Difference between revisions of "UMEP Manual"

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==Processor==
 
===Outdoor Thermal Comfort: SOLWEIG===
 
{|class="wikitable"
 
|-
 
|Contributor||Fredrik Lindberg (Gothenburg)
 
|-
 
|Introduction||The '''SOLWEIG''' plugin can be used to calculate spatial variations of mean radiant temperature (T<sub>mrt</sub>) and radiant fluxes using digital surface models (DSM) and ground cover information. Optionally, vegetation DSMs could also be used. The methodology that is used to generate shadows originates from Ratti and Richens (1990) and is further developed and described in Lindberg and Grimmond (2011) and Lindberg et al. (2016). The current version of the model is 2016a.
 
 
The full manual of the SOLWEIG model can be found [http://urban-climate.net/umep/SOLWEIG here].
 
|-
 
| Location ||
 
The SOLWEIG model is located at
 
* UMEP
 
** Processor
 
*** Outdoor Thermal Comfort
 
**** SOLWEIG
 
|-
 
|Related Preprocessors ||  [http://www.urban-climate.net/umep/UMEP_Manual#Meteorological_Data:_MetPreprocessor MetdataPreprocessor], [http://www.urban-climate.net/umep/UMEP_Manual#Meteorological_Data:_Download_data_.28WATCH.29 Download data (WATCH)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Geometry:_Sky_View_Factor_Calculator SkyViewFactor Calculator], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Geometry:_Wall_Height_and_Aspect Wall Height and Aspect], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Land_Cover:_Land_Cover_Reclassifier LandCoverReclassifier]
 
|-
 
|Dialog box||
 
 
[[File:SOLWEIG.png| none|Dialog for the SOLWEIG model]]
 
|-
 
|Dialog sections ||
 
{|class="wikitable"
 
|-
 
|Spatial data|| Spatial input data is specified
 
|-
 
|Meteorological data ||Meteorological input data is specified, as a continuous file or specific momentary values.
 
|-
 
|Environmental parameters || Possibilities to alter emissiveties and albedos for the different urban surfaces.
 
|-
 
|Optional settings || Here additional setting such as including POIs (Points of Interest) is found.
 
|-
 
|Human exposure parameters || Settings for calculating mean radiant temperature.
 
|-
 
|Output maps|| Options to choose the geotiffs to be saved for each iteration.
 
|}
 
|-
 
|Spatial data ||
 
{|class=wikitable
 
|Building and Ground DSM || A DSM consisting of ground and building heights. This dataset also decides the latitude and longitude used for the calculation of Sun position.
 
 
|-
 
|Vegetation Canopy DSM||A DSM consisting of pixels with vegetation heights above ground. Pixels where no vegetation is present should be set to zero.
 
 
|-
 
|Vegetation Trunk Zone DSM ||A DSM (geoTIFF) consisting of pixels with vegetation trunk zone heights above ground. Pixels where no vegetation is present should be set to zero.
 
 
|-
 
|Use vegetation scheme ||Tick this box if you want to include vegetation (trees and bushes) in the calculations.
 
 
|-
 
|Trunk Zone DSM Exist ||Tick this in if a trunk zone DSM already exist.
 
 
|-
 
|Transmissivity of Light Through Vegetation (%) ||Percentage of light that is penetrating through vegetation. Default value is set to 3 % according to Konarska et al. (2013).
 
 
|-
 
|Percent of Canopy Height ||If a trunk zone vegetation DSM is absent, this can be generated based on the height of the Canopy DSM. The default percentage is set to 25%.
 
 
|-
 
|Save generated Trunk zone DSM || Tick this in if you want to save your TDSM that is generated.
 
 
|-
 
|Use land cover scheme ||Available since v2015a. Land cover grid should be in the UMEP standard format '''except''' for the two tree classes (deciduous and conifer) as the land cover grid should represent what is on the ground surface. UMEP land cover grid can be prepared in the Pre-processor.
 
 
|-
 
|Use land cover grid to produce building grid ||Tick this in if the building grid should be created from the land cover grid. Otherwise, a DEM including only ground heights must be added. This will then be used to derive a building grid together with the ground and building DSM.
 
 
|-
 
|Save generated building grid || Tick this in if you want to save the boolean building grid that is generated.
 
 
|-
 
|SkyViewFactor grids ||The SOLWEIG model make use of SVFs to calculate T<sub>mrt</sub>. The zip-file needed can be created with the SkyViewFactor calculator found in the UMEP Pre-processor.
 
 
|-
 
|Wall height raster ||The SOLWEIG model make use of wall height raster to calculate T<sub>mrt</sub>. This can be calculated using the Wall height and aspect plugin found in the UMEP Pre-processor
 
 
|-
 
|Wall aspect raster ||The SOLWEIG model make use of wall height raster to calculate T<sub>mrt</sub>. This can be calculated using the Wall height and aspect plugin found in the UMEP Pre-processor.
 
|}
 
|-
 
| Meteorological data||
 
{|class=wikitable
 
 
|Use continuous meteorological dataset||Tick this in if a time series of data should be used. The specific format could be prepared in the UMEP Pre-processor.
 
 
|-
 
|Estimate diffuse and direct components from global radiation||Tick this box if diffuse and direct shortwave radiation is unavailable. The Reindl et al. (1990) model is used to calculate diffuse radiation. Direct radiation perpendicular to the solar beam should be considered.
 
 
|-
 
|Settings for one iteration.||If a meteorological dataset is not used there is a possibility to run the model for one iteration using the calendar and spin-boxes to set meteorological variables present here. The default values are for a clear Summer day at 1230 in Göteborg, Sweden.
 
 
|-
 
|UTC offset||Time zone needs to be specified. Positive numbers moving east (e.g. Stockholm UTC +1).
 
|}
 
|-
 
| Optional settings||
 
{|class=wikitable
 
 
|Include POIs || By ticking in the option to include POIs (Point of Interest), a vector point layer can be added and full model output are written out to text files for the specific POI. Multiple POIs can be used by including many points in the vector file. See the [http://www.urban-climate.net/umep/SOLWEIG full manual] for more information.
 
 
|-
 
|Adjust sky-emissivity according to Jonsson et al. (2006)|| Tick this box to include adjustment (0.04) of sky emissivity which was present in the earlier versions of the SOLWEIG model (not recommended).
 
 
|-
 
|Consider human as cylinder instead of box ||Tick this box to consider man as a cylinder instead of a box according to Holmer at al. (2015).
 
|}
 
|-
 
|Environmental parameters||
 
{|class=wikitable
 
 
|-
 
|Albedo (buildings)||Albedo of building walls and roofs.
 
 
|-
 
|Albedo (ground)||Albedo of ground surfaces. Not used if land cover scheme is active.
 
 
|-
 
|Emissivity (walls)||Emissivity of building walls and roofs.
 
 
|-
 
Emissivity (ground)||Emissivity of ground. Not used if land cover scheme is activated.
 
|}
 
 
|-
 
|Human exposure parameters ||
 
{|class=wikitable
 
 
|-
 
|Absorption of shortwave radiation||Amount of shortwave radiation that the human body absorb.
 
 
|-
 
|Absorption of longwave radiation||Amount of longwave radiation that the human body absorb.
 
 
|-
 
Posture of the human body||Choose between standing (default) and sitting.
 
|}
 
|-
 
|Output maps||A number of different outputs can be chosen here. All grids will be written out as GeoTIFFs at the location specified as the output folder.
 
|-
 
|Run || Starts the calculations. As SOLWEIG is a 2.5D model, large grids (i.e. high number of pixels) will take a relatively long time to compute. The model is embedded in a so called worker which means that you can continue working with QGIS while the model runs.
 
 
|-
 
|Add Average mean radiant temperature to the map canvas||If ticked, an average T<sub>mrt</sub> map will be added to the current project.
 
 
|-
 
|Close || Closes the plugin.
 
 
|-
 
|Quick example on how to run SOLWEIG || Here, an example on how to run the model, using our test dataset, is presented:
 
#Download and extract (unzip) the test dataset ([https://bitbucket.org/fredrik_ucg/umep/downloads/testdata_UMEP.zip testdata_UMEP.zip]).
 
