|
|||
| Phase 2 User's Guide |
 |
 |
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
 |
|
|||||||||||||||
|
Nan Rosenbloom
Timothy G.F. Kittel
Cristina Kaufman
Steve Aulenbach
Ecosystem Dynamics and the Atmosphere Section
Climate and Global Dynamics Division
National Center for Atmospheric Research
The completed Phase 1 (equilibrium response) of the project was structured as a sensitivity analysis, with factorial combinations of climate (current and projected under doubled CO2), atmospheric CO2, and mapped and model-generated vegetation distributions. The highly structured nature of the intercomparison allowed rigorous analysis of results, while constraining the range of questions explored. Maps of climate, climate change scenarios, soil properties, and potential natural vegetation were prepared as common boundary conditions and driving variables for the models (Kittel et al. 1995). As a consequence, differences in model results arose only from differences among model algorithms and their implementation rather than from differences in inputs. Results from VEMAP I are reported in VEMAP Members (1995) and selected files are available through the VEMAP1 results web page.
VEMAP completed Phase 2 (transient dynamics) analysis and model intercomparisons in late 2001, with publications in preparation. The objectives of this phase were to compare time-dependent ecological responses of biogeochemical models and coupled biogeochemical-biogeographical models (Dynamic Global Vegetation Models, DGVMs) to historical and projected transient forcings across the conterminous United States. These model experiments were driven by historical time series and projected transient scenarios of climate and atmospheric CO2.
VEMAP 2 also produced a beta release, 75 year (1922-1996) dataset for Alaska. The domain of the Alaskan dataset includes northwestern Canada. Since this release was not been widely tested, please report errors or inconsistencies to the VEMAP data group. This dataset was produced in parallel with the VEMAP 2 dataset for the conterminous U.S., using similar processing techniques. However, in contrast to the conterminous U.S., where the historical time series for temperature and precipitation was gridded from monthly records, the climate record for Alaska was produced by creating gridded monthly temperature and precipitation anomalies from historical records and applying these anomalies to a gridded 1961-1990 baseline climatology.
VEMAP 2 supplemental datasets include 100 year detrended climate input dataset (TSPIN) and GCM simulations of 20th century climate (Suh) for the conterminous US. A complementary 75 year Alaska spinup dataset (TSPINAK), and a GCM simulation of 20th century Alaska climate (SuhAK) are also available. We created the detrended spinup climates by first subtracting a 30yr moving window from the historical timeseries, thus creating a smoothed anomaly record that preserves the structure and much of the variability of the historical record. We then added back a constant value representing the first 15 years of the historical record by month (e.g., 1895-1909 for the conterminuous U.S., and 1922-1936 for Alaska). Adding this period mean to the anomaly field ensures a smooth transition from the detrended spinup period into the historical record.
VEMAP was funded by NASA, Electric Power Research Institute (EPRI),
USDA Forest Service, and US Department of Energy, with additional
support
from the National Science Foundation.
Kittel, T.G.F., N.A. Rosenbloom, J.A. Royle, C. Daly, W.P. Gibson, H.H. Fisher, P. Thornton, D.N. Yates, S. Aulenbach, C. Kaufman, R. McKeown, D. Bachelet, D.S. Schimel, VEMAP2 Participants. 2004. VEMAP Phase 2 bioclimatic database. I. Gridded historical (20th) century climate for modeling ecosystem dynamics across the conterminous USA. Climate Research. vol 27. no. 2, p. 151-170. PDF
Kittel, T.G.F., N.A. Rosenbloom, C. Kaufman, J.A. Royle, C. Daly, H.H. Fisher, W.P. Gibson, S. Aulenbach, R. McKeown, D.S. Schimel, and VEMAP2 Participants (2000). VEMAP Phase 2 Historical and Future Scenario Climate Database. Available online from the VEMAP Data Group, National Center for Atmospheric Research, (Boulder, Colorado).
Rosenbloom, N., T.G.F. Kittel, C. Kaufman, and S. Aulenbach. 2002. User’s Guide to the VEMAP Phase 2 Database. National Center for Atmospheric Research, Boulder, CO. Online document.
