Articles | Volume 14, issue 9
https://doi.org/10.5194/essd-14-4153-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-14-4153-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
08 Sep 2022
Data description paper |
| 08 Sep 2022
| 08 Sep 2022
A benchmark dataset of diurnal- and seasonal-scale radiation, heat, and CO2 fluxes in a typical East Asian monsoon region
Zexia Duan
Climate and Weather Disasters Collaborative Innovation Center, Key Laboratory of Aerosol and Cloud Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of
Information Science and Technology, Nanjing 210044, China
Zhiqiu Gao
Climate and Weather Disasters Collaborative Innovation Center, Key Laboratory of Aerosol and Cloud Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of
Information Science and Technology, Nanjing 210044, China
State Key Laboratory of Atmospheric Boundary Layer Physics and
Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of
Sciences, Beijing 100029, China
Qing Xu
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and
Utilization, School of Environment and Spatial Informatics, China University
of Mining and Technology, Xuzhou 221116, China
Shaohui Zhou
Climate and Weather Disasters Collaborative Innovation Center, Key Laboratory of Aerosol and Cloud Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of
Information Science and Technology, Nanjing 210044, China
Jiangsu Key Laboratory of Coal-Based Greenhouse Gas Control and
Utilization, School of Environment and Spatial Informatics, China University
of Mining and Technology, Xuzhou 221116, China
Yuanjian Yang
CORRESPONDING AUTHOR
Climate and Weather Disasters Collaborative Innovation Center, Key Laboratory of Aerosol and Cloud Precipitation of China Meteorological Administration, School of Atmospheric Physics, Nanjing University of
Information Science and Technology, Nanjing 210044, China
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Liang Wang, Bingcheng Wan, Shaohui Zhou, Haofei Sun, and Zhiqiu Gao
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Atmos. Chem. Phys., 22, 13341–13353, https://doi.org/10.5194/acp-22-13341-2022, https://doi.org/10.5194/acp-22-13341-2022, 2022
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Lian Zong, Yuanjian Yang, Haiyun Xia, Meng Gao, Zhaobin Sun, Zuofang Zheng, Xianxiang Li, Guicai Ning, Yubin Li, and Simone Lolli
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Hamidreza Omidvar, Ting Sun, Sue Grimmond, Dave Bilesbach, Andrew Black, Jiquan Chen, Zexia Duan, Zhiqiu Gao, Hiroki Iwata, and Joseph P. McFadden
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This paper extends the applicability of the SUEWS to extensive pervious areas outside cities. We derived various parameters such as leaf area index, albedo, roughness parameters and surface conductance for non-urban areas. The relation between LAI and albedo is also explored. The methods and parameters discussed can be used for both online and offline simulations. Using appropriate parameters related to non-urban areas is essential for assessing urban–rural differences.
Shaohui Zhou, Yuanjian Yang, Zhiqiu Gao, Xingya Xi, Zexia Duan, and Yubin Li
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Our research has determined the possible relationship between Weibull natural wind mesoscale parameter c and shape factor k with height under the conditions of a desert steppe terrain in northern China, which has great potential in wind power generation. We have gained an enhanced understanding of the seasonal changes in the surface roughness of the desert grassland and the changes in the incoming wind direction.
Shihan Chen, Yuanjian Yang, Fei Deng, Yanhao Zhang, Duanyang Liu, Chao Liu, and Zhiqiu Gao
Atmos. Meas. Tech., 15, 735–756, https://doi.org/10.5194/amt-15-735-2022, https://doi.org/10.5194/amt-15-735-2022, 2022
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This paper proposes a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a random forest (RF) model. The spatial distribution of CUHII was evaluated at 30 m resolution based on the output of the RF model. The present RF model framework for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII.