#Add the raster layers (DSM, CDSM and land cover) from the Goteborg folder into a new QGIS session. The coordinate system of the grids is '''Sweref99 1200 (EPSG:3007)'''.
 
#In order to run SOLWEIG, some additional datasets must be created based on the raster grids you just added. Open the SkyViewFactor Calculator from the UMEP Pre-processor and calculate SVFs using both your DSM and CDSM. Leave all other settings as default.
 
#Open the Wall height and aspect plugin from the UMEP Pre-processor and calculate both wall height and aspect using the DSM and your input raster. Tick in the box to add them to your project. Leave all other settings as default.
 
#Now you are ready to generate your first T<sub>mrt</sub> map. Open SOLWEIG and use the settings as shown in the figure below but replace the paths to the fit your computer environment. When you are finished, press ''Run''.
 
[[File:SOLWEIGfirsttry.png| none|Dialog for the SOLWEIG model]]
 
There is also a meteorological file present in the test dataset that can be used to run the model for a whole day.
 
 
|-
 
|Remarks ||
 
* All DSMs need to have the same extent and pixel size.
 
* This plugin is computationally intensive i.e. large grids will take a lot of time and very large grids will not be possible to use. Large grids e.g. larger than 4000000 pixels should preferably be tiled before.
 
* SOLWEIG focus on pedestrian radiation fluxes and it is not recommended to consider fluxes on building roofs.
 
 
|-
 
| References||
 
*Holmer, B., Lindberg, F., Rayner, D. and Thorsson, S. 2015: How to transform the standing man from a box to a cylinder – a modified methodology to calculate mean radiant temperature in field studies and models, ICUC9 – 9 th International Conference on Urban Climate jointly with 12th Symposium on the Urban Environment, BPH5: Human perception and new indicators. Toulouse, July 2015.
 
* Konarska J, Lindberg F, Larsson A, Thorsson S, Holmer B 2013. Transmissivity of solar radiation through crowns of single urban trees—application for outdoor thermal comfort modelling. [http://link.springer.com/article/10.1007/s00704-013-1000-3 Theoret. Appl. Climatol., 1–14 ]
 
* Lindberg, F., Grimmond, C.S.B., 2011a. The influence of vegetation and building morphology on shadow patterns and mean radiant temperatures in urban areas: model development and evaluation. [http://link.springer.com/article/10.1007/s00704-010-0382-8 Theoret. Appl. Climatol. 105, 311–323 ]
 
* Riendl D.T., Beckman W.A. and Duffie J.A. (1990), Diffuse Fraction Correlations, Solar Energy, Vol. 45, No.1, pp. 1-7.
 
|}
 
 
===Outdoor Thermal Comfort: ExtremeFinder===
 
{|class="wikitable"
 
|-
 
|Contributor||Bei Huang (Reading), Andy Gabey (Reading)
 
|-
 
|Current Options
 
|Identifies extreme high events (e.g. Heat waves) and low events (e.g. Cold Waves). Designed primarily for temperature data (heat waves identified from daily maximum and mean T; cold waves from daily minimum), but can also be used to indicate potential high and low extremes in other meteorological variables.
 
|-
 
|Data must be provided by the user, and can be:
 
|
 
*Previously-downloaded WATCH data in a NetCDF (.nc) file (this can be obtained from the WATCH downloader)
 
*Other NetCDF (.nc) file containing sub-daily measurements, or daily maximum/mean/minimum values. Must contain a ''''time'''' dimension, and variable(s) with name(s) matching those being analysed using the ExtremeFinder.
 
*Text (.txt) file, daily T<sub>max</sub>, T<sub>avg</sub> or T<sub>min</sub> ([http://www.urban-climate.net/watch_data/data%20set%20sample.txt  file sample]: 1979-01-01 to 2009-12-31). Only temperature analysis can be performed using a text file.
 
|-
 
| Method
 
| Basis for thresholds - set into Input.nml (namelist)
 
*[http://science.sciencemag.org/content/305/5686/994 Meehl and Tebaldi (2004)]: 81st, 97.5th
 
*[http://www.nature.com/ngeo/journal/v3/n6/full/ngeo866.html Fischer and Schär (2010)]: 90th
 
*[https://link.springer.com/article/10.1007%2Fs00382-013-1714-z Vautard et al. (2013)]: 90th
 
*[https://link.springer.com/article/10.1007/s00382-014-2434-8 Schoetter et al. (2014)]: 98th
 
*[http://www.kirj.ee/26593/?tpl=1061&c_tpl=1064 Sirje Keevallik (2015)]: 10th
 
*[http://onlinelibrary.wiley.com/doi/10.1002/asl.232/abstract A. K. Srivastava (2009)]: 3 °C
 
*Busuioc et al. (2010): 5 °C
 
|-
 
|Location
 
|
 
*UMEP
 
**Processor
 
***Outdoor Themal Comfort
 
****ExtremeFinder
 
|-
 
|Dialog box ||[[File:Extremefinder3.png| frame |left|The interface for the ExtremeFinder plugin]]
 
|-
 
|Steps to use
 
|
 
#Select climate data: The ExtremeFinder will use all the data available in its analysis. You will be prompted for a text (.txt) or NetCDF (.nc) file:
 
#* ''NetCDF file'': The latitude, longitude, start and end date boxes will be populated automatically, if the data is available in the NetCDF file.
 
#* ''Text file'': The latitude, longitude, start and end date boxes must be filled in by the user, as the information is needed in calculations:
 
#** ''Latitude'' (degrees N) and ''Longitude'' (degrees E) are WGS84 co-ordinates
 
#** ''Start'' and ''end date'' are inclusive and must match the data extent
 
#Select the ''extreme event type'' and the ''calculation method'':
 
#* Event types are either Extreme ''high'' (e.g. Heat wave) or ''low''  (e.g. Cold wave)
 
#* There are several different ways to identify extremes, depending on the event type
 
#* Choose the ''meteorological variable'' to analyse for extremes
 
#** '''Note:''' The methods in the Extreme Finder are based on Tair and may not be appropriate for other variables
 
#Select Output File: A list of extreme events will be written to the file
 
#* Note: this will be overwritten if not a new name
 
#Run: Performs the analysis
 
|-
 
 
|Output: Extreme events (heat waves used as example below)
 
|
 
#Daily T<sub>max</sub> (or T<sub>avg</sub> /  T<sub>min</sub>) with time (Y= Year, X=Month)
 
#*Colour gives Temperature (see key)
 
#*Yellow Box Highlights Heatwave (Coldwave) periods This loads the model interface dialog box: [[File:TMax1.jpg|center|thumb|350px|Heat/Cold wave periods]]
 
#Box plot of distribution of heat (cold) wave by year.
 