Link to other
related VEMAP
publications.
User Acknowledgments:
Users are requested to acknowledge that access to the dataset was provided by the VEMAP data group within the Ecosystem Dynamics and the Atmosphere Section, Climate and Global Dynamics Division, National Center for Atmospheric Research.
Development of the VEMAP database was supported by NASA Mission to Planet Earth, Electric Power Research Institute (EPRI), USDA Forest Service Southern Region Global Change Research Program, and NSF-ATM Climate Dynamics Program through the University Corporation for Atmospheric Research's Climate System Modeling Program.
> ftp ftp.ucar.edu
Name: anonymous
Password: <your_login>
ftp> cd edas/vtrans
ftp> cd <subdirectory>
ftp> get <filename>
DODS uses a client/server architecture with DODS servers providing access to collections of data. The DODS clients request data from the servers using URLs to describe the desired data. Additional information on the DODS transport system is available at the Unidata site.
The full grid contains 5520 grid cells, with 115 columns and 48 rows (Figure 1). Within the grid, 3261 cells are within the boundaries of the conterminous U.S. and predominantly covered by land. Background cells (ocean and inland water cells) are assigned the value of -9999. The VEMAP 'mask', found in the header of each netCDF file, enumerates land cells from 1 to 3261; background cells are indicated by 0.
Table 1. VEMAP grid corners defining the minimum bounding rectangle (MBR).
Figure 1. Layout of the VEMAP gridded array, with grid cell ID numbers.*Negative longitudes are degrees West.
Grid Position Longitude* Latitude Lower Left Corner -124.5deg. 25.0deg. Upper Right Corner -67.0deg. 49.0deg.
Column
1
-to-
115 Row 1 1 2 3 4
...
115
116 117 118 119
...
230
231 ...
-to- .
.
. 48
...
5520
The grid used for the VEMAP 2 Alaska coverage is a 0.5 degree latitude x 0.5 degree longitude grid covering Alaska and part of northwestern Canada. Grid edges are aligned with 1.0 degree and 0.5 degree latitude-longitude lines; grid centers are located at 0.25 degree and 0.75 degree latitude-longitude intersections. Latitude and longitude for each cell are included in the VEMAP 2 Alaska dataset. The grid's minimum bounding rectangle (MBR) is defined by grid domain corners given in Table 2.The full grid contains 3024 grid cells, with 84 columns and 36 rows (Figure 2). Within the grid, 1718 cells are within the boundaries of the domain and predominantly covered by land. Background cells (ocean and inland water cells) are assigned the value of -9999. The VEMAP 'mask', found in the header of each netCDF file, identifies land cells as 1; background cells are indicated by 0.
Table 2. VEMAP grid corners defining the minimum bounding rectangle (MBR).
Figure 2. Layout of the VEMAP gridded array, with grid cell ID numbers.*Negative longitudes are degrees West.
Grid Position Longitude* Latitude Lower Left Corner -170.50deg. 53.50deg. Upper Right Corner -128.50deg. 71.50deg.
Column
1
-to-
84 Row 1 1 2 3 4
...
84
85 86 87 88
...
168
169 ...
-to- .
.
. 36
...
3024
1. Self-Describing. A netCDF file includes information about the data it contains.2. Architecture-independent. A netCDF file is represented in a form that can be accessed by computers with different ways of storing integers, characters, and floating-point numbers.
3. Direct-access. A small subset of a large dataset may be accessed efficiently, without first reading through all the preceding data.
4. Appendable. Data can be appended to a netCDF dataset along one dimension without copying the dataset or redefining its structure. The structure of a netCDF dataset can be changed, though this sometimes causes the dataset to be copied.
5. Sharable. One writer and multiple readers may simultaneously access the same netCDF file.
Unidata also maintains a collection of software libraries for C, Fortran, C++, Java, and perl that provide implementations of the interface. The netCDF source is freely available and can be obtained as a compressed tar file or a zip file from Unidata. Documentation, frequently asked questions, mailing lists, conventions, and searchable archives are available at the same site. Please refer questions about building or installing netCDF software to Unidata support.
