1. 7 oktober 2009 Challenge the future Delft University of Technology Clouds and Climate KNMI Climate Course 2011 A. Pier Siebesma KNMI & TU Delft Multiscale Physics Department The Netherlands Contact: siebesma@knmi.nl

2. 2 Climate modeling Clouds play a crucial role in weather and climate Hydrological cycle Radiation balance

3. 3 Climate modeling Central Questions: How do clouds respond to a perturbed climate and affect this climate (feedback)? Perturbations: Increased Temperature (due to enhanced Greenhouse Gases) Increased aerosol amounts

4. 4 Climate modeling Outline What are clouds and how do they form? Cloud climatology Clouds and Radiation Clouds in Climate models Clouds in our changing Climate

5. 5 Climate modeling 1. What is a cloud and how do they form?

6. 6 Climate modeling What is a Cloud? “just” water ! 28-06-2006 ; 12:00 Amsterdam

7. 7 Climate modeling Saturation specific humidity q sat Clausius-Clayperon Because of the presence of Cloud Condensation Nuclei (CCN’s) in the atmosphere condensation takes place if q v > q sat (p,T) Usually through cooling that results from rising motion. CCN’s are hygroscopic aerosols (salt, dust, etc)

8. 8 Climate modeling Rising air cools with 1 K per 100m ……….. Until it becomes so cold that it starts to condensate… and a cloud is born!!! Cooling through rising air

9. 9 Climate modeling 2. What makes air to rise?

10. 10 Climate modeling 1. Orography Lenticularis above Mount Etna seen from Taormina, Sicily Italy.

11. 11 Climate modeling 2. Convection The sun heats the soil so that….. Thermals are formed…. that rise because of buoyancy…. And a cloud forms as a wig on top of an invisible man 24-07-2006 12:30 Amsterdam: cumulus humilis or “fair weather” cumulus

12. 12 Climate modeling Humidity condensates into cloud water….. And produces latent heat Which serves as onboard fuel that allows the cloud to rise further….. With ~5 m/s…. Until the cloud is stopped by a temperature inversion. 24-07-2006 Amsterdam: cumulus mediocris. 15:30 Wolken basis (~1km) Wolken top (~3 km) But what if the cloud breaks through the inversion?????????

13. 13 Climate modeling Then the cumulus can rise to the tropopause and reach the stage of a socalled cumulonimbus With vertical velocities over 10m/s Up to a height of 5~15 km So that the water becomes ice which gives the fluffy appearance of the top of the cloud and strong precipation is on the way 08-02-2006 Amsterdam: cumulonimbus. Moist Convection occurs all over the globe but is predominant in the tropics and over the subtropical oceans. ijs Wolken top (5~8 km)

14. 14 Climate modeling 3. Large Scale Lifting through fronts Occuring at mid-latitudes } }

15. 15 Climate modeling Different Cloud Types

16. 16 Climate modeling 3. A global view on clouds amount and cloud dynamics

17. 17 Climate modeling Clouds as seen by geostationary satellites (infrared) July 1994

18. 18 Climate modeling Clouds as seen by geostationary satellites (infrared) January 1994

19. 19 Climate modeling Monthly global cloud cover for the period 1983-2008 (source ISCCP) Mean global cloud cover : ~66% No clear trend observed yet….

20. 20 Climate modeling 4. Importance Clouds for Climate

21. 21 Climate modeling Radiative Effects of Clouds 2 main effects: Shortwave Reflection (cooling) “umbrella effect” Longwave Emission (warming) “blanket effect” Top of the atmosphere : planetary albedo = 0.3

22. 22 Attacking the cloud feedback problem Cloud Radiative Forcing Clouds have a net cooling effect Many factors matter: Cloud amount: a Cloud top height: T c Cloud optical depth:  cld Strong correlation between cloud forcing and low clouds ! 31 W/m2 -44 W/m2 -13 W/m2

