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Validation and Spatiotemporal Distribution of GEOS-5–Based Planetary Boundary Layer Height and Relative Humidity in China

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Abstract

Few studies have specifically focused on the validation and spatiotemporal distribution of planetary boundary layer height (PBLH) and relative humidity (RH) data in China. In this analysis, continuous PBLH and surface-level RH data simulated from GEOS-5 between 2004 and 2012, were validated against ground-based observations. Overall, the simulated RH was consistent with the statistical data from meteorological stations, with a correlation coefficient of 0.78 and a slope of 0.9. However, the simulated PBLH was underestimated compared to LIDAR data by a factor of approximately two, which was primarily because of poor simulation in late summer and early autumn. We further examined the spatiotemporal distribution characteristics of two factors in four regions—North China, South China, Northwest China, and the Tibetan Plateau. The results showed that the annual PBLH trends in all regions were fairly moderate but sensitive to solar radiation and precipitation, which explains why the PBLH values were ranked in order from largest to smallest as follows: Tibetan Plateau, Northwest China, North China, and South China. Strong seasonal variation of the PBLH exhibited high values in summer and low values in winter, which was also consistent with the turbulent vertical exchange. Not surprisingly, the highest RH in South China and the lowest RH in desert areas of Northwest China (less than 30%). Seasonally, South China exhibited little variation, whereas Northwest China exhibited its highest humidity in winter and lowest humidity in spring, the maximum values in the other regions were obtained from July to September.

摘要

目前, 很少有研究关注中国地区的边界层高度(PBLH)和相对湿度(RH)的验证及时空分布特征. 本文主要利用地基观测数据分别对GEOS-5在2004-2012年模拟的PBLH和RH进行验证. 结果表明, 模拟的RH与气象台站观测数据集一致性较好, r能达到0.78, 斜率为0.9. 然而, 由于地基激光雷达采样周期处于夏末秋初, 模拟的PBLH至少低估了1倍. 将我国划分为北部, 南部, 西北及青藏四大区域, 从这四个地区的年际和季节变化讨论了PBLH和RH的时空分布特征. 结果表明: PBLH年变化趋势较为平缓, 但受太阳辐射和降雨影响较大, 我国PBLH从高到低分别为青藏, 西北, 北部和南部地区; PBLH季均值呈现夏高冬低的特点, 进一步与湍流垂直变化趋势吻合. RH表现为南部地区相对湿度最大, 而西北干旱的沙漠地区仅在30%以下; 季节尺度上, 南方地区四季差异不大, 西北地区冬季相对湿润, 春季干旱, 北部, 青藏高原地区RH高值多集中在7-9月份.

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References

  • Chen, Z. Y., W. Q. Liu, Y. J. Zhang, N. J. Zhao, and J. Ruan, 2009: Measurements of aerosol distribution by an elastic-backscatter lidar in summer 2008 in Beijing. Chinese Optics Letters, 7, 753–755, https://doi.org/10.3788/COL20090709.0753.

    Article  Google Scholar 

  • Chi, R. L., D.-C. Wu, B. Liu, and J. Zhou, 2009: Dualwavelength mie lidar observations of tropospheric aerosols. Spectroscopy and Spectral Analysis, 29, 1468–1472, https://doi.org/10.3964/j.issn.1000-0593(2009)06-1468-05.

    Google Scholar 

  • Dandou, A., M. Tombrou, K. Schäfer, S. Emeis, A. P. Protonotariou, E. Bossioli, N. Soulakellis, and P. Suppan, 2009: A comparison between modelled and measured mixing-layer height over Munich. Bound.-Layer Meteor., 131, 425–440, https://doi.org/10.1007/s10546-009-9373-7.

    Article  Google Scholar 

  • Doukas, C., T. Pliakas, and I. Maglogiannis, 2010: Mobile healthcare information management utilizing cloud computing and Android OS. Preprints, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Buenos Aires, IEEE, 1037–1040, https://doi.org/10.1109/IEMBS.2010.5628061.

    Chapter  Google Scholar 

  • Emeis, S., C. Munkel, S. Vogt, W. J. Müller, and K. Schäfer, 2004: Atmospheric boundary-layer structure from simultaneous SODAR, RASS, and ceilometer measurements. Atmos. Environ., 38, 273–286, https://doi.org/10.1016/j.atmosenv.2003.09.054.

