This data was produced in collaboration with The Wilderness Society.
This set of files includes downscaled projections of decadal means of annual total potential evapotranspiration (in millimeters, no unit conversion necessary) for each decade from 2010 - 2099 at 2x2 kilometer spatial resolution. Each file represents a decadal mean of an annual total calculated from monthly totals.
The spatial extent includes Alaska.
These potential evapotranspiration (PET) estimates were produced using the Hamon equation (Lu et al. 2005), which calculates PET as a function of temperature and day length. Potential evapotranspiration may also be influenced by cloud cover, humidity, and wind speed. The Hamon equation can not explicitly account for variability in these aspects of weather and climate, so it may over or underestimate changes in PET if humidity, cloud cover, or wind speeds change substantially. In addition, the Hamon equation was developed to calculate daily potential evapotranspiration, and so these estimates, based on monthly data, may differ from those calculated from daily data.
Please see the associated document Hamon_PET_equations.pdf for the equations used. Scripts used for the calculation are available upon request to SNAP.
Lu, Jianbiao; Sun, Ge; McNulty, Steven G.; Amatya, Devendra (2005). A comparison of six potential evaportranspiration methods for regional use in the southeastern United States. Journal of the American Water Resources Association, 41, 621- 633.
Each set of files utilizes data from the Climatic Research Unit (CRU, http://www.cru.uea.ac.uk/) TS 3.0 dataset which was downscaled to 2km by the Scenarios Network for Alaska and Arctic Planning.
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Input Temperature Data 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 selection 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.
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Potential Evapotranspiration was only downscaled for the sresa1b scenario.
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.
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The input temperature files are bias corrected and downscaled via the delta method using PRISM (http://prism.oregonstate.edu/) 1961-1990 as baseline climate. Absolute anomalies are utilized for temperature variables.
For more detailed information on base input data (GCMs, historical data), emission scenarios, the downscaling process, or uncertainty, please go to http://www.snap.uaf.edu/
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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
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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.
pet = potential evapotranspiration
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