Abstract
Two urban schemes within the Joint UK Land Environment Simulator (JULES) are evaluated offline against multi-year flux observations in the densely built-up city centre of London and in suburban Swindon (UK): (i) the 1-tile slab model, used in climate simulations; (ii) the 2-tile canopy model MORUSES (Met Office–Reading Urban Surface Exchange Scheme), used for numerical weather prediction over the UK. Offline, both models perform better at the suburban site, where differences between the urban schemes are less pronounced due to larger vegetation fractions. At both sites, the outgoing short- and longwave radiation is more accurately represented than the turbulent heat fluxes. The seasonal variations of model skill are large in London, where the sensible heat flux in autumn and winter is strongly under-predicted if the large city centre magnitudes of anthropogenic heat emissions are not represented. The delayed timing of the sensible heat flux in the 1-tile model in London results in large negative bias in the morning. The partitioning of the urban surface into canyon and roof in MORUSES improves this as the roof tile is modelled with a very low thermal inertia, but phase and amplitude of the grid box-averaged flux critically depend on accurate knowledge of the plan-area fractions of streets and buildings. Not representing non-urban land cover (e.g. vegetation, inland water) in London results in severely under-predicted latent heat fluxes. Control runs demonstrate that the skill of both models can be greatly improved by providing accurate land cover and morphology information and using representative anthropogenic heat emissions, which is essential if the model output is intended to inform integrated urban services.
Highlights
As urbanisation levels and urban populations continue to grow (United Nations 2018), there is an increasing need for urban climate services (Baklanov et al 2018)
We focus on the following questions: 1. What are the implications of urban land-surface models (ULSM) options, together with resolution and accuracy of ancillary information, in current Unified Model (UM)–Joint UK Land Environment Simulator (JULES) modelling environments used for numerical weather prediction (NWP) and climate simulations?
Simulations based on the JULES science configurations and ancillaries used in the UM for regional NWP (JULES–UKV; 1.5 km resolution) and global high-resolution (∼10 km) climate simulations (HadGEM; JULES–GL7.0) are compared with control runs that use model parameters derived from observations and highresolution (∼1 m) GIS data and more representative QF
Summary
As urbanisation levels and urban populations continue to grow (United Nations 2018), there is an increasing need for urban climate services (Baklanov et al 2018). Prep.) that are similar to coarse resolution numerical weather prediction (NWP) applications (e.g. ECMWF; Holm et al 2016). This means that large metropolitan areas like London cover several grid cells (assuming accurate landcover information) and should be represented . To capture the impact of cities on surface–atmosphere interactions, urban land-surface models (ULSM) are used within NWP and climate models. ULSMs provide a solution to the urban surface-energy balance ΔQS is the net storage heat flux that includes the storage of heat within the urban fabric (thermal inertia, CdT∗/dt, where C is the areal capacity and T∗ the surface temperature; Porson et al 2010a), and the ground-heat flux. Net horizontal advection of heat or moisture is included on the right side of Eq 1 if the ULSM is coupled to an atmospheric model
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