The Netherlands approach for generating climate change scenarios Bart van den Hurk, KNMI and many others
What is the global climate problem? Climate change is normal Natural influences: Internal variability (El Niño) Variations in solar activity and sun/earth geometry (ice ages) (Major) Vulcanic eruptions Antropogenic influences: Greenhouse gas emissions Changes in land use
Variability of surface temperature IPCC, 2007
Signal/noise of future outlook IPCC, 2007
The IPCC process IPCC = Intergovernmental Panel on Climate Change Periodic (~ 5yrs) scientific assessment of climate science No direct initiation of new research Only peer-reviewed publications Open process Lead authors Authors Scientific Reviewers (30.000) Governmental Reviewers 2007: 4 th Assessment Report (AR4)
IPCC structure 3 working groups I: the scientific basis Observed change (also paleo) Nature of the climate system Modelling the system Making future projections (global/regional) II: effects of climate change (adaptation options) III: prevention (mitigation) options Various components Assessment reports (WG-I: 2 reviewed drafts & final version. Electronic version available since May 07) Summary for Policy Makers (SPM): line-by-line acceptance by national representatives (2 Feb 07) Technical Summary See http://ipcc-wg1.ucar.edu/wg1/wg1-report.html
Main findings of AR4 GHG concentrations are rising due to humans This leads to a net positive radiative forcing (rate of energy change at TOA; see WG-I 2.2) IPCC, 2007
IPCC, 2007 Climate change in observations since 1906: 0.074 ± 0.018 K/10yrs since 1956: 0.13 ± 0.03 K/10yrs
IPCC, 2007 Climate change in observations since 1961: 1.8 ± 0.5 mm/yr since 1993: 3.1 ± 0.7 mm/yr thermal expansion: 1.6 ± 0.5 glaciers and ice caps: 0.77 ± 0.22 Greenland ice sheet: 0.21 ± 0.07 Antarctic ice sheet: 0.21 ± 0.35 unexplained: 0.3 ± 1.0 TAR: negative contribution
IPCC, 2007 Climate change in observations From TAR:
and further More water in the atmosphere since 1980 s Ocean temperature increased since 1961 to at least 3000m (absorbing 80% of heat increase) Oceans are fresher at midlatitudes and saltier at lower latitudes Higher temperatures at top of permafrost, 7% reduction in area since 1900 Increased precipitation in higher midlatitudes (incl N.Europe), drying in subtropics (incl Mediterranean), but signal is very noisy IPCC, 2007
Attribution: is it human induced? IPCC, 2007
IPCC, 2007 Model results
Climate sensitivity Climate sensitivity = global T-increase for a doubling of [CO 2 ] T-increase is result of many processes (ocean heat uptake, aerosolconcentration, external forcings) Model simulations constrained by observed transient changes or by equilibrium simulations Beste estimate: 2 4.5 C, likely 3 C
Climate change in Europe: ECA Trends in mean precip and temperature 1946-2006 Annual ONDJFM AMJJAS eca.knmi.nl
Temperature extremes DJF TN10p: nr of days with TN < 10% JJA TX90p: nr of days with TX > 90% eca.knmi.nl
RR1 (nr of wet days) R95p (nr of very wet days > 95%) eca.knmi.nl Precipitation indices JJA DJF
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/)
CO 2 CH 4 Emission Emission scenario s s (SRES) N 2 O SO 2
IPCC, 2007 Results (global mean temperature)
IPCC, 2007 Results (global mean temperature)
IPCC, 2007 Precipitation changes
Winter Summer Projections mean precipitation (2050/1990) with the MPI model A1B A2 +25% -50%
Projections mean precipitation (2050/1990) with the MPI model A1B A2 +25% Winter Gradient N-S gradient in winter SE-NW gradient in summer Summer Mean change Winter change ± +5 +10% Summer change ± -10-15% Resolution Resolution very coarse (>150 km) Extremes Only seasonal mean! No info on extremes or nr of wet days. Difference scenarios A2 a bit stronger in winter A1B a bit stronger in summer -50%
The production of the KNMI 06 scenarios
The production of the KNMI 06 scenarios
Global mean climate change scenarios Start with projections with Global Circulation Models (GCM s): Multiple emission scenarios Multiple models
But there s more than global mean temperature Sea level pressure difference from 2 different GCMs Van Ulden and Van Oldenborgh, 2006
G-west in West-Europe for present-day climate Approx 10 AR4 GCM-runs Observations Models Van Ulden et al, 2006
G-west end of 21 st century with doubled CO 2 -levels Changes relative to present climate
G-west end of 21 st century with doubled CO 2 -levels Changes relative to present climate
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)
Winter temperature and wind direction Eastern winds give low winter temperatures A2 scenario Control simulation Observed 14 12 10 8 6 4 2 0-2 -4-6 -8-10
Rationale of the scenarios The steering variables 1. Global temperature Circulatie verandering Gematigd+ verandering Warm+ verandering + 1 C + 2 C Gematigd Warm Wereld Temperatuur niet wel Strength of west-circulation 2. Strength of seasonal mean west-circulation (not for z sea ) month
The production of the KNMI 06 scenarios
Regional climate change: downscaling GCM-grid box too coarse Global model Regional model