Table 3. Geographic variables.
| Variable
Name Code |
Description | Units |
| elev | Average grid cell elevation | meters |
| lat | Latitude of grid cell center | degrees and hundredths of a degree |
| lon | Longitude of grid cell center | degrees and hundredths of a degree |
| vveg | VEMAP vegetation classification | vegetation classification |
| mask | VEMAP geog mask | 0 = background; 1-3261= land cells |
| varea | Absolute area of a grid cell covered by land and within U.S. borders | km2 |
Alaska.
The 0.5 degree Alaska grid was aggregated from a 2.5-min Alaska DEM,
derived from ETOPO30, the USGS 30-sec worldwide digital terrain grid
(Chris
Daly, pers com). Aggregated elevation for each 0.5 degree
gridcell
was computed using a modified Gaussian filter (after Barnes,
1964).
Elevations for inland water bodies are included; non-background cell
count
= 1718.
| Variable Name Code | Description | Units |
| tmax, tmin | Maximum, minimum temperature | degrees C |
| pptx | Accumulated precipitation | mm |
| srad | Total incident solar radiation at surface | kJ m-2 day-1 |
| irrx | Mean daily irradiance | W m-2 |
| vpxx | Vapor pressure | mb |
| rhum | Relative humidity (mean for daylight hours) | fraction[0-1] |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
pptx rhum srad tmax tmin vpxx |
AK |
CCC1* HAD2* TCC1** TCH2** |
xx |
M D |
4 5 (AK) |
|
example #1: rhumTCLMxxM3i.nc
variable = rhum (relative humidity)example #2: rhumAKTCLMxxM5i.nc
period = TCLM (historical period)
experiment = xx (not applicable for historical period)
time step = M (monthly)
release = 3
grid representation = i (inflated)
variable = rhum (relative humidity)
domain = AK (Alaska)
period = TCLM (historical period)
experiment = xx (not applicable for historical period)
time step = M (monthly)
release = 3
grid representation = i (inflated)
As in the VEMAP 1 database, 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 VEMAP Phase 2 models (minimum and maximum temperature, precipitation, vapor pressure, and solar radiation).
(1) Input monthly datasets. Monthly mean minimum and maximum temperature (Tmo) and monthly precipitation (PPTmo) historical time series were derived from:
(a) NCDC's Historical Climate Network (HCN) monthly data from 1895 (~1200 stations)This merged input dataset provides a high density of stations and adequate-to-excellent spatial sampling of climate throughout most of the conterminous U.S., including at higher elevations (primarily from the SNOTEL sites).(b) Shorter period (e.g., 1951-1990) cooperative network monthly station data (for an additional ~6000-8000 stations)
(c) SNOTEL site data
(2) Serially-complete records. We created serially-complete 99-year monthly min/max Tmo and PPTmo records for climate stations from step (1) using a local (moving-window) kriging model, following Haas (1990, 1995) (Royle et al., in preparation, Kittel et al. 1997). The model imputes monthly climate anomalies where station records are discontinuous or limited in length.
(3) Spatial interpolation with topographic adjustment.The serially complete station data were then passed to Chris Daly (Oregon State University) for spatial interpolation with topographic adjustment. Min/max temperature and precipitation station data were spatially interpolated to the 0.5 degree lat/long VEMAP grid for each month in the 99-yr record using a newly expanded version of PRISM (Daly et al., submitted). PRISM incorporates elevation, aspect, and other topographic information to grid temperature and precipitation data. Daly was funded for this task by USDA Forest Service Global Change Research Program.Animations of VEMAP historical and future climate.
(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). For the conterminous U.S. we further modified the code to permit separate parameterizations for wet vs. dry periods in the record (following the work of Dan Wilks). Data limitations prohibited us from implementing the wet vs. dry period modification for the Alaska dataset.
We parameterized the model based on HCN and coop network daily station data and ran it for the VEMAP grid for the 99-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.
(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 2.5 minute gridded 1961-1990 baseline climatology for Alaska (SCAS, 2000), interpolated to the station locations.
