On the Intercontinental Transferability of Regional Climate Model Response to Severe Forestation
Abstract
:1. Introduction
2. Materials and Methods
2.1. Model Ensemble
2.2. Land Cover
3. Results
3.1. CRCM5 over North America and Europe
3.1.1. Winter
3.1.2. Summer
3.2. Model Intercomparison over North America
3.2.1. Winter
3.2.2. Spring
3.2.3. Summer
3.2.4. Fall
3.3. Energy Fluxes over Needleleaf and Broadleaf Forests
3.3.1. Northern Needleleaf Forests
3.3.2. Southern Broadleaf Forests
3.3.3. General Remarks
4. Discussion
5. Conclusions
- The extreme forestation considered in this study has profound biogeophysical effects on the climate of North America and Europe. The response to forestation mainly depends on the season, latitude, vegetation distribution, and the models used to assess it.
- During winter and spring, forestation causes widespread biogeophysical warming in all models (Figure 6 and Figure 7). Consistent with LUCAS, the warming hotspots occur over snow-masking northern needleleaf forests (except in WRF, which does not represent properly this phenomenon). Snow masking decreases the surface albedo, which increases net shortwave radiation and causes warming.
- The warming effect of snow masking is proportional to insolation (left panel of Figure 3). Snow-masking reduces albedo uniformly, but its effect on net shortwave excess and warming is magnified at low latitudes and during spring.
- Since northern needleleaf forests populate lower, hence sunnier, latitudes in North America than in Europe (Figure 1), the snow-masking effect causes more warming there. In other words, a needleleaf tree planted where it grows naturally may cause more biogeophysical warming in North America than in Europe.
- During the summer and fall, the biogeophysical effects of forestation are more complex and less consistent across models (Figure 9 and Figure 10). The same difficulty appeared in LUCAS and LUCID. The main source of inter-model divergence is the vegetation’s impact on the partitioning of turbulent heat fluxes.
- Consistent with previous investigations, we find an inverse relationship between the summertime near-surface temperature and evaporative fraction (ratio of latent heat fluxes to total turbulent heat fluxes) responses to forestation (right panel of Figure 3). In other words, cooling tends to occur where forestation promotes evapotranspiration at the expense of sensible heat fluxes.
- Overall, we find that the main mechanisms driving the biogeophysical response to forestation—snow-masking in winter/spring and changes in the turbulent heat flux partition in summer/fall—are the same in North America and Europe.
- However, because both forest families (northern needleleaf and southern broadleaf forests) appear at lower latitudes in North America than in Europe, forestation implies more net shortwave radiation excess over North America. The surface ‘spends’ this energy, (that is, distributes it among the other energy fluxes such as longwave radiation and turbulent heat fluxes), in a similar manner over the two continents (Figure 13 and Figure 14).
- As such, the biophysical effects of extreme forestation are largely transferable between Europe and North America after correcting for differences in the distribution of vegetation.
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
CLASS | Canadian Land Surface Scheme |
CORDEX | Coordinated Regional Climate Downscaling Experiment |
CRCM5 | Canadian Regional Climate Model, version 5 |
CRCM6 | Canadian Regional Climate Model, version 6 |
EF | Evaporative fraction |
FPS | Flagship pilot study |
MODIS | Moderate-resolution imaging spectroradiometer |
WRF | Weather research and forecast |
LUCAS | Land-Use and Climate Across Scales |
