Utilizing the IHOP 2002 data to study variability in surface water cycle and precipitation process

F. Chen, M. LeMone, T. Horst, D. Yates, S. Semmer, S. Trier, K. Manning, M. F. Chen, M. LeMone, T. Horst, D. Yates, S. Semmer, S. Trier, K. Manning, M. Tewari, H. McIntyre (NCAR)Tewari, H. McIntyre (NCAR)

R. Grossman (Colorado Research Associates)R. Grossman (Colorado Research Associates) R. Cuenca (Oregon State University)R. Cuenca (Oregon State University) D. Niyogi (North Carolina State University) D. Niyogi (North Carolina State University) P. Blanken, J. Alfieri, J. Uebelherr(University of Colorado)P. Blanken, J. Alfieri, J. Uebelherr(University of Colorado)

MotivationMotivation IHIH22OP surface, vegetation, and soil observation networkOP surface, vegetation, and soil observation network Preliminary resultsPreliminary results

Scientific Issues

How does land surface (soil moisture, How does land surface (soil moisture, vegetation, terrain) contribute to the amount vegetation, terrain) contribute to the amount and variation of water vapor in PBL? and variation of water vapor in PBL? How well the BL structure reflect the How well the BL structure reflect the

underlying surface conditionsunderlying surface conditions Under which condition do mesoscale Under which condition do mesoscale

circulation occurcirculation occur How is BL depth affectedHow is BL depth affected

How do the above influence convection How do the above influence convection initiation and evolution initiation and evolution

IHOP Surface, Soil and Vegetation NetworkURL:http://www.rap.ucar.edu/projects/land/IHOP/index.htm

Part of IHOP network to support the ABL mission Part of IHOP network to support the ABL mission Nine NCAR surface-flux stations provide: Nine NCAR surface-flux stations provide:

Complete surface energy budget, near-surface Complete surface energy budget, near-surface atmospheric conditions, precipitationatmospheric conditions, precipitation

Soil moisture/temperature only at 5 cm depth Soil moisture/temperature only at 5 cm depth Enhance the NCAR surface stations by adding Enhance the NCAR surface stations by adding

soil and vegetation instrumentssoil and vegetation instruments Supported by NCAR Water InitiativeSupported by NCAR Water Initiative

(purchase soil and vegetation sensors, field trips)(purchase soil and vegetation sensors, field trips)

Nine NCAR Surface, soil, and vegetation stations. Plus one (site 10) from CU

ABLE Network

OK MesonetWestern LegSites 1, 2, 3CU station 10

Central LegSites 4, 5, 6

Eastern LegSites 7, 8, 9

Methodology

Strategically place ten surface stations along the flight tracks and Strategically place ten surface stations along the flight tracks and over different landuse types (range grass, wheat, sparsely over different landuse types (range grass, wheat, sparsely vegetated)vegetated)

Single profile of soil moisture and temperature sensors at seven Single profile of soil moisture and temperature sensors at seven stations: stations: measurements centered at measurements centered at 7.5, 15, 22.5, 37.5, 60, 70-95 7.5, 15, 22.5, 37.5, 60, 70-95 cmcm

Three profiles at Sites 1 and 9 ‘super sites’Three profiles at Sites 1 and 9 ‘super sites’

IHOPNo

LandCover

Fetch Lat Long Elevation (m)

Legal

1 WW 10 36 28.370 100 37.075 871 S55 B10 HT and B Survey(Texas)

2 CRP grass 9 36 37.327 100 37.619 859 SW¼S19T2NR23E

3 Sagebrush + mesquite + cactus

9 36 51.662 100 35.670 780 N ¼ S32 T5NR23E

4 Grass 7-8 37 21.474 98 14.679 509 SE ¼ S12T31S R9W

5 WW 10 37 22.684 98 09.816 506 W ½ S2 T31S R8W

6 WW 10! 37 21.269 97 39.200 417 NW ¼ S16 T31S R3W

7 Grass, grazed 8 37 18.972 96 56.323 382  NE ¼ S36-T31S R4E

8 Grass,May be burned

9 37 24.418 96 45.937 430 SW¼ S27 T30S R6E

9 Grass, will graze cattle.

8-9,rolling

37 24.618 96 34.028 447 E½ S30 T30S R8E

10 Heavily grazed 9+ 36 53.544 100 36.202   NE ¼ S19T5NR23E (CU site)

Expected Data

Near-surface weather conditions, PAR, surface incoming and Near-surface weather conditions, PAR, surface incoming and net radiation (full component at sites 1,8, and 9), precipitation, net radiation (full component at sites 1,8, and 9), precipitation, surface heat fluxes, ground heat flux surface heat fluxes, ground heat flux

