The Regional Impacts of Climate Change


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C.5. Future Climate Scenarios

Estimation of the potential impacts of global warming should utilize several future climate scenarios, since the magnitude, timing and spatial details of global warming vary among climate models. Most published impacts studies were based on atmospheric General Circulation Model (GCM) doubled CO2 radiative forcing equilibrium experiments with simple mixed-layer oceans. Doubled CO2 radiative forcing (2 x CO2) includes only about 50% actual CO2 forcing with the balance arising from other greenhouse gases. More recent, transient experiments with coupled atmosphere-ocean GCMs have suggested a global average increase in temperature of about 1.0-3.5C by the time of CO2 doubling, estimated as 60-70 years from now (described in the IPCC Second Assessment Report, SAR; IPCC 1996, WG I, Section 6; Annex B). The most recent GCMs include sulfate aerosols in some experiments, which can cool the climate. The analysis presented here will rely both on the older 2 x CO2 equilibrium GCM scenarios (described in the IPCC First Assessment Report, FAR; IPCC 1990, WG I, Section 3; Annex B), since most published analyses have relied on them, and on three new simulations, two from the Hadley Center (HADCM2GHG and HADCM2SUL; Johns et al., submitted; Mitchell et al., 1995; IPCC 1996, WG I, Sections 5, 6), and one from the Max Planck Institute for Meteorology (MPI-T106; Bengtsson, et al. 1995; Bengtsson, et al., 1996; IPCC 1996, WG I, Section 6), which have been made using coupled atmosphere-ocean GCMs and considering sulfate aerosol forcing.

To allow direct comparison with the previously completed VEMAP simulations over the conterminous U.S. (VEMAP Members, 1995), the same three equilibrium GCM scenarios were utilized for the global simulations: UKMO (Mitchell and Warrilow, 1987); GFDL-R30 (IPCC 1990, WG I, Section 3; IPCC 1990, WG I, Section 5); and OSU (Schlesinger and Zhao, 1989). The coarse grid from each model was interpolated to a 0.5 x 0.5, lat.-long. grid. Scenarios were constructed by applying ratios ((2 x CO2)/(1 x CO2)) of all climate variables (except temperature) back to a baseline longterm average monthly climate dataset (Leemans and Cramer, 1991). Ratios were used to avoid negative numbers (e.g., negative precipitation), but were not allowed to exceed 5, to prevent unrealistic changes in regions with normally low rainfall. Temperature scenarios were calculated as a difference ((2 x CO2) - (1 x CO2)) and applied to the baseline dataset.

The newer GCM scenarios are extracted from transient GCM simulations wherein trace gases were allowed to increase gradually over a long period of years, allowing the climate to adjust while incorporating inherent lags in the ocean-atmosphere systems. In order to run the equilibrium vegetation models under the newer transient GCMs, a control climate is extracted as an average of either 30 years (Hadley Center) or 10 years (Max Planck Institute) of model output associated with present climate (e.g. 1961-1990). Likewise, a 30 or 10 year average is extracted from the time period approximating 2 x CO2 forcing (e.g. 2070- 2099). These average climates are then used to drive the vegetation models. Note that because the vegetation models are equilibrium models, the results must be interpreted as indicating the potential vegetation, i.e., the climatically suitable vegetation. Time lags and transient responses of the vegetation to climate change are not considered here.

C.6. Interpretation of Biogeographic Model Simulations

Each of the ten IPCC regions was supplied with a set of MAPSS and BIOME3 output. Included were figures of vegetation distribution under current and future climate, vegetation density change (indexed by leaf area change), and runoff change. Also included were summary tables of the areas of the different biomes within each region under current and future climate, a change matrix indicating the area shifts from current biome type to other types, the areas within each biome expected to undergo an increase or decrease in vegetation density (change in LAI) and the areas within each biome expected to undergo an increase or decrease in annual runoff. These results were supplied for each vegetation model and for each GCM scenario. MAPSS and BIOME3 were both run under the Hadley Center scenarios; BIOME3 alone was run under the Max Planck Institute scenario; and, MAPSS alone was run under the older OSU, GFDL-R30 and UKMO scenarios. The Hadley and MPI simulations were run both with and without a direct CO2 effect (applied in the ecological models); while, the OSU, GFDL-R30 and UKMO scenarios were only run with the direct CO2 effects incorporated, in keeping with the VEMAP analyses.