Xinyan Li, Yuanjian Yang, Jiaqin Mi, Xueyan Bi, You Zhao, Zehao Huang, Chao Liu, Lian Zong, and Wanju Li
Atmos. Meas. Tech., 14, 7007–7023, https://doi.org/10.5194/amt-14-7007-2021, https://doi.org/10.5194/amt-14-7007-2021, 2021
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A random forest (RF) model framework for Fengyun-4A (FY-4A) daytime and nighttime quantitative precipitation estimation (QPE) is established using FY-4A multi-band spectral information, cloud parameters, high-density precipitation observations and physical quantities from reanalysis data. The RF model of FY-4A QPE has a high accuracy in estimating precipitation at the heavy-rain level or below, which has advantages for quantitative estimation of summer precipitation over East Asia in future.
Xiaolu Ling, Ying Huang, Weidong Guo, Yixin Wang, Chaorong Chen, Bo Qiu, Jun Ge, Kai Qin, Yong Xue, and Jian Peng
Hydrol. Earth Syst. Sci., 25, 4209–4229, https://doi.org/10.5194/hess-25-4209-2021, https://doi.org/10.5194/hess-25-4209-2021, 2021
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Soil moisture (SM) plays a critical role in the water and energy cycles of the Earth system, for which a long-term SM product with high quality is urgently needed. In situ observations are generally treated as the true value to systematically evaluate five SM products, including one remote sensing product and four reanalysis data sets during 1981–2013. This long-term intercomparison study provides clues for SM product enhancement and further hydrological applications.
Lian Zong, Yuanjian Yang, Meng Gao, Hong Wang, Peng Wang, Hongliang Zhang, Linlin Wang, Guicai Ning, Chao Liu, Yubin Li, and Zhiqiu Gao
Atmos. Chem. Phys., 21, 9105–9124, https://doi.org/10.5194/acp-21-9105-2021, https://doi.org/10.5194/acp-21-9105-2021, 2021
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In recent years, summer O3 pollution over eastern China has become more serious, and it is even the case that surface O3 and PM2.5 pollution can co-occur. However, the synoptic weather pattern (SWP) related to this compound pollution remains unclear. Regional PM2.5 and O3 compound pollution is characterized by various SWPs with different dominant factors. Our findings provide insights into the regional co-occurring high PM2.5 and O3 levels via the effects of certain meteorological factors.
Cited articles
Ao, X., Grimmond, C. S. B., Chang, Y., Liu, D., Tang, Y., Hu, P., Wang, Y.,
Zou, J., and Tan, J.: Heat, water and carbon exchanges in the tall megacity
of Shanghai: challenges and results, Int. J. Climatol.,
36, 4608–4624, https://doi.org/10.1002/joc.4657, 2016.
Baldocchi, D. and Ma, S.: How will land use affect air temperature in the
surface boundary layer? Lessons learned from a comparative study on the
energy balance of an oak savanna and annual grassland in California, USA,
Tellus Ser. B, 65, 19994,
https://doi.org/10.3402/tellusb.v65i0.19994, 2013.
Baldocchi, D. D.: Assessing the eddy covariance technique for evaluating
carbon dioxide exchange rates of ecosystems: past, present and future,
Glob. Change Biol., 9, 479–492,
https://doi.org/10.1046/j.1365-2486.2003.00629.x, 2003.
Bi, X., Gao, Z., Deng, X., Wu, D., Liang, J., Zhang, H., Sparrow, M., Du,
J., Li, F., and Tan, H.: Seasonal and diurnal variations in moisture, heat,
and CO2 fluxes over grassland in the tropical monsoon region of
southern China, J. Geophys. Res.-Atmos., 112, D10106,
https://doi.org/10.1029/2006JD007889, 2007.
Bian, L., Gao, Z., Xu, Q., Lu, L., and Cheng, Y.: Measurements of turbulence
transfer in the near-surface layer over the southeastern Tibetan Plateau,
Bound.-Lay. Meteorol., 102, 281–300,
https://doi.org/10.1023/A:1013177629245, 2002.
