1. An empirical formulation of soil ice fraction based on in situ observations Mark Decker, Xubin Zeng Department of Atmospheric Sciences, the University of Arizona CCSM Land/BGC, March 28, 2006, Boulder (GRL 33, L05402, doi:10.1029/2005GL024914, 2006)

2. Outline Introduction –Purpose, Motivation, Fundamentals, General Model Description Dataset Overview Methodology –Calculation of ice fraction Parameterization Comparison –ECMWF, NCEP Noah, Proposed Offline Simulation Results

3. Purpose In situ soil water and temperature observations Derive a relation between soil ice and temperature for use in climate and weather prediction Compare new and current parameterizations Test the sensitivity of CLM

4. Motivation Why be concerned with frozen soil water? –Water ice transition alters various time scales Diurnal –Latent Heat release Seasonal –Infiltration of Spring Runoff

5. Fundamentals Soil water doesn’t freeze at 0 o Celsius? –Dissolved salts –Capillary forces –Forces between minerals and soil water –Heterogeneous Composition

6. Datasets Various sources –CEOP CAMP –GEWEX GAME –National Snow Ice Data Center Data from various climate regimes

7. Datasets SiteLonLat Depths (cm) Dates AK Shrub 64.9 N 164.7 W 16,269/2000-9/2001 AK Woodland 64.9 N 163.7 W 16,439/2000-9/2001 AK Forest 64.9 N 163.7 W 15,319/2000-9/2001 AK Tundra 70.4 N 148.5 W 239/1999-8/2001 Mongolia Grass 46 N 107 E 1510/2002-10/2003 Siberia Tundra 71.6 N 128.9 E 1010/2000-10/2001

8. Observations

9. Methodology Assume total soil moisture constant –  i =  t –  l Define –  s the Saturated Volumetric Moisture  s the Saturated Volumetric Moisture –10 km soil composition data –CLM formulation

10. Observed f i

11. Current Formulations ECMWF T > T frz + 1 T frz - 3 < T < T frz +1 T < T frz - 3  cap = 0.323 m 3 /m 3

12. Current Formulations Noah If divergent c k =0 then solved explicitly CLM3 T < T frz T >T frz T < T frz

13. Modeled f i vs. Observations Site t/st/st/st/sobsECMWFNoah AK Shrub 16 cm 0.9660.7620.7080.821 AK Shrub 26 cm 0.8220.8680.8320.801 AK Wood 16 cm 0.8821.0000.7760.810 AK Wood 43 cm 0.9020.9120.7570.813 AK Forest 15 cm 0.9440.8380.7760.818 AK Forest 31 cm 0.9020.7950.7570.813 AK Tundra 1999 0.9550.7520.7170.820 AK Tundra 2000 0.9640.7430.7100.821 AK Tundra 2001 0.9720.7950.7040.822 Mongolia Grass 0.2440.1501.0000.527

14. Proposed Formulation Derived to capture observed trends rapid increase of  i /  t to a value greater than 0.8 as T drops below T frz when  t /  s is greater than 0.8  i /  t increases more slowly as T decreases for small  t /  s Partially based on Noah formulation  and  are adjustable parameters Chosen as 2 and 4 respectively

15. Comparison Noah b = 4.5 Noah b = 5.5 Noah b = 4.5 c k =0 Noah b = 5.5 c k =0 ECMWF Proposed

16. Observations vs Proposed

17. Sensitivity of CLM Offline NCEP Reanalysis Forcing T-42 Resolution 20 Year run cycling 1998 Model Defined Initial Condition Only Soil Ice Calculation Was Altered

18. Results ECMWF-Control Sensible Heat Flux Latent Heat Flux Ground Temperature

19. Results Noah-Control Sensible Heat Flux Latent Heat Flux Ground Temperature

20. Results Proposed-Control Sensible Heat Flux Latent Heat Flux Ground Temperature

21. Results Proposed F i Proposed F i Difference Proposed-Control

22. Summary of Results All Three: –Showed a reduction in ground temperature –Drying of the soil column –Reduction in sensible heat flux –Increase in ground heat flux to balance the change in sensible –Reduction in latent heat flux The proposed formulation had a larger magnitude and extent of all these changes

23. Summary In situ data used to –Calculate ratio of volumetric ice content to total moisture content versus temperature –Evaluate current model formulations –Derive a new empirical formulation Sensitivity of CLM tested –Reduction in ground temperature –Lowering of ice fraction

24. Derivation of a New Maximum Snow Albedo Dataset Using MODIS Data M.Barlage, X.Zeng, H.Wei, K.Mitchell; GRL 2005

25. Motivation Maximum snow albedo is used as an end member of the interpolation from snow- to non-snow covered grids Current dataset is based on 1-year of DMSP observations from 1979 Current resolution of 1° Create new dataset using 4+ years of MODIS data with much higher resolution

26. Raw MODIS Albedo Data Tucson: little variation; no snow Minnesota: cropland; obvious annual cycle Canada: annual snow cycle; little summer variation Moscow: some cloud complications

27. How can you be sure it’s snow? NDSI: Exploiting the differences in spectral signature between visible and NIR albedo.

28. NDSI and NDVI

29. Final 0.05° Maximum Snow Albedo

30. Comparison with RK 0.05deg MODIS RK Figure 5

31. High-resolution Improvements

32. Application of MODIS Maximum Snow Albedo to WRF-NMM/NOAH WRF-NMM Model: 10min(0.144°) input dataset converted from 0.05° by simple average; model run at 12km; initialized with Eta output; Winter simulation: 24hr simulation beginning 12Z 31 Jan 2006

33. Comparison of MODIS Maximum Snow Albedo with CCSM Structure of CCSM maximum albedo is similar to MODIS maximum snow albedo Albedo of boreal regions is high compared to MODIS Albedo of high latitude open shrub/tundra is low compared to MODIS