Evaluation of CLMVIC in Global and Regional Simulations

Transcription

1 Evaluation of CLMVIC in Global and Regional Simulations L. Ruby Leung, Maoyi Huang, and Hongyi Li Pacific Northwest National Laboratory 1

2 Merging of CLM and VIC Surface- and groundwater interactions Saturation excess runoff Infiltration excess runoff ARNO baseflow curve Hydraulic redistribution Interactions of water movement between the root system and soil porous media

3 Runoff parameterizations CLM Physically based TOPMODEL Assumptions: High resolution topographic data are available Subsurface flow is topographically driven A quasi-steady state to approximate saturated zone dynamics Recharge to groundwater is spatially uniform Assumptions are invalid over flat terrain or arid regions VIC Conceptual Limited assumptions: land surface, and therefore surface runoff generation, is heterogeneous Subsurface flow is a nonlinear function of deeplayer water availability Calibration of parameters are recommended 3

4 Approach CLM and CLMVIC are compared and evaluated at different spatial scales: global, large river basin, catchment Global simulations ( ; 0.9 o x1.25 o ) Forcing: Qian et al Land cover: NCAR 0.5 o Three CLMVIC simulations have been performed: DEF: Default VIC parameters (b, Dsmax, Ds, and Ws) CAL: Calibrated VIC parameters from Princeton for GLDAS SUR: Calibrated b surface runoff parameter, others default North American simulations ( ; 1/8 o x1/8 o ) Forcing: NLDAS2 Land cover: PNNL 0.05 o 4

5 Summer LH ( ) CLM CLMVIC-DEF CLM CLMVIC-CAL CLM CLMVIC-SUR CLM 5

6 Summer total runoff ( ) CLM CLMVIC-DEF CLM CLMVIC-CAL CLM CLMVIC-SUR CLM 6

7 Global mean LH and total runoff LH Global mean LH Difference Runoff Runoff CLMVIC-CAL CLMVIC-SUR CLMVIC-DEF CLM CLMVIC-CAL CLM CLMVIC-SUR CLM CLMVIC-DEF CLM 7

8 Global mean surface and subsurface runoff Global mean Surface runoff Surface runoff Difference Subsurface runoff Subsurface runoff CLMVIC-CAL CLMVIC-SUR CLMVIC-DEF CLM CLMVIC-CAL CLM CLMVIC-SUR CLM CLMVIC-DEF CLM 8

9 Comparison over MOPEX basins (Annual LH) 9

10 Mean annual LH over MOPEX basins Mean latent heat ( ) Latent heat (W/m 2 ) CLM (50.6) CLMVIC (48.1) NOAH (57.0) VIC (62.1) MOSAIC (80.1) 1:1 line MODIS (46.2) MODIS latent heat (W/m 2 ) 10

11 Mean annual runoff over MOPEX basins 1,200 Mean annual total runoff 1,000 Model simulation (mm) CLM (400) CLMVIC (427) NOAH (458) VIC (504) MOSAIC (438) 1:1 USGS line (403) ,000 1,200 USGS observation (mm) 11

12 Mean annual surface runoff over MOPEX basins 600 Mean annual surface runoff 500 Model simulation (mm) CLM (169) CLMVIC (88) NOAH (79) VIC (259) MOSAIC (289) 1:1 USGS line (133) USGS observation (mm) June 8, 2012 DRAFT 12

13 Mean annual subsurface runoff over MOPEX basins 1,200 Mean annual subsurface runoff 1,000 Model simulation (mm) CLM (231) CLMVIC (338) NOAH (380) VIC (244) MOSAIC (148) 1:1 USGS line (269) ,000 1,200 USGS observation (mm) 13

14 Comparison over 9 selected MOPEX basins WA ID NY North CA MO VA South CA TX FL 14

15 Summary Both CLM and CLMVIC produce reasonable simulations of LH and runoff comparable to or better than other NLDAS simulations Structural differences in the TOPMODEL vs VIC runoff parameterizations can lead to differences in global mean LH and runoff by 5 10% annually Using default and previously calibrated parameters, the VIC runoff parameterizations simulate much higher subsurface runoff because CLM has a deeper soil column recalibration of CLMVIC is necessary The ratio of surface to subsurface runoff and runoff timing available from MOPEX and other datasets are useful for constraining/calibrating VIC runoff parameters Ongoing research to relate VIC parameters to physical quantities Next: Evaluate the combined VIC runoff and groundwater parameterizations in CLM and the coupled CLM - MOSART 15

16 Backup Slides June 8, 2012 DRAFT 16

17 CLMVIC-SUR CLM (summer) Surface runoff Subsurface runoff Latent heat Terrestrial water storage 17

18 Comparison over 9 selected MOPEX basins WA ID NY North CA MO VA South CA TX FL 18

19 Comparison over 9 selected MOPEX basins WA ID NY North CA MO VA South CA TX FL 19

20 Coupling CLM and MOSART CLM-MOSART driven by NLDAS2 at 1/8 o Developed global hydrography data at 6 resolutions (2, 1, ½, ¼, 1/8, 1/16 degree) DRAFT 20

21 River discharge in large river basins Amazon Congo Yangtze Mississippi Yenisey Mekong OBS CLMVIC-CAL CLMVIC-DEF CLM 21

22 NLDAS simulations: Summer LH ( ) CLM CLMVIC VIC MODIS 22