LUCID | Land-Use and Climate, Identification of Robust Impacts |
RCM | Regional climate model |
WCRP | World Climate Research Program |
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Model Name | WRF | CRCM5 | CRCM6 |
---|---|---|---|
Institution | NCAR | Ouranos | UQAM |
Land Surface Scheme | Unified NOAH | CLASS v3.5c | CLASS v3.6 |
Land cover classes (principal classes used in FOREST or GRASS are in bold, classes used but with a minor impact are italiziced) | 1: Urban and Built-up Land | 1: Evergreen Needleleaf Trees | 1: Evergreen Needleleaf Trees |
2: Dryland Cropland and Pasture | 2: Evergreen Broadleaf Trees | 2: Evergreen Broadleaf Trees | |
3: Irrigated Cropland and Pasture | 3: Deciduous Needleleaf Trees | 3: Deciduous Needleleaf Trees | |
4: Mixed Dryland/Irrigated Cropland and Pasture | 4: Deciduous Broadleaf Trees | 4: Deciduous Broadleaf Trees | |
5. Cropland/Grassland Mosaic | 5: Tropical Broadleaf Trees | 5: Tropical Broadleaf Trees | |
6. Cropland/Woodland Mosaic | 6: Drought Deciduous Trees | 6: Drought Deciduous Trees | |
7. Grassland | 7: Evergreen Broadleaf Shrub | 7: Evergreen Broadleaf Shrub | |
8. Shrubland | 8: Deciduous Shrubs | 8: Deciduous Shrubs | |
9. Mixed Shrubland/Grassland | 9: Thorn Shrubs | 9: Thorn Shrubs | |
10. Savanna | 10: Short Grass & Forbs | 10: Short Grass & Forbs | |
11. Deciduous Broadleaf Forest | 11: Long Grass | 11: Long Grass | |
12. Deciduous Needleleaf Forest | 12: Crops | 12: Crops | |
13. Evergreen Broadleaf | 13: Rice | 13: Rice | |
14. Evergreen Needleleaf | 14: Sugar | 14: Sugar | |
15. Mixed Forest | 15: Maize | 15: Maize | |
16. Water Bodies | 16: Cotton | 16: Cotton | |
17. Herbacious Wetland | 17: Irrigated Crops | 17: Irrigated Crops | |
18. Wooden Wetland | 18: Urban | 18: Urban | |
19. Barren or Sparlsely Vegetated | 19: Tundra | 19: Tundra | |
20. Herbaceous Tundra | 20: Swamp | 20: Swamp | |
21. Wooded Tundra | 21: Desert | 21: Desert | |
22. Mixed Tundra | 22: Mixed Wood Forests | 22: Mixed Wood Forests | |
23. Bare Ground Tundra | 23: Mixed Shrubs | 23: Mixed Shrubs | |
24. Snow or Ice | |||
Conversion method to implement the vegetation maps (FOREST and GRASS) | bare soil = 19 | bare soil = 21 | bare soil = 21 |
Needleleaf Evergreen Temperate = 14 | Needleleaf Evergreen Temperate = 1 | Needleleaf Evergreen Temperate = 1 | |
Needleleaf Evergreen Boreal = 14 | Needleleaf Evergreen Boreal = 1 | Needleleaf Evergreen Boreal = 1 | |
Needleleaf Deciduous Boreal = 12 | Needleleaf Deciduous Boreal = 3 | Needleleaf Deciduous Boreal = 3 | |
Broadleaf Evergreen Tropical = 13 | Broadleaf Evergreen Tropical = 2 | Broadleaf Evergreen Tropical = 2 | |
Broadleaf Evergreen Temperate = 13 | Broadleaf Evergreen Temperate = 2 | Broadleaf Evergreen Temperate = 2 | |
Broadleaf Deciduous Tropical = 11 | Broadleaf Deciduous Tropical = 4 | Broadleaf Deciduous Tropical = 4 | |
Broadleaf Deciduous Temperate = 11 | Broadleaf Deciduous Temperate = 4 | Broadleaf Deciduous Temperate = 4 | |
Broadleaf Deciduous Boreal = 11 | Broadleaf Deciduous Boreal = 4 | Broadleaf Deciduous Boreal = 4 | |
C3 Arctic Grass = 7 | C3 Arctic Grass = 10 | C3 Arctic Grass = 10 | |
C3 Grass = 7 | C3 Grass = 10 | C3 Grass = 10 | |
C4 Grass = 7 | C4 Grass = 10 | C4 Grass = 10 | |
Representation of sub-grid scale vegetation heterogeneity | The dominant class sets the surface properties, other class properties ignored | The surface properties are averaged over the different classes present on a given tile | The surface properties are averaged over the different classes present on a given tile |