#*whiskers  =1.5* IQR
 
#* + outliers - any data beyond the whiskers  [[File:HW_Box.jpg|center|thumb|350px|Box-and-whisker plot of Heat/Cold wave days each year]]
 
#Number of heat (cold) waves days per year [[File:HWDays.jpg|center|thumb|350px|Plot|Histogram showing number of Heat/Cold wave days each year]]
 
|-
 
|}
 
 
===Urban Energy Balance: GQ<sub>F</sub>===
 
{|class="wikitable"
 
|-
 
| Contributors ||
 
Andy Gabey (Reading), Izzy Capel Timms (Reading), Sue Grimmond (Reading)
 
|-
 
| How to Cite
 
|
 
* Gabey A, S Grimmond, I Capel-Timms 2018: Anthropogenic Heat Flux: advisable spatial resolutions when input data are scarce Theoretical and Applied Climatology https://doi.org/10.1007/s00704-018-2367-y
 
* Lindberg F, CSB Grimmond, A Gabey, B Huang, CW Kent, T Sun, NE Theeuwes, L Järvi, H Ward, I Capel-Timms, YY Chang, P Jonsson, N Krave, DW Liu, D Meyer, KFG Olofson, JG Tan, D Wästberg, L Xue, Z Zhang 2018: Urban multiscale environmental predictor (UMEP) - An integrated tool for city-based climate services Environmental Modelling and Software 99, 70–87 10.1016/j.envsoft.2017.09.020
 
|-
 
|Introduction || [http://urban-climate.net/umep/GQF_Manual See separate manual]
 
|-
 
|Location ||
 
The GreaterQF plugin is located at
 
* UMEP
 
** Processor
 
*** Urban Energy Balance
 
**** GreaterQF
 
 
|-
 
|Dialog box ||[[File:GQF.png| none|Start dialog for Greater QF]]
 
|-
 
|Dialog sections ||
 
The model run is configured using the dialog box:
 
 
*''Start date'' and ''end date'': The first and final dates for which the model should be run.
 
*''Output areas'': Two options are currently available: Local authority areas and 1km grid. These select the spatial units of the model calculations.
 
*''Include QF components'': The components of anthropogenic heat flux for the model to include in calculations.
 
*''Output path'': A directory that houses model outputs.
 
|-
 
|Model outputs ||
 
'''Example map'''
 
 
The total anthropogenic heat flux for the first time step is displayed in QGIS to demonstrate model output and the output areas. In order for these areas to be displayed correctly, the coordinate reference system must be selected. The QGIS “Select CRS” screen will appear, and EPSG 27700 (British National Grid) must be chosen.
 
 
The layer displaying model output also contains the other contributions to QF (e.g. car transport). These can be visualised using standard QGIS methods of styling the layer according to the selected component, or inspecting the layer attributes table.
 
 
''' CSV files '''
 
 
A CSV file is generated for each of the 19 contributions to QF (e.g. car travel, wastewater heating) and the total QF. Each file contains a column per output area (shown in the example map) and a row per time step. These are labelled accordingly. The filenames are abbreviated where necessary for compatibility, with the following convention used:
 
{|class="wikitable"
 
|-
 
||El || Electricity
 
|-
 
||Gas|| Gas
 
|-
 
||Dm||Domestic use
 
|-
 
||Id||Industrial use
 
|-
 
||Tspt||Transport
 
|-
 
||Unre||Unrestricted electricity (non-Economy 7)
 
|-
 
||Eco7||Economy 7 electricity
 
|-
 
|| Everything || Grand total QF across all sources
 
|}
 
 
'''Python data object''' (For internal use)
 
 
A “pickled” Python data object containing the results is also saved in the local temporary folder for future use with other UMEP components.
 
 
 
|-
 
 
|-
 
| References||
 
* Iamarino M, Beevers S & Grimmond CSB (2012) High-resolution (space, time) anthropogenic heat emissions: London 1970-2025 [http://doi.wiley.com/10.1002/joc.2390 International J. of Climatology 32, 11, 1754-1767]
 
* Gabey A, S Grimmond, I Capel-Timms 2018: Anthropogenic Heat Flux: advisable spatial resolutions when input data are scarce Theoretical and Applied Climatology https://doi.org/10.1007/s00704-018-2367-y
 
* Lindberg F, CSB Grimmond, A Gabey, B Huang, CW Kent, T Sun, NE Theeuwes, L Järvi, H Ward, I Capel-Timms, YY Chang, P Jonsson, N Krave, DW Liu, D Meyer, KFG Olofson, JG Tan, D Wästberg, L Xue, Z Zhang 2018: Urban multiscale environmental predictor (UMEP) - An integrated tool for city-based climate services Environmental Modelling and Software 99, 70–87 10.1016/j.envsoft.2017.09.020
 
 
|}
 
 
===Urban Energy Balance: LQ<sub>F</sub>===
 
{|class=wikitable
 
|-
 
|Contributors ||Andy Gabey (Reading), Izzy Capel-Timms (Reading), Sue Grimmond (Reading), Sam Jackson (Reading), XY Ao (SIMS), Bei Huang(Tsinghua Unviersity)
 
|-
 
|Introduction ||[http://urban-climate.net/umep/LQF_Manual See separate manual]
 
|-
 
| References||
 
* Allen, L., Lindberg, F. and Grimmond, C. (2011) Global to city scale urban anthropogenic heat flux: model and variability. [http://onlinelibrary.wiley.com/doi/10.1002/joc.2210/abstract International Journal of Climatology 31:13, 1990-2005.]
 
* Lindberg, F., Grimmond, C., Yogeswaran, N., Kotthaus, S. and Allen, L. (2013a) Impact of city changes and weather on anthropogenic heat flux in Europe 1995–2015. [http://www.sciencedirect.com/science/article/pii/S2212095513000059 Urban Climate 4, 1-15.]
 
* Gabey A, S Grimmond, I Capel-Timms 2018: Anthropogenic Heat Flux: advisable spatial resolutions when input data are scarce Theoretical and Applied Climatology https://doi.org/10.1007/s00704-018-2367-y
 
* Lindberg F, CSB Grimmond, A Gabey, B Huang, CW Kent, T Sun, NE Theeuwes, L Järvi, H Ward, I Capel-Timms, YY Chang, P Jonsson, N Krave, DW Liu, D Meyer, KFG Olofson, JG Tan, D Wästberg, L Xue, Z Zhang 2018: Urban multiscale environmental predictor (UMEP) - An integrated tool for city-based climate services Environmental Modelling and Software 99, 70–87 https://10.1016/j.envsoft.2017.09.020
 
 
|-
 
|}
 
 
===Urban Energy Balance: Urban Energy Balance (SUEWS/BLUEWS, advanced)===
 
{|class="wikitable"
 
|-
 
|Contributor||Fredrik Lindberg (Gothenburg)
 
|-
 
|Introduction ||
 
This plugin makes it possible to run the Surface Urban Energy and Water Balance Scheme (SUEWS). SUEWS is also available as a separate program and a simplified version within UMEP (SUEWS Simple).
 