Chen, C., Li, D., Gao, Z., Tang, J., Guo, X., Wang, L., and Wan, B.:
Seasonal and Interannual Variations of Carbon Exchange over a Rice-Wheat
Rotation System on the North China Plain, Adv. Atmos. Sci.,
32, 1365–1380, https://doi.org/10.1007/s00376-015-4253-1, 2015.
Chen, H., Zhang, Y., Yu, M., Hua, W., Sun, S., Li, X., and Gao, C.:
Large-scale urbanization effects on eastern Asian summer monsooncirculation
and climate, Clim. Dynam., 47, 117–136,
https://doi.org/10.1007/s00382-015-2827-3, 2016.
Chen, H. S. and Zhang, Y.: Sensitivity experiments of impacts of large-scale
urbanization in East China on East Asian winter monsoon, Chinese Sci.
Bull., 58, 809–815, https://doi.org/10.1007/s11434-012-5579-z, 2013.
Chen, S., Yang, Y., Deng, F., Zhang, Y., Liu, D., Liu, C., and Gao, Z.: A
high-resolution monitoring approach of canopy urban heat island using a
random forest model and multi-platform observations, Atmos. Meas. Tech., 15,
735–756, https://doi.org/10.5194/amt-15-735-2022, 2022.
Chen, X., Yu, Y., Chen, J., Zhang, T., and Li, Z.: Seasonal and interannual
variation of radiation and energy fluxes over a rain-fed cropland in the
semi-arid area of Loess Plateau, northwestern China, Atmos. Res.,
176–177, 240–253, https://doi.org/10.1016/j.atmosres.2016.03.003, 2016.
Cheng, X. L., Liu, X. M., Liu, Y. J., and Hu, F.: Characteristics of
CO2 Concentration and Flux in the Beijing Urban Area, J.
Geophys. Res.-Atmos., 123, 1785–1801,
https://doi.org/10.1002/2017JD027409, 2018.
Cuntz, M., Mai, J., Samaniego, L., Clark, M., Wulfmeyer, V., Branch, O.,
Attinger, S., and Thober, S.: The impact of standard and hard-coded
parameters on the hydrologic fluxes in the Noah-MP land surface model,
J. Geophys. Res.-Atmos., 121, 10676–10700,
https://doi.org/10.1002/2016JD025097, 2016.
Dai, S., Ju, W., Zhang, Y., He, Q., Song, L., and Li, J.: Variations and
drivers of methane fluxes from a rice-wheat rotation agroecosystem in
eastern China at seasonal and diurnal scales, Sci. Total
Environ., 690, 973–990, https://doi.org/10.1016/j.scitotenv.2019.07.012,
2019.
Dou, J., Grimmond, S., Cheng, Z., Miao, S., Feng, D., and Liao, M.:
Summertime surface energy balance fluxes at two Beijing sites, International
J. Climatol., 39, 2793–2810, https://doi.org/10.1002/joc.5989,
2019.
Duan, Z., Grimmond, C. S. B., Gao, C. Y., Sun, T., Liu, C., Wang, L., Li,
Y., and Gao, Z.: Seasonal and Interannual Variations in the Surface Energy
Fluxes of a Rice–Wheat Rotation in Eastern China, J. Appl.
Meteorol. Clim., 60, 877–891,
https://doi.org/10.1175/jamc-d-20-0233.1, 2021a.
Duan, Z., Yang, Y., Wang, L., Liu, C., Fan, S., Chen, C., Tong, Y., Lin, X.,
and Gao, Z.: Temporal characteristics of carbon dioxide and ozone over a
rural-cropland area in the Yangtze River Delta of eastern China, Sci.
Total Environ., 757, 143750,
https://doi.org/10.1016/j.scitotenv.2020.143750, 2021b.
Duan, Z., Gao, Z., Xu, Q., Zhou, S., Qin, K., and Yang, Y.: A benchmark
dataset of diurnal- and seasonal-scale radiation, heat and CO2 fluxes
in a typical East Asian monsoon region, Zenodo [data set],
https://doi.org/10.5281/zenodo.6552301, 2022.
