The Effects of Surface Heterogeneity on
Boundary-Layer Structure and Fluxes
Margaret LeMone and Fei Chen, with acknowledgments to
collaborators:
T. Horst, S. Semmer, R. Roberts, Jim Wilson (NCAR)
B. Geerts (Univ. of Wyoming) R. Cuenca (Oregon State) + R. Grossman (CoRA) +
P. Blanken (CU) + D. Niyogi (NCSU) + E. Small (CU) + D. Stauffer and K.
Davis (PSU), T. Holt (NRL)
Goals:
1. Collect and analyze IHOP surface/vegetation/soil/aircraft
data
2. Validate and improve models (Noah LSM, CLM, HRLDAS,
Coupled WRF/Noah system)
3. Investigate the relationships between land variability and
convection initiation
15 King-Air BLH Missions + 10 NCAR Surface,
Soil, and Vegetation Stations
Central Track
Sites 4, 5, 6
Eastern Track
Sites 7, 8, 9
ABLE
Network
Western Track
Sites 1, 2, 3
CU station 10
OK Mesonet
Characteristics of the Flight Tracks
The Eastern Track
Compare CASES-97
To IHOP
David Gochis (left) and Bob Grossman (right)
Eastern Track:
Radiometric Surface Temperature
IHOP: Riparian
areas warm
CASES97: Riparian
areas cool
Winter wheat effect?
Eastern Track: Potential Temperature
IHOP: West warm
CASES97: Center
warm
CASES-97: Mesoscale Circulations
Flight Track
Evaluation of flux measurements for relating to
surface heterogeneity
1. Statistics
F
 2l F

 
F  Lx



1
2
 1  rw2's ' 
 2 
 rw's ' 
Lx = record length
F = flux (average w’s’)
lF = turbulence integral scale
rw’s’’2 = correlation between w’ and s’
2. Adherence to surface energy balance constraint:
H + LE = Rn – G ~ constant spatially
H = sensible heat flux
LE = latent heat flux
Rn = net radiatioin
G = heat flux into ground
3. Existence of horizontal variability
June 17, 20, 22
composite (21 legs)
Last rain on
15 June
17 J 201 deg at 7.7 m/s
20 J 163 deg at 5.3 m/s
22 J 179 deg at 9.4 m/s
For comparison…CASES-97 Sensible Heat Flux (H)
-96.9o is site of low
H; maximum
shifted to east
CASES-97 LE (-96.9o High LE)
Net result of flux difference:
17 June – W 250 m deeper than E
boundary-layer depth 150-250 m 20 June – W 150 m deeper than E
deeper at west end of track
22 June – W 240 m deeper than E
Eastern Track Synthesis reinforces findings of
Grossman et al. 2004.
Land use affects radiometric surface temperature (Ts),
potential temperature (Q) , fluxes (H and LE),
and turbulence level (w’2)
Ts, Q, H, w’2 higher and LE lower over dormant
vegetation; reverse for green vegetation
Vegetation related to terrain
April-early May (CASES): Winter wheat to W and
in riparian zones green, grass dormant
late May-June (IHOP): Grass green, winter wheat
senescent and then harvested.
Soil moisture effect less obvious (long drydown for
17,20, 22 June)
Western Track: Radiometric Surface Temperature
Silty Clay Loam Sandy Loam
Soils
Land cover
Rainfall:
16-17 May < 5 mm
23 May ~ 3 mm
26-27 May: 20-30 mm
in north to
>80 mm to south
4-5 June ~15-20 mm
Air Temperature
Rainfall:
16-17 May < 5 mm
23 May ~ 3 mm
26-27 May:
30-30 mm north
90 mm south
4-5 June 15-20 mm
Distribution of Fluxes (Sensible Heat)
191/4.9
177/13.2
133/2.5
199/10.6
Distribution of Fluxes (Latent Heat)
29 May 2002: Contrast Between Station 3
(north) and Station 1 (south) ~50 km apart
Site 1 (western track)
Site 3 (western track)
Soil moisture
rain
Site3: drier, larger
sensible heat flux
Latent heat
Net Rad
Sensible heat
Turbulence – 29 May 2002
Wyoming Cloud Radar: Independent Confirmation
of More vigorous BL to north on 29 May
NORTH – More Vigorous Convection
SOUTH – Less Vigorous Convection
Bart Geerts
Synthesis for Western Track
Potential temperature H, and Ts larger to
north most days (but not all)
-- Sandy soil to north (better drained)
-- More rain to south
29 May strong heterogeneity due heavy rain on
south end of track 2 days previous.