    Article  Google Scholar 

  • Feng, J., H. Liao, and J. P. Li, 2016: The impact of monthly variation of the Pacific-North America (PNA) teleconnection pattern on wintertime surface-layer aerosol concentrations in the United States. Atmos. Chem. Phys., 16, 4927–4943, https://doi.org/10.5194/acp-16-4927-2016.

    Article  Google Scholar 

  • Gao, Y., M. Zhang, Z. Liu, L. Wang, P. Wang, X. Xia, M. Tao, and L. Zhu, 2015: Modeling the feedback between aerosol and meteorological variables in the atmospheric boundary layer during a severe fog-haze event over the North China Plain. Atmos. Chem. Phys., 15, 4279–4295, https://doi.org/10.5194/acp-15-4279-2015.

    Article  Google Scholar 

  • Guo, J.-P., and Coauthors, 2009: Correlation between PM concentrations and aerosol optical depth in eastern China. Atmos. Environ., 43, 5876–5886, https://doi.org/10.1016/j.atmosenv.2009.08.026.

    Article  Google Scholar 

  • Guo, J. P., and Coauthors, 2016: The climatology of planetary boundary layer height in China derived from radiosonde and reanalysis data. Atmos. Chem. Phys., 16, 13 309–13 319, https://doi.org/10.5194/acp-16-13309-2016.

    Google Scholar 

  • Gupta, P., S. A. Christopher, J. Wang, R. Gehrig, Y. Lee, and N. Kumar, 2006: Satellite remote sensing of particulate matter and air quality assessment over global cities. Atmos. Environ., 40, 5880–5892, https://doi.org/10.1016/j.atmosenv.2006.03.016.

    Article  Google Scholar 

  • Hägeli, P., D. G. Steyn, and K. B. Strawbridge, 2000: Spatial and temporal variability of mixed-layer depth and entrainment zone thickness. Bound.-Layer Meteor., 97, 47–71, https://doi.org/10.1023/A:1002790424133.

    Article  Google Scholar 

  • Hayden, K. L., and Coauthors, 1997: The vertical chemical and meteorological structure of the boundary layer in the Lower Fraser Valley during Pacific’ 93. Atmos. Environ., 31, 2089–2105, https://doi.org/10.1016/S1352-2310(96)00300-7.

    Article  Google Scholar 

  • Hennemuth, B., and A. Lammert, 2006: Determination of the atmospheric boundary layer height from radiosonde and lidar backscatter. Bound.-Layer Meteor., 120, 181–200, https://doi.org/10.1007/s10546-005-9035-3.

    Article  Google Scholar 

  • Hu, X.-M., J. W. Nielsen-Gammon, and F. Q. Zhang, 2010: Evaluation of three planetary boundary layer schemes in the WRF model. J. Appl. Metorol. Clim., 49, 1831–1844, https://doi.org/10.1175/2010JAMC2432.1.

    Article  Google Scholar 

  • Jones, R. H., S. Westra, and A. Sharma, 2010: Observed relationships between extreme sub-daily precipitation, surface temperature, and relative humidity. Geophys. Res. Lett., 37, L22805, https://doi.org/10.1029/2010GL045081.

    Google Scholar 

  • Koelemeijer, R. B. A., C. D. Homan, and J. Matthijsen, 2006: Comparison of spatial and temporal variations of aerosol optical thickness and particulate matter over Europe. Atmos. Environ., 40, 5304–5315, https://doi.org/10.1016/j.atmosenv.2006.04.044.

    Article  Google Scholar 

  • Li, H., Y. Yang, X.-M. Hu, Z.W. Huang, G. Y.Wang, B. D. Zhang, and T. J. Zhang, 2017: Evaluation of retrieval methods of daytime convective boundary layer height based on lidar data. J. Geophys. Res., 122, 4578–4593, https://doi.org/10.1002/2016JD025620.

    Google Scholar 

  • Li, S., R. Kahn, M. Chin, M. J. Garay, and Y. Liu, 2015: Improving satellite-retrieved aerosol microphysical properties using GOCART data. Atmospheric Measurement Techniques, 8, 1157–1171, https://doi.org/10.5194/amt-8-1157-2015.

