Urban geometry and materials combine to create complex spatial, temporal and directional patterns of longwave infrared (LWIR) radiation. Effective anisotropy (or directional variability) of thermal radiance causes remote sensing (RS) derived urban surface temperatures to vary with RS view angles. Here a new and novel method to resolve effective thermal anisotropy processes from LWIR camera observations is demonstrated at the Comprehensive Outdoor Scale MOdel (COSMO) test site. Pixel-level differences of brightness temperatures reach 18.4 K within one hour of a 24-h study period. To understand this variability, the orientation and shadowing of surfaces is explored using the Discrete Anisotropic Radiative Transfer (DART) model and Blender three-dimensional (3D) rendering software. Observed pixels and the entire canopy surface are classified in terms of surface orientation and illumination. To assess the variability of exitant longwave radiation () from the 3D COSMO surface (3), the observations are prescribed based on class. The parameterisation is tested by simulating thermal images using a camera view model to determine camera perspectives of 3 fluxes. The mean brightness temperature differences per image (simulated and observed) are within 0.65 K throughout a 24-h period. Pixel-level comparisons are possible with the high spatial resolution of 3 and DART camera view simulations. At this spatial scale (< 0.10 m), shadow hysteresis, surface sky view factor and building edge effects are not completely resolved by 3. By simulating apparent brightness temperatures from multiple view directions, effective thermal anisotropy of 3 is shown to be up to 6.18 K. The developed methods can be extended to resolve some of the identified sources of sub-facet variability in realistic urban settings. The extension of DART to the interpretation of ground-based RS is shown to be promising. List of symbols and acronyms [units] β, ϕ, ω Euler angles describing a sequence of rotations within the (, ,) coordinate frame BOA Bottom of atmosphere BRF Bidirectional reflectance factor C Non-specific camera COSMO COmprehensive urban Scale MOdel Camera focal plane array size [mm] DART Discrete Anisotropic Radiative Transfer model (Gastellu-Etchegorry et al., 2012) DSM Digital surface model ε Emissivity ↓ Broadband longwave radiation flux (irradiance) downward from sky [W m-2 ] ↓ Broadband shortwave radiation flux (irradiance) downward from sky [W m-2 ] , ↓ 3 Broadband longwave radiation flux (exitance) from discrete points of an urban surface, resolved in 3D [W m-2 ] Camera derived broadband longwave radiation flux (exitance) [W m-2 ] Non-specific broadband longwave radiation flux (exitance) from urban canopy elements [W m-2 ]
34Urbanization modifies atmospheric energy and moisture balances, forming distinct 35 features, e.g., urban heat islands (UHIs) and enhanced or decreased precipitation. 36These produce significant challenges to science and society, including rapid and incudes complex topography with mountains, plains, and coastal areas (Fig. 1a), and 261 seven of the 10 most polluted Chinese cities, with 40% of days during 2013 (mostly in 262 winter) having "very hazardous" air quality (CMEP 2014 adaptation, air quality, planning, and emergency-response management. 298The critical science needed to achieve these goals was identified as increased WUQ), and one rural (SDZ) tower (all PBL observational sites are shown in Fig. 1). 335Other operational PBL sensors ( conditions. Photos of a selection of these instruments and sites are shown in Fig. 2. flown over pre-approved flight paths (Fig. 1) at altitudes from 600 to 3 600 m (at 300 357 m intervals). The aircraft is equipped with atmospheric gas and aerosol instrumenta- Additional observation data (e.g., weather radar, aircraft, and lightning) will be added. BTH area centered on Beijing (a somewhat larger area than in Fig. 1a). 439Additional details on all of these steps are provided by Zhang et al. (2017a (Fig. 1) were used to show that the dominant linear relationship between * and also 494 exists over urban canopies. The strong wind shear from the rough urban surfaces produces 495 turbulence in near neutral urban stability conditions, shown by Bornstein 1968 to exist over 496 NYC, as stable boundary layers over urban canopies are thus hard to maintain. The role of 497 surface roughness on turbulent mixing is also reflected in the increasing slope (Fig. 4) Table 4a shows the average midday (1000-1400 LST) radiative and energy fluxes 515Although MIY has higher outgoing longwave radiation, the net all-wave radiations 516 are nearly equal. Significant differences existed, however, in the surface energy 517 partitions, as IAP has smaller turbulent sensible and latent heat fluxes, and thus a 518 larger (estimated) residual heat storage. Another contributing factor to urban heat 519 storage is its anthropogenic heat flux source (discussed below). 520Daily mean Bowen ratios (ratio of turbulent sensible to latent-heat flux; Table 4b Normalized relative backscatter (NRB) data from two MPL lidar (in a vertical to 545 zenith scan mode) were also used to concurrently estimate midday PBL heights on 11 546August 2015 from 1250-1402 LST, both alone a mobile route (Fig. 1b) and at a fixed 547 site (adjacent to the urban IAP tower). As MPL instruments cannot be absolutely Beijing and fluxes from the 140-m level of the IAP tower (Fig. 1b). The modeling 574 period was 4-11 July 2015, which included dry (6 th -11 th ) and wet (4 th -5 th ) days. 575Results show major improvement for daytime "total" sensible plus latent heat flux 576 values ( Fig. 7a and b), although the timing of its peak was about 2 h too late. The 577 increased latent heat flux during the EC simulation (ac...
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