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EGU2016_CORDEXBE

Hendrik Wouters
Hendrik Wouters

1) The study quantifies the impact of greenhouse gas emissions, climate downscaling, and land-use change on urban heat stress scenarios in Belgium. 2) It reconstructs urban heat stress for 1979-2010 and projects future changes using a regional climate model under different greenhouse gas concentration scenarios and land use change projections. 3) The results indicate urban and semi-urban areas will experience greater increases in heat stress than rural areas due to synergistic effects of climate change, urban heat islands, and urban expansion.

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The impact of green-house gas emissions, climate downscaling and land-use change on Belgian urban heat stress scenarios Hendrik Wouters, Nicole van Lipzig, Sam Vanden Broucke, Lien Poelmans, Hossein Tabari, Parisa Hosseinzadeh Talaee, Johan Brouwers, Matthias Demuzere, Dirk Lauwaet, Bino Maiheu, and Koen De Ridder
Rapid changes in global society
GHG Emission
Land use change
EGU2016_CORDEXBE
There were more than 400 additional deaths in Belgium during heat wave in summer 2015 Belgian Scientific Institute of Public Health = ~遜
Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
min, max,18.2 29.6 ,i i i i HGD T C T C h 刻 逸 削 誌 Urban heat stress index [De Ridder., et al 2015] Heat-wave degree days [属C day]: Heat wave day hi Threshold-based index
City centre Rural area Heat-wave degrees for Antwerp [C 属 day] Urban heat stress index [De Ridder., et al 2015]
COSMO-CLM Regional climate model [Rockel et al., 2008]
COSMO-CLM Scenarios Risk assessment Land characteristics GHG concentration Boundary climate High-resolution 3D climate statistics GHG Emissions Land-use change Urban heat stress Heavy precipitation and floods Air pollution Regional climate model [Rockel et al., 2008]Regional climate model
TERRA_URB Urban land-surface scheme of the COSMO(-CLM) model [Wouters et al. 2015 (UCLIM); Wouters et al. 2016 (GMDD)]
Hiresolution climate modelling COSMO-CLM TERRA_ML Europe: CORDEX.EU domain COSMO-CLM TERRA_URB Brussels Belgium: CORDEX.be domain 12.5km resolution 2.8km resolution [Jacob et al.] [Termonia et al.]
Reconstruction heat-stress index for 1979-2003
Reconstruction heat-stress index for 1979-2003
Reconstruction heat-stress index for 1979-2010 COSMO-CLM + TERRA-URB (composite) cascade-nested in ERA-INTERIM
Reconstruction heat-stress index for 1979-2010 COSMO-CLM + TERRA-URB (composite) cascade-nested in ERA-INTERIM
Reconstruction heat-stress index for 1979-2010 COSMO-CLM + TERRA-URB (composite) cascade-nested in ERA-INTERIM
Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
Impervious surface area [%] Output from Spatial model [Engelen et al., 2011)] Land use change
Impervious surface area [%] Land use change Business as usual Output from Spatial model [Engelen et al., 2011)]
Delta change approach [Tabari et al., 2014] Changes in ensemble statistics are applied to the hindcast RCP2.6, RCP4.5, RCP6.5 and RCP 8.5 11 GCM models, 31 simulations Three ensemble scenarios: GHG Emission
Delta change approach (Tabari et al., 2014) Offset applied on HISTorical record RCP2.6, RCP4.5, RCP6.5 and RCP 8.5 11 GCM models, 31 simulations Three scenarios: Low temperatures High temperatures GHG Emission 60-year Changes in daily temperatures [属C] 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 bin Apr may Jun Jul Aug Sep 0 1 2 3 4 5 HIGH MEDIAN LOW Low temperatures High temperatures
EGU2016_CORDEXBE
Urban Semi-urban Rural Clim.spread Clim. average
Future change heat stress LAND:2060 GHG:MEDIAN
Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers for future HS changes
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly mean temperature change
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature distribution
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature distribution High-resolution climate downscaling Monthly-mean
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution change and downscaling
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling GHG Emission 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 Low temperatures High temperatures Temperature change [属C]
Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling
Wouters et al. (in preparation), Green-house gas induced excess heat waves, heat islands and urban expansion comprise inordinate future heat stress at the mid-latitude.