23. 23 Attacking the cloud feedback problem Latent Heating by Cumulus Convection

24. 24 Climate modeling 5. Clouds in Climate Models

25. 25 Climate Modelling 1. How did I get here? ~1    m - 1m ~10 7 m~10 5 m ~10 3 m The planetary scale Cloud cluster scale Cloud scale Cloud microphysical scale The climate system : A truly multiscale problem

26. 10 m100 m1 km10 km100 km1000 km10000 km turbulence  Cumulus clouds Cumulonimbus clouds Mesoscale Convective systems Extratropical Cyclones Planetary waves Large Eddy Simulation (LES) Model Cloud System Resolving Model (CSRM) Numerical Weather Prediction (NWP) Model Global Climate Model No single model can encompass all relevant processes DNS mm Cloud microphysics

27. 27 Climate modeling Grid-box size is limited by computational capability Processes that act on scales smaller than our grid box will be excluded from the solutions. We need to include them by means of parametrization (a largely statistical description of what goes on “inside” the box). Similar idea to molecules being summarized statistically by temperature and pressure, but much more complex! Parametrization

28. 28 Climate modeling Examples for processes that need to be parametrized in the atmosphere Parametrization

29. 29 Climate modeling As parametrizations are simplifications of the actual physical laws, their (necessary) use is an additional source of model uncertainty. Parametrization

30. 30 Climate modeling 6. Clouds in a Future Climate

31. 31 Climate modeling Uncertainties in Future Climate model Predictions with different climate models 2.5-4.3°C IPCC 2007 PastFuture Present 1900

32. 32 Climate modeling Climate Model Sensitivity  temperature  radiative forcing Water vapour With feedbacks: Snow albedo clouds

33. 33 Climate modeling Dufresne & Bony, Journal of Climate 2008 Radiative effects only Water vapor feedback Surface albedo feedback Cloud feedback Cloud effects “remain the largest source of uncertainty” in model based estimates of climate sensitivity IPCC 2007 2XCO 2 Scenario for 12 Climate Models

34. 34 Climate Modelling Primarily due to marine low clouds “Marine boundary layer clouds are at the heart of tropical cloud feedback uncertainties in climate models” (duFresne&Bony 2005 GRL) Stratocumulus Shallow cumulus

35. 35 Climate Modelling Definition: temperature change resulting from a perturbation of 1 Wm -2 Radiative forcing for 2XCO2 3.7 Wm -2 (  R) Temperature response of climate models for 2XCO2 2~4.3 K (  T) Climate model sensitivity : 0.5-1.2 K per Wm -2 (  T/  R) The climate model sensitivity is not (very) dependent on the source of the perturbation (radiative forcing) Main reason for this uncertainty are the representation of (low) clouds Reducing uncertainty of climate models can only be achieved through a more realistic representation of cloud processes and is one of the major challenges of climate modelling Climate Model Sensitivity

36. 36 Climate modeling 7. Clouds and Aerosols

37. 37 Climate modeling Definition: "Radiative forcing is a measure of the influence a factor (think CO2) has in altering the balance of incoming and outgoing energy in the Earth-Atmosphere system and is an index of the importance of the factor as a potential climate change mechanism. In this report (IPCC 2007) radiative forcing values are for changes relative to preindustrial conditions defined at 1750 and are expressed in watts per square meter (W/m2).“ What is Radiative Forcing? Remark: We have just calculated the radiative forcing for CO2 Other important radiative forcings that are quantified in the IPCC report:

38. 38 Future Climate Radiative Forcing Components (Source IPCC 2007)

39. 39 Future Climate Droplet concentration and Radiation: "Indirect" aerosol effect

40. 40 Future Climate Direct and Indirect Aerosol effects

41. 41 Future Climate More info : Pier Siebesma (siebesma@knmi.nl) ; siebesma@knmi.nlsiebesma@knmi.nl