A Numerical Simulation of Urban Heat Island Effect in Kunming
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摘要: 本文利用WRF（V3.9.1）模式中耦合Noah/SLUCM方案作为Control试验，研究了土地利用类型（Md04试验）、陆面过程（NoUCM试验）和湖泊（Nolake试验）对城市热岛强度及昆明城市气象要素水平、垂直的时空分布影响。主要结论如下：（1）四个试验城市热岛强度的平均日变化趋势相似，白天城市热岛强度较弱、夜间较强，在20时（北京时，下同）左右达到最大值。城市冠层（湖泊）对城市热岛有较明显的减（增）温，Control-NoUCM（Nolake）试验中，平均日最大差值为−0.79°C（+1.07°C）。（2）从能量平衡方程分析Control-Md04试验，感热（潜热）通量的差值为+46.18（−79.71）W m−2，潜热通量释放大于感热通量的绝对值。Control-NoUCM试验中，感热（潜热）通量的差值为−40.88（+29.60）W m−2；因NoUCM试验未考虑几何建筑物储热与遮挡，太阳辐射大部分被地表所吸收，导致感热通量偏大。（3）四种试验中，15（07）时边界层高度达到最大（小）值。NoUCM（Nolake）试验中城市边界层高度分别降低103 m（32 m）左右，而Md04试验中城市边界层高度增加102 m左右。（4）湖泊（滇池）对城市热岛环流影响的试验表明，湖泊上空垂直运动较弱，但水平方向湖陆风较大，这有利于向城市输送水汽，增加干空气湿度，使城市中空气的水汽含量增加，同时增大潜热能量释放，降低感热通量，减小了垂直温度梯度。Abstract: This paper uses the coupling Noah/Single-layer Urban Canopy scheme coupled with WRF (V3.9.1) model is used as a Control experiment to investigate the effects of land-use type (Md04 experiment), land surface process (NoUCM experiment), and lake (Nolake experiment) on the intensity of urban heat island, and the horizontal and vertical spatial distribution characteristics of urban meteorological elements in Kunming. The following are the main findings: (1) In all four experiments, the average daily variation trend of urban heat island intensity is almost similar. The urban heat island (UHI) intensity is low during the daytime and high at night, peaking at around 2000 BJT (Beijing time). The average daily maximum difference for Control-NoUCM (Nolake) is −0.79°C (+1.07°C). (2) The difference of the sensible heat (latent heat) flux is +46.18 (−79.71) W m−2 based on the energy balance equation analysis of the Control-Md04 experiment, and the release of latent heat flux is greater than the absolute value of the sensible heat flux. In the Control-NoUCM experiment, the sensible heat (latent heat) flux difference is −40.88 (+29.60) W m−2. The NoUCM experiment does not take into account the heat storage and shielding of geometric buildings. The land surface absorbs the majority of solar radiation, resulting in a large absolute value of the sensible heat flux. (3) The boundary layer height reaches its maximum (minimum) value at 1500 (0700) BJT in all four experiments. The height of the urban boundary layer decreased by approximately 103 m (32 m) in NoUCM (Nolake), while it increased by approximately 102 m in Md04 experiment. (4) The numerical simulation results of the influence of the lake (Dianchi lake) on the circulation of urban heat islands show that the vertical movement over the lake is weak, but the horizontal lake-land breeze is strong. The breeze’s circulation benefits from the transportation of water vapor to the city center, which increases the humidity of dry air and enlarges the water vapor content. Furthermore, it increases the release of latent heat flux and reduces the sensible heat flux and the temperature gradient.
