Documentation  Community Datasets Phase 2 Alaska - Transient Dynamics

VEMAP Phase 2 Alaska [beta release] - Transient Climate Dataset Documentation

Overview
Historical Climate
Climate Change Scenarios
References

OVERVIEW OF VEMAP2 ALASKA - GRIDDED CLIMATE TIME SERIES [beta release]

Features of this database are:

Component Climate Sets

•  Historical Climate Series -- Based on NOAA HCN, Snotel, and other station data
•  Time-Dependent ('Transient') Climate Change Scenarios -- Derived from coupled atmospheric-ocean global climate model experiments with transient greenhouse gas and sulfate aerosol forcing, from the following modeling centers:

- Canadian Centre for Climate Modeling and Analysis (model = CGCM1)
- Hadley Centre for Climate Prediction and Research, UK (model = HADCM2)

Domain

•  Alaska

 
•  Gridded at 0.5deg. lat/lon -- Spatially realistic (e.g., terrain-adjusted interpolation by PRISM, Daly et al.)

Variables

• T_min, T_max, Precipitation
• VP (& RH), SR (& Irradiance)

- Estimated with MTCLIM3 (Thornton et al. 1999, 2001)
- All variables physically consistent in space and time

Time Step

•  Monthly -- Interannual and decadal variation

-  Historical: Based on observed data
-  Scenarios: Derived from coupled climate models
 
•  Daily -- From stochastic wx generator: modified WGEN (Richardson et al, Mearns, Katz)

- Historical: Realistic daily covariance structure
- Scenarios: Daily covariance statistics from historical period
- No daily spatial autocorrelation

Record Period

•  Historical: 1922-1996 -- Temporally complete
•  Scenarios: 1997-~2100 -- Scenario records begin at end of the historical series

More Information

• See VEMAP Phase 2 User's Guide for descriptions of

- grid
- auxiliary datasets
• vegetation
• soil

Transient Model Climate Input Data Development:

 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.
 
 

Transient Climate Change Scenarios (TSCENARIOS)

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.
 
 

References

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.

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