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Recent Results and Near-Future Planned Changes for the Noah LSM at NCEP

Recent Results and Near-Future Planned Changes for the Noah LSM at NCEP. Ken Mitchell, Mike Ek, Helin Wei, Vince Wong, Youlong Xia, Rongqian Yang, Jesse Meng, Yihua Wu, Weizhong Zheng Unified Noah LSM Development Workshop NCAR 25-26July 2007.

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Recent Results and Near-Future Planned Changes for the Noah LSM at NCEP

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  1. Recent Results and Near-FuturePlanned Changes for the Noah LSM at NCEP Ken Mitchell, Mike Ek, Helin Wei, Vince Wong, Youlong Xia, Rongqian Yang, Jesse Meng, Yihua Wu, Weizhong Zheng Unified Noah LSM Development Workshop NCAR 25-26July 2007

  2. Strategic Issues of this Noah LSM Workshop(for later workshop reference: not subject of this talk) • Migrating all Noah developers to “Unified Noah” in public WRF Repository • Centralized “version control” Noah software • Migrating to ESMF and LIS • Maintaining ESMF compatibility in WRF repository • Coordinating Noah development paths • Using new satellite-derived land surface fields • “Strategic” (major) Noah physics improvements • See next frame for examples • “Tactical” (modest) Noah physics improvements • This is emphasis of remainder of this talk and emphasis of current Noah upgrades in NCEP Land Team

  3. Strategic (major) improvements to Noah physics:often by collaborators outside of NCEP and NCAR(not subject of this talk) • Groundwater state and Topmodel approach (U. Texas) • Multi-layer snowpack (U. Texas) • Multi-layer vegetation canopy (U. Texas) • Ball-Berry canopy resistance (Purdue U.) • Snow albedo treatment (U. Arizona) • Irrigation treatment (NASA HSB) • Van Genuchten soil hydraulics (NASA HSB) • Spatially varying soil layer thickness • Unified surface layer treatment (over land) • Others (TBD at this workshop)

  4. Recent Results and Plans for Noah LSM at NCEP:Outline of Remainder of Talk • GLDAS-LIS/Noah: Jesse Meng • T126 and T382 • Component in next NCEP Global Reanalysis • Climate Forecast System (CFS):Rongqian Yang • Impacts of Noah and T126 GLDAS • Global Forecast System (GFS):Helin Wei, Weizhong Zheng • Impact of T382 GLDAS • Impact of new weekly realtime global vegetation fraction (GVF) • Surface layer scheme: Zot changes • N. American WRF model (NAM): Mike Ek, Vince Wong • Unified Noah: Impacts • Surface layer scheme: Zot changes • NLDAS: Youlong Xia, Helin Wei • improve Noah physics (seasonal LAI, canopy resist., snow albedo, sfc layer, infiltration) • Add seasonal prediction capability (with U. Washington and Princeton U.) • Hurricane WRF Model (HWRF): Yihua Wu • Replace surface slab model with Noah LSM • PILPS: • San Pedro (Luis Bastidas) and LBA (U. Texas/Yang & Niu) • Joint Center for Satellite Data Assim (JCSDA): Weizhong Zheng • New satellite land surface fields (mostly MODIS) • Land surface skin temp (LST) and land surface emissivity

  5. Choice ofLand Model CFS/Noah CFS/OSU Choice of LandInitial Conditions GR2/OSU GR2/OSU (CONTROL) GLDAS/Noah GLDAS/Noah Climo “GR2” denotes NCEP/DOE Global Reanalysis 2 CFS Land Experiments: 4 configurationsLand Experiments of T126 CFS with CFS/Noah and CFS/OSU