    Article  Google Scholar 

  • Li, S. S., L. F. Chen, X. Z. Xiong, J. H. Tao, L. Su, D. Han, and Y. Liu, 2013: Retrieval of the haze optical thickness in North China Plain using MODIS data. IEEE Transactions on Geoscience and Remote Sensing, 51, 2528–2540, https://doi.org/10.1109/TGRS.2012.2214038.

    Article  Google Scholar 

  • Li, S. S., C. Yu, L. F. Chen, J. H. Tao, H. Letu, W. Ge, Y. D. Si, and Y. Liu, 2016: Inter-comparison of model-simulated and satellite-retrieved componential aerosol optical depths in China. Atmos. Environ., 141, 320–332, doi: 10.1016/j.atmosenv.2016.06.075.

    Article  Google Scholar 

  • Liu, J. J., J. P. Huang, B. Chen, T. Zhou, H. R. Yan, H. C. Jin, Z. W. Huang, and B. D. Zhang, 2015: Comparisons of PBL heights derived from CALIPSO and ECMWF reanalysis data over China. Journal of Quantitative Spectroscopy and Radiative Transfer, 153, 102–112, https://doi.org/10.1016/j.jqsrt.2014.10.011.

    Article  Google Scholar 

  • Liu, X. G., and Coauthors, 2013: Formation and evolution mechanism of regional haze: A case study in the megacity Beijing, China. Atmos. Chem. Phys., 13, 4501–4514, https://doi.org/10.5194/acp-13-4501-2013.

    Article  Google Scholar 

  • Liu, Y., R. J. Park, D. J. Jacob, Q. B. Li, V. Kilaru, and J. A. Sarnat, 2004: Mapping annual mean ground-level PM2.5 concentrations using Multiangle Imaging Spectroradiometer aerosol optical thickness over the contiguous United States. J. Geophys. Res., 109, D22206, https://doi.org/10.1029/2004jd005025.

    Google Scholar 

  • Lock, A. P., A. R. Brown, M. R. Bush, G. M. Martin, and R. N. B. Smith, 2000: A new boundary layer mixing scheme. Part I: Scheme description and single-column model tests. Mon. Wea. Rev., 128, 3187–3199, https://doi.org/10.1175/1520-0493(2000)128<3187:ANBLMS>2.0.CO;2.

    Google Scholar 

  • Luo, T., R. Yuan, and Z. Wang, 2014: Lidar-based remote sensing of atmospheric boundary layer height over land and ocean. Atmospheric Measurement Techniques, 7, 173–182, https://doi.org/10.5194/amt-7-173-2014.

    Article  Google Scholar 

  • Ma, M. J., Z. X. Pu, S. G. Wang, and Q. Zhang, 2011: Characteristics and numerical simulations of extremely large atmospheric boundary-layer heights over an arid region in north-west China. Bound.-Layer Meteor., 140, 163–176, https://doi.org/10.1007/s10546-011-9608-2.

    Article  Google Scholar 

  • Ma, Z. W., X. F. Hu, L. Huang, J. Bi, and Y. Liu, 2014: Estimating ground-level PM2.5 in China using satellite remote sensing. Environ. Sci. Technol., 48, 7436–7444, https://doi.org/10.1021/es5009399.

    Article  Google Scholar 

  • Ma, Z. W., and Coauthors, 2016: Satellite-based spatiotemporal trends in PM2.5 concentrations: China, 2004- 2013. Environmental Health Perspectives, 124, 184–192, https://doi.org/10.1289/ehp.1409481.

    Article  Google Scholar 

  • McGrath-Spangler, E. L., and A. Molod, 2014: Comparison of GEOS-5 AGCM planetary boundary layer depths computed with various definitions. Atmos. Chem. Phys., 14, 6717–6727, https://doi.org/10.5194/acp-14-6717-2014.

    Article  Google Scholar 

  • Medeiros, B., A. Hall, and B. Stevens, 2005: What controls the mean depth of the PBL? J. Climate, 18, 3157–3172, https://doi.org/10.1175/JCLI3417.1.

