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昆明城市热岛效应的数值模拟研究

周晓宇 王咏薇 孙绩华 段玮 杨大虎

周晓宇, 王咏薇, 孙绩华, 等. 2022. 昆明城市热岛效应的数值模拟研究[J]. 大气科学, 46(4): 921−935 doi: 10.3878/j.issn.1006-9895.2105.21062
引用本文: 周晓宇, 王咏薇, 孙绩华, 等. 2022. 昆明城市热岛效应的数值模拟研究[J]. 大气科学, 46(4): 921−935 doi: 10.3878/j.issn.1006-9895.2105.21062
ZHOU Xiaoyu, WANG Yongwei, SUN Jihua, et al. 2022. A Numerical Simulation of Urban Heat Island Effect in Kunming [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(4): 921−935 doi: 10.3878/j.issn.1006-9895.2105.21062
Citation: ZHOU Xiaoyu, WANG Yongwei, SUN Jihua, et al. 2022. A Numerical Simulation of Urban Heat Island Effect in Kunming [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 46(4): 921−935 doi: 10.3878/j.issn.1006-9895.2105.21062

昆明城市热岛效应的数值模拟研究

doi: 10.3878/j.issn.1006-9895.2105.21062
基金项目: 第二次青藏高原综合科学考察研究项目2019QZKK0105
详细信息
    作者简介:

    周晓宇,男,1992年出生,硕士研究生,主要从事大气边界层与大气环境研究。E-mail: zxy245144672@163.com

  • 中图分类号: P401

A Numerical Simulation of Urban Heat Island Effect in Kunming

Funds: Second Comprehensive Scientific Research Project of Qinghai Tibet Plateau (Grant 2019QZKK0105)
  • 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。
  • 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ZcZrZa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MODIS2018MODIS2004MODIS2018MODIS2018
    (湖泊替换为农田)
    城市冠层方案SLUCMSLUCM未添加SLUCMSLUCM
    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)
    下载: 导出CSV

    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
    RoRMSE/°CRRoRMSERRoRMSE/m s−1R
    昆明188825.00102.651.331.450.921.3515.88%0.851.421.590.41
    安宁184824.92102.501.070.800.981.057.63%0.951.201.250.60
    呈贡1976.624.90102.821.211.290.951.266.37%0.921.281.490.56
    富民1692.725.23102.500.811.540.970.6612.08%0.941.591.590.60
    嵩明1919.725.35103.080.911.050.960.819.48%0.871.581.500.36
    晋宁1893.124.68102.571.051.320.951.096.62%0.931.011.810.49
    宜良1532.524.92103.170.971.200.940.837.66%0.851.221.560.29
    寻甸1873.225.52103.270.891.450.940.778.96%0.871.051.190.56
    石林1695.824.75103.271.001.480.931.036.47%0.910.971.140.61
    禄劝1750.925.55102.450.901.440.940.6913.30%0.931.631.620.31
    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。
    下载: 导出CSV
  • [1] Chen F, Dudhia J. 2001. Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part II: Preliminary model validation [J]. Mon. Wea. Rev., 129(4): 587−604. doi: 10.1175/1520-0493(2001)129<0587:CAALSH>2.0.CO;2
    [2] Chen F, Manning K W, Lemone M A, et al. 2007. Description and evaluation of the characteristics of the NCAR high-resolution land data assimilation system [J]. J. Appl. Meteor. Climatol., 46(6): 694−713. doi: 10.1175/JAM2463.1
    [3] Chen F, Yang X, Zhu W, et al. 2014. WRF simulations of urban heat island under hot-weather synoptic conditions: The case study of Hangzhou City, China [J]. Atmospheric Research. 138(2014): 364–377. doi:10.1016/j.atmosres.2013.12.005
    [4] 陈艳, 段旭, 董文杰, 等. 2012. 昆明地区城市热岛效应的再分析 [J]. 高原气象, 31(6): 1753−1760.

    Chen Yan, Duan Xu, Dong Wenjie, et al. 2012. Reanalysis on the urban heat island effect in Kunming [J]. Plateau Meteor. (in Chinese), 31(6): 1753−1760.
    [5] D’ Amour C B, Reitsma F, Baiocchi G, et al. 2017. Future urban land expansion and implications for global croplands [J]. Proc. Natl. Acad. Sci. USA, 114(34): 8939−8944. doi: 10.1073/pnas.1606036114
    [6] De Meij A, Vinuesa J F. 2014. Impact of SRTM and corine land cover data on meteorological parameters using WRF [J]. Atmos. Res., 143: 351−370. doi: 10.1016/j.atmosres.2014.03.004
    [7] 杜云松, 彭珍, 张宁, 等. 2011. 南京地区一次降水过程湍流特征研究[J]. 南京大学学报(自然科学), 47(6): 703–711.