Feddema, J. J., Oleson, K. W., Bonan, G. B., Mearns, L. O., Buja, L. E.,
Meehl, G. A., and Washington, W. M.: The importance of land-cover change in
simulating future climates, Science, 310, 1674–1678,
https://doi.org/10.1126/science.1118160, 2005.
Flerchinger, G. N., Xaio, W., Marks, D., Sauer, T. J., and Yu, Q.:
Comparison of algorithms for incoming atmospheric long-wave radiation, Water
Resour. Res., 45, W03423, https://doi.org/10.1029/2008WR007394, 2009.
Gao, Z., Chae, N., Kim, J., Hong, J., Choi, T., and Lee, H.: Modeling of
surface energy partitioning, surface temperature, and soil wetness in the
Tibetan prairie using the Simple Biosphere Model 2 (SiB2), J.
Geophys. Res.-Atmos., 109, D06102,
https://doi.org/10.1029/2003JD004089, 2004.
Ge, H., Zhang, H., Zhang, H., Cai, X., Song, Y., and Kang, L.: The
characteristics of methane flux from an irrigated rice farm in East China
measured using the eddy covariance method, Agr. Forest
Meteorol., 249, 228–238, https://doi.org/10.1016/j.agrformet.2017.11.010,
2018.
Grimmond, C. S. B., King, T. S., Cropley, F. D., Nowak, D. J., and Souch,
C.: Local-scale fluxes of carbon dioxide in urban environments:
methodological challenges and results from Chicago, Environ. Pollut.,
116, S243–S254, https://doi.org/10.1016/S0269-7491(01)00256-1, 2002.
Guo, W., Wang, X., Sun, J., Ding, A., and Zou, J.: Comparison of land–atmosphere interaction at different surface types in the mid- to lower reaches of the Yangtze River valley, Atmos. Chem. Phys., 16, 9875–9890, https://doi.org/10.5194/acp-16-9875-2016, 2016.
Hassan, A. A.: Diurnal and Monthly Variations in Atmospheric CO2 Level
in Qena, Upper Egypt, Resour. Environ., 5, 59–65,
2015.
Hoelzle, M., Hauck, C., Mathys, T., Noetzli, J., Pellet, C., and Scherler, M.: Long-term energy balance measurements at three different mountain permafrost sites in the Swiss Alps, Earth Syst. Sci. Data, 14, 1531–1547, https://doi.org/10.5194/essd-14-1531-2022, 2022.
Hu, C., Liu, S. D., Wang, Y. W., Zhang, M., Xiao, W., Wang, W., and Xu, J.
P.: Anthropogenic CO2 emissions from a megacity in the Yangtze River
Delta of China, Environ. Sci. Pollut. Res., 25,
23157–23169, https://doi.org/10.1007/s11356-018-2325-3, 2018.
Huang, W., Griffis, T. J., Hu, C., Xiao, W., and Lee, X.: Seasonal
Variations of CH4 Emissions in the Yangtze River Delta Region of China
Are Driven by Agricultural Activities, Adv. Atmos. Sci., 38,
1537–1551, https://doi.org/10.1007/s00376-021-0383-9, 2021.
Jin, Y. and Roy, D. P.: Fire-induced albedo change and its radiative forcing
at the surface in northern Australia, Geophys. Res. Lett., 32, L13401,
https://doi.org/10.1029/2005GL022822, 2005.
Kaimal, J. C. and Finnigan, J. J.: Atmospheric Boundary Layer Flows: Their
Structure and Measurement, Oxford University Press, New York, 302 pp.,
https://doi.org/10.1093/oso/9780195062397.001.0001, 1994.
Kang, M. and Cho, S.: Progress in water and energy flux studies in Asia: A
review focused on eddy covariance measurements, J. Agr.
Meteorol., 77, 2–23, https://doi.org/10.2480/agrmet.D-20-00036, 2021.