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EGU2016_CORDEXBE

  • 1. The impact of green-house gas emissions, climate downscaling and land-use change on Belgian urban heat stress scenarios Hendrik Wouters, Nicole van Lipzig, Sam Vanden Broucke, Lien Poelmans, Hossein Tabari, Parisa Hosseinzadeh Talaee, Johan Brouwers, Matthias Demuzere, Dirk Lauwaet, Bino Maiheu, and Koen De Ridder
  • 2. Rapid changes in global society
  • 6. There were more than 400 additional deaths in Belgium during heat wave in summer 2015 Belgian Scientific Institute of Public Health = ~遜
  • 7. Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
  • 8. Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
  • 9. min, max,18.2 29.6 ,i i i i HGD T C T C h 刻 逸 削 誌 Urban heat stress index [De Ridder., et al 2015] Heat-wave degree days [属C day]: Heat wave day hi Threshold-based index
  • 10. City centre Rural area Heat-wave degrees for Antwerp [C 属 day] Urban heat stress index [De Ridder., et al 2015]
  • 11. COSMO-CLM Regional climate model [Rockel et al., 2008]
  • 12. COSMO-CLM Scenarios Risk assessment Land characteristics GHG concentration Boundary climate High-resolution 3D climate statistics GHG Emissions Land-use change Urban heat stress Heavy precipitation and floods Air pollution Regional climate model [Rockel et al., 2008]Regional climate model
  • 13. TERRA_URB Urban land-surface scheme of the COSMO(-CLM) model [Wouters et al. 2015 (UCLIM); Wouters et al. 2016 (GMDD)]
  • 14. Hiresolution climate modelling COSMO-CLM TERRA_ML Europe: CORDEX.EU domain COSMO-CLM TERRA_URB Brussels Belgium: CORDEX.be domain 12.5km resolution 2.8km resolution [Jacob et al.] [Termonia et al.]
  • 17. Reconstruction heat-stress index for 1979-2010 COSMO-CLM + TERRA-URB (composite) cascade-nested in ERA-INTERIM
  • 18. Reconstruction heat-stress index for 1979-2010 COSMO-CLM + TERRA-URB (composite) cascade-nested in ERA-INTERIM
  • 19. Reconstruction heat-stress index for 1979-2010 COSMO-CLM + TERRA-URB (composite) cascade-nested in ERA-INTERIM
  • 20. Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
  • 21. Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
  • 22. Impervious surface area [%] Output from Spatial model [Engelen et al., 2011)] Land use change
  • 23. Impervious surface area [%] Land use change Business as usual Output from Spatial model [Engelen et al., 2011)]
  • 24. Delta change approach [Tabari et al., 2014] Changes in ensemble statistics are applied to the hindcast RCP2.6, RCP4.5, RCP6.5 and RCP 8.5 11 GCM models, 31 simulations Three ensemble scenarios: GHG Emission
  • 25. Delta change approach (Tabari et al., 2014) Offset applied on HISTorical record RCP2.6, RCP4.5, RCP6.5 and RCP 8.5 11 GCM models, 31 simulations Three scenarios: Low temperatures High temperatures GHG Emission 60-year Changes in daily temperatures [属C] 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 bin Apr may Jun Jul Aug Sep 0 1 2 3 4 5 HIGH MEDIAN LOW Low temperatures High temperatures
  • 28. Future change heat stress LAND:2060 GHG:MEDIAN
  • 29. Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers future HS changes
  • 30. Objectives Hindcast for urban heat stress in Belgium Projections To quantify the different drivers for future HS changes
  • 31. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural
  • 32. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly mean temperature change
  • 33. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature distribution
  • 34. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature distribution High-resolution climate downscaling Monthly-mean
  • 35. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency
  • 36. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change
  • 37. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution change and downscaling
  • 38. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling
  • 39. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling
  • 40. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling GHG Emission 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 Low temperatures High temperatures Temperature change [属C]
  • 41. Future change heat stress: drivers (Decomposition methodology: Stein and Alpert, 1993) Urban Semi-urban Rural Greenhouse gas-induced changes in climate statistics Monthly-mean temperature change Changes in temperature Distribution High-resolution climate downscaling Monthly-mean Time dependency Land-use change Synergy temperature distribution and downscaling
  • 42. Wouters et al. (in preparation), Green-house gas induced excess heat waves, heat islands and urban expansion comprise inordinate future heat stress at the mid-latitude.