[1] Brown, P. J., and A. T. DeGaetano, 2009: A method to detect inhomogeneities in historical dewpoint temperature series. J. Appl. Meteor. Climatol., 48, 2362–2376. doi: 10.1175/2009jamc2123.1
[2] Camalier, L., W. Cox, and P. Dolwick, 2007: The effects of meteorology on ozone in urban areas and their use in assessing ozone trends. Atmos. Environ., 41, 7127–7137. doi: 10.1016/j.atmosenv.2007.04.061
[3] Compo, G. P., J. S. Whitaker, P. D. Sardeshmukh, et al., 2011: The Twentieth Century Reanalysis project. Quart. J. Roy. Meteor. Soc., 137, 1–28. doi: 10.1002/qj.776
[4] Dai, A. G., 2001a: Global precipitation and thunderstorm frequencies. Part I: Seasonal and interannual variations. J. Climate, 14, 1092–1111. doi: 10.1175/1520-0442(2001)014<1092:gpatfp>2.0.co;2
[5] Dai, A. G., 2001b: Global precipitation and thunderstorm frequencies. Part II: Diurnal variations. J. Climate, 14, 1112–1128. doi: 10.1175/1520-0442(2001)014<1112:gpatfp>2.0.co;2
[6] Dai, A. G., 2006: Recent climatology, variability, and trends in global surface humidity. J. Climate, 19, 3589–3606. doi: 10.1175/jcli3816.1
[7] Dai, A. G., and C. Deser, 1999: Diurnal and semidiurnal variations in global surface wind and divergence fields. J. Geophys. Res. Atmos., 104, 31109–31125. doi: 10.1029/1999jd900927
[8] Dai, A. G., and J. H. Wang, 1999: Diurnal and semidiurnal tides in global surface pressure fields. J. Atmos. Sci., 56, 3874–3891. doi: 10.1175/1520-0469(1999)056<3874:dastig>2.0.co;2
[9] Dai, A. G., T. R. Karl, B. M. Sun, et al., 2006: Recent trends in cloudiness over the United States: A tale of monitoring inadequacies. Bull. Amer. Meteor. Soc., 87, 597–606. doi: 10.1175/bams-87-5-597
[10] Dunn, R. J. H., K. M. Willett, P. W. Thorne, et al., 2012: HadISD: A quality-controlled global synoptic report database for selected variables at long-term stations from 1973–2011. Climate Past, 8, 1649–1679. doi: 10.5194/cp-8-1649-2012
[11] Ilyas, M., C. M. Brierley, and S. Guillas, 2017: Uncertainty in regional temperatures inferred from sparse global observations: Application to a probabilistic classification of El Niño. Geophys. Res. Lett., 44, 9068–9074. doi: 10.1002/2017gl074596
[12] Liang, X., L. P. Jiang, Y. Pan, et al., 2020: A 10-yr global land surface reanalysis interim dataset (CRA-Interim/Land): Implementation and preliminary evaluation. J. Meteor. Res., 34, 101–116. doi: 10.1007/s13351-020-9083-0
[13] Liu, Z. Q., C. X. Shi, Z. J. Zhou, et al., 2017: CMA global reanalysis (CRA-40): Status and plans. Proc. 5th International Conference on Reanalysis, 13–17 November 2017, Rome, Italy, 16 pp. Available at https://climate.copernicus.eu/sites/default/files/repository/Events/ICR5/Talks/zhinqua%20liu_13pm.pdf. Accessed on 21 October 2021.
[14] Lott, N., 2004: The quality control of the integrated surface hourly database. Preprints, 84th AMS Annual Meeting, Amer. Meteor. Soc., Seattle, WA, 1–7. Available online at https://ams.confex.com/ams/84Annual/webprogram/Paper71929.html. Accessed on 7 September 2021.
[15] Saha, S., S. Moorthi, H.-L. Pan, et al., 2010: The NCEP climate forecast system reanalysis. Bull. Amer. Meteor. Soc., 91, 1015–1058. doi: 10.1175/2010bams3001.1
[16] Smith, A., N. Lott, and R. Vose, 2011: The integrated surface database: Recent developments and partnerships. Bull. Amer. Meteor. Soc., 92, 704–708. doi: 10.1175/2011bams3015.1
[17] Willett, K. M., N. P. Gillett, P. D. Jones, et al., 2007: Attribution of observed surface humidity changes to human influence. Nature, 449, 710–712. doi: 10.1038/nature06207
[18] Willett, K. M., P. D. Jones, N. P. Gillett, et al., 2008: Recent changes in surface humidity: Development of the HadCRUH dataset. J. Climate, 21, 5364–5383. doi: 10.1175/2008jcli2274.1
[19] WMO, 2011: Manual on Codes—Regional Codes and National Coding Practices. Volume II. World Meteorological Organization, WMO-No. 306, 1–352. Available online at https://library.wmo.int/doc_num.php?explnum_id=5730. Accessed on 7 September 2021.
[20] WMO, 2019: Manual on Codes—International Codes. Volume I.1. Part A—Alphanumeric Codes. World Meteorological Organization, WMO-No. 306, 1–480. Available online at https://library.wmo.int/doc_num.php?explnum_id=10235. Accessed on 7 September 2021.
[21] Yang, S., P. D. Jones, H. Jiang, et al., 2020: Development of a near-real-time global in situ daily precipitation dataset for 0000–0000 UTC. Int. J. Climatol., 40, 2795–2810. doi: 10.1002/joc.6367
[22] Zou, B., 2010: How should environmental exposure risk be assessed? A comparison of four methods for exposure assessment of air pollutions. Environ. Monit. Assess., 166, 159–167. doi: 10.1007/s10661-009-0992-8