Urban signals in high-resolution weather and climate simulations: role of urban land-surface characterisation

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 pre- diction 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 varia- tions 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 anthro- pogenic 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 gridbox-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

Arctic Ice Fog:Its Microphysics and Prediction

Home Physics and Chemistry of the Arctic Atmosphere ChapterArctic Ice Fog: Its Microphysics and PredictionDownload book PDFDownload book EPUBArctic Ice Fog: Its Microphysics and PredictionIsmail Gultepe, Andrew J. Heymsfield & Martin Gallagher ChapterFirst Online: 30 January 2020940 Accesses1 CitationsPart of the Springer Polar Sciences book series (SPPS)AbstractIce fog consists of suspended small ice crystals with maximum sizes less than about 200 μm, having similar fall velocities as fog droplets, and that often reduces visibility to less than 1 km. Its formation is strongly dependent on high number concentrations of available heterogeneous ice nuclei (IN) at temperatures (T) > −40 ºC, homogeneous nucleation below −40 ºC, and available moisture in the air. Radiative cooling, advective cooling, and cold air subsidence, particularly over the Polar region or high elevation mountainous geographical regions, play an important role in its formation and development. Ice fog crystals form at cold T when the relative humidity with respect to ice (RHi) is ≥100%. Favorable ice nucleation conditions typically occur at T < −15 ºC and its microphysical characteristics and their evolution needs to be better understood for a physically based representation in numerical forecast models. This is likely to be of growing societal importance due to the known sensitivity of the Arctic environment to climate change. Accidents related to low visibility over the northern latitudes may increase tenfold over the Arctic regions because of increasing population and traffic. This suggests that ice fog conditions can have major impacts on aviation and ground/water-based transportation, as well as on climate change and ecosystem. These open issues, as well as challenges related to ice fog measurements and predictions, are discussed in detail, and its importance for evaluating weather and climate conditions over cold environments are emphasized