 
SUEWS (Järvi et al. 2011, 2014, Ward et al. 2016a, b) simulates the urban radiation, energy and water balances using commonly measured/modeled meteorological variables and information about the surface cover. It utilizes an evaporation-interception approach (Grimmond et al. 1991), similar to that used in forests, to model evaporation from urban surfaces. 
 
 
The model uses seven surface types: paved, buildings, evergreen trees/shrubs, deciduous trees/shrubs, grass, bare soil and water. The surface state for each surface type at each time step is calculated from the running water balance of the canopy where the evaporation is calculated from the Penman-Monteith equation. The soil moisture below each surface type (excluding water) is taken into account. 
 
 
Model applicability: Local scale – so forcing data should be above the height of the roughness elements (trees, buildings)
 
 
SUEWS is designed to be executed for a single location but the model is also able to be executed on a grid.
 
 
|-
 
|Location ||
 
The SUEWS Simple plugin is located at
 
* UMEP
 
** Processor
 
*** Urban Energy Balance
 
**** Urban Energy Balance (SUEWS/BLUEWS, Advanced)
 
|-
 
|Related Preprocessors || [http://www.urban-climate.net/umep/UMEP_Manual#Meteorological_Data:_MetPreprocessor MetdataPreprocessor], [http://www.urban-climate.net/umep/UMEP_Manual#Meteorological_Data:_Download_data_.28WATCH.29 Download data (WATCH)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Land_Cover:_Land_Cover_Reclassifier LandCoverReclassifier], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Land_Cover:_Land_Cover_Fraction_.28Point.29 LandCoverFraction (Point)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Land_Cover:_Land_Cover_Fraction_.28Grid.29 LandCoverFraction (Grid)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Morphology:_Image_Morphometric_Parameters_Calculator_.28Point.29 Image Morphometric Parameters Calculator (Point)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Morphology:_Image_Morphometric_Parameter_Calculator_.28Grid.29 Image Morphometric Parameters Calculator (Grid)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Morphology:_Source_Area_.28Point.29 Foot Print Model (Point)]
 
|-
 
|Dialog box ||[[File:SuewsAdvanced.png| none|Start dialog for SUEWS]]
 
|-
 
|Dialog sections ||
 
When you run the plugin, you will see the dialog shown below. To use this plugin, all input data needs to be prepared beforehand. This can be done using the various plugins in the pre-processor in UMEP. The settings available in this plugin is used for specifying the settings for a specific model run. You should consult the manual ([http://www.urban-climate.net/umep/SUEWS]) for instructions and information on what settings to use. For extensive models run it is recommended to execute the model outside of QGIS (see manual). The interface below creates a so-called namelist ('''RunControl.nml''') that is used be the model for general settings. After running the model, this file can be found in the suewsmodel directory in the UMEP plugin directory.
 
|-
 
| References||
 
 
* Järvi L, Grimmond CSB & Christen A (2011) The Surface Urban Energy and Water Balance Scheme (SUEWS): Evaluation in Los Angeles and Vancouver [http://www.sciencedirect.com/science/article/pii/S0022169411006937 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, [http://www.geosci-model-dev.net/7/1691/2014/ doi:10.5194/gmd-7-1691-2014].
 
* Ward HC, L Järvi, S Onomura, F Lindberg, CSB Grimmond (2016a) [http://urban-climate.net/umep/SUEWS SUEWS Manual]: Version 2016a
 
* Ward HC. S Kotthaus, L Järvi, CSB Grimmond (2016b) Surface Urban Energy and Water Balance Scheme (SUEWS): development and evaluation at two UK sites [[:File:SUEWS_UKEvaluationPaper_Revised_v1-03.pdf| Urban Climate (in press)]].
 
|}
 
 
===Solar Radiation: Daily Shadow Pattern===
 
{|class="wikitable"
 
|-
 
|Contributor||Fredrik Lindberg (Gothenburg)
 
|-
 
|Introduction||The '''Shadow generator''' plugin can be used to generate pixel wise shadow analysis using ground and building digital surface models (DSM). Optionally, vegetation DSMs could also be used. The methodology that is used to generate shadows originates from Ratti and Richens (1990) and is further developed and described in Lindberg and Grimmond (2011). Position of the Sun is calculated using '''PySolar''', a python library for various Sun related applications ([http://pysolar.org/]).
 
|-
 
| Location ||
 
The Shadow Generator is located at
 
* UMEP
 
** Processor
 
*** Solar Radiation
 
**** Daily Shadow Pattern
 
|-
 
|Dialog box||
 
 
[[File:shadow_generator.jpg| none|Start Dialog for the Shadow Generator package]]
 
|-
 
|Dialog sections ||
 
{|class="wikitable"
 
|-
 
|top || input data is specified
 
|-
 
|middle ||setting for positioning the Sun on the hemisphere 
 
|-
 
|bottom || to specify the output and to run the calculations
 
|}
 
|-
 
|Building and Ground DSM || A DSM consisting of ground and building heights. This dataset also decides the latitude and longitude used for the calculation of Sun position.
 
 
|-
 
|Vegetation Canopy DSM||A DSM consisting of pixels with vegetation heights above ground. Pixels where no vegetation is present should be set to zero.
 
 
|-
 
|Vegetation Trunk Zone DSM ||A DSM (geoTIFF) consisting of pixels with vegetation trunk zone heights above ground. Pixels where no vegetation is present should be set to zero.
 
 
|-
 
|Use vegetation DSMs ||Tick this box if you want to include vegetation (trees and bushes) when shadows are generated.
 
 
|-
 
|Trunk Zone DSM Exist ||Tick this in if a trunk zone DSM already exist.
 
 
|-
 
|Transmissivity of Light Through Vegetation (%) ||Percentage of light that is penetrating through vegetation. Default value is set to 3 % according to Konarska et al. (2013).
 
 
|-
 
|Percent of Canopy Height ||If a trunk zone vegetation DSM is absent, this can be generated based on the height of the Canopy DSM. The default percentage is set to 25%.
 
 
|-
 
|Specify Data ||The data need to be set in the middle section.
 
 
|-
 
|Cast Shadows Only Once ||Tick this box if you only want to cast one shadow. Below this tick box you can set the time that is needed to decide the position of the sun.
 
 
|-
 
|Time Interval between Casting of each Interval ||If the above tick box (Cast shadows only once) is not ticked in, a number of shadows is generated based on the interval set.
 
 
|-
 
|UTC Offset (Hours) ||Time zone needs to be specified. Positive numbers moving east(e.g. Stockholm UTC +1).
 
 
|-
 
|Output Folder ||A specified folder where the result will be saved.
 
 
|-
 
|Run ||Starts the calculations
 
 
|-
 
|Add Results to Project||If ticked, the shadow raster will be added to the map canvas.
 
 
|-
 
| Close ||Closes the plugin.
 
|-
 
| Output||If only one shadow image is generated, one geoTIFF will be produced where pixel values of zero indicates shadow and one indicates sunlit. If daily shadow casting is used (Cast shadows only once ticked off), one shadow image for each time step as well as one shadow fraction image is generated. The shadow fraction image is given in percent where 100% meaning the a pixel is sunlit throughout the day used in the calculation. 
 
 
|-
 
|Example of input data and result || shadow image in Gothenburg (1 m resolution), Sweden at 1 pm on the 2nd of October 2015 (daylight savings time).
 