Since the regional maps are of a much smaller extent and include quantitative information, the detailed interpretation will be left to the regions and the following discussion will only address general features of the simulations, particularly the differences between the older and newer GCMs and the MAPSS and BIOME3 intercomparisons. Although each region received the full set of figures, only a subset will be presented here. The MAPSS and BIOME3 results are sufficiently similar that the ranges presented in Tables C-1, C-2, C-3, C-4 and C-5 encompass the output from both models to indicate the full range of uncertainties within the scope of these experiments and models.


Table C-1: Potential future biome area (percentage of current) simulated by the MAPSS and BIOME3 biogeography models under three older (IPCC 1990, WG I), equilibrium 2 x CO2 GCM scenarios and under three newer (IPCC 1996, WG I), transient simulations from which 2 x CO2 scenarios were extracted. The reported ranges include both ecological models under several GCM scenarios. The baseline areas estimates are outputs from each model. Since BIOME3 does not differentiate Taiga/Tundra from Boreal Forest, two different aggregations are presented. The Taiga/Tundra summaries are MAPSS data only; while the "Boreal + Taiga/Tundra" and "Total Forest + Taiga/Tundra" summaries are from both models. The ranges of percent change for Boreal Conifer are from both models (except FAR scenarios, which are MAPSS output). The Taiga/Tundra under the MAPSS simulations decreases in area in all scenarios; while, Boreal conifer increases in area. Were these two vegetation zones aggregated in MAPSS, they would exhibit either increases or decreases, as in the BIOME3 simulations. The decreases in Boreal Conifer, shown in the table, are BIOME3 simulations.

  Baseline Area (Mha) With CO2 Effect Without CO2 Effect
Biome Type MAPSS BIOME3 FAR Scenarios SAR Scenarios SAR Scenarios

Tundra 792 950 33-59% 43-60% 43-60%
Taiga/Tundra 999 35-62% 56-64% 56-64%
Boreal Conifer Forest 1,024 1,992 109-133% 64-116% 68-111%
Boreal + Taiga/Tundra
2,023 1,992 72-95% 64-90% 68-87%
Temperate Evergreen Forest 1,142 816 104-121% 104-137% 84-109%
Temperate Mixed Forest 744 1,192 125-161% 139-199% 104-162%
Total Temperate Forest
1,886 2,008 116-125% 137-158% 107-131%
Tropical Broadleaf Forest 1,406 1,582 71-151% 120-138% 70-108%
Savanna/Woodland 2,698 2,942 90-130% 78-89% 100-115%
Shrub-Steppe 994 1,954 61-70% 70-136% 81-123%
Grassland 2,082 554 109-126% 45-123% 120-136%
Total Shrub/Grassland
3,076 2,508 96-108% 105-127% 111-126%
Arid Lands 1,470 1,351 71-72% 59-78% 83-120%
Total Vegetation 13,351 13,333 100-101% 100-101% 100-101%

Note: FAR = First Assessment Report (IPCC 1990, WG I); SAR = Second Assessment Report (IPCC 1996, WG I).

 

Table C-2: Percentage area of current biomes which could undergo a loss of leaf area (i.e., biomass decrease) due to global warming under various older (FAR) and newer (SAR) GCM scenarios, and with or without a direct CO2 effect (see Table C-1 for details), as simulated by the MAPSS and BIOME3 biogeography models (ranges include both models). The losses in leaf area generally indicate a less favorable water balance (drought).