    Article  Google Scholar 

  • Miao, Y. C., X.-M. Hu, S. H. Liu, T. T. Qian, M. Xue, Y. J. Zheng, and S. Wang, 2015: Seasonal variation of local atmospheric circulations and boundary layer structure in the Beijing-Tianjin-Hebei region and implications for air quality. Journal of Advances in Modeling Earth Systems, 7, 1602–1626, https://doi.org/10.1002/2015MS000522.

    Article  Google Scholar 

  • Miao, Y. C., S. H. Liu, Y. J. Zheng, and S. Wang, 2016: Modeling the feedback between aerosol and boundary layer processes: A case study in Beijing, China. Environmental Science and Pollution Research, 23, 3342–3357, https://doi.org/10.1007/s11356-015-5562-8.

    Article  Google Scholar 

  • Moradi, I., P. Arkin, R. Ferraro, P. Eriksson, and E. Fetzer, 2016: Diurnal variation of tropospheric relative humidity in tropical regions. Atmos. Chem. Phys., 16, 6913–6929, https://doi.org/10.5194/acp-16-6913-2016.

    Article  Google Scholar 

  • Quan, J. N., and Coauthors, 2013: Evolution of planetary boundary layer under different weather conditions, and its impact on aerosol concentrations. Particuology, 11, 34–40, https://doi.org/10.1016/j.partic.2012.04.005.

    Article  Google Scholar 

  • Seibert, P., F. Beyrich, S.-E. Gryning, S. Joffre, A. Rasmussen, and P. Tercier, 2000: Review and intercomparison of operational methods for the determination of the mixing height. Atmos. Environ., 34, 1001–1027, doi: 10.1016/S1352-2310(99)00349-0.

    Article  Google Scholar 

  • Seidel, D. J., Y. H. Zhang, A. Beljaars, J.-C. Golaz, A. R. Jacobson, and B. Medeiros, 2012: Climatology of the planetary boundary layer over the continental United States and Europe. J. Geophys. Res., 117, D17106, https://doi.org/10.1029/2012jd018143.

    Article  Google Scholar 

  • Stott, P., 2016: How climate change affects extreme weather events. Science, 352, 1517–1518, doi: 10.1126/science.aaf 7271.

    Article  Google Scholar 

  • Sun, Y. L., and Coauthors, 2016: Rapid formation and evolution of an extreme haze episode in Northern China during winter 2015. Scientific Reports, 6, 27151, https://doi.org/10.1038/srep27151.

    Article  Google Scholar 

  • Tao, J. H., M. G. Zhang, L. F. Chen, Z. F. Wang, L. Su, C. Ge, X. Han, and M. M. Zou, 2013: A method to estimate concentrations of surface-level particulate matter using satellite-based aerosol optical thickness. Science China Earth Sciences, 56, 1422–1433, https://doi.org/10.1007/s11430-012-4503-3.

    Article  Google Scholar 

  • Veerabuthiran, S., A. K. Razdan, M. K. Jindal, D. K. Dubey, and R. C. Sharma, 2011: Mie lidar observations of lower tropospheric aerosols and clouds. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy, 84, 32–36, https://doi.org/10.1016/j.saa.2011.08.021.

    Article  Google Scholar 

  • Vergados, P., A. J. Mannucci, C. O. Ao, J. H. Jiang, and H. Su, 2015: On the comparisons of tropical relative humidity in the lower and middle troposphere among COSMIC radio occultations and MERRA and ECMWF data sets. Atmospheric Measurement Techniques, 8, 1789–1797, https://doi.org/10.5194/amt-8-1789-2015.

    Article  Google Scholar 

  • Wang, J., and S. A. Christopher, 2003: Intercomparison between satellite-derived aerosol optical thickness and PM2.5 mass: Implications for air quality studies. Geophys. Res. Lett., 30, 2095, https://doi.org/10.1029/2003gl018174.

    Article  Google Scholar 

  • Wang, Z. F., L. F. Chen, J. H. Tao, Y. Zhang, and L. Su, 2010: Satellite-based estimation of regional particulate matter (PM) in Beijing using vertical-and-RH correcting method. Remote Sensing of Environment, 114, 50–63, https://doi.org/10.1016/j.rse.2009.08.009.

    Article  Google Scholar 

  • Xu, C. C., J. Zhao, J. X. Li, S. T. Gao, R. P. Zhou, H. Z. Liu, and Y. P. Chen, 2015: Climate change in Urumqi City during 1960-2013. Quaternary International, 358, 93–100, https://doi.org/10.1016/j.quaint.2014.11.062.

