Climate Change Scenarios
- Canadian Centre for Climate Modeling and Analysis (model = CGCM1)
- Hadley Centre for Climate Prediction and Research, UK (model = HADCM2)
The historical dataset has: (1) daily and monthly versions, (2)
physical consistency among variables on a daily basis, (3) consistency
between climate and topography, and (4) needed input variables for VEMAP2
models (minimum and maximum temperature, precipitation, vapor pressure,
and solar radiation).
Key steps in the development of the gridded, multivariate, monthly and daily historical dataset were:
(1) Input monthly datasets. Monthly mean minimum and maximum
temperature (Tmo) and monthly
precipitation (PPTmo) historical time series were derived from NCDC's Historical Climate Network (HCN) and
cooperative network monthly station data from 1922 - 1996 (~250 stations).
(2) Monthly Anomaly time-series. We created a 75-year
timeseries of monthly precipitation and
temperature anomalies by comparing the historical records against a 4km 1961-1990 baseline climatology for
Alaska, interpolated to the station locations. (Chris Daly, OSU).
(3) Spatial interpolation. These monthly anomalies
were then kriged to the 0.5 degree VEMAP grid. The
monthly anomalies (deltas for temperature, ratios for precipitation) were then applied (added or multiplied) to
a 0.5 degree aggregation of the gridded 4km baseline climatology to create the 75-year historical record. (4) Daily temperature and precipitation generation. We generated daily min/max temperature and precipitation using a modified version of Richardson's (1981, Richardson and Wright 1984) stochastic weather generator WGEN. The version was provided by Sue Ferguson (USFS) and incorporated modifications from Rick Katz and Linda Mearns (NCAR).
We parameterized the model based on HCN and coop network daily station data and ran it for the VEMAP grid for the 75-yr record. The daily values were constrained by gridded monthly T and PPT data from step (3), so that the daily and monthly versions of the historical dataset represent the same climate.
As part of our quality checking process, we compared daily statistics
from the gridded, generated product and station data. We found that daily
frequency distributions and extremes match well for a range of climates
across the domain.
(5) Estimation of solar radiation and humidity. We implemented a new version of MTCLIM (version 3; Thornton and Running 1999, Thornton et al. 2000) for VEMAP2 to create daily (and monthly) vapor pressure (VP), daytime relative humidity, total incident solar radiation (SR), and irradiance (IRR) from daily T and PPT. This version of MTCLIM includes improved estimation of radiation and humidity, as developed by Peter Thornton, Steve Running, John Kimball, and Rob Kremer (U. of Montana) (Kimball et al. 1997, Thornton and Running 1999, Thornton et al. 2000).
Generated vapor pressure fields compare well with the Marks (1990) VP
climatology and simulated SR with NCDC/NREL SAMSON data.
We have processed scenarios from transient greenhouse gas experiments
with sulfate aerosols from the Canadian
Climate Center (CCC) and the Hadley Centre (HADCM2; Mitchell et al.
1995, Johns et al. 1997); accessed via the Climate
Impacts LINK Project, Climatic Research Unit, University of East Anglia.
Daly, C., W.P. Gibson, G.H. Taylor, GL Johnson, and P. Pasteris. In review. Towards a knowledge-based approach to the statistical mapping of climate. Climate Research.
Daly, C., G.H. Taylor, W. P. Gibson, T.W. Parzybok, G. L. Johnson, P. Pasteris. 2001. High-quality spatial climate data sets for the United States and beyond. Transactions of the American Society of Agricultural Engineers 43: 1957-1962.
Haas, T.C. 1990. Lognormal and moving window methods of estimating acid deposition. J. Amer. Stat. Assoc. 85:643-652.
Haas, T.C. 1995. Local prediction of a spatio-temporal process with an application to wet sulfate deposition. J. Amer. Stat. Assoc. 90:1189-1199.
Johns, T.C., R.E. Carnell, J.F. Crossley, J.M. Gregory, J.F.B. Mitchell, C.A. Senior, S.F.B. Tett, and R.A. Wood. 1997. The second Hadley Centre coupled ocean-atmosphere GCM: Model description, spinup and validation. Climate Dynamics 13:103-134.
Kimball, J.S., S.W. Running, and R. Nemani. 1997. An improved method for estimating surface humidity from daily minimum temperature. Agricultural and Forest Meteorology. 85:87-98.
Kittel, T.G.F., J.A. Royle, C. Daly, N.A. Rosenbloom, W.P. Gibson, H.H. Fisher, D.S. Schimel, L.M. Berliner, and VEMAP2 Participants. 1997. A gridded historical (1895-1993) bioclimate dataset for the conterminous United States. Pages 219-222, in: Proceedings of the 10th Conference on Applied Climatology, 20-24 October 1997, Reno, NV. American Meteorological Society, Boston.
Marks, D. 1990. The sensitivity of potential evapotranspiration to climate change over the continental United States. Pages IV-1 - IV-31 in: Biospheric feedbacks to climate change: The sensitivity of regional trace gas emissions, evapotranspiration, and energy balance to vegetation redistribution. Gucinski, H., D. Marks, and D.P. Turner, (eds.) EPA/600/3-90/078. U.S. Environmental Protection Agency, Corvallis, OR.
Mitchell J.F.B., T.C. Johns, J.M. Gregory, and S. Tett. 1995. Climate response to increasing levels of greenhouse gases and sulphate aerosols. Nature. 376:501-504.
Richardson, C.W. 1981. Stochastic simulation of daily precipitation, temperature and solar radiation. Water Resources Research 17:182-190.
Richardson, C.W., and D.A. Wright. 1984. WGEN: A Model for Generating Daily Weather Variables. U.S. Department of Agriculture, Agricultural Research Service, ARS-8, p 83.
Thornton, P.E., and S.W. Running. 1999. An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agricultural and Forest Meteorology, 93:211-228.
Thornton, P.E., H. Hasenauer, and M.A. White. 2000. Simultaneous estimation of daily solar radiation and humidity from observed temperature and precipitation: an application over complex terrain in Austria. Agricultural and Forest Meteorology, 104:255-271.