Modelling of climate and climate change

1. Modelling of climate and climate change Čedo Branković Croatian Meteorological and Hydrological Service (DHMZ) Zagreb cedo.brankovic@cirus.dhz.hr

2. Outline 1. What is climate and what is climate change 2. Evidence of existing climate change 3. Climate models and climate modelling - validation - climate change and human impact - future projections - uncertainties 4. Climate change and forest fire risk

3. What is climate? * Climate of an area is an aggregate of expected values of meteorological parameters * It is based on measurements and observations over long periods (minimum 30 years) * Climate is influenced by dynamics and interactions of the components of climate system – atmosphere, hydrosphere, cryosphere (ice cover), soil, biosphere (vegetation) * “External” manifestation of complex and non-linear processes * Elements of climate: solar insolation, air temperature, atmospheric pressure, speed and direction of wind, moisture, cloudiness, precipitation, evaporation, snow cover, …

4. What is climate change? * Significant and permanent changes in statistical distribution of weather phenomena (on time scales of decades to millions of years) * Variation (of weather phenomena) at shorter time scales is not climate change; they are inherent to climate system and are the consequence of atmosphere’s chaotic nature * Climate change occurs because of the change in Earth’s energy balance - natural - variations in Earth’s orbit (Milanković cycles), volcanic eruptions (aerosols), variations in solar radiation, tectonics (!) - anthropogenic - deforestation, land use, burning of fossil fuels, … - they can cause an increase in the level of the greenhouse gases, aerosols, damage ozone layer

5. Evidence of climate change - global * From measurements * Change relative to 1961-1990 Source:IPCC (Intergovernmental Panel on Climate Change) report(2007)

6. Evidence of climate change - local Crikvenica summer season 1952-2010 1981-2010 * Trends in air temperature at the Croatian Adriatic stations (°C/10 yr) Source:Č. Branković, I. Güttler, M. Gajić-Čapka Climate Dynamics (2013)

7. Climate models and climate modelling * Atmosphere is fluid governed by laws of physics (hydrodynamics and thermodynamics) but also chemistry; they can be described in the form of mathematical nonlinear partial differential equations * When adapted for computational purposes (computers), the system of equations is called (numerical) atmospheric or climate model * Climate models are essentialfor estimates of climate change; only models can “predict” future state of the atmosphere and climate; however ... * Climate models are only approximations of real climate system because of - lack of knowledge of all the processes involved - discretisation of analytical equations * Complex climate models require huge computational resources and their development depends greatly on development of computer technology (super-computers) * Climate models can be broadly divided to - global models – cover the whole globe, relatively coarse resolution - regional models – cover a region, much finer resolution

8. Climate models and climate modelling - validation * Climate simulations for periods with available observational data * Estimates of model systematic errors influence our confidence in a model ECHAM5/MPI-OM vs. CRU Total precipitation over land during winter, 1961-1990 global model observations Source:Č.Branković, L.Srnec, M.Patarčić Climatic Change (2010) RegCM vs. CRU (errors) Air temperature at 2 m, winter 1961-1990 Source:Č.Branković, M.Patarčić, I.Güttler, L.Srnec Climate Research (2012)

9. Climate models and climate modelling – human impact * Human impact is most likely crucial for atmospheric warming (because of increased concentration of greenhouse gases) all factors: natural and human observed change only natural factors Source: www.meted.ucar.edu

10. individual simulation certainty (!?) natural fluctuation Climate models and climate modelling – future projections European average temperature anomaly: * Certainty in climate trend * Possible development(s) * Variations can obscure trend Source: Hawkins, Weather (2011)

11. Climate models and climate modelling – what scenario? * We do not know future concentrations of GHGs * Depend on socio-economic development strong forcing weak forcing Changes are not uniformly distributed Source: IPCC (2013)

12. Climate models and climate modelling - uncertainties * Various uncertainties related to modelling of climate and climate change Main sources of uncertainties: * Natural: internal variability of climate system (unpredictable!) - natural fluctuation can mask future (weak) climate changes * Scientific and technical: imperfections in climate modelling - our limited knowledge of climate system - inadequacies of computer models (approximations) - parameterisation of unresolved processes - turbulence, cloud microphysics ... (various models may give different “answers” to the same forcing) * Socio-economic: scenario uncertainty - lack of knowledge of future concentrations of greenhouse gases - depends on Earth’s population, industrial & technological development... Source: Hawkins and Sutton, Bull.Amer.Meteor.Soc. (2009) Cartoon movie on: www.climrun.eu

13. Climate change and forest fire risk – current climate Data provided by Dr. Christos Giannakopoulos from National Observatory of Athens (FP7 project Clim-Run) * Forest Fire Weather Index (FWI): temperature, air relative humidity, 10m wind speed and 24-h accumulatedprecipitation * Divided into fire danger classes: low 0–7, medium 8–16, high 17–31, extreme > 32 *Daily output data from three RCMs from ENSEMBLES project at a 25 km x 25 km resolution *Present day simulations 1961-1990 (control period) and future projections for 2021-2050 (near future) and 2071-2100 (distant future). ~30 ~15

14. Climate change and forest fire risk – future projections Change: 2021-2050 minus 1961-1990 +15 +5 Change: 2071-2100 minus 1961-1990 +35 +15