 
[[File:Shadow2.jpg| none|Example of Input Data and the Resulting Shadow Image in Gothenburg (1 m Resolution), Sweden at 1 pm on the 2nd of October 2015 (Daylight Savings Time).]]
 
|-
 
|Remarks ||
 
* All DSMs need to have the same extent and pixel size.
 
* This plugin is computationally intensive i.e. large grids will take a lot of time and very large grids will not be possible to use. Large grids e.g. larger than 4000000 pixels should be tiled before.
 
 
|-
 
| References||
 
 
* Konarska J, Lindberg F, Larsson A, Thorsson S, Holmer B 2013. Transmissivity of solar radiation through crowns of single urban trees—application for outdoor thermal comfort modelling. [http://link.springer.com/article/10.1007/s00704-013-1000-3 Theoret. Appl. Climatol., 1–14 ]
 
* Lindberg, F., Grimmond, C.S.B., 2011a. The influence of vegetation and building morphology on shadow patterns and mean radiant temperatures in urban areas: model development and evaluation. [http://link.springer.com/article/10.1007/s00704-010-0382-8 Theoret. Appl. Climatol. 105, 311–323 ]
 
* Ratti CF, Richens P (1999) Urban texture analysis with image processing techniques. In: Proceedings of the CAADFutures99, Atalanta, GA
 
|}
 
 
===Solar Radiation: Solar Energy on Building Envelopes (SEBE)===
 
{|class="wikitable"
 
|-
 
|Contributor||Fredrik Lindberg (Gothenburg), Dag Wäsrberg (Tyréns)
 
|-
 
|Introduction||The '''SEBE''' plugin (Solar Energy on Building Envelopes) can be used to calculate pixel wise potential solar energy using ground and building digital surface models (DSM). SEBE is also able to estimate irradiance on building walls. Optionally, vegetation DSMs could also be used. The methodology that is used to generate irradiance is presented in Lindberg et al. (2015).
 
 
|-
 
| Location ||The SEBE plugin is located at
 
* UMEP
 
** Processor
 
*** Solar Radiation
 
**** Solar Energy on Building Envelopes (SEBE)
 
|-
 
|Related Preprocessors ||  [http://www.urban-climate.net/umep/UMEP_Manual#Meteorological_Data:_MetPreprocessor MetdataPreprocessor], [http://www.urban-climate.net/umep/UMEP_Manual#Meteorological_Data:_Download_data_.28WATCH.29 Download data (WATCH)], [http://www.urban-climate.net/umep/UMEP_Manual#Urban_Geometry:_Wall_Height_and_Aspect Wall Height and Aspect]
 
|-
 
|Dialog box|| Consists of
 
*top section where input data is specified
 
*bottom section for specifying the output and for running the calculations
 
 
[[File:SEBE1.png| none|Start Dialog for the Solar Energy on Building Envelopes package]]
 
 
|-
 
|Building and Ground DSM||A DSM consisting of ground and building heights. This dataset also decides the latitude and longitude used for the calculation of the Sun position.
 
 
|-
 
| Vegetation Canopy DSM ||A DSM consisting of pixels with vegetation heights above ground. Pixels where no vegetation is present should be set to zero.
 
|-
 
|Vegetation Trunk Zone DSM ||A DSM (geoTIFF) consisting of pixels with vegetation trunk zone heights above ground. Pixels where no vegetation is present should be set to zero.
 
 
|-
 
|Use Vegetation DSMs ||Tick this box if you want to include vegetation (trees and bushes) into the analysis.
 
 
|-
 
|Trunk Zone DSM Exist||Tick this in if a trunk zone DSM already exist.
 
 
|-
 
|Transmissivity of Light Through Vegetation (%) ||Percentage of light that is penetrating through vegetation. Default value is set to 3 % according to Konarska et al. (2013).
 
 
|-
 
|Percent of Canopy Height||If a trunk zone vegetation DSM is absent, this can be generated based on the height of the Canopy DSM. The default percentage is set to 25%.
 
 
|-
 
|Wall Height Raster ||A raster of the same size and extent as the ground and building DSM including information of the wall pixels and its height in meters above ground should be specified here. Non wall pixels should be set to zero. This raster is used to estimate irradiance on building walls and can be generated using the Wall Height and Aspect plugin located at UMEP -> Pre-processing -> Urban Geometry -> Wall Height and Aspect.
 
 
|-
 
|Wall Aspect Raster ||A raster of the same size and extent as the ground and building DSM including information of the wall pixels and its aspect, i.e. angle, should be specified here. For example a wall facing towards the south has a value of 180°. Non wall pixels should be set to zero. This raster are used to estimate irradiance on building walls and can be generated using the Wall Height and Aspect plugin located at UMEP -> Pre-processing -> Urban Geometry -> Wall Height and Aspect.
 
 
|-
 
|Albedo ||This parameter specifies the reflectivity of shortwave radiation of all surfaces (ground, roofs, walls and vegetation). It should be a value between 0 and 1. The default value is set to 0.15.
 
|-
 
| UTC Offset (Hours)||Time zone needs to be specified. Positive numbers increase when moving east (e.g. Stockholm UTC +1).
 
 
|-
 
|Estimate Diffuse and Direct Shortwave Components from Global Radiation ||Tick this in if only global radiation is present. Diffuse and direct shortwave components will then be estimated from global radiation based on the statistical model presented by Reindl et al. (1990). If air temperature and relative humidity is present, the statistical model will perform better but it is able to estimate the components using only global shortwave radiation.
 
 
|-
 
|Input Meteorological File ||Input meteorological data specifically formatted to be used in UMEP. This specific format can be created using UMEP -> Pre-processing -> Meteorological data -> Prepare existing data. A dataset with '''hourly''' time resolution should be used for SEBE, preferably at least '''one year in length'''. The time should be in [http://urban-climate.net/umep/UMEP_Manual#Abbreviations LST] for the specific location to be modelled. Multiple years can also be used to improve the model outcome. Model output is dependent on the meteorological input data so if a short dataset is used, potential solar energy would be valid for that particular time period only.
 
 
Mandatory data is global shortwave radiation, but the model will perform best if also diffuse and direct components are available.
 
