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The Netherlands approach for generating climate change scenarios

The Netherlands approach for generating climate change scenarios Bart van den Hurk, KNMI and many others Exercise from last week Give an order of estimate of the climate sensitivity based on the observed CO 2 and T. Give arguments about the validity of this approach

JasminFlorian
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The Netherlands approach for generating climate change scenarios

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  1. The Netherlands approach for generating climate change scenarios Bart van den Hurk, KNMI and many others New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  2. Exercise from last week • Give an order of estimate of the climate sensitivity based on the observed CO2 and T. Give arguments about the validity of this approach New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  3. What are climate scenarios? • No predictions but What if… projections prob T New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  4. What are climate scenarios? • No predictions but What if… projections • With the following characteristics: • Plausible: fair chance of actually occuring in the future (excluding very unlikely situations) • Internally consistent: mean and extreme precipitation, temperature etc can all occur in the same climate • Relevant: aimed at information needs for impact assessment or policy evaluation applications New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  5. Model projections of future global climate • Models are imperfect • Future greenhouse gas concentrations are unknown • Coordinated effort: • define set of emission scenarios • calculate concentration evolution • use this to make projections with range of GCMs • AR4: Large (~25) nr of GCMs available for 1900 – 2200 (http://www-pcmdi.llnl.gov/) New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  6. Projections mean precipitation (2050/1990) with the MPI model A2 A1B +25% Winter Summer -50% New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  7. Projections mean precipitation (2050/1990) with the MPI model A2 A1B +25% Winter Mean change Winter change  +5 – +10% Summer change  -10 – -15% Difference scenarios A2 a bit stronger in winter A1B a bit stronger in summer Gradient N-S gradient in winter SE-NW gradient in summer Resolution Resolution very coarse (>150 km) Extremes Only seasonal mean! No info on extremes or nr of wet days. Summer -50% New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  8. The production of the KNMI’06 scenarios New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  9. The production of the KNMI’06 scenarios New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  10. Global mean climate change scenarios • Start with projections with Global Circulation Models (GCM’s): • Multiple emission scenarios • Multiple models New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  11. But there’s more than global mean temperature Sea level pressure difference from 2 different GCMs Van Ulden and Van Oldenborgh, 2006 New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  12. G-west in West-Europe for present-day climate • Approx 10 AR4 GCM-runs Observations Models Van Ulden et al, 2006 New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  13. G-west end of 21st century with doubled CO2-levels • Changes relative to present climate New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  14. G-west end of 21st century with doubled CO2-levels • Changes relative to present climate New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  15. The influence from the driving GCM! • Change of precipitation annual cycle in Rhine area from multiple regional climate model simulations • Two different GCM’s ECHAM4/OPYC (more Atlantic advection in winter, less in summer) HadAM3H (small changes in circulation statistics) New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  16. Winter temperature andwind direction A2 scenario Control simulation Observed 14 12 10 8 6 4 2 0 -2 -4 -6 -8 -10 • Eastern winds give low winter temperatures New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  17. Rationale of the scenarios • The steering variables • 1. Global temperature – 2. Strength of seasonal mean west-circulation (not for zsea) Strength of west-circulation month New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  18. The production of the KNMI’06 scenarios New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  19. Regional climate change: downscaling • GCM-grid box too coarse Global model Regional model New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  20. Downscaling • Downscaling = local interpretation of GCM-scenario by using local added information • Orography, land/sea • Land use, … • 2 families of methods • Statistical • Dynamical New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  21. Statistical downscaling • Ingredients: • Local observed time series of weather variable (e.g. precipitation) • Archive of large scale circulation-indicators (e.g. air pressure, temperature/wind in higher atmosphere, gradients of humidity, pressure, …) • Correlation-equation • Large scale circulation-indicators from a GCM projection to be downscaled New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  22. Statistical downscaling I from GCM’s + a and b from local calibration  local P New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  23. Dynamical downscaling: Regional Climate Model (RCM) • High resolution GCM (50 – 20 km) • better resolving land-sea, orography, atm.gradients • Lateral boundary conditions from reanalysis (present-day climate conditions) or GCM runs (scenario runs) • multi-level • temporal frequency dependent on domain • Inner domain free evolving New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  24. Analysis of AR4 GCMs: precipitation and temperature • Local downscaling: • Daily values rather than seasonal means • (Soft) extremes • Number of rain days • 10 PRUDENCE RCM’s • 8x HadAM3H (fairly dry in summer, modest SST, strong circ in summer, less in winter) • 2x ECHAM4 (very wet in winter and dry in summer, strong circ, stronger effect SST) • Problem: no GCM run representative for circ  0 • “Escape”: • KNMI RCM remains fairly wet in summer (can be used for G- en W-scenario) • in winter the RCM runs cover the GCM-variability reasonable New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  25. Analysis of AR4 GCMs: precipitation and temperature • Downscaling with RCM’s • Relationship local variables – steering variables New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  26. Analysis of