1. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Land-atmosphere interactions, the water cycle, and climate extremes Sonia I. Seneviratne, Edouard Davin, Peter Greve, Lukas Gudmundsson, Martin Hirschi, Brigitte Mueller, Boris Orlowsky, and Rene Orth Institute for Atmospheric and Climate Science, ETH Zurich, Switzerland sonia.seneviratne@env.ethz.ch WWOSC, August 17, 2014

2. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Land in the climate system Atmosphere OceansLand

3. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC T, P Land in the climate system Atmosphere OceansLand We are generally interested in weather and climate over land! Land climate is strongly affected by land processes in several regions

4. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Recent trends in temperature extremes (Seneviratne, Donat, Mueller, and Alexander, 2014, Nature Climate Change) Land area ratio affected by exceedant warm days (relative to 1979-2010 average) Temperature trends (ERA-interim, HadCRUT4)

5. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Recent trends in temperature extremes (Seneviratne, Donat, Mueller, and Alexander, 2014, Nature Climate Change) Land area ratio affected by exceedant warm days (relative to 1979-2010 average) Temperature trends (ERA-interim, HadCRUT4) Continued increase of measures of hot extremes despite apparent pause of global mean temperature

6. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC (Seneviratne, Donat, Mueller, and Alexander, 2014, Nature Climate Change) Land area ratio affected by exceedant warm days (relative to 1979-2010 average) Temperature trends (ERA-interim, HadCRUT4) Continued increase of measures of hot extremes despite apparent pause of global mean temperature Recent trends in temperature extremes

7. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Land water and energy balances PE Rn E SW in WaterEnergy H Radiative budget E=60%P E=50-60%Rn Variations of  : 0.1- 0.2 Evaporative cooling SW out

8. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Outline Introduction Soil moisture-temperature feedbacks Droughts Forcing of land surface albedo on temperature extremes Conclusions

9. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Coupling between soil moisture and evapotranspiration (Seneviratne et al. 2010, Earth-Science Reviews) Evaporative fraction (see also Budyko 1956)

10. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture-temperature feedbacks

11. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Global Land-Atmosphere Coupling Experiment (GLACE) – Phase 2 skill increase conditioned on strength of local initial soil moisture anomaly Extreme terciles all points Extreme deciles 16-30 days 31-45 days 46-60 days Forecast skill: r 2 with land ICs vs r 2 w/o land ICs Dates for conditioning vary w/location (Koster et al. 2010, GRL) Temperature forecasts: Skill from soil moisture (JJA) Extreme quintiles

12. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Temperature forecasts: Skill from soil moisture (JJA) GLACE-2: Skill increase in Europe: Effects up to 3-4 weeks (van den Hurk et al. 2012, Clim. Dyn.)

13. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Temperature forecasts: Skill from soil moisture (JJA) GLACE-2: Skill increase in Europe: Effects up to 3-4 weeks NB: Little effects within GLACE- 2 in regions beside N. America and Europe, but: Focus on JJA Focus on mean temperature (van den Hurk et al. 2012, Clim. Dyn.)

14. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Analysis for Southeastern Europe Quantile regression of %HD with 6- month SPI (Hirschi et al. 2011, Nature Geoscience) Impact of soil moisture on hot extremes Soil moisture-temperature feedbacks: Extreme events

15. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC (Mueller and Seneviratne 2012, PNAS) NHD: # hot days SPI: Standardized Precipitation Index Soil moisture-temperature feedbacks: Extreme events Analysis for hottest month at each location

16. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture-temperature feedbacks: Extreme events (Mueller and Seneviratne 2012, PNAS) Link to forecasting: conditional probability NHD: # hot days SPI: Standardized Precipitation Index

17. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Combined roles of soil moisture & circulation (Quesada et al. 2012, Nature Climate Change) European analysis: High percentage of hot days found for combination of 1) dry springs and 2) anticyclonic summer weather regimes

18. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Combined roles of soil moisture & circulation (Quesada et al. 2012, Nature Climate Change) European analysis: High percentage of hot days found for combination of 1) dry springs and 2) anticyclonic summer weather regimes

19. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Combined roles of soil moisture & circulation (Quesada et al. 2012, Nature Climate Change) European analysis: High percentage of hot days found for combination of 1) dry springs and 2) anticyclonic summer weather regimes Improved soil moisture initialization and modeling together with improved prediction of summer weather regimes can help forecasting extreme hot days NB: Both necessary but not sufficient conditions!

20. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Comparing sm-only based T forecast with ECMWF Thought experiment: How much skill for temperature forecasts can be obtained from soil moisture alone? 1)Simple water balance model (Koster and Mahanama 2012, JHM; Orth et al. 2013, JHM) Driven with observed forcing up to start date (i.e. optimal initial conditions) Driven with ECMWF subseasonal forecast after that (only atmospheric forcing) 2) Derive link between soil moisture anomalies and temperature anomalies from linear regression Compare with skill of ECMWF subseasonal forecast (Orth and Seneviratne 2014, Climate Dyn., publ. online)

21. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Comparing sm-only based T forecast with ECMWF (Orth and Seneviratne 2014, Climate Dyn., publ. online) Mean forecasts: Better skill (R 2 ) at week 4 for many catchments (i.e higher correlation of time series)

22. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Comparing sm-only based T forecast with ECMWF (Orth and Seneviratne 2014, Climate Dyn., publ. online) Mean forecasts: Better skill (R 2 ) at week 4 for many catchments (i.e higher correlation of time series) NB: with other measure of skill (continuous ranked probability skill scores, CRPSS), ECMWF forecast performs better (range of ensemble member better fit observations)

23. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture-temperature feedbacks: Remote sensing data (Mueller and Seneviratne 2012, PNAS) (Hirschi et al. 2014, Remote Sens. Env., in press) Similar hot spots with remote-sensing based estimates of soil moisture (microwave, ESA CCI product), but weaker signal Correlation NHD E-Int and preceding 3-month soil moisture

24. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture-temperature feedbacks: Remote sensing data Lower signal in remote sensing product: Soil moisture variability is underestimated under dry conditions when using only surface conditions In-situ observations (Hirschi et al. 2014, Remote Sens. Env., in press)

25. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Outline Introduction Soil moisture-temperature feedbacks Droughts Forcing of land surface albedo on temperature extremes Conclusions

26. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Trends in global drought Impact of formulation of potential evapotranspiration for drought trends over land (Sheffield et al. 2012, Nature) Thornthwaite Ep Penman- Monteith Ep

27. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Using Budyko framework to assess errors in land datasets (Budyko 1956, Fu et al. 1981)

28. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Using Budyko framework to assess errors in land datasets (Greve et al., in press) Large uncertainty in evapotranspiration! Issues with soil moisture limitation?

29. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture memory (R. Orth, ETH Zurich)

30. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture memory Additional skill (Orth et al. 2013, JGR) Idealized soil moisture forecasts in Switzerland (mean performance in 22 catchments)

31. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Soil moisture memory Additional skill (Orth et al. 2013, JGR) Idealized soil moisture forecasts in Switzerland (mean performance in 22 catchments) Using forecast to drive model improves predictive skill for soil moisture beyond the range in which the forecast has actual skill! (propagation through soil moisture memory)

32. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Outline Introduction Soil moisture-temperature feedbacks Droughts Forcing of land surface albedo on temperature extremes Conclusions

33. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Changes in albedo induced by agricultural management (Davin et al. 2014, PNAS) Differences in surface albedo from no-till farming

34. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Changes in albedo induced by agricultural management (Davin et al. 2014, PNAS) Preferential cooling of warmer extremes from surface albedo forcing

35. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Changes in albedo induced by agricultural management (Davin et al. 2014, PNAS) Overall effect of no-till farming (also including evaporation impacts): Strong preferential cooling of hot extremes!

36. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Changes in albedo induced by agricultural management (Davin et al. 2014, PNAS) Overall effect of no-till farming (also including evaporation impacts): Strong preferential cooling of hot extremes! These effects are not considered in climate and weather models!

37. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Outline Introduction Soil moisture-temperature feedbacks Droughts Forcing of land surface albedo on temperature extremes Conclusions

38. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Conclusions Land surface processes and land-atmosphere interactions play an important role for a number of extremes (temperature, droughts)

39. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Conclusions Land surface processes and land-atmosphere interactions play an important role for a number of extremes (temperature, droughts) Soil moisture information can improve weather forecasts: –Initialization of soil moisture (compare performance when using offline land model estimate vs remote sensing)

40. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Conclusions Land surface processes and land-atmosphere interactions play an important role for a number of extremes (temperature, droughts) Soil moisture information can improve weather forecasts: –Initialization of soil moisture (compare performance when using offline land model estimate vs remote sensing) Non-linear effects impacting extremes differently from mean climate: These should be validated separately (partly different driving processes) –Potential for more interaction between weather and climate communities (e.g. also between WCRP and WWRP)

41. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC

42. Sonia Seneviratne / IAC ETH Zurich 17.08.2014 WWOSC Recent trends in temperature extremes (Seneviratne, Donat, Mueller, and Alexander, 2014, Nature Climate Change)