Regional Climate Modelling (RCM) High resolution GCM (50 20 km) 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
Precipitation extremes in summer (difference A2 CTL) Purpose of downscaling: extra spatial and temporal detail Mean; 90%; 95%; 99%; 99.5%; 99.9% more Danish Met. Institute less
Precipitation extremes in summer (difference A2 CTL) Mean; 90%; 95%; 99%; 99.5%; 99.9% more Danish Met. Institute less
Precipitation extremes in summer (difference A2 CTL) Mean; 90%; 95%; 99%; 99.5%; 99.9% ~10 times per summer more Danish Met. Institute less
Precipitation extremes in summer (difference A2 CTL) Mean; 90%; 95%; 99%; 99.5%; 99.9% ~5 times per summer more Danish Met. Institute less
Precipitation extremes in summer (difference A2 CTL) Mean; 90%; 95%; 99%; 99.5%; 99.9% ~annual wettest summer day more Danish Met. Institute less
Precipitation extremes in summer (difference A2 CTL) Mean; 90%; 95%; 99%; 99.5%; 99.9% ~shower exceeded once per 5 yrs more Danish Met. Institute less
Precipitation extremes in summer (difference A2 CTL) Mean; 90%; 95%; 99%; 99.5%; 99.9% ~shower exceeded once per 10 yrs more Danish Met. Institute less
Model predictions in number of wet days Difference A2 CTL winter summer About equal Reduced by 25-35%
Result: change in 2050 relative to 1990 Result: change in 2050 relative to 1990
Result: change in 2050 relative to 1990 mean temperature yearly coldest day With circulation change the coldest temperature changes more than mean
Result: change in 2050 relative to 1990 Nr of wet days strongly dependent on circulation change wet day frequency
Result: change in 2050 relative to 1990 Wet day mean precipitation dependent on global temperature rise mean precipitation
Result: change in 2050 relative to 1990 Extreme precipitation is more likely in a wetter climate daily precipitation exceeded 1/10yrs
Result: change in 2050 relative to 1990 annual maximum daily mean wind Windscenarios hardly show a significant change
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
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)
Tailored climate scenarios Specific use in water management requires tailoring Dutch Programme Climate Changes Spatial Planning co-funded a tailoring project Examples (not all from this project) High resolution time series of precipitation Ground water tables in the Netherlands Rhine discharge Closure of Maasland barrier
The production of the KNMI 06 scenarios
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)
30 25 20 obs W W+ W+ linear Generation of high resolution time series non-linear transformation introduces dry day and different changes for different intensities 15 10 n-lin > obs lin < obs 5 0 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 Julian Days n-lin < obs lin < obs precipitation (mm/day)
9.5 9.25 9 8.75 8.5 8.25 8 7.75 7.5 Effect on groundwater table (example) Oirschot (906) non-linear transformation has tendency to be wetter in wet episodes and drier in dry spells obs W W_linear W+ W+_linear 1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 Julian Days groundwater level to NAP (cm)
Groundwater tables in the Netherlands Current practice: detailed hydrological model is used to calculate high resolution ground water balance Climate change assessment needs long records: expensive! To enable affordable climate change assessment: can one construct a single reference year that reproduces proper reference climatological ground water product?
Groundwater tables in the Netherlands Result: a spatially and temporally varying factor is needed to relate a single year to a climatological mean Not all features of variability can be captured in a single year! optimally corrected single year (e.g. 1967) 30yr mean residual difference
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 Start of growing season: generally wetter Lowest water table during growing season: generally drier courtesy Timo Kroon, Franziska Keller ea
Assessment of impact of KNMI 06 scenarios on Rhine discharge Old WB21 scenarios New KNMI 06 scenarios
Assessment of impact of KNMI 06 scenarios on Rhine discharge old +1 and +2 new +1 and +2 (no circ)
Assessment of impact of KNMI 06 scenarios on Rhine discharge old +1 and +2 new +1 and +2 (no circ) new +1 and +2 (with circ)
Closure of Maasland-barrier: costly! Dependent on (simultaneous) high water level due to surge and Rhine discharge Rhine discharge ( 1000 m 3 /s) H vd Brink ea Sea level at Hoek v Holland (m)
Closure of Maasland-barrier: costly! Dependent on (simultaneous) high water level due to surge and Rhine discharge Closure return time (years) Rhine discharge ( 1000 m 3 /s) Sea level rise (m) H vd Brink ea Sea level at Hoek v Holland (m)
Final remarks Generic scenarios Designed to span a wide range of possible climate change, suitable for many applications Tailoring Process of tailoring is important for application in practice. Close multi-disciplinary cooperation is required Dry summers Particularly dry summer conditions gain additional attention in Dutch climate adaptation policy