AR4 GCMs: precipitation and temperature • Downscaling with RCM’s • Relationship local variables – steering variables • Circulation-dependent and –independent regression-coefficient xcirc en xT • Apply regression in scenarios: var = xT Tglob + xcirc circ • Weigh RCM’s per scenario to enhance differences New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  27. Result: change in 2050 relative to 1990 New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  28. Result: change in 2050 relative to 1990 mean temperature yearly coldest day With circulation change the coldest temperature changes more than mean New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  29. Result: change in 2050 relative to 1990 Nr of wet days strongly dependent on circulation change wet day frequency New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  30. Result: change in 2050 relative to 1990 Wet day mean precipitation dependent on global temperature rise mean precipitation New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  31. Result: change in 2050 relative to 1990 Extreme precipitation is more likely in a wetter climate daily precipitation exceeded 1/10yrs New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  32. Result: change in 2050 relative to 1990 annual maximum daily mean wind Windscenarios hardly show a significant change New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  33. Result: change in 2050 relative to 1990 Sea level scenario’s after 2050 show acceleration: For 2100 the range is between 35 and 85 cm sea level rise New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  34. General picture • Extreme temperature change is stronger than mean, especially when circulation also changes • When circulation changes number of precipitation days is strongly reduced in summer, causing a reduction of mean summertime precipitation • In winter mean precipitation increases (dependent on circulation) • Extreme precipitation increases both in summer and winter • Sea level rise is slightly smaller than in TAR • 1/yr Wind slightly increases (but not significantly) New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  35. Tailored climate scenarios • Specific use in many applications (e.g. water management) requires “tailoring” • Examples • High resolution time series of precipitation • Ground water tables in the Netherlands • Long (>100 yr) time series • Dynamical downscaling in Rhine basin • Closure of Maasland barrier New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  36. The production of the KNMI’06 scenarios New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  37. Generation of high resolution time series • Climate scenarios provide general key numbers (change of mean, change of 1/10yr return value) • Change an existing (obs) time series of precipitation • linearly (using only mean change) • non-linearly (changing also shape of distribution and # wet days) New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  38. Non-linear time series transformation • Determination of extremes (via statistical downscaling) • From previous step: p50, p99, scaled to pn via assumed scaling of pdf • Observed time series transformed with pn • From transformed time series: • Return time of extremes • Nr of frost days • Length growing season… New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  39. Generation of high resolution time series non-linear transformation introduces dry day n-lin > obs lin < obs and different changes for different intensities n-lin < obs lin < obs New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  40. Effect on groundwater table (example) non-linear transformation has tendency to be wetter in wet episodes and drier in dry spells New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  41. Change in ground water table the Netherlands • Aim: first assessment of effect of W+ scenario on ground water table in various stages of the growing season • Tailoring: • production of location specific meteo (applied linearly in this example) • running high resolution ground water model Lowest water table during growing season: generally drier Start of growing season: generally wetter courtesy Timo Kroon, Franziska Keller ea New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  42. Long time series • Extremes (1/x jr; x»1) have more impact than the mean climate • Length of time series is limited • Observations: < 150 jr • GCM’s: < 200 jr • RCM’s: < 50 jr • Estimation of extremes by: • Extrapolation of fitted Generalized Extreme Value (GEV) functions • Creation of long time series by resampling New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  43. Fit of GEV-distribution • Assume that yearly maxima obey a given ditribution P(,) (for instance Gumbel) • Determine return time from ranked sequence • Fit GEV to ranked sequence • Extrapolate return times   New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  44. Resampling • Use historical time series of combination of weather variables (P, T, u) • Select a random day • Search for analogues • Select a random analogue day • Take next day in historical time series • Preservation of temporal correlation New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  45. Resampling Simulated rainfall series  Historical rainfall series date value (mm) Resampling with replacement New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  46. Resampling Historical rainfall series date value (mm) Largest 4-day amount: 46 mm Simulated rainfall series  Largest 4-day amount: 80 mm New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  47. Dynamical downscaling using 1 RCM: results for Rhine discharge Control J F M A M J J A S O N D SWURVE project (Lenderink et al, 2003) New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  48. Dynamical downscaling using 1 RCM: results for Rhine discharge Annual cycle increases A2-scenario 2070-2100 Extreme value analysis: Shorter return period of peak discharge J F M A M J J A S O N D SWURVE project (Lenderink et al, 2003) New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  49. Closure of Maasland-barrier: costly! • Dependent on (simultaneous) high water level due to surge and Rhine discharge Sea level at Hoek v Holland (m) Rhine discharge ( 1000 m3/s) H vd Brink ea New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

  50. Closure of Maasland-barrier: costly! • Dependent on (simultaneous) high water level due to surge and Rhine discharge Sea level at Hoek v Holland (m) Closure return time (years) Rhine discharge ( 1000 m3/s) Sea level rise (m) H vd Brink ea New climate scenarios for the Netherlands – www.knmi.nl/climatescenarios

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