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Key words:
- Urban heat island /
- WRF model /
- Urban canopy /
- Land use type /
- Lake land breeze
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图 1 WRF-Noah/SLUCM及NoUCM空间示意图。LH（SH）表示潜（感）热通量，T代表温度，G代表热通量；下标veg、w、g、r分别表示植被、墙面、地面、屋顶；Tc为街道峡谷的气温，Ta表示模式第一层的气温；左侧垂直结构中Zc、Zr、Za分别为街道峡谷、屋顶、模式第一层高度
Figure 1. Space diagram of WRF-Noah/SLUCM and NoUCM. WRF-Noah/SLUCM and NoUCM represent Weather Research and Forecasting model coupled with Noah single layer urban canopy mode and no single layer urban canopy mode added, respectively. LH (SH) is the latent (sensible) heat fluxes; subscripts veg, w, g, r represent the vegetated fraction, wall, ground flux, roof, respectively; Tc, Ta denotes the air temperature (T) for the street canyon and the first level of the atmospheric model; Zc, Zr, Za represent street canyon height, rooftop height, and the first level of the atmospheric model, respectively
图 2 （a）2018年7月18日14时（北京时，下同）NCEP FNL（1°×1°）分析资料500 hPa温度场（彩色阴影，单位：°C）、位势高度场（等值线，单位：dagpm）、风场（箭头，单位：m s−1）；（b）模式的四重嵌套区域和地形高度分布（彩色阴影，单位：m）
Figure 2. (a) Temperature (shadings, units: °C), geopotential height (contours; units: dagpm), and wind (vectors, units: m s−1) at 500 hPa from NCEP FNL (1°×1°) analysis data at 1400 BJT (Beijing time) 18 July 2018; (b) coverage and terrain height (shadings, units: m) of model domains 1, 2, 3 and 4 (denoted by do1, do2, do3, and do4, respectively)
图 3 （a）2004年、（b）2018年do4区域MODIS的土地类型分类。黑、黄、蓝色圆点分别表示城市、近郊、远郊站点，线段AB为图8中垂直剖面的位置
Figure 3. Land types of MODIS (Moderate Resolution Imaging Spectroradiometer) in the do4 area in (a) 2004, (b) 2018. The black, yellow, and blue dots indicate urban, suburban, and outer suburban sites, respectively. The line AB is the vertical cross-section in Fig. 8
图 4 2018年7月17～19日昆明市（a、d、g）城市、（b、e、h）近郊、（c、f、i）远郊站点观测（蓝色线）与模拟（红色线）的（a–c）T2、（d–f）RH、（g–i）V10的小时平均值
Figure 4. (a–c) 2-m temperature (T2), (d–f) relative humidity (RH), (g–i) 10-m wind speed (V10) hourly averaged from observation (obs, blue lines) and simulation (sim, red lines) of average value for Kunming (a, d, g) urban, (b, e, h) suburban, and (c, f, i) outer suburban sites during 17–19 July 2018
图 5 2018年7月17～19日平均的（a）Control、Md04、NoUCM、Nolake试验中城市热岛（UHI）强度的日变化，（b）Control试验与Md04、NoUCM、Nolake试验城市热岛平均日变化的差值
Figure 5. (a) Daily change of urban heat island (UHI) intensity in experiments Control, Md04, NoUCM, and Nolake, (b) differences of the average daily change of UHI between the experiment Control and experiments Md04, NoUCM, Nolake averaged during 17–19 July 2018
图 6 2018年7月17～19日Control试验与（a、c）Md04试验、（b、d）NoUCM试验模拟的（a、b）2 m温度T2（彩色阴影，单位：°C）、（c、d）比湿Q2（彩色阴影，单位：g kg−1）叠加10 m风场V10（箭矢，单位：m s−1）的平均差值
Figure 6. Average differences of 10-m wind V10 (vectors, units: m s−1) and (a, b) 2-m temperature (T2, shadings, units: °C), (c, d) specific humidity (Q2, shadings, units: g kg−1) between the experiment Control and (a, c) experiment Md04, (b, d) experiment NoUCM during 17–19 July 2018
图 7 2018年7月17～19日Control试验与（a、c）Md04试验、（b、d）NoUCM试验模拟的（a、b）感热通量SH（单位：W m−2）、（c、d）潜热通量LH（单位：W m−2）叠加10 m风场V10矢量（箭矢，单位：m s−1）的平均差值
Figure 7. Average differences of 10-m wind V10 (vectors, units: m s−1) and (a, b) sensible heat flux (SH, shadings, units: W m−2), (c, d) latent heat flux (LH, shadings, units: W m−2) between the experiment Control and (a, c) experiment Md04, (b, d) experiment NoUCM during 17–19 July 2018