    Du Yunsong, Peng Zhen, Zhang Ning, et al. 2011. Turbulent characteristics of surface layer during a heavy precipitation event over the Nanjing area, eastern China[J]. J. Nanjing Univ Nat. Sci.) (in Chinese), 47(6): 703–711. doi:10.13232/j.cnki.jnju.2011.06.006
    [8] 段旭, 陶云, 段长春. 2011. 云南省细网格气候区划及气候代表站选取 [J]. 大气科学学报, 34(3): 336−342. doi: 10.3969/j.issn.1674-7097.2011.03.010

    Duan Xu, Tao Yun, Duan Changchun. 2011. A fine mesh climate division and the selection of representative climate stations in Yunnan Province [J]. Trans. Atmos. Sci. (in Chinese), 34(3): 336−342. doi: 10.3969/j.issn.1674-7097.2011.03.010
    [9] Dudhia J. 1989. Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model [J]. J. Atmos. Sci., 46(20): 3077−3107. doi: 10.1175/1520-0469(1989)046<3077:NSOCOD>2.0.CO;2
    [10] Giannaros T M, Melas D, Daglis I A, et al. 2013. Numerical study of the urban heat island over Athens (Greece) with the WRF model [J]. Atmos. Environ., 73: 103−111. doi: 10.1016/j.atmosenv.2013.02.055
    [11] Gogoi P P, Vinoj V, Swain D, et al. 2019. Land use and land cover change effect on surface temperature over eastern India [J]. Sci. Rep., 9(1): 8859. doi: 10.1038/s41598-019-45213-z
    [12] Grimm N B, Faeth S H, Golubiewski N E, et al. 2008. Global change and the ecology of cities [J]. Science, 319(5864): 756−760. doi: 10.1126/science.1150195
    [13] Hong S Y, Dudhia J, Chen S H. 2004. A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation [J]. Mon. Wea. Rev., 132(1): 103−120. doi: 10.1175/1520-0493(2004)132<0103:ARATIM>2.0.CO;2
    [14] Hunt J C, Timoshkina Y V, Bohnenstengel S I, et al. 2013. Implications of climate change for expanding cities worldwide [J]. Proc. Inst. Civil Eng. -Urban Des. Plan., 166(4): 241−254. doi: 10.1680/udap.10.00062
    [15] Janjić Z I. 2002. Nonsingular implementation of the Mellor–Yamada Level 2.5 scheme in the NCEP Meso Model [R]. NCEP Office Note 437.
    [16] Jiang Q O, Tang C C, Ma E J, et al. 2014. Variations of near surface energy balance caused by land cover changes in the semiarid grassland area of China [J]. Adv. Meteor., 2014: 894147. doi: 10.1155/2014/894147
    [17] Kain J S, Fritsch J M. 1993. Convective parameterization for mesoscale models: The Kain-Fritsch scheme [M]//Emanuel K A, Raymond D J. The Representation of Cumulus Convection in Numerical Models. Boston: American Meteorological Society, 165–170. doi:10.1007/978-1-935704-13-3_16
    [18] Kedia S, Bhakare S P, Dwivedi A K, et al. 2021. Estimates of change in surface meteorology and urban heat island over Northwest India: Impact of urbanization [J]. Urban Climate, 36: 100782. doi: 10.1016/j.uclim.2021.100782
    [19] Kolokotroni M, Ren X, Davies M, et al. 2012. London’s urban heat island: Impact on current and future energy consumption in office buildings [J]. Energy Build., 47: 302−311. doi: 10.1016/j.enbuild.2011.12.019
    [20] Kovats R S, Hajat S. 2008. Heat stress and public health: A critical review [J]. Annu. Rev. Public Health, 29: 41−55. doi: 10.1146/annurev.publhealth.29.020907.090843
    [21] Kusaka H, Kimura F. 2004. Coupling a single-layer urban canopy model with a simple atmospheric model: Impact on urban heat island simulation for an idealized case [J]. J. Meteor. Soc. Japan, 82(1): 67−80. doi: 10.2151/jmsj.82.67
    [22] Kusaka H, Kondo H, Kikegawa Y, et al. 2001. A simple single-layer urban canopy model for atmospheric models: Comparison with multi-layer and slab models [J]. Bound. -Layer Meteor., 101(3): 329−358. doi: 10.1023/A:1019207923078
    [23] Liang D, Zuo Y, Huang L S, et al. 2015. Evaluation of the consistency of MODIS land cover product (MCD12Q1) based on Chinese 30 m GlobeLand30 datasets: A case study in Anhui Province, China [J]. ISPRS Int. J. Geo-Inf., 4(4): 2519−2541. doi: 10.3390/ijgi4042519