 
The direct radiation component used as input in the SOLWEIG model is not the direct shortwave radiation on a horizontal surface but on a surface perpendicular to the light source. Hence, the relationship between global radiation and the two separate components are:
 
 
Global radiation = direct radiation * sin(h) + diffuse radiation
 
 
where h is the sun altitude. Since diffuse and direct components of short wave radiation is not common data, it is also possible to calculate diffuse and direct shortwave radiation (see above).
 
 
|-
 
|Save Sky Irradiance Distribution ||When the box is ticked in, it is possible to save the radiation distribution from the sky vault calculated from the meteorological file. SEBE first distributes the radiation on 145 sky patches on the sky vault and then generates shadows on the DSMs based on these patches, i.e. the core loop in the model iterates 145 times. For more detailed information on this, see Lindberg et al. (2015).
 
 
|-
 
|Output Folder ||A specified folder where result will be saved should be specified here. One raster showing irradiance on ground and building roofs named Energyyearroof.tif is saved as well as a text file of wall irradiance (Energyyearwall.txt). Also, the ground and building DSM is saved in the output folder to be used later in a SEBE visualization plugin (UMEP -> Post-processing -> Solar Energy -> SEBE (Visualisation)).
 
|-
 
| Run ||This starts the calculations.
 
 
|-
 
|Add Roof and Ground Irradiance Result Raster to Project ||If this is ticked in, '''Energyyearroof.tif''' will be loaded into to the map canvas.
 
 
|-
 
|Close ||This button closes the plugin.
 
 
|-
 
|Output ||As mentioned earlier, three mandatory datasets are save is the model was successful. The geoTIFF '''Energyyearroof.tif''' show pixel wise total irradiance in kWh. '''Energyyearwall.txt''' show total wall irradiance for each wall column. The column voxel is decided based on the pixel resolution of the input data. Also, the ground and building DSM is saved in the output folder for later use. If the vegetation DSMs were added, one additional file ('''Vegetationdata.txt''') including information of vegetation height and location are also saved. This file is also be used in the SBEB visualization plugin.
 
|-
 
|Example of input data and result ||Input DSM (left) and irradiance image (right) in Gothenburg using data from 1977.
 
 
[[File:SEBE2.jpg| none|Example of Input Data and the Resulting Irradiance Image in Gothenburg (1977)]]
 
|-
 
| Remarks ||
 
 
* All DSMs need to have the same extent and pixel size.
 
* This plugin is computationally intensive i.e. large grids will take a lot of time and very large grids will not be possible to use. Large grids e.g. larger than 4000000 pixels should be tiled before.
 
 
|-
 
|References||
 
 
* Konarska J, Lindberg F, Larsson A, Thorsson S, Holmer B 2013. Transmissivity of solar radiation through crowns of single urban trees—application for outdoor thermal comfort modelling. Theoret. Appl. Climatol., 1–14 [http://link.springer.com/article/10.1007/s00704-013-1000-3 Link to Paper]
 
* Lindberg, F., Jonsson, P. & Honjo, T. and Wästberg, D. (2015) Solar energy on building envelopes - 3D modelling in a 2D environment. Solar Energy. 115 (2015) 369–378 [http://www.sciencedirect.com/science/article/pii/S0038092X15001164 Link to Paper]
 
* Reindl DT, Beckman WA, Duffie JA (1990) Diffuse fraction correlation. Sol Energy 45:1–7. [http://www.sciencedirect.com/science/article/pii/0038092X9090060P Link to paper]
 
|}
 
  
 
==Post-Processor==
 
==Post-Processor==

Revision as of 14:51, 11 July 2018

New manual Homepage

https://umep-docs.readthedocs.io/en/latest/

UMEP: How to Cite

Please use the reference below when UMEP is used:

Lindberg F, Grimmond CSB, Gabey A, Huang B, Kent CW, Sun T, Theeuwes N, Järvi L, Ward H, Capel-Timms I, Chang YY, Jonsson P, Krave N, Liu D, Meyer D, Olofson F, Tan JG, Wästberg D, Xue L, Zhang Z (2017) Urban Multi-scale Environmental Predictor (UMEP) - An integrated tool for city-based climate services.  Environmental Modelling and Software https://doi.org/10.1016/j.envsoft.2017.09.020

The manual should be cited as:

Lindberg F, Grimmond CSB, A Gabey, L Jarvi, CW Kent, N Krave, T Sun, N Wallenberg, HC Ward (2017) Urban Multi-scale Environmental Predictor (UMEP) Manual. http://urban-climate.net/umep/UMEP_Manual University of Reading UK, University of Gothenburg Sweden, SIMS China

=

=

Post-Processor

Solar Radiation: SEBE (Visualisation)

Contributor Niklas Krave (Gothenburg)
Introduction The SEBE (Visualisation) plugin can be used to visulise 3D output from model results generated by the SEBE plugin.
Location

The Shadow Generator is located at

  • UMEP
    • Post-Processor
      • Solar Radiation
        • SEBE (Visualisation)
Dialog box
Dialog for the SEBE (Visualisation) plugin
Dialog sections
top Canvas for visualisation
bottom Input data and settings
Select input folder The directory where results from a previous model run in SEBE is located.
Area of visualisation When this pushbutton is clicked, a recanglge can be drawn on the map canvas. This is the area that will be visulised.
Visulise When this button is clicked, the selected rectangular area will be visulised in the SEBE (visualisation) canvas at the top of the GUI.
Close This closes the plugin.

Outdoor Thermal Comfort: SOLWEIG Analyzer

Contributor Fredrik Lindberg (Gothenburg)
Introduction The SOLWEIG Analyzer plugin can be used to make basic analysis of model results generated by the SOLWEIG plugin.
Location

The SOLWEIG Analyzer is located at

  • UMEP
    • Post-Processor
      • Outdoor Thermal Comfort
        • SOLWEIG Analyzer
Dialog box
Dialog for the SOLWEIG Analyzer plugin
Dialog sections
top Input data is specified
left Plotting of time series derived from Points of Interest during model calculations in SOLWEIG
bottom Analysis of spatial results from model calculations in SOLWEIG
Load model result The directory where results from a previous model run in SOLWEIG is located.
Point of Interest data
POIs available Here, a list of all available POI files are listed. Specify one of the POIs. If no variable is available, then no data if found in the Model output folder.
Variable Specify one of the available variables to plot.
Add another POI / variable Tick this in to add another variable in the plot.
Scatterplot Tick this in to generate a scatterplot between the two variables specified above.
Plot Plot the data selected above
Spatial data
Variable to visualize Select a listed variable to process. If no variable is available, then no data if found in the Model output folder.
Show animation This produces a time-related animation of the selected variable scaled based on the settings to the left in the GUI.
Exclude building pixels Tick this in to exclude building pixels using a building grid generated from the SOLWEIG run. The building grid must have the same extent and pixel resolution as the generated output maps in the model output folder.
Diurnal average Tick this in to include all grids for the selected variable to derive a pixelwise average.
Daytime average Tick this in to include all daytime grids for the selected variable to derive a pixelwise average.
Nightime average Tick this in to include all nighttime grids for the selected variable to derive a pixelwise average.
Maximum Tick this in to get the pixelwise maximum for the selected variable.
Minimum Tick this in to get the pixelwise minimum for the selected variable.
Average of specific time of day The average of the selected time of day for the variable selected is generated. If 'Not Specified' is highlighted, no grid will be generated.
Maximum of specific time of day The maximum of the selected time of day for the variable selected is generated. If 'Not Specified' is highlighted, no grid will be generated.
Minimum of specific time of day The minimum of the selected time of day for the variable selected is generated. If 'Not Specified' is highlighted, no grid will be generated.
Tmrt: Percent of time above threshold (degC) If Tmrt is the selected variable, this box become active and calculates the percent of time that Tmrt for each is above the threshold specified to the right.
Tmrt: Percent of time below threshold (degC) If Tmrt is the selected variable, this box become active and calculates the percent of time that Tmrt for each is below the threshold specified to the right.
Output folder Directory where the results specified above will be saved.
Add analysis to map canvas All analysis specified above will be added to the map canvas if this box is ticked in.
Generate Starts the spatial processing/analysis.
Close This closes the plugin.