  6. CFS Summer-Season Land Experiments Objective:Demonstrate Impact on CFS of: A) new land model (Noah LSM vs OSU LSM)B) new land initial conditions (GLDAS vs GR2) • 25-year (1980-2004) 10-member 6-month T126 CFS runs ( GFS-OP3T3, MOM-3 ) • Four configurations of T126 CFS: • A) CFS/OSU/GR2: - OSU LSM, initial land states from GR2 (CONTROL) • B) CFS/Noah/GR2: - Noah LSM, initial land states from GR2 • C) CFS/Noah/GLDAS: - Noah LSM, initial land states from T126 GLDAS/Noah • D) CFS/Noah/GLDAS-Climo: - Noah LSM, initial land states from GLDAS/Noah climo • Initial conditions: 00Z daily from Apr 19-23 29,30, and May 1-3 Key Theme From Results that Follow: Configuration B is clearly the worst configuration for CONUS JJA precip

  7. Soil Moisture Comparison:T126 GLDAS/Noah vs. T62 Global Reanalysis-2/OSU

  8. Monthly Time Series (1985-2004) of Area-mean Illinois 2-meter Soil Moisture [mm]:Observations (black), GLDAS/Noah (purple),GR2/OSU (green) Total Climatology Anomaly The climatology of GLDAS/Noah soil moisture is higher and closer to the observed climatology than that of GR2/OSU, while the anomlies of all three show generally better agreement with each other (though some exceptions)

  9. GLDAS/Noah (top) versus GR2/OSU (bottom)2-meter soil moisture (% volume) May 1stClimatology 01 May 1999Anomaly Top: observed 90-day Precipitation Anomaly (mm) valid 30 April 99 Bottom: Climatology GLDAS/Noah GLDAS/Noah GR2/OSU GR2/OSU Left column: GLDAS/Noah soil moisture climo is generally higher then GR2/OSU Middle column: GLDAS/Noah soil moisture anomaly pattern agrees better than that of GR2/OSU with observed precipitation anomaly (right column: top)

  10. GLDAS/Noah (top row) versus GR2/OSU (bottom row)2-meter soil moisture (% volume): GLDAS/Noah values are higher Climatology (left column) is from 25-year period of ~1981-2005)May 1stClimatology01 May 1999Anomaly GLDAS/Noah GLDAS/Noah GR2/OSU GR2/OSU

  11. JJA Precip Correlation Skill w Different LSMs and ICs Noah/ GLDAS Noah/ GR2 Worst OSU/ GR2 Noah/ GLDAS Climo 10 Members each case (same initial dates)

  12. JJAPrecip Correlation Skills South America Noah/ GLDAS Noah/ GR2 Best Noah/ GLDAS Climo OSU/ GR2

  13. JJA Mean SST Correlation Skill w Different LSM/ICs Globally Noah/ GR2 Noah/ GLDAS Noah/ GLDAS Climo OSU/ GR2 10 Members each case (same initial dates)

  14. Realtime T382 GLDAS/Noah System: dew. Daily execution. Software: LIS (Land Information System) Land surface model: Noah (as in operational GFS/GDAS) Forcing: GDAS hourly sfluxCMAP precip (1-7 days behind realtime) Output: Global land states validate at 00z. GLDAS-based gdas1.t00z.sfcanl

  15. CONUS CPC Precip Anomaly http://www.cpc.ncep.noaa.gov/cgi-bin/anom_realtime.sh

  16. CONUS GDAS vs CMAP precip Up to 50 mm differences in 30-day precip accumulation of 200 mm.

  17. CONUS GDAS/SMC

  18. CONUS LIS/SMC – GDAS/SMC

  19. Experiments: GFS/GLDAS: 31 static 6-day T382 forecasts with GLDAS/Noah land states as initial conditions Period: May 4-June 3, 2007 The Impact of using GLDAS/Noah initial land states on GFS Forecasts(T382 GFS Static Runs)

  20. Hypothesis: GDAS tends to overestimate precip over eastern half of CONUS in warm season-->wet soil moisture-->high evaporation-->cool temperature With CMAP precip in T382 GLDAS: less precip over east half of CONUS-->lower soil moisture-->lower evaporation-->warmer temperature

