UMEP Manual/ Tutorials/ SUEWS Advanced
- 1 SUEWS/BLUEWS (Advanced)
- 2 How to Run from the UMEP-plugin
- 3 Generating data from the geodatasets
- 4 Reporting a bug
- 5 References
- 6 Definitions and Notation
- 7 Further explanation
SUEWS - Simple tutorial should be completed first
- To explore the link between QGIS and SUEWS to include new site-specific information
- To examine how it affects the energy fluxes
Overview of steps
- Initially become familiar with SUEWS/BLUEWS advanced which is a plugin that makes it possible for you to set all parameters that can be manipulated in SUEWS.
- Derive new surface information
- Run the model
How to Run from the UMEP-plugin
|How to run SUEWS Advanced:
The default dataset included in Suews Simple has parameters calculated from a source area model to obtain the appropriate values for the input parameters. Roughness parameters such as roughness length (z0) and zero plane displacement length (zd) are calculated using morphometric models. Now you will explore the differences in fluxes using the default settings or using input parameters from the geodata included in the test datasets available for this tutorial. Download the zip-file (see below) and extract the files to a suitable location where you both have reading and writing capabilities.
Data for the tutorial can be downloaded here
|Ground and building DSM (digital surface model)||DSM_LondonCity_1m.tif (m asl)|
|Vegetation DSM||CDSM_LondonCity_1m.tif (m agl)|
|DEM (digital elevation model)||DEM_LondonCity_1m.tif (masl)|
They are all projected in UTM 31N (EPSG:32631). The three surface models originate from a LiDAR dataset. The land cover data is a mixture of Ordnance Survey and the LiDAR data.
- Open the geodatasets. Go to Layer > Add layer > Add Raster Layer. Locate the files you downloaded before (see above).
- A QGIS style file (.qml) is available for the land cover grid. It can found in C:\Users\your_user_name\.qgis2\python\plugins\UMEP\ LandCoverReclassifier\. Load it in the Layer > Properties > Style > Style (lower left) Load file.
- Click Apply before you close so that the names of the classes also load. You can also get the properties of a layer by right-click on a layer in the Layers-window.
- If you have another land cover dataset you can use the LandCoverReclassifier in the UMEP pre-processor to populate with the correct values suitable for the UMEP plugin environment.
- Now take a moment and investigate the different geodatasets. What is the sparial (pixel) resolution? How is ground represented in the CDSM?
Generating data from the geodatasets
|If you get an error window. This error is generate by SUEWS as the sum of the land cover fractions is not 1. If you calculate carefully, one part of a thousand is missing (this is probably a rounding error during data extraction). To fix this issue: add 0.001 to e.g. bare soil. Now run again.|
You are now familiar with the Suews Simple plugin. Your next task is to choose another location within the geodataset domain, generate data and run the model. If you choose an area where the fraction of buildings and paved surfaces are low, consider lowering the population density to get more realistic model outputs. Compare the results for the different area.
Currently Known Bugs (August 2016)
UMEP : https://bitbucket.org/ fredrik_ucg/umep/issues If you try to save (e.g. the zoomed-in) plot as a .png-file when using the 64-bit version of QGIS, the software probably will crash.
- Grimmond CSB and Oke 1999: Aerodynamic properties of urban areas derived, from analysis of surface form. Journal of Applied Climatology 38:9, 1262-1292
- Grimmond et al. 2015: Climate Science for Service Partnership: China, Shanghai Meteorological Servce, Shanghai, China, August 2015.
- Järvi L, Grimmond CSB & Christen A 2011: The Surface Urban Energy and Water Balance Scheme (SUEWS): Evaluation in Los Angeles and Vancouver J. Hydrol. 411, 219-237
- Järvi L, Grimmond CSB, Taka M, Nordbo A, Setälä H &Strachan IB 2014: Development of the Surface Urban Energy and Water balance Scheme (SUEWS) for cold climate cities, , Geosci. Model Dev. 7, 1691-1711
- Kormann R, Meixner FX 2001: An analytical footprint model for non-neutral stratification. Bound.-Layer Meteorol., 99, 207–224
- Kotthaus S and Grimmond CSB 2014: Energy exchange in a dense urban environment – Part II: Impact of spatial heterogeneity of the surface. Urban Climate 10, 281–307
- Onomura S, Grimmond CSB, Lindberg F, Holmer B, Thorsson S 2015: Meteorological forcing data for urban outdoor thermal comfort models from a coupled convective boundary layer and surface energy balance scheme. Urban Climate. 11:1-23 (link to paper)
- Ward HC, L Järvi, S Onomura, F Lindberg, A Gabey, CSB Grimmond 2016 SUEWS Manual V2016a, http://urban-climate.net/umep/SUEWS Department of Meteorology, University of Reading, Reading, UK
- Ward HC, Kotthaus S, Järvi L and Grimmond CSB 2016b: Surface Urban Energy and Water Balance Scheme (SUEWS): Development and evaluation at two UK sites. Urban Climate http://dx.doi.org/10.1016/j.uclim.2016.05.001
- Ward HC, S Kotthaus, CSB Grimmond, A Bjorkegren, M Wilkinson, WTJ Morrison, JG Evans, JIL Morison, M Iamarino 2015b: Effects of urban density on carbon dioxide exchanges: observations of dense urban, suburban and woodland areas of southern England. Env Pollution 198, 186-200
Authors this document: Lindberg and Grimmond (2016)
Definitions and Notation
To help you find further information about the acronyms they are classified by T: Type of term: C: computer term, S: science term, G: GIS term.
|DEM||Digital elevation model||G|
|DSM||Digital surface model||G|
|FAI (λF)||Frontal area index||S||Grimmond and Oke (1999), their figure 2|
|GUI||Graphical User Interface||C|
|LAI||Leaf Area Index||S|
|PAI (λP)||Plan area index||S|
|png||Portable Network Graphics||C||format for saving plots/figures|
|SUEWS||Surface Urban Energy and Water Balance Scheme||S|
|Tif||Tagged Image File Format||C||format for saving plots/figures|
|UMEP||Urban Multi-scale Environmental predictor||C|
|z0||Roughness length for momentum||S||Grimmond and Oke (1999)|
|zd||Zero plane displacement length for momentum||S||Grimmond and Oke (1999)|
Morphometric Methods to determine Roughness parameters:
For more and overview and details see Grimmond and Oke (1999). This uses the height and spacing of roughness elements (e.g. buildings, trees) to model the roughness parameters. UMEP has tools for doing this: Pre-processor -> Urban Morphology
Source Area Model
For more details see Kotthaus and Grimmond (2014b). The Kormann and Meixner (2001) model is used to determine the probable area that a turbulent flux measurement was impacted by. This is a function of wind direction, stability, turbulence characteristics (friction velocity, variance of the lateral wind velocity) and roughness parameters.