Urban Energy Balance: SUEWS Analyser

Contributor Fredrik Lindberg (Gothenburg)
Introduction The SUEWS Analyzer plugin can be used to make basic analysis of model results generated by the SUEWS Simple and SUEWS Advanced plugins.
Location

The SUEWS Analyzer is located at

  • UMEP
    • Post-Processor
      • Urban Energy Balance
        • SUEWS Analyzer
Dialog box
Dialog for the SUEWS Analyzer plugin
Dialog sections
top Model results to be analyzer is specified.
left Plotting of time series derived from Points of Interest during model calculations in SUEWS
bottom Analysis of spatial results from model calculations in SUEWS
Load model result A namelist (RunControl.nml) used for the model run should be specified. This can be located in the suewsmodel directory found as a sub-directory of the UMEP-plugin directory. Note that the namelist includes information on the last model run performed.
Point data
Grid Here, a list of all available modeled grids are listed. Specify one of the grid IDs. If no grid is available, then no data if found in the model output folder.
Year to investigate Specify one of the available years to plot.
Plot basic data Tick this in to plot a summary of the most essential output variables.
Time Period (DOY) Specify the time period to plot.
Variable Specify one of the available variables to plot.
Include another variable Tick this in to add another variable in the plot.
Grid Here, a list of all available modeled grids are listed. Specify one of the grid IDs. If no grid is available, then no data if found in the model output folder.
Variable Specify one of the available variables to plot.
Scatterplot Tick this in to generate a scatterplot between the two variables specified above.
Plot Plot the data selected above
Spatial data
Variable to analyze Select a listed variable to process. If no variable is available, then no data if found in the Model output folder.
Year to investigate Specify one of the available years to plot.
Time Period (DOY) Specify the time period to plot.
Average Tick this in to derive a grid-wise average.
Maximum Tick this in to derive a grid-wise maximum.
Minimum Tick this in to derive a grid-wise minimum.
Median Tick this in to derive a grid-wise median value.
IQR Tick this in to derive a grid-wise interquartile range.
Diurnal Tick this in to include diurnal (all) data.
Daytime Tick this in to include daytime data.
Nightime Tick this in to include nighttime data.
Vector polygon grid used in the SUEWS model Specify the grid that was used to generate the input data to the SUEWS model run of interest.
ID Specify the attribute ID used to generate the input data to the SUEWS model run of interest.
Add result to polygon grid Tick this box to add the results in the attribute table of the grid specified.
Save of GeoTIFF Tick this in to generate a raster grid from the analyze settings specified.
Irregular grid (not squared) Tick this in if a grid is irregular i.e. not squared and aligned north to south.
Pixel resolution (m) When a irregular grid is used, a pixel resolution in meters must be specified.
Output filename Name of the GeoTIFF to be saved.
Add analysis to map canvas All analysis specified above will be added to the map canvas if this box is ticked in.
Generate Starts the spatial processing/analysis.
Close This closes the plugin.

Benchmark System

Contributors

Ting Sun (Reading), Sue Grimmond (Reading)

Overview

Note: the current version runs in a command-line interface (CLI) driven by Python and the GUI-based version is under construction.

The Benchmark System for SUEWS (BSS) can be used with SUEWS to assess the model performance between different configurations and model generations. BSS is written in Python and shipped with an example namelist and an MS Excel spreadsheet for header lookup between different SUEWS versions.

Location

The SUEWS Analyzer is located at

  • UMEP
    • Post-Processor
      • Benchmark
Benchmark results

Two types of metrics are provided:

Alt text
Figure 1: BSS results for (a) the overall performance and (b) a specific statistics (e.g., RMSE)
  • overall performance score: a score between 0 and 100 with larger score denoting better overall performance
  • specific statistics: a range of statistics, including Mean absolute error (MAE), root mean square error (RMSE), standard deviation (Std), etc., to indicate detailed performance in specific variables.

The users can use the overall performance score to get the performance overview of all configurations (Fig. 1a) and specific statistics to examine the performance details (Fig. 1b).

Usage
Figure 2: Required file organisation by BSS.

To use BSS, in addition to the mandatory BSS files (i.e., Benchmark_SUEWS.py, benchmark.nml and head-2016to2017.xlsx), the SUEWS output results are required to be placed in a separate folder (e.g., “input”) that contains the sub-folders of results produced by different configurations. A sample layout of the BSS test case refers to Fig. 2. It must be noted that the output files to be benchmarked should be of consistent temporal organisation (i.e., identical length and resolution) while the headers of different files are not necessarily to be identical as BSS will handle the header inconsistency automatically. Besides, two sub-folders, "base" and "ref", which contain the baseline results to be tested against and reference results to be compared with, respectively, must exist otherwise the BSS will stop.

When the SUEWS output files are prepared, the namelist (i.e., benchmark.nml) needs to be set for the benchmarking. The benchmark namelist is fairly self-explanatory and consists two sections, "file" and "benchmark", to play with. One tip is about the variable list (i.e., var_list): if one non-string value is set (e.g., 123, 3.2, etc.), all valid variables will be included in the benchmarking. Then the user can execute the Benchmark_SUEWS.py script and a PDF file with benchmark results will be generated (e.g., benchmark.pdf in Fig. 2).

Namelist: benchmark.nml

The benchmark namelist is fairly self-explanatory and consists two sections, "file" and "benchmark", to play with.

One tip is about the variable list (i.e., var_list): if one non-string value is set (e.g., 123, 3.2, etc.), all valid variables will be included in the benchmarking.

A sample namelist is as follows:

&file
  input_dir = 'input'
  output_pdf = 'benchmark'
/
&benchmark
  list_var='QN' 'QS' 'QE' 'QH'
  list_metric='MAE' 'MBE' 'RMSE'
  method_score=1 ! not used yet
/




People Involved & Acknowledgements

Group Institution & Support Acknowledged Team
Sue Grimmond University of Reading, UK
Met Office/Newton Fund CSSP - China
NERC TRUC NERC ClearfLo
EPSRC LoHCool EPSRC PhD Studentships
EUf7 Bridge EUf7 emBRACE
H2020 UrbanFluxes NERC Case Studentship
Christoph W. Kent
Helen Ward
Ting Sun
Izzy Capel-Timms
Andy Gabey
Bei HUANG
Fredrik Lindberg University of Gothenburg, Sweden
H2020 UrbanFluxes
FORMAS Climplan
Frans Olofsson
Niklas Krave
Shiho Onomura
Leena Järvi University of Helsinki, Finland
Maj and Tor Nessling foundation
Academy of Finland
EUf7 Bridge
Tom Kokkonen
Jian Guo Tan Shanghai Institute of Meteorological Sciences, SMS, CMA, China
Yuan Yong Chang
Dongwei Liu
XY Ao

Tutorials

To help users getting started with UMEP, the community is working on setting up tutorials and instructions for different parts of the UMEP tool. The following gives what are available and planned.