Leaf area index | Estimated using seasonally varying green vegetation coverage fraction (FVEG) and the minimum and maximum values for LAI (LAIMIN and LAIMAX, respectively) prescribed for each vegetation type. LAI = ((1.0 − FVEG) * LAIMIN) + (FVEG * LAIMAX) | Seasonal cycle with the onset of spring budburst and fall senescence triggered by near-zero values of the air temperature and the first soil layer temperature. | Seasonal cycle with the onset of spring budburst and fall senescence triggered by near-zero values of the air temperature and the first soil layer temperature. |
Total soil depth and number of hydrologically/thermally active soil layers | 4 thermally and hydrologically active soil layers with a maximum depth of 2 m | 17 thermally and hydrologically active soil layers with maximum depth of 5 m. | 17 thermally and hydrologically active soil layers with maximum depth of 5 m. |
Initialization and spin-up | Initialization with ERA-Interim | Initialization with ERA-Interim | Initialization with ERA-Interim |
Lateral boundary formulation | linear relaxation | 10 semi-lag departure points | 10 semi-lag departure points |
Buffer (no. of grid cells) | 5 | 20 grid cells lateral sponge zone | grid cells lateral sponge zone: 10 in longitude, 15 in latitude |
No. of vertical levels | 28 | 56 | 71 |
Turbulence and planetary boundary layer scheme | [36] | 1.5-order closure based on prognostic turbulence kinetic energy [37]. Mixing length based on [38]. Stability functions from [39] | 1.5-order closure based on prognostic turbulence kinetic energy [37]. Mixing length based on [38], except in laminar conditions where [40] is used. Stability functions from [37]. |
Radiation scheme | Longwave: RRTM [41]; Shortwave: Goddard [42] | [43] | [43], with a few updates described in [34] |
Deep Convection scheme | Kain-Fritsch w/ETA trigger [44] | [45] | [44], with a few updates described in [34] |
Shallow Convection scheme | n/a | [45] transient | [46] |
Microphysics scheme | WSM3 [47] | [48,49] | [38,49] |
Greenhouse gases | Historical | Historical + RCP4.5 | Historical + RCP8.5 |
Aerosols | Prescribed Observed, Uniform | Prescribed Observed | Hardcoded: higher values ove land than ove ocean; higher values at the equator than at the poles |
CRCM-CLASS | Needleleaf | Broadleaf | Grasses |
---|---|---|---|
Min. Stomatal Resistance (s/m) | 250 | 130 | 150 |
Albedo (visible/near-IR) | 0.03/0.19 | 0.05/0.29 | 0.05/0.31 |
LAI (min–max) | 1.6–2 | 0.5–6 | 4 |
Root Depth (m) | 1 | 2 | 1.2 |
Roughness Length (m) | 1.5 | 2 | 0.08 |
WRF-NOAH | Needleleaf | Broadleaf | Grasses |
Min. Stomatal Resistance (s/m) | 125 | 100 | 40 |
Albedo (min–max) | 0.12 | 0.16–0.17 | 0.19–0.23 |
LAI (min–max) | 5–6.4 | 1.85–3.31 | 0.52–2.90 |
Root Depth (n layers) | 4 | 4 | 3 |
Roughness Length (m) | 0.5 | 0.5 | 0.1 |
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Asselin, O.; Leduc, M.; Paquin, D.; Di Luca, A.; Winger, K.; Bukovsky, M.; Music, B.; Giguère, M. On the Intercontinental Transferability of Regional Climate Model Response to Severe Forestation. Climate 2022, 10, 138. https://doi.org/10.3390/cli10100138
Asselin O, Leduc M, Paquin D, Di Luca A, Winger K, Bukovsky M, Music B, Giguère M. On the Intercontinental Transferability of Regional Climate Model Response to Severe Forestation. Climate. 2022; 10(10):138. https://doi.org/10.3390/cli10100138
Chicago/Turabian StyleAsselin, Olivier, Martin Leduc, Dominique Paquin, Alejandro Di Luca, Katja Winger, Melissa Bukovsky, Biljana Music, and Michel Giguère. 2022. "On the Intercontinental Transferability of Regional Climate Model Response to Severe Forestation" Climate 10, no. 10: 138. https://doi.org/10.3390/cli10100138
APA StyleAsselin, O., Leduc, M., Paquin, D., Di Luca, A., Winger, K., Bukovsky, M., Music, B., & Giguère, M. (2022). On the Intercontinental Transferability of Regional Climate Model Response to Severe Forestation. Climate, 10(10), 138. https://doi.org/10.3390/cli10100138