CO2 concentrations at sites 1 and 8CO2 concentrations at sites 1 and 8 Soil moisture content, soil water tension (potential), and soil Soil moisture content, soil water tension (potential), and soil

temperature profiles from the surface to a depth of 90 cm temperature profiles from the surface to a depth of 90 cm (about seven weeks). Three profiles at sites 1 and 9(about seven weeks). Three profiles at sites 1 and 9

Soil bulk density, soil texture, saturated hydraulic conductivity, Soil bulk density, soil texture, saturated hydraulic conductivity, unsaturated hydraulic conductivity function, thermal unsaturated hydraulic conductivity function, thermal conductivity, and the soil-water retention function. conductivity, and the soil-water retention function.

Weekly vegetation data: NDVI, LAI, stomatal resistance, Weekly vegetation data: NDVI, LAI, stomatal resistance, transpiration transpiration

Diurnal cycle of stomatal resistance and transpiration for a few Diurnal cycle of stomatal resistance and transpiration for a few selected stiesselected sties

Rain accumulation (mm) Latent heat flux (W m-2)

West leg Sites 1, 2, 3

Central leg Sites 4, 5, 6

East leg Sites 7, 8, 9

Weather Research Forecast(WRF)/ LSM coupled model verification (with 10-km grid spacing)

31 May 2002

Sites 1, 2, 3

Sites 7, 8, 9

M. Tewari and F. Chen

WRF/LSM coupled model verification

Sites 1, 2, 3

Sites 7, 8, 9

M. Tewari and F. Chen

High-resolution land data assimilation system (HRLDAS) Multi-resolution (4, 12 km)Multi-resolution (4, 12 km) Utilize:Utilize:

4-km hourly NCEP Stage-II; 1-km landuse type and 4-km hourly NCEP Stage-II; 1-km landuse type and soil texture maps; 0.5 degree hourly satellite soil texture maps; 0.5 degree hourly satellite derived downward solar radiation; T,q, u, v, from derived downward solar radiation; T,q, u, v, from model based analysis; model based analysis;

To simulate the evolution To simulate the evolution

of soil moisture and of soil moisture and

temperature, evaporationtemperature, evaporation

and runoff. and runoff. Hourly product (Jan-JulyHourly product (Jan-July

2002)2002)4-km surface soil moistureValid at 12 Z May 29 2002

Impact of soil moisture on QPF 3-h rainfall ending 18Z 19 June 1998 (dryline case)

MM5 using soil moisture from HRLDAS

MM5 using soil moisture from NCEP EDAS coarse resolution and too wet

S. Trier, K. Manning, and F. Chen

Important BL processes for convection initiation and intensification

for the 19 June 1998 dryline case

Quasi-stationary convective rolls formed at the dryline seem criticalfor CI

Mesoscale circulation formed as result of differential heating in the morning may be responsible for CI in OK

S. Trier, K. Manning, and F. Chen

Summary Comprehensive atmospheric, soil, and vegetation data Comprehensive atmospheric, soil, and vegetation data

set from IHOP surface/soil/vegetation network set from IHOP surface/soil/vegetation network Allow a detailed analysis and improvement of LSM Allow a detailed analysis and improvement of LSM

componentscomponents Verify couple model simulationVerify couple model simulation

Study relationships among S-pol water vapor (Roberts Study relationships among S-pol water vapor (Roberts and Wilson), King Air fluxes and water vapor and Wilson), King Air fluxes and water vapor (LeMone), and HRLDAS soil moisture and surface (LeMone), and HRLDAS soil moisture and surface evaporationevaporation

Investigate the role of convective rolls and mesoscale Investigate the role of convective rolls and mesoscale circulations in CI and QPF with IHOP datacirculations in CI and QPF with IHOP data