1. Part I: Representation of the Effects of Sub- grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects of Soil Moisture on the Simulation of Surface Climate and Hydrology Jeremy Pal Filippo Giorgi, Raquel Francisco, Elfatih Eltahir

2. Part I: Representation of the Effects of Sub- grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects of Soil Moisture on the Simulation of Surface Climate and Hydrology

3. Subgrid Topography and Landuse Scheme ► Land surfaces are characterized by pronounced spatial heterogeneity that span a wide range of scales (down to 100s of meters). ► Topography and landuse exert a strong forcing on atmospheric circulations and land-atmosphere exchanges. ► Current climate models cannot capture the full range of scales, thus intermediate techniques can be used. 10-km 60-km

4. 360-kmTopography60-kmTopography10-kmTopography ► Coarse Domain:  ~250 grid points ► Medium Domain:  ~9,000 grid points ► Fine Domain:  ~325,000 grid points

5. 60-kmLanduse 10-kmLanduse 360-kmLanduse ► Coarse Domain:  ~250 grid points ► Medium Domain:  ~9,000 grid points ► Fine Domain:  ~325,000 grid points

6. General Methodology ► Define a regular fine scale sub-grid for each coarse scale model grid-box.  Landuse, topography, and soil texture are characterized on the fine grid. ► Disaggregate climatic fields from the coarse grid to the fine grid (e.g. temperature, water vapor, precipitation).  Disaggregation technique based on the elevation differences between the coarse grid and the fine grid. ► Perform BATS surface physics computations on the fine grid. ► Reaggregate the surface fields from the fine grid to the coarse grid. 60-km Mean Landuse and Elevation

7. Methodology: Disaggregation sg = subgrid; i,j = subgrid cell; overbar coarse grid T = near surface air temperature; h = topographical elevation GT = average atmospheric lapse rate = 6.5 °C/km Temperature disaggregated according to the subgrid elevation difference:Temperature disaggregated according to the subgrid elevation difference:

8. Methodology: Disaggregation Relative humidity is held constant (more or less).Relative humidity is held constant (more or less). sg = subgrid; i,j = subgrid cell; overbar coarse grid T = near surface air temperature; h = topographical elevation  T = average atmospheric lapse rate = 6.5 °C/km Temperature disaggregated according to the subgrid elevation difference:

9. Methodology: Disaggregation Relative humidity is held constant (more or less). Height, temperature, and moisture conserved.Height, temperature, and moisture conserved. –For example: sg = subgrid; i,j = subgrid cell; overbar coarse grid T = near surface air temperature; h = topographical elevation  T = average atmospheric lapse rate = 6.5 °C/km Temperature disaggregated according to the subgrid elevation difference:

10. Methodology: Disaggregation Relative humidity is held constant (more or less). sg = subgrid; i,j = subgrid cell; overbar coarse grid T = near surface air temperature; h = topographical elevation  T = average atmospheric lapse rate = 6.5 °C/km Temperature disaggregated according to the subgrid elevation difference: Height, temperature, and moisture conserved. –For example: Convective precipitation is randomly distributed over 30% of the gridcell [e.g. CCM; Kiehl et al 96]Convective precipitation is randomly distributed over 30% of the gridcell [e.g. CCM; Kiehl et al 96]

11. Methodology: Reaggregation ► The surface heat fluxes, temperature and humidity are reaggregated to the coarse grid after BATS computations are performed  For example, for the latent heat flux LH:

12. Numerical Experiments 10-km 15-km 60-km ► Simulation period: 1 Oct 1994 to 1 Sept 1995 ► Land Surface computations performed on subgrid.  CTL ► 60-km; no subgrid cells  EXP15 ► 15-km; 16 subgrid cells  EXP10 ► 10-km; 36 subgrid cells