Mesoscale variability on some days of currently
unknown origin
IHOP Boundary Layer/Surface Data
•
•
Data sets completed
– Near-surface weather conditions, PAR, surface incoming and net radiation
(full component at sites 1,8, and 9), precipitation, surface heat fluxes,
ground heat flux
– Latent heat fluxes recalculated from energy budgets
– Soil bulk density, soil texture, saturated hydraulic conductivity, unsaturated
hydraulic conductivity function, thermal conductivity, and the soil-water
retention function
– Weekly vegetation data: NDVI, leaf area index (LAI), stomatal resistance,
transpiration
– CO2 concentrations at sites 1 and 8
– MODIS data
– Diurnal cycle of stomatal resistance and transpiration for a few selected
sties
– Aircraft fluxes and NDVI along the flight tracks
– Available @ www.rap.ucar.edu/projects/land/IHOP/index.htm
Data sets being processed
– Soil moisture content, soil water tension (potential), and soil temperature
profiles from the surface to a depth of 90 cm (about seven weeks). Three
profiles at sites 1 and 9
– Landsat data
Modeling and Analysis Effort
• Validate and improve LSMs
– Weather Community Noah LSM (CU/NCAR, NCSU/NCAR):
– CLM (CU/NCAR)
• Verify WRF/Noah LSM coupled model (NCAR)
• Verify high-resolution land data assimilation
system (HRLDAS)
• Understand relationships between soil moisture
and convection initiation (extension of our
USWRP work)
High-Resolution Land Data Assimilation System
(HRLDAS) : Capturing Small-Scale Variability
• Input:
– 4-km hourly NCEP
Stage-II rainfall
– 1-km landuse type and
soil texture maps
– 0.5 degree hourly GOES
downward solar radiation
– 0.15 degree AVHRR
vegetation fraction
– T,q, u, v, from model
based analysis
• Output: long term evolution
of multi-layer soil moisture
and temperature, surface
fluxes, and runoff
4-km HRLDAS surface soil moisture
in IHOP domain 12 Z May 29 2002
High-Resolution Land Data Assimilation
System (HRLDAS) Concept
Run uncoupled LSM on the same grid
as MM5/WRF to avoid:
• Mismatch of terrain, land use
type, soil texture, physical
parameters between sources of
soil data and NWP models
• Need for interpolation
4-month (2002) HRLDAS Soil Moisture
vs Oklahoma Mesonet Observation
Surface (0-10 cm) volumetric soil moisture
averaged for Mesonet 62 stations
IHOP Data Improve HRLDAS
monthly average diurnal cycle of downward solar radiation fluxes (9 sites)
GOES derived downward solar radiation have high bias for low solar angle
An adjustment of radiation input has been made to HRLDAS
IHOP Refractivity
12:00
Hourly HRLDAS Evaporation (mm)
12:00
Refractivity
14:00
Refractivity
14:00
IHOP Refractivity
16:00
Hourly HRLDAS Evaporation (mm)
16:00
Refractivity
18:00
Refractivity
18:00
Comparison between WRF/Noah (10-km) and
Wyoming King Air data
Surface heat flux along the western leg
valid @ 19Z 29 May 2002
Comparison between WRF/Noah (10-km) and
Wyoming King Air data
Variance of surface heat flux along the western leg
valid @ 19Z 29 May 2002
Where from here
Generalize fluxes using surface, aircraft, satellite info
Use data to test models (LSMs, WRF PBL, CI)
How much can models do?
How can we improve models?
Does this improve prediction of convective
initiation?
Iterate….
Comparison between HRLDAS (4-km)
and Wyoming King Air data
Surface heat flux along the western leg
valid @ 19Z 29 May 2002
Comparison between HRLDAS (4-km)
and Wyoming King Air data
Variance of surface heat flux along the western leg
valid @ 19Z 29 May 2002