  21. As in previous slide, but for CONUS

  22. Daytime (18-21h) 40-100 cm Soil Moisture averaged from 20070511 to 20070610 tested GFS – ops GFS

  23. Mean Daytime (18-21h) Surface Latent Heat Flux (W/m**2) from 20070511 to 20070610 tested GFS – ops GFS

  24. Threat Score Bias Valid period: 20070507-20070603 CONUS: Precip scores 12-36h 07 May – 03 Jun

  25. West CONUS East CONUS

  26. New NESDIS fields of weekly realtime global green vegetation fraction (GVF) and their impact on T382 GFS forecasts GVF Data Set: (i) Old climatology GVF monthly data (Gutman) (ii) Multi-year mean GVF weekly data (24 years: 1982-2005) (iii) Real-time weekly GVF data (from 1982 to present) GFS Sensivity Case Selection: Summer 2006: August 1, 2006

  27. Global GVF Data: August 01, 2006 • Old climatology GVF data (Gutman); • Mult-year mean GVF weekly data (24 years); • Difference of two climatology datasets; • Anomaly of real-time weekly GVF data;

  28. Climatology: for Aug 01 Old GVF: Upper left New GVF: Upper right Difference (New-minus-Old): Lower right New GVF is generally higher

  29. CONUS version of previous frame Climatology: for Aug 01 Old GVF: Upper left New GVF: Upper right Difference (New-minus-Old): Lower right New GVF is generally higher

  30. Top Panel: Climatology of New GVF for Aug 01 Bottom Right Panel: Realtime Anomaly for 01 August 2006: (New Weekly Realtime GVF minus Climatology of New Realtime GVF) Bottom Left Panel: CONUS version of bottom right panel

  31. Two Sensitivity Tests with GFS: August 01, 2006 • (1)Impact of climatology difference: • Control: Execute GFS with climatology of old GVF product • Test: Execute GFS with climatology of new GVF product • (2) Impact of weekly anomaly: • Control: Execute GFS using climatology of new GVF product • Test: Execute GFS using the realtime weekly field of new GVF product • GFS: 7 days forecast, starts from Aug.01,2006. • Only Experiment 1 is completed to date and its results shown in next frame (Plots of Test-minus-Control Differences: Tsfc, Ta, Sensible heat flux and Latent heat flux at 1800 UTC for GFS 36-hour forecast valid at 1800 UTC from 0000 UTC initial conditions on 01 August 2006)

  32. Test-minus-Control Difference Fields: Tskin (upper left), 2-m air T (upper right), • Sensible heat flux (lower left), Latent heat flux (lower right) • GFS 36-hour forecast valid at 1800 UTC from 0000 UTC initial time on 01 Aug 06) Where differences are significant, higher GVF values in new vs old climo Result in cooler Tskin and higher surface latent heat flux.

  33. Mike Ek will present recent work with Unified Noah LSM in WRF/NMM (NAM) mesoscale modelplus:1 - surface layer test results in NAM2- iterative surface energy balance in Noah

  34. NLDAS Phase 2: 1 – Add seasonal prediction component 2- Employ improved versions of Noah (and VIC, Mosaic, SAC) 3- Add CLM Following frames focus on improvements to Noah LSM: -- seasonal LAI -- canopy resistance (vapor pressure deficit function, soil moisture stress) -- infiltration parameters (Ksat, Kdt) as tested in DMIP-2

  35. Impact in NLDAS simulations of a bundle of following seven changes to Noah LSM • -- replace constant LAI treatment with a seasonally and spatially varying LAI • -- allow a seasonally varying vertical profile of root density • -- change the function for the vapor-pressure deficit term in the canopy resistance • -- change the upper threshold of soil moisture at which the vegetation feels a soil moisture deficit • -- change the minimum stomatal resistance parameter for a few vegetation classes • -- change the treatment for the diurnal variation of surface albedo • -- change the single parameter in the formulation for the roughness length for heat (to increase the daytime aerodynamic conductance) • Decrease CZIL from 0.10 to 0.05

  36. Adding Seasonal LAI treatment to Noah: Use current green veg fraction (GVF), scale between annual min and max values of LAI Seasonal LAI Approach LAImin and LAImax are from Brian Cosgrove’s table.