13. Results: Temperature OBS (CRU)CTL OBS (CRU)CTL WINTER (DJF) SUMMER (JJA)

14. Results: Temperature WINTER (DJF) OBS (CRU)CTL SUMMER (JJA) OBS (CRU)CTL EXP15EXP10 EXP15EXP10

15. Results: Precipitation OBS (CRU)CTL OBS (CRU)CTL WINTER (DJF) SUMMER (JJA) OBS (Frei & Schär)

16. Results: Precipitation OBS (CRU) WINTER (DJF) CTL SUMMER (JJA) OBS (CRU)CTL EXP15EXP10 EXP15EXP10 OBS (Frei & Schär)

17. Results: Snow WINTER (DJF) CTL SPRING (MAM) CTL EXP15EXP10 EXP15EXP10 Station OBS

18. Results: Water Budget

19. Results: Energy Budget

20. Part I: Summary & Conclusions ► Fine scale topography and landuse variability can have a significant effect on surface climate. ► Better agreement of temperature, precipitation (summer) and snow with observations.  implies improved simulation of the seasonal evolution of the surface hydrologic cycle. ► Primary effects are likely to be due to topographic variability (not landuse). ► Our mosaic-type approach can provide an effective tool of intermediate complexity to bridge the scaling gap between climate models (both global and regional) and surface hydrologic processes.

21. In the works… ► Implement parameterization of subgrid scale effects on the formation of precipitation (both large-scale and convective). ► Apply disaggregation techniques for other variables (e.g. precipitation, radiation) 60-km Mean Landuse and Elevation 60-km

22. Part I: Representation of the Effects of Sub-grid Scale Topography and Landuse on the Simulation of Surface Climate and Hydrology Part II: The Effects of Soil Moisture on the Simulation of Surface Climate and Hydrology

23. Rainfall Anomalies (mm/d) June & July 1993 May & June 1988 Rainfall Anomalies (mm/d) ISWS Soil Saturation Time Series What role does soil moisture play in the prediction rainfall? What are the pathways and mechanisms responsible for the soil moisture-rainfall feedback?

24. Domain & Topography Analysis Domain Full Model Domain

25. 25MW Fixed Patch Experiment: Initial Root Zone Soil Moisture Midwest: 25MW Fixed Soil Moisture (25%) Interactive Soil Moisture (CTL) Storm Track Capping Inversion LLJ 25%

26. ► Decrease in the energy per unit depth of boundary layer via radiative effects ► Should decrease the likelihood and magnitude of rainfall of the region of the anomaly Boundary Layer Height Net Radiation Net Radiation 25MW-CTL 25MW-CTL 25MW-CTL Moist Static Energy 25MW-CTL Rainfall (U.S. only)

27. 500mb Zonal Winds 500mb Zonal Winds 25MW-CTL25MW-CTL 500mb Winds & Heights 500mb Winds & Heights CTL ► Decrease in convection via local feedbacks ► Anomalous high pressure ► Anomalous anticyclonic flow ► Increased descent and a northward stormtrack shift ► Changes in rainfall distribution

28. Storm Track Capping Inversion LLJ 75% 75SW Fixed Patch Experiment: Initial Root Zone Soil Moisture Southwest: 75SW Fixed Soil Moisture (75%) Interactive Soil Moisture (CTL)

29. 75SW Experiments 75SW-CTL Rainfall (U.S. only) 500mb Zonal Winds 500mb Zonal Winds 75SW-CTL

30. Local Soil Moisture-Rainfall Feedbacks A dry soil moisture anomaly A high pressure anomaly Less local rainfall (Pal& Eltahir,2001) A low pressure anomaly More local rainfall (Pal& Eltahir,2001) A wet soil moisture anomaly

31. (1)Dry anomaly (2)High pressure anomaly (3)Shift in Storm-track northward Remote Soil Moisture-Rainfall Feedbacks A soil moisture anomaly leads to a shift in the storm-track Pal and Eltahir (2003), QJRMS

32. (1)Wet anomaly (2)Low pressure anomaly (3)Shift in Storm-track southward Remote Soil Moisture-Rainfall Feedbacks A soil moisture anomaly leads to a shift in the storm-track Pal and Eltahir (2003), QJRMS

33. Precipitation (U.S. only) USHCN (Obs) CLMCTL 25%50%75%

34. Part II: Summary & Conclusions ► The feedbacks of soil moisture to the local climate can induce positive feedbacks to the large-scale circulation patterns.  Local soil moisture anomalies can potentially lead to drought- and flood-like conditions not only in the local region, but also in remote regions. ► An accurate representation of the distribution of soil moisture is crucial to accurately represent observed rainfall.  The spatial variability of soil moisture in North America appears to be an important in predicting rainfall.

35. Initial Root Zone Soil Moisture (June 25) Climatology 1988 1993

36. Additional Soil Moisture- Rainfall Mechanism Normal Storm Track Wet Soil Storm Track Dry Soil Storm Track