Kljun, N., Calanca, P., Rotach, M. W., and Schmid, H. P.: A simple two-dimensional parameterisation for Flux Footprint Prediction (FFP), Geosci. Model Dev., 8, 3695–3713, https://doi.org/10.5194/gmd-8-3695-2015, 2015.
Lee, B., Kim, N., Kim, E., Jang, K., Kang, M., Lim, J., Cho, J., and Lee,
Y.: An Artificial Intelligence Approach to Predict Gross Primary
Productivity in the Forests of South Korea Using Satellite Remote Sensing
Data, Forests, 11, 1000, https://doi.org/10.3390/f11091000, 2020.
Lee, X., Massman, W., and Law, B.: Handbook of micrometeorology: a guide for surface flux measurement and analysis, Springer Dordrecht, https://doi.org/10.1007/1-4020-2265-4, 2004.
Lee, X., Liu, S., Xiao, W., Wang, W., Gao, Z., Cao, C., Hu, C., Hu, Z.,
Shen, S., Wang, Y., Wen, X., Xiao, Q., Xu, J., Yang, J., and Zhang, M.: The
Taihu Eddy Flux Network: An Observational Program on Energy, Water, and
Greenhouse Gas Fluxes of a Large Freshwater Lake, B. Am.
Meteorol. Soc., 95, 1583–1594,
https://doi.org/10.1175/BAMS-D-13-00136.1, 2014.
Li, D. and Wang, L.: Sensitivity of Surface Temperature to Land Use and Land
Cover Change-Induced Biophysical Changes: The Scale Issue, Geophys.
Res. Lett., 46, 9678–9689, https://doi.org/10.1029/2019GL084861,
2019.
Li, D., Sun, T., Liu, M. F., Yang, L., Wang, L. L., and Gao, Z. Q.:
Contrasting responses of urban and rural surface energy budgets to heat
waves explain synergies between urban heat islands and heat waves,
Environ. Res. Lett., 10, 054009,
https://doi.org/10.1088/1748-9326/10/5/054009, 2015.
Li, Q. and Xue, Y. K.: Simulated impacts of land cover change on summer
climate in the Tibetan Plateau, Environ. Res. Lett., 5, 015102,
https://doi.org/10.1088/1748-9326/5/1/015102, 2010.
Li, X., Gao, Z., Li, Y., and Tong, B.: Comparison of Sensible Heat Fluxes
Measured by a Large Aperture Scintillometer and Eddy Covariance System over
a Heterogeneous Farmland in East China, Atmosphere, 8, 101,
https://doi.org/10.3390/atmos8060101, 2017.
Mai, B., Deng, X., Zhang, F., He, H., Luan, T., Li, F., and Liu, X.:
Background Characteristics of Atmospheric CO2 and the Potential Source
Regions in the Pearl River Delta Region of China, Adv. Atmos.
Sci., 37, 557–568, https://doi.org/10.1007/s00376-020-9238-z, 2020.
Martano, P.: Estimation of Surface Roughness Length and Displacement Height
from Single-Level Sonic Anemometer Data, J. Appl. Meteorol., 39,
708–715, https://doi.org/10.1175/1520-0450(2000)039<0708:eosrla>2.0.co;2, 2000.
Michel, D., Philipona, R., Ruckstuhl, C., Vogt, R., and Vuilleumier, L.:
Performance and Uncertainty of CNR1 Net Radiometers during a One-Year Field
Comparison, J. Atmos. Ocean. Tech., 25, 442–451,
https://doi.org/10.1175/2007JTECHA973.1, 2008.
Nelli, N. R., Temimi, M., Fonseca, R. M., Weston, M. J., Thota, M. S.,
Valappil, V. K., Branch, O., Wizemann, H.-D., Wulfmeyer, V., and Wehbe, Y.:
Micrometeorological measurements in an arid environment: Diurnal
characteristics and surface energy balance closure, Atmos. Res.,
234, 104745, https://doi.org/10.1016/j.atmosres.2019.104745, 2020.
