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 HydrologyJeremy PalFilippo Giorgi, Raquel Francisco, Elfatih Eltahir

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

Subgrid Topography and Landuse SchemeLand 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-km60-km

360-kmTopography60-kmTopography

60-kmLanduse10-kmLanduse360-kmLanduseCoarse Domain:~250 grid pointsMedium Domain:~9,000 grid pointsFine Domain:~325,000 grid points

General MethodologyDefine 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.

Methodology: Disaggregationsg = subgrid; i,j = subgrid cell; overbar coarse gridT = near surface air temperature; h = topographical elevationGT = average atmospheric lapse rate = 6.5 C/kmTemperature disaggregated according to the subgrid elevation difference:

Methodology: DisaggregationRelative humidity is held constant (more or less).sg = subgrid; i,j = subgrid cell; overbar coarse gridT = near surface air temperature; h = topographical elevationGT = average atmospheric lapse rate = 6.5 C/kmTemperature disaggregated according to the subgrid elevation difference:

Methodology: DisaggregationRelative humidity is held constant (more or less).sg = subgrid; i,j = subgrid cell; overbar coarse gridT = near surface air temperature; h = topographical elevationGT = average atmospheric lapse rate = 6.5 C/kmTemperature disaggregated according to the subgrid elevation difference:

Methodology: DisaggregationRelative humidity is held constant (more or less).sg = subgrid; i,j = subgrid cell; overbar coarse gridT = near surface air temperature; h = topographical elevationGT = average atmospheric lapse rate = 6.5 C/kmTemperature 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]

Methodology: ReaggregationThe surface heat fluxes, temperature and humidity are reaggregated to the coarse grid after BATS computations are performedFor example, for the latent heat flux LH:

Numerical ExperimentsSimulation period:1 Oct 1994 to 1 Sept 1995Land Surface computations performed on subgrid.CTL60-km; no subgrid cellsEXP1515-km; 16 subgrid cellsEXP1010-km; 36 subgrid cells

10-km15-km60-km

Results: TemperatureWINTER (DJF)SUMMER (JJA)

Results: TemperatureWINTER (DJF)SUMMER (JJA)

Results: PrecipitationOBS (CRU)CTLWINTER (DJF)SUMMER (JJA)

Results: PrecipitationOBS (CRU)WINTER (DJF)CTLSUMMER (JJA)

Results: Snow

Results: Water Budget

Results: Energy Budget

Part I: Summary & ConclusionsFine 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.

In the worksImplement 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)

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

Rainfall Anomalies (mm/d)June & July 1993 May & June 1988 Rainfall Anomalies (mm/d)

Domain & Topography

25MW Fixed Patch Experiment: Initial Root Zone Soil MoistureMidwest: 25MWFixed SoilMoisture (25%)Interactive SoilMoisture (CTL)25%

Decrease in the energy per unit depth of boundary layer via radiative effectsShould decrease the likelihood and magnitude of rainfall of the region of the anomalyBoundary Layer Height Net Radiation25MW-CTL25MW-CTL25MW-CTLMoist Static Energy

Decrease in convection via local feedbacksAnomalous high pressureAnomalous anticyclonic flowIncreased descent and a northward stormtrack shiftChanges in rainfall distribution 500mb Zonal Winds25MW-CTL25MW-CTL 500mb Winds & Heights

75SW Fixed Patch Experiment: Initial Root Zone Soil Moisture75%Southwest: 75SWFixed SoilMoisture (75%)Interactive SoilMoisture (CTL)

75SW Experiments75SW-CTLRainfall (U.S. only) 500mb Zonal Winds75SW-CTL

Local Soil Moisture-Rainfall FeedbacksA dry soil moisture anomaly A high pressureanomalyLess local rainfall (Pal& Eltahir,2001)A low pressureanomalyMore local rainfall (Pal& Eltahir,2001)A wet soil moisture anomaly

(1)Dry anomaly

(2)High pressure anomaly(3)Shift inStorm-tracknorthwardRemote Soil Moisture-Rainfall FeedbacksA soil moisture anomaly leads to a shift in the storm-trackPal and Eltahir (2003), QJRMS

(1)Wet anomaly

(2)Low pressure anomaly(3)Shift inStorm-tracksouthwardRemote Soil Moisture-Rainfall FeedbacksA soil moisture anomaly leads to a shift in the storm-trackPal and Eltahir (2003), QJRMS

Precipitation (U.S. only)

Part II: Summary & ConclusionsThe 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.

Initial Root Zone Soil Moisture (June 25)Climatology19881993

Additional Soil Moisture-Rainfall Mechanism