(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). Data limitations prohibited us from implementing a wet vs. dry period modification for the Alaska dataset.
We parameterized the model based on HCN and coop network daily station data and ran it for the VEMAP Alaska 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.
Generated vapor pressure fields compare well with the Marks (1990) vapor pressure climatology and simulated solar radiation with NCDC/NREL SAMSON data.
irrx = srad x (1 day/day length) x (1000J/1kJ)
where day length is in seconds.
7.2 - Alaska
McGuire et al., in prep.
Table 6. VEMAP vegetation types: vveg
identifying
code and corresponding VEMAP vegetation type.
| vveg.v2 Code | Vegetation Type |
| TUNDRA | |
| 1 | Tundra |
| FOREST | |
| 2 | Boreal Coniferous Forest |
| (includes Boreal/Temperate Transitional and Temperate Subalpine Forests) | |
| 3 | Maritime Temperate Coniferous Forest |
| 4 | Continental Temperate Coniferous Forest |
| 5 | Cool Temperate Mixed Forest |
| 6 | Warm Temperate/Subtropical Mixed Forest |
| 7 | Temperate Deciduous Forest |
| 8 | Tropical Deciduous Forest (not present)** |
| 9 | Tropical Evergreen Forest (not present) |
| XEROMORPHIC WOODLANDS and FORESTS | |
| 10 | Temperate Mixed Xeromorphic Woodland |
| 11 | Temperate Conifer Xeromorphic Woodland |
| 12 | Tropical Thorn Woodland (not present) |
| SAVANNAS | |
| 13 | Temperate Deciduous Savanna |
| 14 | Warm Temperate / Subtropical Mixed Savanna |
| 15 | Temperate Conifer Savanna |
| 16 | Tropical Deciduous Savanna (not present) |
| GRASSLANDS | |
| 17 | C3 Grasslands (includes Short, Mid-, and Tall C3 Grasslands) |
| 18 | C4 Grasslands (includes Short, Mid-, and Tall C4 Grasslands) |
| SHRUBLANDS | |
| 19 | Mediterranean Shrubland |
| 20 | Temperate Arid Shrubland |
| 21 | Subtropical Arid Shrubland |
| EXCLUDED SURFACE TYPES | |
| 90 | Ice (not present) |
| 91 | Inland Water Bodies (includes ocean inlets) |
| 92 | Wetlands (includes floodplains and strands) |
** not present = vegetation type is not present in the current
distribution
of types for the U.S. on the 0.5 degree grid. These types are included
because they are outputs of VEMAP biogeographical models where
vegetation
distribution could change under altered climate and CO2 forcing,
and
they were used as inputs to selected biogeochemical model runs.
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.
Animations of climate scenarios.
Access to the VEMAP
model
results files from the Community Datasets.
Access to these Supplemental
Datasets is through the Community Data Portal.
Kimball, J. S.W. Running, and R. Nemani (1996) An improved method for estimating surface humidity from daily minimum temperature. Agricultural and Forest Meteorology, in press.
Kittel, T.G.F., D.S. Ojima, D.S. Schimel, R. McKeown, J.G. Bromberg, T.H. Painter, N.A. Rosenbloom, W.J. Parton, and F. Giorgi (1996) Model-GIS integration and dataset development to assess terrestrial ecosystem vulnerability to climate change. Pp. 293-297, in: GIS and Environmental Modeling: Progress and Research Issues. M.F. Goodchild, L.T. Steyaert, B.O. Parks, C. Johnston, D. Maidment, M. Crane, and S. Glendinning (eds). GIS World, Inc., Ft. Collins, CO.
Kittel, T.G.F., N.A. Rosenbloom, T.H. Painter, D.S. Schimel, and VEMAP Modeling Participants (1995) The VEMAP integrated database for modeling United States ecosystem/vegetation sensitivity to climate change. J. Biogeog. 22:857-862.
Küchler, A.W. (1964) Manual to Accompany the Map, Potential Natural Vegetation of the Conterminous United States. Spec. Pub. No. 36. American Geographical Society, New York. 143 pp.
