Urban Heat Island - Urban Weather Generator

Introduction

In this tutorial you will generate input data for the Urban Weather Generator and simulate spatial (and temporal) variations of urban heat island (UHI) in Gothenburg, Sweden.

The Urban Weather Generator (UWG) tool is an implementation of the Ladybug application with the same name. The original Urban Weather Generator was developed by Bruno Bueno for his PhD thesis at MIT. Since this time, it has been validated 3 times and has been enhanced by Aiko Nakano. In 2016, Joseph Yang also improved the engine and added a range of building templates. For more detailed information on UWG, follow the links above.

This tutorial makes use of local high resolution detailed spatial data. If this kind of data is unavailable, other datasets derived from e.g. Open Street Map can be exploited. However, it is strongly recommended to go through this tutorial before moving on to more user-specific datasets.

Objectives

To perform and analyse intra urban temperature variations within an area in Gothenburg, Sweden using the Urban Weather Generator.

Initial Steps

UMEP is a Python plugin used in conjunction with QGIS. To install the software and the UMEP plugins see the getting started section in the UMEP manual. For this tutorial you will need both UMEP and UMEP for Processing.

Loading and analyzing the spatial data

All the geodata used in this tutorial can be downloaded from here.

Unzip and place in a folder that you have read and write access to.
Start by loading all the raster and vector datasets into an empty QGIS project. All layers are in SWEREF99 1200 (EPSG:3007).

The order in the Layers Panel determines what layer is visible. You can choose to show a layer (or not) with the tick box. You can modify layers by right-clicking on a layer in the Layers Panel and choose Properties. Note for example that that CDSM (vegetation) is given as height above ground (meter) and that all non-vegetated pixels are set to zero. This makes it hard to get an overview of all 3D objects (buildings and trees). QGIS default styling for a raster is using the 98 percentile of the values. Therefore, not all the range of the data is shown in the layer window to the left.

Right-click on your CDSM layer and go to Properties > Style and choose Singleband pseudocolor with a min value of 0 and max of 35. Choose a colour scheme of your liking.
Go to Transparency and add an additional no data value of 0. Click ok.
Now put your CDSM layer at the top and your DSM layer second in your Layers Panel. Now you can see both buildings and vegetation 3D object in your map canvas.

The land cover grid comes with a specific QGIS style file.

Right-click on the land cover layer (lc_kville) and choose Properties. At the bottom left of the window there is a Style-button. Choose Load Style and open landcoverstyle.qml and click OK.
Make only your land cover class layer visible to examine the spatial variability of the different land cover classes.

The land cover grid has already been classified into the seven different classes used in most UMEP applications (see Land Cover Reclassifier). If you have a land cover dataset that is not UMEP formatted you can use the Land Cover Reclassifier found at UMEP > Pre-processor > Urban Land Cover > Land Cover Reclassifier in the menu-bar to reclassify your data.

Furthermore, a polygon grid (400 m x 400 m) to define the study area and individual grids is included (gridKville.shp). Such a grid can be produced directly from the Processing Toolbox in QGIS (Create Grid) or an external grid can be used.

Load the vector layer gridKville.shp into your QGIS project.
In the Style tab in layer Properties, choose a Simple fill and set Fill style to No Brush, to be able to see the spatial data within each grid.
Also, add the label IDs for the grid to the map canvas in Properties > Labels > Single Labels to make it easier to identify the different grid squares later on in this tutorial.

There is also a vector polygon layer (topologiesKville.shp) describing the different urban topologies within the area. Open the attribute table associated with this layer. Here you see an attribute called urbantype which describes the various urban typologies in the area. This is in Swedish so below you find a translation and description for each type.

Swedish

English

Description

industri

industry

Extensive low buildings

bland

Mixed city

Modern high density residential neighbourhood

slut

Traditional neighbourhood

Early 20th century urban development

miljon

The Million Programme

Mid 20th century modernistic suburban neighbourhood development

folkhem

Nordic Functionalism

low dense early/mid 20th century suburban development

smahus

detached houses

sub-urban residential houses

The typology poloygon layer is used to describe types of buildings which will affect the building energy model within UWG.

Preparing input data

First we need to derive surface fractions etc. from the geodata for each grid. This is similar as done in many other tutorials e.g. Urban Energy Balance - SUEWS Spatial. We start with calculate roughness parameters based on the building geometry within your grids. Open UMEP > Pre-Processor > Urban Morphology > Morphometric Calculator (Grid).

Use the settings as in the figure below and press Run.
When calculation ids done, close the plugin.

Note

For mac users, use this workaround: manually create a directory, go into the folder above and type the folder name. It will give a warning “—folder name–” already exists. Do you want to replace it? Click replace.

none — Fig. 132 The settings for calculating building morphology. Click on image for enlargement.

This operation should have produced 16 different text files; 15 (anisotrophic) that include morphometric parameters from each 5 degree section for each grid and one file (isotropic) that includes averaged values for each of the 15 grids. You can open kv_IMPGrid_isotropic.txt and compare the different values for different grids. Header abbreviations are explained here.

Moving on to land cover fraction calculations for each grid.

Open UMEP > Pre-Processor > Urban Land Cover > Land Cover Fraction (Grid).
Use the settings as in the figure below and press Run.
When calculation is done, close the plugin.

Finally, you need to reclassify the urban typology layer layer into typologies that UWG use.

Open UMEP -> Pre-processor -> Urban Heat Island -> UWG Reclassifier and use the settings below:

Preparing input data for the Urban Weather Generator

Now all input information required is pre-processed apart from the final step which is to create the uwg-files used by the model.

Open UWG Prepare (UMEP > Pre-Processor > Urban Heat Island > UWG prepare) and use the following settings.

Here you can see the various settings that can be modified.

Meteorological forcing data

Before we execute the Urban Weather Generator, meteorological forcing data is required. The UWG make use of Energy Plus Weather (EPW) files (.epw). These files are generated for purposes of building energy simulation and are one full year in length (hourly resolution). However, the UWG can preferably model just a portion of a year and not always a full year which will take long computation time, especially if multiple grids are inverstigated. Information on EWP-files and possible downloads for your location can be found here. In the zip-file downloaded for this tutorial, a .epw file from a nearby airport is availabe. This is a so-called typical meteorological dataset where a typical year in the Gothenburg region is created including natural variation within a year.

Executing the model

Open UMEP -> Processor -> Urban Heat Island: Urban Weather Generator and use the settings below. Before starting the calculations, open the Python Console in QGIS to see a more detailed information from the model while is runs. The period selected is a warm week in June.

Analysing the results

If you take a look in your output folder, you see a number of UMEP-formatted meteorological files which is the output from the model, one for each grid. First, try to plot grid 9 by opening UMEP -> Post Processor -> Urban Heat Island -> UWGAnalyzer and use the settings below beofre clicking Plot:

The result should look something like this:

Finally, you can also make a spatial grid from your model reults, both as a raster of add output to your grid polygon layer. You will add a new attribute to your grid polygon layer. Open the same tool but in UMEP for Processing and use the following settings:

Open the attribute table for your grid and you should have a column called mean. As you can see the differences of nocturnal temperature differences between the airport and any specific grid is about 3.5 degrees celsius. However, the differences between the grids are very small. The reason for this could have many answers but one main explanation is that UWG is not very sensitive to vegetation changes that could create temperature variations within a city. Also, the model seem to be unsensitive to small changes in building density and regional climate. See here for a more detailed investigation on the performance of UWG for the Gothenburg region. The UMEP development team is also adding a new UHI-model (TARGET) into UMEP that is more sensitive to blue and green infrastructure in urban areas.

Tutorial finished.