  With CO2 Effect Without CO2 Effect
Biome Type FAR Scenarios SAR Scenarios SAR Scenarios

Tundra 1-3% 0-1% 0-2%
Taiga/Tundra 1-5% 1% 2%
Boreal Conifer Forests 39-67% 0-20% 3-69%
Temperate Evergreen Forests 24-57% 1-18% 28-51%
Temperate Mixed Forests 54-86% 1-29% 15-75%
Tropical Broadleaf Forests 5-63% 1-42% 26-33%
Savanna/Woodlands 10-21% 7-17% 38-75%
Shrub-Steppe 26-45% 1-24% 20-59%
Grasslands 33-37% 5-46% 43-75%
Arid Lands 8-12% 0-13% 0-29%

 

Table C-3: Percentage area of current biomes which could undergo a gain of leaf area (i.e., biomass increase) due to global warming under various older (FAR) and newer (SAR) GCM scenarios, and with or without a direct CO2 effect (see Table C-1 for details), as simulated by the MAPSS and BIOME3 biogeography models (ranges include both models). The gains in leaf area generally indicate a more favorable water balance.

  With CO2 Effect Without CO2 Effect
Biome Type FAR Scenarios SAR Scenarios SAR Scenarios

Tundra 20-74% 20-58% 49-82%
Taiga/Tundra 91-98% 92-95% 91-94%
Boreal Conifer Forests 13-21% 36-93% 3-58%
Temperate Evergreen Forests 20-41% 46-67% 7-18%
Temperate Mixed Forests 4-26% 50-91% 9-21%
Tropical Broadleaf Forests 7-40% 16-87% 0-7%
Savanna/Woodlands 74-88% 46-84% 4-31%
Shrub-Steppe 46-64% 64-80% 16-42%
Grasslands 56-60% 45-78% 3-28%
Arid Lands 51-57% 53-80% 23-66%

 

Table C-4: Percentage area of current biomes which could undergo a loss of annual runoff due to global warming under various older (FAR) and newer (SAR) GCM scenarios, and with or without a direct CO2 effect (see Table C-1 for details), as simulated by the MAPSS and BIOME3 biogeography models (ranges include both models).

  With CO2 Effect Without CO2 Effect
Biome Type FAR Scenarios SAR Scenarios SAR Scenarios

Tundra 19-32% 16-45% 28-46%
Taiga/Tundra 79-90% 71-79% 76-82%
Boreal Conifer Forests 1-25% 3-53% 33-81%
Temperate Evergreen Forests 12-21% 25-37% 33-67%
Temperate Mixed Forests 59-77% 51-66% 62-68%
Tropical Broadleaf Forests 11-40% 15-54% 23-68%
Savanna/Woodlands 14-19% 37-60% 31-46%
Shrub-Steppe 43-61% 23-44% 18-42%
Grasslands 34-38% 41-60% 33-56%
Arid Lands 24-26% 1-20% 2-20%

 

Table C-5: Percentage area of current biomes which could undergo a gain of annual runoff due to global warming under various older (FAR) and newer (SAR) GCM scenarios, and with or without a direct CO2 effect (see Table C-1 for details), as simulated by the MAPSS and BIOME3 biogeography models (ranges include both models).

  With CO2 Effect Without CO2 Effect
Biome Type FAR Scenarios SAR Scenarios SAR Scenarios

Tundra 67-80% 36-82% 32-70%
Taiga/Tundra 10-20% 20-28% 18-23%
Boreal Conifer Forests 74-98% 41-95% 14-63%
Temperate Evergreen Forests 78-87% 58-73% 29-66%
Temperate Mixed Forests 23-41% 33-47% 11-37%
Tropical Broadleaf Forests 60-89% 46-85% 32-76%
Savanna/Woodlands 80-84% 31-60% 51-59%
Shrub-Steppe 23-44% 15-45% 23-48%
Grasslands 38-41% 19-32% 17-40%
Arid Lands 7-24% 4-15% 3-15%

 


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