图 8 2018年7月17～19日（a）四个试验城市区域边界层高度的平均日变化，（b）Control试验与三个试验边界层高度平均日变化的差值，四个试验（c）07时、（d）15时、（e）20时平均湍流动能TKE的垂直廓线
Figure 8. (a) Average daily change in the boundary layer height in the four experiments, (b) differences of average daily change in the boundary layer height between the experiment Control and the three experiments, vertical profiles of the average TKE (turbulent kinetic energy) in the four experiments at (c) 0700 BJT, (d) 1500 BJT, and (e) 2000 BJT 17 to 19 July 2018
图 9 2018年7月18日（a1、a2）06时、（b1、b2）12时、（c1、c2）17时、（d1、d2）22时Control试验（左）与Nolake试验（右）的温度（彩色阴影，单位：°C）、风场（箭矢，单位：m s−1，其中垂直风速扩大5倍）和相对湿度（等值线，单位：%）沿图3b中AB线段的垂直剖面。横坐标上的黑色线、蓝色线、灰色线、绿色线代表城市（urban）、湖泊（water）、农田（corpland）、稀树草原（savannas），白色区域为地形高度
Figure 9. Vertical cross-sections of temperature (shadings, units: °C), wind (vectors, units: m s−1, the vertical wind speed is expanded by 5 times) and relative humidity (color lines; units: %) along the line AB in Fig. 3b for experiment Control (left) and experiment Nolake (right) at (a1, a2) 0600 BJT, (b1, b2) 1200 BJT, (c1, c2) 1700 BJT and (d1, d2) 2200 BJT 18 July 2018. In x-axis, the black line, blue line, gray line, and green line represent the urban, water, cropland, and savannas, respectivey. The white area is the terrain height
图 10 2018年7月17～19日（a、e）06时、（b、f）12时、（c、g）17时、（d、h）22时四个试验城市区域平均（a–d）位温θ的垂直廓线与（e–h）相对湿度RH的垂直廓线
Figure 10. Vertical profiles of the average (a–d) potential temperature (θ) and (e–h) relative humidity (RH) for urban areas in the four experiments at (a, e) 0600 BJT, (b, f) 1200 BJT, (c, g) 1700 BJT, (d, h) 2200 BJT from 17 to 19 July 2018
表 1 数值模拟试验与参数化方案设置
Table 1. Numerical simulation cases and parameterization scheme settings
Control试验 Md04试验 NoUCM试验 Nolake试验 地形数据 MODIS2018 MODIS2004 MODIS2018 MODIS2018
（湖泊替换为农田）城市冠层方案 SLUCM SLUCM 未添加SLUCM SLUCM WRF版本 WRFV3.9.1（以下设置均保持一致） 陆面过程方案 Noah陆面过程（Chen and Dudhia, 2001） 绿洲效应参数 1.5 植被灌溉 夏季（5～9月）每晚21时灌溉 垂直分层 53层（其中2 km以下设置21层） 区域中心经纬度 25.03°N，102.71°E 模拟时间 2018年7月16日08时至19日24时（总积分时长88 h） 四重嵌套网格数
（经向×纬向）第一层：110×110；第二层：154×157；第三层：160×166；第四层：214×232 水平格点分辨率 第一层：13.5 km，第二层：4.5 km，第三层：1.5 km，第四层：0.5 km 初始边界条件 逐6 h的NCEP再分析资料（1°×1°） 微物理过程方案 WSM3微物理方案（Hong et al., 2004） 长波辐射过程方案 RRTM长波辐射方案（Mlawer et al., 1997） 短波辐射过程方案 Dudhia方案（Dudhia, 1989） 边界层方案 MYJ边界层方案（Janjić, 2002） 积云对流方案 Kain-Fritsch方案（Kain and Fritsch, 1993） （第一层嵌套使用） 
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表 2 10个气象观测站点信息与2018年7月17～19日平均的2 m气温、相对湿度、10 m风速的统计值
Table 2. Information from ten meteorological observation stations and statistical index values of 2-m temperature, relative humidity, and 10-m wind speed during 17–19 July 2018
站名 海拔高度/m 经度（°N） 纬度（°E） 2 m气温 相对湿度 10 m风速 Ro RMSE/°C R Ro RMSE R Ro RMSE/m s−1 R 昆明 1888 25.00 102.65 1.33 1.45 0.92 1.35 15.88% 0.85 1.42 1.59 0.41 安宁 1848 24.92 102.50 1.07 0.80 0.98 1.05 7.63% 0.95 1.20 1.25 0.60 呈贡 1976.6 24.90 102.82 1.21 1.29 0.95 1.26 6.37% 0.92 1.28 1.49 0.56 富民 1692.7 25.23 102.50 0.81 1.54 0.97 0.66 12.08% 0.94 1.59 1.59 0.60 嵩明 1919.7 25.35 103.08 0.91 1.05 0.96 0.81 9.48% 0.87 1.58 1.50 0.36 晋宁 1893.1 24.68 102.57 1.05 1.32 0.95 1.09 6.62% 0.93 1.01 1.81 0.49 宜良 1532.5 24.92 103.17 0.97 1.20 0.94 0.83 7.66% 0.85 1.22 1.56 0.29 寻甸 1873.2 25.52 103.27 0.89 1.45 0.94 0.77 8.96% 0.87 1.05 1.19 0.56 石林 1695.8 24.75 103.27 1.00 1.48 0.93 1.03 6.47% 0.91 0.97 1.14 0.61 禄劝 1750.9 25.55 102.45 0.90 1.44 0.94 0.69 13.30% 0.93 1.63 1.62 0.31 注：Ro、RMSE、R分别表示模拟与观测的标准差之比、均方根误差、相关系数。
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