Küchler, A.W. (1975) Potential Natural Vegetation of the Conterminous United States. (2nd ed.) (Map 1:3,168,000) American Geographical Society, New York.
Marks, D. (1990) The sensitivity of potential evapotranspiration to climate change over the continental United States. Pp. IV-1 - IV-31, in: Biospheric Feedbacks to Climate Change: The Sensitivity of Regional Trace Gas Emissions, Evapotranspiration, and Energy Balance to Vegetation Redistribution. H. Gucinski, D. Marks, and D.P. Turner (eds). EPA/600/3-90/078. U.S. Environmental Protection Agency, Corvallis, OR.
NFNOC (Navy Fleet Numeric Oceanographic Center) (1985) 10-minute Global Elevation Terrain, and Surface Characteristics. (Re-processed by NCAR and NGDC). NOAA National Geophysical Data Center. Digital dataset.
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. 83 pp.
Running, S.W., R.R. Nemani, and R.D. Hungerford (1987) Extrapolation of synoptic meteorological data in mountainous terrain and its use for simulating forest evapotranspiration and photosynthesis. Can. J. For. Res. 17:472-483.
SCAS 2000. PRISM 2.5-minute gridded precipitation and temperature for Alaska. Spatial Climate Analysis Service, Oregon State University. Contact: George Taylor, taylor@coas.oregonstate.edu.
Thornton, P.E., Hasenauer, H., and White, M.A. (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.
Thorton, P.E., and Running, S.W. (1999) An improved algorithm for estimating incident daily solar radiation from measurements of temperature, humidity, and precipitation. Agriculture and Forest Meteorology. 93:211-228.
VEMAP Members (1995) Vegetation/Ecosystem Modeling and Analysis Project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling. Global Biogeochem. Cycles 9:407-437.
| VVEG | VEMAP Vegetation Type | Küchler Vegetation Types | |
| vveg.v2 | |||
| 1 | Tundra | 52 | |
| 2 | Boreal coniferous forest | 15, 21, 93, 96 | |
| 3 | Temperate maritime coniferous forest | 1, 2, 3, 4, 5, 6 | |
| 4 | Temperate continental coniferous forest | 8, 10, 11, 12, 13, 14, 16, 17, 18, 19, 20, 95 | |
| 5 | Cool temperate mixed forest | 106, 107, 108, 109, 110 | |
| 6 | Warm temperate/ subtropical mixed forest | 26, 28, 29, 89, 90, 111, 112 | |
| 7 | Temperate deciduous forest | 98, 99, 100, 101, 102, 103, 104 | |
| 8 | Tropical deciduous forest | not present | |
| 9 | Tropical evergreen forest | not present | |
| 10 | Temperate mixed xeromorphic woodland | 30, 31, 32, 36, 37 | |
| 11 | Temperate conifer xeromorphic woodland | 23 | |
| 12 | Tropical thorn woodland | not present | |
| 13 | (v1) Temperate/subtropical deciduous savanna | 71, 81, 82, 84, 88 | |
| (v2) Temperate deciduous savanna | |||
| 14 | Warm temperate/ subtropical mixed savanna | 60, 61, 62, 83, 85, 86, 87 | |
| 15 | Temperate conifer savanna | 24 | |
| 16 | Tropical deciduous savanna | not present | |
| 17 | C3 grasslands | 47, 48, 50, 51, 63, 64, 66, 67, 68 | |
| 18 | C4 grasslands | 53, 54, 65, 69, 70, 74, 75, 76, 77 | |
| 19 | Mediterranean shrubland | 33, 34, 35 | |
| 20 | Temperate arid shrubland | 38, 39, 40, 46, 55, 56, 57 | |
| 21 | Subtropical arid shrubland | 41, 42, 43, 44, 45, 58, 59 | |
| 90 | Ice | not present | |
| 91 | Inland water bodies | no symbol | |
| 92 | Wetlands | 49, 78, 79, 80, 92, 94, 113, 114 | |
|
|
|
Contacts |