High-Resolution Land Use Data in WPS/WRF for Urban Regions

Michael DudaMMM Division, NCAR

Boulder, Colorado, USA

Third workshop on the Asian urban heat island issues 2006 February 28, Meisei University

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

Third workshop on the Asian urban heat island issues 2006 February 28, Meisei University

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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

Third workshop on the Asian urban heat island issues 2006 February 28, Meisei University

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Background - UCM

Consider two ways to model urban effects 1. 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

2. 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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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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Components of the WPS

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geogrid : Defines simulation grids and horizontally static fields

Components of the WPS

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ungrib : Extract meteorological and time-varying surface fields from GRIB files

Components of the WPS

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metgrid : Horizontally interpolates time-varying fields to simulation grids

Components of the WPS

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High-resolution gridded urban data are provided here

The WRF Preprocessing System

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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

The WRF Preprocessing System

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How are land use categories transferred to simulation grid?

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

Model grid cell

Land use category data

The WRF Preprocessing System

Third workshop on the Asian urban heat island issues 2006 February 28, Meisei University

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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

The WRF Preprocessing System

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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

The WRF Preprocessing System

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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

The WRF Preprocessing System

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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

The WRF Preprocessing System

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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)

The WRF Preprocessing System

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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

Impact of High-Res Urban Categories

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WRFV2.2/UCM Runs: 18 hr simulations starting 25 Aug 2000, 12Z

4-domain nested run (27,9,3,1km) using AWIP data

1. WRF (using USGS landuse with 1 urban category)

2. WRF (using USGS landuse + high resolution urban land use data)

3. WRF-UCM (using USGS landuse + high resolution urban land use data)

Impact of High-Res Urban Categories

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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

Test Case: Houston

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Urban areas (black) using USGS 24-category data set

Area of Houston data tile in relation to model domain; white=missing

data and blue=valid data

Land use modifications for Houston based on high-resolution data

New categories:31 – Low-intensity residential32 – High-intensity residential33 – Commercial/Industrial

Test Case: Houston

Third workshop on the Asian urban heat island issues 2006 February 28, Meisei University

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Urban areas (black) using USGS 24-category data set

Augmented urban areas (red shades) using new LU data set

Land use modifications for Houston based on high-resolution data

Impact on 2-m Temperature of High Resolution Landuse over Houston RegionWRF 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

Impact on Sensible Heat Flux of High Resolution Landuse over Houston

Region

Local Time: 9pm Local Time: Midnight

Using high-resolution data produces more detailed distribution over the different

urban categories and produces higher SHF at night time

2m-Temperature (UCM versus WRF)

Local Time: 9pm Local Time: Midnight

UCM produces 1-1.5 C higher temperatures as compared with WRF over

urban regions and is more detailed

UCM WRF

Sensible Heat Flux (W/m2) (UCM versus WRF)

Local Time: 9pm Local Time: Midnight

UCM produces 30-40 W/m2 higher night time fluxas compared to WRF over urban regions

Summary and Conclusions

Third workshop on the Asian urban heat island issues 2006 February 28, Meisei University

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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

Summary and Conclusions

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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

Questions?

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