Update (August 2016) The Urb-ADAPT modelling approach

Update from WP2 / WP3 – Devising a Modelling Approach for identifying climate risk

In a previous post, the treatment of the land cover included in Urb-ADAPT was outlined, in this post, we outline the overall modelling approach for the Urb-ADAPT project.

To recap the previous post: the CORINE land cover classification was modified to simplify non-urban land cover while maintaining the same level of detail for urban land cover. As a result, we identified 11 land use classes for our region of interest:

Urban
1. Dense
2. Sparse
3. Industrial
4. Paved
Non-Urban
5. Coniferous Trees
6. Deciduous Trees
7. Grass
8. Mixed Trees
9. Soils
10. Water
11. Wet Soils

The urban land cover classes used in the Urb-ADAPT project are loosely associated with the “local climate zone” classification scheme of Stewart and Oke (2012)  and have been applied in Dublin previously by Alexander and Mills (2014). It has been shown that the Dense (LCZ 2) Sparse (LCZ 6) and Industrial (LCZ 8) zones collectively capture 2/3rd of the types of urban areas found in Dublin city and immediate surroundings.

Having defined how the urban area is treated within the Urb-ADAPT project, the next step is to devise a modeling approach (based on available data – Work Package 2) to identify:

1. The present level of exposure to heat-hazard

2. Potential future exposure to heat-hazard.

From this, we are able to generate hazard/risk maps for the present situation and under climate change. The modelling approach to achieve this is outlined below:

Simple_Model_Overview-page-001

  1. Forcing Data – Hourly meteorological data for the period 2000-2015 obtained from Dublin Airport (WMO standard station) is used to characterise the present meso-scale climate (2020s) Future projections of climate (derived from dynamical downscaling of different global climate models (e.g. HadGEM2-ES, EC-Earth) using regional climate models (e.g. CLM4, WRF) are used to assess the impact of climate change on present day exposure levels. The future data are obtained at 3 hourly intervals, so a weather generator is used to obtain hourly values
  2. These data are used to force a Land Surface Scheme (LSS) / Urban Energy Budget (UEB) Model – the Surface Urban Energy and Water Balance Scheme (SUEWS – Järvi et al. 2011) which is based upon the urban energy budget (a separate post explaining this will be made available shortly!)
  3. The produces an energy budget for our 11 land use classes – these are used as inputs for an Analytical Heat Different Model (AHDM) which relates the various components of the UEB model to air temperature – this provides an estimate of air temperature for each 1x1km
  4. However, the air temperature estimate assumes that the underlying surface is flat, which for Dublin city is appropriate given its is generally flat landscape. However since we include complex topography south of the city, it is important to correct these air temperatures for differences in elevation. A very high resolution (20m) digital terrain model is used to correct air temperature estimates for the effect of topography. The lapse rate is based on spatial correlation between the DTM and observed air temperatures for the period 1981-2010 obtained from Met Éireann (2012)
  5. These corrected air temperatures are used to evaluate model performance using a suite of meteorological stations located across the region of interest, these data are also used as an input for the Radiation on the Human Body (RayMan – Matzarakis et al. 2007) model, which calculates Mean Radiant Temperatures and Physiological Equivalent Temperature for each of our land cover types.

More updates on the modelling approach will follow in the coming months.

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