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NUDAPT vs UT-Globus Distribution of Building Heights UCP

madhavijain

New member
I was using NUDAPT dataset provided on the WPS_GEOG data website for running BEPBEM WRF simulations. I later developed my own set of UCPs required from the explicit building footprints and building heights data we had. I followed some of the older documentations of NUDAPT (https://ral.ucar.edu/sites/default/files/public/product-tool/NUDAPT_44_Documentation.pdf) and AMS presentation of Jason Ching for this. There seems to be some confusion around computation of Distribution of Building Hgts UCP (0-75m)- should it be computed as percentages (range 0-100%) or as fractions (range 0-1), when ingesting in WPS?

When I plot the NUDAPT distribution of building hgts (URB_PARAM Index 118-132) from geo_em.nc or from wrfinput.nc, this specific UCP shows up as a fraction ranging from 0-1. I computed my custom UCPs at a 500m resolution as fractions (Image attached below)

But several new publications suggest that it should be computed as a percentage? A new dataset UT-Globus had computed fractions for the the 15 layers of Dist of Building hgts UCP, but later ask to recompile the WRF, so that this UCP can be read as a percentage. Can anyone please clarify on what is the correct methodology for this particular UCP.


How to run BEP-BEM model in WRF using UT-GLOBUS urban canopy parameters (GLObal Building heights for Urban Studies (UT-GLOBUS))

Step 0: Before compiling WRF, go to 'dyn_em' folder and open 'module_initialize_real.F'.
Change line 3121 (in version 4.5.2):
From
grid%HI_URB2D(i,k,j) = grid%URB_PARAM(i,k+117,j)
To
grid%HI_URB2D(i,k,j) = grid%URB_PARAM(i,k+117,j)*100.
 

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  • UCP_NUDAPT_ClimateIQ.jpg
    UCP_NUDAPT_ClimateIQ.jpg
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Hello

madhavijain,​


Even I am presently working with dataset of UT Globus. Regarding to your question about what should be the methodology to prepare histogram of building height i.e in percentage or in fraction, I believe it can be both. But ensure using same methodology if you are computing building heights histograms with different datasets and further using the results for comparison.
Pls note that the above is my personal opinion based on my limited knowledge. Thanks
 
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