    Article  Google Scholar 

  • Zhang, G. H., Z. C. Li, Y. Song, Y. L. Wu, and X. L. Wang, 2011: Spatial patterns of change trend in rainfall of China and the role of East Asia summer monsoon. Arid Land Geography, 34, 34–42. (in Chinese)

    Google Scholar 

  • Zhang, W. C., J. P. Guo, Y. C. Miao, H. Liu, Y. Zhang, Z. Q. Li, and P. M. Zhai, 2016: Planetary boundary layer height from CALIOP compared to radiosonde over China. Atmos. Chem. Phys., 16, 9951–9963, https://doi.org/10.5194/acp-16-9951-2016.

    Article  Google Scholar 

  • Zhang, Y., X.-Y. Wen, and C. J. Jang, 2010: Simulating chemistryaerosol-cloud-radiation-climate feedbacks over the continental U.S. using the online-coupledWeather Research Forecasting Model with chemistry (WRF/Chem). Atmos. Environ., 44, 3568–3582, https://doi.org/10.1016/j.atmosenv.2010.05.056.

    Article  Google Scholar 

  • Zhang, Y. H., S. D. Zhang, C. M. Huang, K. M. Huang, Y. Gong, and Q. Gan, 2014: Diurnal variations of the planetary boundary layer height estimated from intensive radiosonde observations over Yichang, China. Science China Technological Sciences, 57, 2172–2176, https://doi.org/10.1007/s11431-014-5639-5.

    Article  Google Scholar 

  • Zhang, Z. Z., X. H. Cai, Y. Song, L. Kang, X. Huang, and Q. Y. Li, 2013: Temporal and spatial variation of atmospheric boundary layer height over Hainan Island and its adjacent sea areas. Acta Scientiarum Naturalium Universitatis Pekinensis, 49, 783–790. (in Chinese)

    Google Scholar 

  • Zhou, L., X. D. Xu, G. A. Ding, M. Y. Zhou, and X. H. Cheng, 2005: Diurnal variations of air pollution and atmospheric boundary layer structure in Beijing during winter 2000/2001. Adv. Atmos. Sci., 22, 126–132, https://doi.org/10.1007/BF02930876.

    Article  Google Scholar 

  • Zhu, Y. L., H. J. Wang, W. Zhou, and J. H. Ma, 2011: Recent changes in the summer precipitation pattern in east China and the background circulation. Climate Dyn., 36, 1463–1473, https://doi.org/10.1007/s00382-010-0852-9.

    Article  Google Scholar 

  • Fernald, F., Herman, M., Reagan, J., 1972: Determination of aerosol height distributions by Lidar. Journal of Applied Meteorology, 11, 482–489, https://doi.org/10.1175/1520-0450(1972)011 <0482:DOAHDB>2.0.CO;2.

    Article  Google Scholar 

  • Louis, J., Tiedtke, M., and Geleyn, J., 1982: A short history of the PBL parameterization at ECMWF, Workshop on Planetary Boundary Layer Parameterization, ECMWF, Reading, England, 5–27 November 1981, 59–79.

  • Menut, L., C. Flamant, J. Pelon, and P. H. Flamant, 1999: Urban boundary-layer height determination from lidar measurements over the Paris area. Appl. Optics, 38, 945–954.

    Article  Google Scholar 

  • Song, Y. F., Y. J. Liu, and Y. H. Ding, 2012: A study of surface humidity changes in china during the recent 50 years. Acta Meteorologica Sinica, 26, 541–553.

    Article  Google Scholar 

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Acknowledgements

This work was supported by the National Key R&D Program of China (2016YFC0201507) and the National Natural Science Foundation of China (Grant Nos. 41471367, 91543128 and 41571417). We thank the National Meteorological Information Center and their staff for gathering and maintaining the data from the meteorological stations used in this investigation.

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Si, Y., Li, S., Chen, L. et al. Validation and Spatiotemporal Distribution of GEOS-5–Based Planetary Boundary Layer Height and Relative Humidity in China. Adv. Atmos. Sci. 35, 479–492 (2018). https://doi.org/10.1007/s00376-017-6275-3

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