1. High-Resolution Land Use Data in WPS/WRF for Urban Regions
Michael Duda
MMM Division, NCAR
Boulder, Colorado, USA
Third workshop on the Asian urban heat island issues
2006 February 28, Meisei University

2. Motivation
With the latest release, version 2.2, of the WRF model in December 2006, two new components can be used in simulations over urban areas
1) The WRF Preprocessing System (WPS) is a new software package to replace the previous preprocessor
- WPS includes capabilities for mapping high- resolution data sets onto model domains
2) The Urban Canopy Model (UCM) is now a standard component in WRF
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3. Outline I. Background II. Urban Canopy Model
III. WRF Preprocessing System
IV. Mapping Land Use Data with WPS
V. UCM+Urban Landuse Impact
VI. Summary and Conclusions
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4. Background - UCM Consider two ways to model urban effects
Vary the soil constants (e.g. heat capacity and thermal conductivity) and parameters (e.g. surface albedo, roughness length and moisture availability) in atmospheric model
Couple an Urban canopy model-layer model with atmospheric model
Latter approach has many advantages, so UCM was added as a component for WRF in v2.2
Couple Noah LSM in WRF with a single layer urban-canopy model (UCM), based on Kusaka et al, 2001
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5. Background - WPS
In WRF v2.2, the WPS replaces the previous preprocessor, the WRF SI
The WPS contains several new features that allow for flexibility in creating initial fields
Ability to ingest arbitrary gridded fields (after encoding them in the correct file format)
Ability to combine different data sets of differing resolutions and projections
E.g., USGS land use field and high-resolution urban land use
Fine-grained control over how individual fields are interpolated
Masked fields benefit in particular from this!
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6. Components of the WPS
geogrid : Defines simulation grids and horizontally static fields
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7. Components of the WPS
ungrib : Extract meteorological and time- varying surface fields from GRIB files
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8. Components of the WPS
metgrid : Horizontally interpolates time-varying fields to simulation grids
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9. Components of the WPS
High-resolution gridded urban data are provided here
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10. The WRF Preprocessing System
High-resolution urban data are given in separate files:
Default global 24-category USGS land use data set
(30-sec. resolution)
High-resolution urban land use data set
Advantage: High-res data do not need to be re-projected or subsampled onto global data set
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11. The WRF Preprocessing System
How are land use categories transferred to simulation grid?
Model grid cell
For a model grid cell, we consider all source grid cells that are >50% in that grid cell
- we want the dominant, or most common, category among all source grid cells within model grid cell
Land use category data
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12. The WRF Preprocessing System
How are land use categories transferred to simulation grid?
Example:
12 – category 31
9 – category 32
5 – category 33
Thus, this model grid cell will receive urban land use category 31
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13. The WRF Preprocessing System
What about combining default and high- resolution urban data?
Suppose the high-resolution data set is regional
Step 1: Map regional data set categories onto model grid as before
- here, we must respect areas with null values
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14. The WRF Preprocessing System
What about combining default and high- resolution urban data?
After mapping high-resolution, regional data set to model domain, some model grid cells still have not been assigned a category
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15. The WRF Preprocessing System
What about combining default and high- resolution urban data?
Step 2: Map global (or larger regional) data set onto only those points that have not already been assigned a cateogry!
NB : This procedure can be applied repetitively for an arbitrary number of data sets
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16. The WRF Preprocessing System
Important points regarding WPS interpolation of high-resolution urban data sets:
1) Within interior of high-resolution data set, interpolation is “correct” regardless of relative resolution of source data
2) Near edges of data set, the extent of urban areas may be exaggerated when
(resolution of data) > (resolution of model)
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17. The WRF Preprocessing System
The problem of over-extension of urban areas:
High-resolution urban data set shown on top of coarse model grid; unshaded cells are assigned “missing value” flag
Model grid cells receiving an urban category; note that a model grid cell is urban if it contains at least ½ of an urban source cell
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18. Impact of High-Res Urban Categories
WRFV2.2/UCM Runs: 18 hr simulations starting 25 Aug 2000, 12Z
4-domain nested run (27,9,3,1km) using AWIP data
WRF (using USGS landuse with 1 urban category)
WRF (using USGS landuse + high resolution urban land use data)
WRF-UCM (using USGS landuse + high resolution urban land use data)
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19. Impact of High-Res Urban Categories
Domain configuration
Domain 1 (27-km resolution): 85 x 68
Domain 2 ( 9-km resolution) : 145 x 106
Domain 3 ( 3-km resolution) : 190 x 160
Domain 4 ( 1-km resolution) : 199 x154
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20. Test Case: Houston
Land use modifications for Houston based on high-resolution data
New categories:
31 – Low-intensity residential
32 – High-intensity residential
33 – Commercial/Industrial
Area of Houston data tile in relation to model domain; white=missing data and blue=valid data
Urban areas (black) using USGS 24-category data set
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21. Test Case: Houston
Land use modifications for Houston based on high-resolution data
Urban areas (black) using USGS 24-category data set
Augmented urban areas (red shades) using new LU data set
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22. Impact on 2-m Temperature of High Resolution Landuse over Houston Region
WRF with high resolution LU
WRF without high resolution LU
Local Time: 9pm
Local Time: Midnight
Using high-resolution data produces more detailed distribution over the different urban categories and warmer 2-m T at night time over urban regions

23. Impact on Sensible Heat Flux of High Resolution Landuse over Houston Region
Local Time: Midnight
Local Time: 9pm
Using high-resolution data produces more detailed distribution over the different urban categories and produces higher SHF at night time

24. 2m-Temperature (UCM versus WRF)
Local Time: 9pm
Local Time: Midnight
UCM produces C higher temperatures as compared with WRF over urban regions and is more detailed

25. Sensible Heat Flux (W/m2) (UCM versus WRF)
Local Time: Midnight
Local Time: 9pm
UCM produces W/m2 higher night time flux
as compared to WRF over urban regions

26. Summary and Conclusions
In WRF V2.2, UCM is a standard component for use with Noah LSM
The new capability of urban canopy modeling
Provides detailed distribution of urban heat island
Enhances mesoscale model forecasted wind and thermal structure over urban area
Specification of urban landuse is critical
High-resolution urban land use data sets are easily processed with WPS
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27. Summary and Conclusions
The data mapping capability of WPS can handle arbitrary gridded fields, not just land use
Additional fields can be mapped to WRF domain as required by new urban model development
For urban land use data sets, any number of categories may be mapped
If model can make use of more specific categories, these can be handled in WPS
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28. Questions? Third workshop on the Asian urban heat island issues
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