  37. Exp: scaling LAI (left hand Y-axis) by means of green veg fraction (right hand Y-axis) This example for a winter-wheat location in central Oklahoma LAI Greenness

  38. Changing humidity stress and soil moisture stress functions in Jarvis treatment in Noah To reduce low LH biases during the Summer Using a narrow range of thistends to overestimate the evaporation during wet periods (spring) and underestimate the evaporation during dry periods (summer). SMHIGH and SMLOW BXEXP From Chen et al. 1996

  39. CONTROL BUNDLE Bundle of 7 changes to Noah LSM physics reduces Noah’s generally negative runoff bias Normalized bias of mean-annual basin average runoff from 2-year uncoupled Noah LSM simulations (Oct 97 to Sep 99) for selected unregulated basins in the NLDAS test bed for a control version (left panel) and test version (right panel) of the Noah LSM. The test version (labeled “BUNDLE”) includes the seven physical changes listed in Section 5 of the progress report. The changes in the test version reduce the negative runoff bias in the east half of the CONUS. Those basins in central Great Plains with high positive bias (dark green) are likely basins were streamflow is diverted for irrigation and hence should be discarded from the set of validating basins. Normalized bias is defined as [(model-minus-observed)/observed]

  40. Diurnal cycle (x-axis) by month of year (y-axis) of differences between Noah simulated and observed surface latent heat flux BUNDLE of 7 Noah changes CONTROL BUNDLE + GRNDWTR Monthly mean diurnal cycle (horizontal axis) by month (vertical axis) of the difference of model-minus observed surface latent heat flux as computed from the average of such differences at 24 ARM/CART flux stations for a 21-month simulation in the NLDAS test bed of three configurations of the Noah LSM described in the text.

  41. Noah simulations for DMIP-2:improving Noah streamflow simulations by tuning Ksat and Kdt parameters

  42. Mean annual cycle from six years (Oct 96 – Sep 02) of observed and Noah LSM simulated monthly streamflow for the Blue River and Eldon River basins in Oklahoma. Changes to two Noah runoff related parameters recommended by the MOPEX project reduces the low bias in the simulation.

  43. As in previous figure, but for monthly time series spanning six years (Oct 96 – Sep 02).

  44. PILPS San Pedro (semi-arid: S. Arizona)Lead: Luis Bastidas • See PILPS San Pedro arcticle in most recent issue of GEWEX Newsletter • Noah simulations fared reasonably well • Runoff timing one of the best of participating models • Runoff magnitude much too low (as in almost all models) • Latent heat flux was low

  45. New Land-Surface Fieldsfrom JCSDA thrusts To be shown on Day 2 of workshop

  46. New Satellite-Based Land-Surface Fieldsfrom JCSDA thrustsTo be shown on Day 2 of workshop • Landuse (Mark Friedl, Boston U.) • Albedo: snow-free (Mark Friedl, Boston U.) • LAI (Mark Friedl, Boston U.) • Deep snow albedo (Xubin Zeng, U. Arizona) • Greenness fraction • Realtime weekly (NESDIS/STAR) • Monthly climo (Xubin Zeng, U. Arizona) • Land Surface emissivity (Ben Ruston, NRL)

  47. NCEP recommended modestchanges to Noah • Seasonal LAI • Modify Ksat and Kdt parameters • Change humidity stress function in Jarvis • Modify RSmin for some veg classes • Modifyy SMCREF and SMCWLT • Modify Zot for stable conditions

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