Nishimura, S., Yonemura, S., Minamikawa, K., and Yagi, K.: Seasonal and
diurnal variations in net carbon dioxide flux throughout the year from soil
in paddy field, J. Geophys. Res.-Biogeo., 120,
63–76, https://doi.org/10.1002/2014JG002746, 2015.
Ohtaki, E. and Matsui, T.: Infrared device for simultaneous measurement of
fluctuations of atmospheric carbon dioxide and water vapor, Bound.-Lay.
Meteorol., 24, 109–119, https://doi.org/10.1007/BF00121803, 1982.
Rao, K. G. and Reddy, N. N.: On Moisture Flux of the Indian Summer Monsoon:
A New Perspective, Geophys. Res. Lett., 46, 1794–1804,
https://doi.org/10.1029/2018GL080392, 2019.
Ren, Z., Zhang, Z., Sun, C., Liu, Y., Li, J., Ju, X., Zhao, Y., Li, Z.,
Zhang, W., Li, H., Zeng, X., Re, X., Liu, Y., and Wang, H.: Development of
three-step quality control system of real-time observation data from AWS in
China, Meteorol. Monthly, 41, 1268–1277,
https://doi.org/10.7519/j.issn.1000-0526.2015.10.010, 2015 (in Chinese).
Schmidt, M., Reichenau, T. G., Fiener, P., and Schneider, K.: The carbon
budget of a winter wheat field: An eddy covariance analysis of seasonal and
inter-annual variability, Agr. Forest Meteorol., 165,
114–126, https://doi.org/10.1016/j.agrformet.2012.05.012, 2012.
Sun, T., Wang, Z. H., and Ni, G. H.: Revisiting the hysteresis effect in
surface energy budgets, Geophys. Res. Lett., 40, 1741–1747,
https://doi.org/10.1002/grl.50385, 2013.
Tsai, J., Tsuang, B., Lu, P., Yao, M., and Shen, Y.: Surface Energy
Components and Land Characteristics of a Rice Paddy, J. Appl.
Meteorol. Clim., 46, 1879–1900,
https://doi.org/10.1175/2007jamc1568.1, 2007.
Vickers, D. and Mahrt, L.: Quality Control and Flux Sampling Problems for
Tower and Aircraft Data, J. Atmos. Ocean. Tech., 14,
512–526, https://doi.org/10.1175/1520-0426(1997)014<0512:qcafsp>2.0.co;2, 1997.
Wang, L., Fan, S., Hu, F., Miao, S., Yang, A., Li, Y., Liu, J., Liu, C.,
Chen, S., Ho, H. C., Duan, Z., Gao, Z., and Yang, Y.: Vertical Gradient
Variations in Radiation Budget and Heat Fluxes in the Urban Boundary Layer:
A Comparison Study Between Polluted and Clean Air Episodes in Beijing During
Winter, J. Geophys. Res.-Atmos., 125, e2020JD032478,
https://doi.org/10.1029/2020JD032478, 2020.
Wang, W., Xiao, W., Cao, C., Gao, Z., Hu, Z., Liu, S., Shen, S., Wang, L.,
Xiao, Q., Xu, J., Yang, D., and Lee, X.: Temporal and spatial variations in
radiation and energy balance across a large freshwater lake in China,
J. Hydrol., 511, 811–824,
https://doi.org/10.1016/j.jhydrol.2014.02.012, 2014.
Webb, E. K., Pearman, G. I., and Leuning, R.: Correction of flux
measurements for density effects due to heat and water vapour transfer,
Q. J. Roy. Meteor. Soc., 106, 85–100,
https://doi.org/10.1002/qj.49710644707, 1980.
