Spatial and temporal patterns of surface-atmosphere energy exchange in a dense urban environment using scintillometryCrawford, B., Grimmond, C. S. B. ORCID: https://orcid.org/0000-0002-3166-9415, Ward, H. C., Morrison, W. and Kotthaus, S. (2017) Spatial and temporal patterns of surface-atmosphere energy exchange in a dense urban environment using scintillometry. Quarterly Journal of the Royal Meteorological Society, 143 (703). pp. 817-833. ISSN 1477-870X
It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1002/qj.2967 Abstract/SummarySpatially-integrated measurements of the surface energy balance (SEB) are needed in urban areas to evaluate urban climate models and satellite observations. Scintillometers allow observations of sensible heat flux (QH) over much larger areas than techniques such as eddy covariance (EC), however methods are needed to partition between remaining unmeasured SEB terms. This is the first study to use observed spatial and temporal patterns of QH from a scintillometer network to constrain estimates of remaining SEB terms in a dense, heterogeneous urban environment. Results show that QH dominates the surface energy balance in central London throughout the year, with expected diurnal courses and seasonal trends in QH magnitude related to solar radiation input. Measurements also reveal a clear anthropogenic component of QH with winter (summer) weekday QH values 11.7% (5.1%) higher than weekends. Spatially, QH magnitude is correlated with vegetation and building land cover fraction in the measurement source areas. Spatial analysis provides additional evidence of anthropogenic influence with highest weekday/weekend ratios (1.55) from the City of London. Spatial differences are used to estimate horizontal advection and a novel method to estimate monthly latent heat flux is developed based on observed land cover and wet-dry surface variations in normalized QH. Annual anthropogenic heat emissions are estimated to be 46.3 W m−2 using an energy balance residual approach. The methods presented here have potential to significantly enhance understanding of urban areas, particularly in areas with tall buildings where there is little observational data.
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