>5; DD_18 = DD<18; DD18 = DD>18.
3. The interface has been changed to display all the variables.
A bug for handling missing values in elevation fixed for time series option.
A bug for repeated runs for time series fixed.
Top 10 AR4 scenarios recommended by Dave and Trevor added
AR3 scenarios removed.
Annual climate data update:
2007-2009 annual data added with full coverage (data for Alaska added)
2003-2006 annual data replaced by the new dataset with full coverage
A bug was fixed in "Time Series" option. The bug caused the program to freeze when a location with "No data values" was encountered.
"ClimateWNA v4.522_npb.exe" has also been updated to v4.60 for those who use managed computers without installation privileges.
A bug in estimating EMT was identified and fixed.
An additional EXE file named "ClimateWNA v4.522_npb.exe" is included for those who use managed computers without installation privileges.
A bug in estimating NFFD was identified and fixed.
Derived variables calibrated and improved based on observations from weather stations in western North America.
Add all CGCM3 scenario means over five individual runs
Derived variables validated and improved
Add CGCM3 means over five runs
Eref: Hargreaves annual reference evaporation
CMD: Hargreaves annual climatic moisture deficit
AR4 GCM data do not cover the edges of the land.
Bugs identified and fixed:
Nodata values interrupt process
Elevation adjustment generates some weird values in the north (>lat=60°)
GCM data added with compression.
GCM AR4 (12 scenarios) added
Historical data for recent years (2003-2006) added
Historical data (1901-2002) added with compression.
Coverage expanded to include entire West North America (lat. 24.5 - 80° N; long. -100 - 179° W).
Historical data are compressed by eliminating nodata (-9999) data points.
PRISM data compressed by eliminating nodata (-9999) data points. Storage requirement has been reduced to half.
1. Range expansion: Integrated the coverage of ClimateBC, ClimatePP, and ClimateUS01. Elevation adjustment is carried out separately for "BC and PP" and US. The joint was tested and found no steps at 100m resolution.
2. The resolution of input historical averages for decadal and normal periods changed from 1° to 0.5°.
3. More normal periods for historical data.
4. Calculations of winter and related variables improved. For individual year historical climate variables, both target and previous years' data are used to calculate winter seasonal variables and one annual variable "precipitation as snow (PAS)", which is the sum between August in previous year and July in the target year.
5. Time series function added. This function allow users to obtain climate variables for multiple location and for multiple years.
6. More option added for selecting output variables . Users now can choose all the 83 variables at once.
7. The Output format for interactive mode (for single location) improved. The new format makes it easier for users to put the output into spreadsheet file (space delimited).
ClimateBC version history
The following bugs have been fixed:
· An error was identified for the degree input option at the interface. Fixed
· Blank rows at the end of an input file cause the program to generate error message. Fixed
The resolution of the historical climate data (1901-2002) was restored from 1° to the original resolution (0.5°) of the datasets generated by Mitchell and Jones (2005) to improve the prediction precisions.
Historical climate data (1901-2002) ( Mitchell and Jones 2005) were integrated into the model. The historical data were upsampled from the resolution of 0.5° to 1° using Anuspline to match the resolution of downscaled GCM datasets.
More GCMs were added.
Some bugs were identified and fixed.
The downscaling of the PRISM data was achieved through the combination of bilinear interpolation and elevational adjustments.
Monthly, seasonal and derived climate variables were included.
Three GCMs were integrated.
The downscaling of the PRISM data was achieved through elevational adjustments.
Eight annual climate variables were included.