Wei, C., Wang, M., Fu, Q., Dai, C., Huang, R., and Bao, Q.: Temporal
characteristics of greenhouse gases (CO2 and CH4) in the megacity
Shanghai, China: Association with air pollutants and meteorological
conditions, Atmos. Res., 235, 104759,
https://doi.org/10.1016/j.atmosres.2019.104759, 2020.
Xue, Y., Juang, H. M. H., Li, W. P., Prince, S., DeFries, R., Jiao, Y., and
Vasic, R.: Role of land surface processes in monsoon development: East Asia
and West Africa, J. Geophys. Res.-Atmos., 109, D03105,
https://doi.org/10.1029/2003JD003556, 2004.
Yang, J. and Wang, Z.: Physical parameterization and sensitivity of urban
hydrological models: Application to green roof systems, Build.
Environ., 75, 250–263, https://doi.org/10.1016/j.buildenv.2014.02.006,
2014.
Yang, J., Wang, Z., and Huang, H.: Intercomparison of the Surface Energy
Partitioning in CMIP5 Simulations, Atmosphere, 10, 602,
https://doi.org/10.3390/atmos10100602, 2019.
Yang, Y., Zhang, M., Li, Q., Chen, B., Gao, Z., Ning, G., Liu, C., Li, Y.,
and Luo, M.: Modulations of surface thermal environment and agricultural
activity on intraseasonal variations of summer diurnal temperature range in
the Yangtze River Delta of China, Sci. Total Environ., 736,
139445, https://doi.org/10.1016/j.scitotenv.2020.139445, 2020a.
Yang, Y., Fan, S., Wang, L., Gao, Z., Zhang, Y., Zou, H., Miao, S., Li, Y.,
Huang, M., Yim, S. H. L., and Lolli, S.: Diurnal Evolution of the Wintertime
Boundary Layer in Urban Beijing, China: Insights from Doppler Lidar and a
325-m Meteorological Tower, Remote Sensing, 12, 3935,
https://doi.org/10.3390/rs12233935, 2020b.
You, Q., Xue, X., Peng, F., Dong, S., and Gao, Y.: Surface water and heat
exchange comparison between alpine meadow and bare land in a permafrost
region of the Tibetan Plateau, Agr. Forest Meteorol., 232,
48–65, https://doi.org/10.1016/j.agrformet.2016.08.004, 2017.
Zhang, Y., Wang, X., Hu, R., Pan, Y., and Zhang, H.: Variation of albedo to
soil moisture for sand dunes and biological soil crusts in arid desert
ecosystems, Environ. Earth Sci., 71, 1281–1288,
https://doi.org/10.1007/s12665-013-2532-7, 2014.
Zhang, Y., Ning, G., Chen, S., and Yang, Y.: Impact of Rapid Urban Sprawl on
the Local Meteorological Observational Environment Based on Remote Sensing
Images and GIS Technology, Remote Sensing, 13, 2624,
https://doi.org/10.3390/rs13132624, 2021.
Zhang, Z., Zhang, M., Cao, C., Wang, W., Xiao, W., Xie, C., Chu, H., Wang, J., Zhao, J., Jia, L., Liu, Q., Huang, W., Zhang, W., Lu, Y., Xie, Y., Wang, Y., Pu, Y., Hu, Y., Chen, Z., Qin, Z., and Lee, X.: A dataset of microclimate and radiation and energy fluxes from the Lake Taihu eddy flux network, Earth Syst. Sci. Data, 12, 2635–2645, https://doi.org/10.5194/essd-12-2635-2020, 2020.
Short summary
Land–atmosphere interactions over the Yangtze River Delta (YRD) in China are becoming more varied and complex, as the area is experiencing rapid land use changes. In this paper, we describe a dataset of microclimate and eddy covariance variables at four sites in the YRD. This dataset has potential use cases in multiple research fields, such as boundary layer parametrization schemes, evaluation of remote sensing algorithms, and development of climate models in typical East Asian monsoon regions.
Land–atmosphere interactions over the Yangtze River Delta (YRD) in China are becoming more...
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