    [24] Lin C Y, Chen F, Huang J C, et al. 2008. Urban heat island effect and its impact on boundary layer development and land–sea circulation over northern Taiwan [J]. Atmos. Environ., 42(22): 5635−5649. doi: 10.1016/j.atmosenv.2008.03.015
    [25] Liu Z F, He C Y, Zhou Y Y, et al. 2014. How much of the world’s land has been urbanized, really? A hierarchical framework for avoiding confusion [J]. Landscape Ecol., 29(5): 763−771. doi: 10.1007/s10980-014-0034-y
    [26] Miao J F, Chen D, Borne K. 2007. Evaluation and comparison of Noah and Pleim-Xiu Land surface models in MM5 using GÖTE2001 data: Spatial and temporal variations in near-surface air temperature [J]. J. Appl. Meteor. Climatol., 46(10): 1587−1605. doi: 10.1175/JAM2561.1
    [27] Miao S G, Chen F. 2008. Formation of horizontal convective rolls in urban areas [J]. Atmos. Res., 89(3): 298−304. doi: 10.1016/j.atmosres.2008.02.013
    [28] Miao S G, Chen F. 2014. Enhanced modeling of latent heat flux from urban surfaces in the Noah/single-layer urban canopy coupled model [J]. Sci. China Earth Sci., 57(10): 2408−2416. doi: 10.1007/s11430-014-4829-0
    [29] Miao J F, Chen D, Wyser K, et al. 2008. Evaluation of MM5 mesoscale model at local scale for air quality applications over the Swedish west coast: Influence of PBL and LSM parameterizations [J]. Meteor. Atmos. Phys., 99(1-2): 77−103. doi: 10.1007/s00703-007-0267-2
    [30] Miao S G, Chen F, LeMone M A, et al. 2009. An observational and modeling study of characteristics of urban heat island and boundary layer structures in Beijing [J]. J. Appl. Meteor. Climatol., 48(3): 484−501. doi: 10.1175/2008JAMC1909.1
    [31] Mlawer E J, Taubman S J, Brown P D, et al. 1997. Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave [J]. J. Geophys. Res., 102(D14): 16663−16682. doi: 10.1029/97JD00237
    [32] Mora C, Dousset B, Caldwell I R, et al. 2017. Global risk of deadly heat [J]. Nat. Climate Change, 7(7): 501−506. doi: 10.1038/nclimate3322
    [33] Myrup L O. 1969. A numerical model of the urban heat island [J]. J. Appl. Meteor., 8(6): 908−918. doi: 10.1175/1520-0450(1969)008<0908:ANMOTU>2.0.CO;2
    [34] Oke T R. 1979. Advectively-assisted evapotranspiration from irrigated urban vegetation [J]. Bound. -Layer Meteor., 17(2): 167−173. doi: 10.1007/BF00117976
    [35] Oke T R. 1982. The energetic basis of the urban heat island [J]. Quart. J. Roy. Meteor. Soc., 108(455): 1−24. doi: 10.1002/qj.49710845502
    [36] Pielke R A. 1984. Mesoscale Meteorological Modeling [M]. Orlando: Academic Press, 541–599. doi:10.1016/B978-0-08-092526-4.50019-5
    [37] Ramamurthy P, Bou-Zeid E. 2014. Contribution of impervious surfaces to urban evaporation [J]. Water Resour. Res., 50(4): 2889−2902. doi: 10.1002/2013WR013909
    [38] Rizwan A M, Dennis L Y C, Liu C. 2008. A review on the generation, determination and mitigation of urban heat island [J]. J. Environ. Sci., 20(1): 120−128. doi: 10.1016/S1001-0742(8)60019-4
    [39] Roth M. 2007. Review of urban climate research in (sub) tropical regions [J]. Int. J. Climatol., 27(14): 1859−1873. doi: 10.1002/joc.1591
    [40] Sarrat C, Lemonsu A, Masson V, et al. 2006. Impact of urban heat island on regional atmospheric pollution [J]. Atmos. Environ., 40(10): 1743−1758. doi: 10.1016/j.atmosenv.2005.11.037
    [41] Sharma A, Fernando H J S, Hamlet A F, et al. 2017. Urban meteorological modeling using WRF: A sensitivity study [J]. Int. J. Climatol., 37(4): 1885−1900. doi: 10.1002/joc.4819
    [42] Skamarock W C, Klemp J B, Dudhia J, et al. 2008. A description of the advanced research WRF version 3 [R]. No. NCAR/TN-475+STR. doi:10.5065/D68S4MVH
    [43] 孙绩华, 冯健武, 段玮. 2015. 昆明城市热岛效应变化特征研究 [J]. 气候与环境研究, 20(6): 645−653. doi: 10.3878/j.issn.1006-9585.2015.15072

