Anthropogenic heat flux: advisable spatial resolutions when input data are scarce
Anthropogenic heat flux: advisable spatial resolutions when input data are scarce
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DOI：
10.1007/s00704-018-2367-y
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发表时间：
2019-01-01
影响因子：
3.4
通讯作者：
Capel-Timms, I.
中科院分区：
文献类型：
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作者：
Gabey, A. M.;Grimmond, C. S. B.;Capel-Timms, I.
人为热通量（Q(F)）在城市可能是显著的，特别是在低太阳辐照度和夜间。它引起了包括气象学家、城市规划师和气候学家在内的许多从业者的兴趣。精细时空分辨率下的Q(F)估计值可以从使用不同数量经验数据的模式中得出。这项研究比较了欧洲大城市（伦敦）在5亿空间分辨率下的简单模型和详细模型。简单模型（LQF）使用空间分解的人口数据和国家能源统计数据。详细模型（GQF）还使用了当地的能源、道路网络和工作日人口数据。分数技能分数（FSS）和偏差用于评估简单模型从详细模型中再现Q(F)及其子组件的空间模式和大小的技能。在远离市中心和主要道路的90%的城市，LQF的技能一直很好。剩下的10%包含高排放和“热点”，占全市能源总量的30-40%。这种结构的丢失是因为它需要工作日的人口、空间分解的建筑能耗和/或道路网络数据。根据国家数据估计的每日总建筑和交通能耗与当地值相差不超过+/- 40%。逐渐提高到5km的空间分辨率提高了总Q(F)的技能，但当居住人口控制空间变化时，在所有分辨率下都丢失了重要特征（热点、交通网络）。结果表明，简单的Q(F)模型应该以保守的空间分辨率应用于像伦敦这样表现出时变能源使用模式的城市。
Anthropogenic heat flux (Q(F)) may be significant in cities, especially under low solar irradiance and at night. It is of interest to many practitioners including meteorologists, city planners and climatologists. Q(F) estimates at fine temporal and spatial resolution can be derived from models that use varying amounts of empirical data. This study compares simple and detailed models in a European megacity (London) at 500m spatial resolution. The simple model (LQF) uses spatially resolved population data and national energy statistics. The detailed model (GQF) additionally uses local energy, road network and workday population data. The Fractions Skill Score (FSS) and bias are used to rate the skill with which the simple model reproduces the spatial patterns and magnitudes of Q(F), and its sub-components, from the detailed model. LQF skill was consistently good across 90% of the city, away from the centre and major roads. The remaining 10% contained elevated emissions and "hot spots" representing 30-40% of the total city-wide energy. This structure was lost because it requires workday population, spatially resolved building energy consumption and/or road network data. Daily total building and traffic energy consumption estimates from national data were within +/- 40% of local values. Progressively coarser spatial resolutions to 5km improved skill for total Q(F), but important features (hot spots, transport network) were lost at all resolutions when residential population controlled spatial variations. The results demonstrate that simple Q(F) models should be applied with conservative spatial resolution in cities that, like London, exhibit time-varying energy use patterns.