Topic Parts of UMEP Name Application
Source Area Footprint Pre-Processor Footprint Interpretation of eddy covariance flux source areas
Urban energy balance Processor Introduction to SUEWS Energy, water and radiation fluxes
Urban energy balance Pre-Processor and Processor SUEWS Advanced Energy, water and radiation fluxes
Potential solar energy production on building envelopes Processor and Post-Processor SEBE Amount of solar energy received on building facets
Outdoor thermal comfort Pre-Processor and Processor Introduction to SOLWEIG Mean radiation temperature modelling in complex urban settings
Anthropogenic heat Processor GQF Anthropogenic heat modelling for the greater London area using GQF (uses the GreaterQF methodology)
Anthropogenic heat Processor LQF Anthropogenic heat modelling in London using LQF (uses the LUCY methodology)

How to Contribute

UMEP is an an open source tool that we are keen to get others inputs and contributions. There are two main ways to contribute:

  1. Submit comments or issues to the repository
  2. Participate in Coding or adding new features.
  3. Create new tutorials for the UMEP-plugin.

Reporting a Bug

  • As a good citizen of the open source community please report bugs. If it is a UMEP plugin related issue - report this to the https://bitbucket.org/fredrik_ucg/umep/issues UMEP plugin. You can see if your bug is already reported. In order for the UMEP team to solve your issue as easy as fast as possible, please provide a full description of the problem including steps to repeat it. The more info given, the easier it is for us to solve your issues.
  • Please have a look at Known Issues and FAQ (found below) before submitting an issue to the repository.
  • A bug may also be caused by QGIS. By reporting bugs (and also maybe helping out to solve them) is essential to the open source community. At [www.qgis.org www.qgis.org] you can find out more on what you can do to get involved.
  • QGIS: how to report a QGIS issue: http://qgis.org/en/site/getinvolved/development/index.html#qgis-bugreporting.

Known Issues

  • QGIS (27/September/2017) had an issue using gdal which causes QGIS to create a minidump when the software is closed. This issue has now been fixed (issue #13061). Other issues found should be reported to our repository.
  • UMEP plugin is not compatible with matplotlib versions 2.x. Use instead 1.5.x. (23/August/2017)
  • Mac users might have issue pointing at non-existing directories. Work around is to manually create directories before starting any UMEP-process.
  • Only use standard English alpha-numeric characters (e.g. no space, å, % etc.)
  • Issues has been reported using .sdat rasters. GeoTiff are recommended.

FAQ (Frequently Asked Questions)

Question Answer
How do I upgrade the plugin? When a new LTR version is released it will be available from the repository. In QGIS to check for updates, go to Plugins>Manage and Install Plugins....

If the UMEP plugin is in bold, a new version is available. On how to upgrade to the development version, see Getting started.

How do I uninstall the plugin? Go to Plugins>Manage and Install Plugins.... Locate the UMEP plugin and click Uninstall.
How do I install other python packages (e.g. pandas) as well as other libraries not included in the Desktop Express Install of QGIS? Follow the instruction from this link.
MY new raster is just black after using e.g. the Wall Height and Aspect plugin. What is wrong? Probably nothing. Is is just QGIS that scales the a loaded raster by excluding outliers and if you have large areas with e.g. zeros (which you have in the resulting raster from this plugin) it looks like there is only zeros in your new raster. Go to properties of your new raster layers and reclassify your values that should visualized.
Can the UMEP-plugin be used when Nodata-values are present in the input rasters? Yes, it can but we strongly recommend you to reclassify Nodata values to e.g. 0 before using them in UMEP. Here is a forum discussion that can help: https://gis.stackexchange.com/questions/12418/redefining-nodata-value-into-zero-in-qgis
Why is UMEP having problems saving output files? Check that your path contains only English characters. For Mac users: the UMEP graphical interface will occasionally want to create a folder instead of selecting a folder. In this case in Save As: write the folder name you would like to save your output, press Save, when it asks “...folder name...” already exists. Do you want to replace it? press Replace.
How is frontal area index calculated in Image Morphometric Parameters plugins? Our method is only using one line through the center of the grid for each wind direction. This is because we rotate the DSM and hence it is only the center line that includes height information. We do this since we are using a pure raster-based approach and if we were to instead rotate the search direction vector we would end up with different lengths for each wind direction. If you want to investigate a certain wind direction I suggest that you use a section of wind directions; e.g. 45 degrees.
How do I report a bug? Report it at the repository
What can UMEP do? Tool Architecture provides an overview
Who has developed this? People involved in development
What are the development guidelines? http://urban-climate.net/umep/DevelopmentGuidelines
How can I uninstall QGIS?
Uninstall.png

Uninstalling QGIS on a Windows PC is not done via the Control Panel as most other software. To uninstall completely, start the OSGeo4W setup (found in your start menu) and choose Advanced install. Continue until you come up to the window where you can add, remove and upgrade the different packages in your QGIS installation. Click on the small wheel with two arrows next to Desktop until Uninstall is seen. This removes shortcuts and most of the files related to QGIS. However, not all OSGeo products are removed. IF you want remove everything, open your File Explorer and remove the folder manually where you installed the OSGEO products (usually under C:\OSGeo4W64).

How do I ask other questions? There is an email list. Or you can ask them at the repository

Abbreviations

Acronym Defintion Comments
CDSM Canopy Digital Surface Model A vegetation raster grid where vegetation heights is given in meter above ground level. Pixels with no vegetation should be zero.
CRS Coordinate Reference System
CRU Climatic Research Unit
DEM Digtial Elevation Model Here, same definition as DTM.
DSM Digital Surface Model A raster grid including both buildings and ground given in meter above sea level.
DTM Digtial Terrain Model A raster grid including only ground heights given in meter above sea level.
ECMWF European Centre for Medium-Range Weather Forecasts
GIS Geographical Information System
LCZ Local Climate Zone
LST Local Standard Time
LTR Long term release
LUCY Large scale Urban Consumption of energy model
m agl metres above ground level
m asl metres above sea level
OTF On the Fly Used in QGIS when different geodatasets with different coordinate systems are projected in the same automatically.
QF Anthropogenic heat flux
SEBE Solar Energy on Building Envelopes
SOLWEIG Solar and longwave environmental irradiance geometry model
SUEWS Surface urban energy and water balance scheme
SVF Sky View Factor
TDSM Trunk zone Digital Surface Model A raster grid specifying the height up to the buttom of a vegetation canopy in meter above ground level. Pixels with no trunk height should be zero.
UMEP Urban Multi-scale Environmental Predictor
WFDEI WATCH Forcing Data methodology applied to ERA-Interim data
WUDAPT The World Urban Database and Access Portal Tools