    Sun Jihua, Feng Jianwu, Duan Wei. 2015. Change in the urban heat island effect in Kunming [J]. Climatic Environ. Res. (in Chinese), 20(6): 645−653. doi: 10.3878/j.issn.1006-9585.2015.15072
    [44] Sun T, Bou-Zeid E, Wang Z H, et al. 2013. Hydrometeorological determinants of green roof performance via a vertically-resolved model for heat and water transport [J]. Build. Environ., 60: 211−224. doi: 10.1016/j.buildenv.2012.10.018
    [45] 孙永, 王咏薇, 高阳华, 等. 2019. 复杂地形条件下城市热岛及局地环流特征的数值模拟 [J]. 大气科学学报, 42(2): 280−292. doi: 10.13878/j.cnki.dqkxxb.20180204001

    Sun Yong, Wang Yongwei, Gao Yanghua, et al. 2019. Numerical simulation of urban heat island and local circulation characteristics under complex terrain conditions [J]. Trans. Atmos. Sci. (in Chinese), 42(2): 280−292. doi: 10.13878/j.cnki.dqkxxb.20180204001
    [46] Twine T E, Kucharik C J, Foley J A. 2004. Effects of land cover change on the energy and water balance of the Mississippi River basin [J]. J. Hydrometeorol., 5(4): 640−655. doi: 10.1175/1525-7541(2004)005<0640:EOLCCO>2.0.CO;2
    [47] 伍见军, 王咏薇, 朱彬, 等. 2013. WRF模式中城市冠层参数化方案在重庆气象环境模拟中的性能比较 [J]. 长江流域资源与环境, 22(12): 1627−1634.

    Wu Jianjun, Wang Yongwei, Zhu Bin, et al. 2013. Performance comparison of different urban canopy schemes in WRF model under Chongqing meteorological simulation [J]. Resour. Environ. Yangtze Basin (in Chinese), 22(12): 1627−1634.
    [48] Yang J C, Wang Z H, Chen F, et al. 2015. Enhancing hydrologic modelling in the coupled weather research and forecasting–urban modelling system [J]. Bound. -Layer Meteor., 155(1): 87−109. doi: 10.1007/s10546-014-9991-6
    [49] Yao X W, Wang Z Q, Wang H. 2015. Impact of urbanization and land-use change on surface climate in middle and lower reaches of the Yangtze River, 1988–2008 [J]. Adv. Meteor., 2015: 395094. doi: 10.1155/2015/395094
    [50] Zhang D L, Shou Y X, Dickerson R R. 2009. Upstream urbanization exacerbates urban heat island effects [J]. Geophys. Res. Lett., 36(24): L24401. doi: 10.1029/2009GL041082
    [51] Zhang D L, Shou Y X, Dickerson R R, et al. 2011. Impact of upstream urbanization on the urban heat island effects along the Washington-Baltimore Corridor [J]. J. Appl. Meteor. Climatol., 50(10): 2012−2029. doi: 10.1175/JAMC-D-10-05008.1
    [52] 郑亦佳, 刘树华, 何萍, 等. 2017. 滇中地区夏季城市热岛效应的数值模拟研究 [J]. 北京大学学报(自然科学版), 53(4): 639−651. doi: 10.13209/j.0479-8023.2016.127

    Zheng Yijia, Liu Shuhua, He Ping, et al. 2017. Numerical study of summertime urban heat island in Dianzhong [J]. Acta Scientiarum Naturalium Universitatis Pekinensis (in Chinese), 53(4): 639−651. doi: 10.13209/j.0479-8023.2016.127
    [53] 朱丽, 苗峻峰, 高阳华. 2020. 重庆城市热岛环流结构和湍流特征的数值模拟 [J]. 大气科学, 44(3): 657−678. doi: 10.3878/j.issn.1006-9895.2003.19239

    Zhu Li, Miao Junfeng, Gao Yanghua. 2020. A numerical simulation of urban breeze circulation structure and turbulence in Chongqing [J]. Chinese Journal of Atmospheric Sciences (in Chinese), 44(3): 657−678. doi: 10.3878/j.issn.1006-9895.2003.19239
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出版历程
  • 收稿日期:  2021-04-13
  • 录用日期:  2021-06-23
  • 网络出版日期:  2021-11-18
  • 刊出日期:  2022-07-19

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