This set of files includes downscaled projections decadal means of annual of day of freeze or thaw for each decade from 2010 - 2100 (see exceptions below) at 2x2 kilometer spatial resolution. Each file represents a decadal mean of an annual mean calculated from mean monthly data.
==========================================
Units are ordinal day 15-350 with the below special cases.
For Day of Freeze (DOF)
0 = Primarily Frozen
365 = Rarely Freezes
For Day of Thaw (DOT)
0 = Rarely Freezes
365 = Primarily Frozen
==========================================
The spatial extent includes Alaska, the Yukon Territories, British Columbia, Alberta, Saskatchewan, and Manitoba.
=========
Overview:
Most of SNAP’s climate projections come in multiple versions. There are 5 climate models, one 5 model average, 3 climate scenarios, 12 months, and 100 years. This amounts to 21,600 files per variable for monthly data. Some datasets are derived products such as monthly decadal averages or specific seasonal averages, among others. This specific dataset is one subset of those.
Each set of files originates from one of five top ranked global circulation models or is calculated as a 5 Model Average. These models are referred to by the acronyms: cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, miroc3_2_medres, or 5modelavg. For a description of the model seletion process, please see Walsh et al. 2008. Global Climate Model Performance over Alaska and Greenland. Journal of Climate. v. 21 pp. 6156-6174
cccma_cgcm31 - Canadian Centre for Climate Modelling and Analysis, Coupled General Circulation Model version 3.1 - t47, Canada
mpi_echam5 - Max Planck Institute for Meteorology, European Centre Hamburg Model 5, Germany
gfdl_cm21 - Geophysical Fluid Dynamics Laboratory, Coupled Model 2.1, United States
ukmo_hadcm3 - UK Met Office - Hadley Centre, Coupled Model version 3.0, United Kingdom
miroc3_2_medres - Center for Climate System Research, Model for Interdisciplinary Research on Climate 3.2(medres), Japan
5modelavg - Calculated as the mean of the above 5 models.
* Exceptions *
The UK MET Office Hadley Centre (ukmo_hadcm3) GCM model only included outputs up to December 2099 for the A2 scenario, so outputs for the files named <tas_mean_C_ar4_ukmo_hadcm3_sresa2_mm_yyyy.tif> as well as the 5 Model Average A2 scenario, <tas_mean_C_ar4_5modelAvg_sresa2_mm_yyyy.tif> end in December 2099.
Each set of files also represents one projected emission scenario referred to as: sresb1, sresa2, or sresa1b.
=============================
Emmission scenarios in brief:
The Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) created a range of scenarios to explore alternative development pathways, covering a wide range of demographic, economic and technological driving forces and resulting greenhouse gas emissions. The B1 scenario describes a convergent world, a global population that peaks in mid-century, with rapid changes in economic structures toward a service and information economy. The Scenario A1B assumes a world of very rapid economic growth, a global population that peaks in mid-century, rapid introduction of new and more efficient technologies, and a balance between fossil fuels and other energy sources. The A2 scenario describes a very heterogeneous world with high population growth, slow economic development and slow technological change.
=============================
Downscaling:
These files are bias corrected and downscaled via the delta method using PRISM (http://prism.oregonstate.edu/) 1961-1990 (for 2km Alaska and Western Canada data) or 1971-2000 (for 771 meter Alaska data) as baseline climate. Absolute anomalies are utilized for temperature variables. Proportional anomalies are utilized for precipitation variables.
For more detailed information on base input data (GCMs, historical data), emmission scenarios, the downscaling process, or uncertainty, please go to http://www.snap.uaf.edu/
===============================
Day of Freeze, Day of Thaw, Length of Growing Season calculations:
Estimated ordinal days of freeze and thaw are calculated by assuming a linear change in temperature between consecutive months. Mean monthly temperatures are used to represent daily temperature on the 15th day of each month. When consecutive monthly midpoints have opposite sign temperatures, the day of transition (freeze or thaw) is the day between them on which temperature crosses zero degrees C. The length of growing season refers to the number of days between the days of freeze and thaw.
This amounts to connecting temperature values (y-axis) for each month (x-axis) by line segments and solving for the x-intercepts. Calculating a day of freeze or thaw is simple. However, transitions may occur several times in a year, or not at all. The choice of transition points to use as the thaw and freeze dates which best represent realistic bounds on a growing season is more complex. Rather than iteratively looping over months one at a time, searching from January forward to determine thaw day and from December backward to determine freeze day, stopping as soon as a sign change between two months is identified, the algorithm looks at a snapshot of the signs of all twelve mean monthly temperatures at once, which enables identification of multiple discrete periods of positive and negative temperatures. As a result more realistic days of freeze and thaw and length of growing season can be calculated when there are idiosyncrasies in the data.
===================
File naming scheme:
While it’s hard to have a completely static file naming scheme, we make every attempt to keep some consistency across our various datasets. This naming scheme outlined below is our general guide, although it does vary depending upon each dataset.
[variable]_[metric]_[units]_[format]_[assessmentReport]_[groupModel]_[scenario]_[timeFrame].[fileFormat]
some examples of these file names parts include:
[variable] pr, tas, logs, dot, dof, veg, age, dem
[metric] mean, total, decadal mean monthly mean
[units] mm, C, in, km
[format] optional, if layer is formatted for special use
[assessmentReport] ar4, ar5 (assessment report, for projected data only)
[groupModel] cccma_cgcm31, mpi_echam5, gfdl_cm21, ukmo_hadcm3, miroc3_2_medres, 5modelavg, cru_ts31
[scenario] sresb1, sresa2, sresa1b
[timeFrame] yyyy or mm_yyyy or yyyy_yyyy or mm_yyyy_mm_yyyy
[fileFormat] tif, txt, png, pdf
=======================
full file name examples:
tas_mean_C_ar4_cccma_cgcm3_1_sresb1_05_2034.tif
This file represents May 2034 mean temperature in degrees Celsius from the 4th Assessment Report on Climate Change from the CCCMA modeling group, using their CGCM3.1 model, under the B1 climate scenario.
pr_decadal_mean_DJF_total_mm_cru_TS31_historical_1920_1929.tif
This file represents mean total winter(Dec, Jan, Feb) precipitation from 1920-1929 from downscaled CRU TS 3.1 data.
tas = near-surface air temperature
pr = precipitation including both liquid and solid phases
dof = day of freeze
dot = day of thaw
logs = length of growing season