• Alexandersson, H., 1986: A homogeneity test applied to precipitation data. Int. J. Climatol., 6, 661675, https://doi.org/10.1002/joc.3370060607.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Begert, M., G. Seiz, T. Schlegel, M. Musa, G. Baudraz, and M. Moesch, 2003: Homogenisierung von Klimamessreihen der Schweiz und Bestimmung der Normwerte 1961-1990. MeteoSchweiz Tech. Rep. 67, 170 pp.

  • Cheng, C. S., 2014: Evidence from the historical record to support projection of future wind regimes: An application to Canada. Atmos.–Ocean, 52, 232241, https://doi.org/10.1080/07055900.2014.902803.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeGaetano, A., 1997: A quality-control routine for hourly wind observations. J. Atmos. Oceanic Technol., 14, 308317, https://doi.org/10.1175/1520-0426(1997)014<0308:AQCRFH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • DeGaetano, A., 1998: Identification and implications of biases in U.S. surface wind observation, archival, and summarization methods. Theor. Appl. Climatol., 60, 151162, https://doi.org/10.1007/s007040050040.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Dunn, R. J. H., K. M. Willett, D. E. Parker, and L. Mitchell, 2016: Expanding HadISD: Quality-controlled, sub-daily station data from 1931. Geosci. Instrum. Methods Data Syst., 5, 473491, https://doi.org/10.5194/gi-5-473-2016.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Durre, I., M. J. Menne, B. E. Gleason, T. G. Houston, and R. S. Vose, 2010: Comprehensive automated quality assurance of daily surface observations. J. Appl. Meteor. Climatol., 49, 16151633, https://doi.org/10.1175/2010JAMC2375.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Fiebrich, C. A., C. R. Morgan, A. G. McCombs, P. K. Hall, and R. A. McPherson, 2010: Quality assurance procedures for mesoscale meteorological data. J. Atmos. Oceanic Technol., 27, 15651582, https://doi.org/10.1175/2010JTECHA1433.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gandin, L., 1988: Complex quality control of meteorological observations. Mon. Wea. Rev., 116, 11371156, https://doi.org/10.1175/1520-0493(1988)116<1137:CQCOMO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • García-Bustamante, E., J. F. González-Rouco, J. Navarro, E. Xoplaki, P. A. Jiménez, and J. P. Montávez, 2012: North Atlantic atmospheric circulation and surface wind in the Northeast of the Iberian Peninsula: Uncertainty and long term downscaled variability. Climate Dyn., 38, 141160, https://doi.org/10.1007/s00382-010-0969-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • García-Bustamante, E., and Coauthors, 2013: Relationship between wind power production and North Atlantic atmospheric circulation over the northeastern Iberian Peninsula. Climate Dyn., 40, 935949, https://doi.org/10.1007/s00382-012-1451-8.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gower, J. F. R., 1996: Intercalibration of wave and wind data from TOPEX/POSEIDON and moored buoys off the west coast of Canada. J. Geophys. Res., 101, 38173829, https://doi.org/10.1029/95JC03281.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Graybeal, D., A. DeGaetano, and K. Eggleston, 2004: Complex quality assurance of historical hourly surface airways meteorological data. J. Atmos. Oceanic Technol., 21, 11561169, https://doi.org/10.1175/1520-0426(2004)021<1156:CQAOHH>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gruber, C., and L. Haimberger, 2008: On the homogeneity of radiosonde wind time series. Meteor. Z., 17, 631, https://doi.org/10.1127/0941-2948/2008/0298.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hubbard, K., S. Goddard, W. Sorensen, N. Wells, and T. Osugi, 2005: Performance of quality assurance procedures for an applied climate information system. J. Atmos. Oceanic Technol., 22, 105112, https://doi.org/10.1175/JTECH-1657.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P., E. García-Bustamante, J. González-Rouco, F. Valero, J. Montávez, and J. Navarro, 2008: Surface wind regionalization in complex terrain. J. Appl. Meteor. Climatol., 47, 308325, https://doi.org/10.1175/2007JAMC1483.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P., J. González-Rouco, E. García-Bustamante, J. Navarro, J. Montávez, J. de Arellano, J. Dudhia, and A. Muñoz-Roldan, 2010a: Surface wind regionalization over complex terrain: Evaluation and analysis of a high-resolution WRF simulation. J. Appl. Meteor. Climatol., 49, 268287, https://doi.org/10.1175/2009JAMC2175.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Jiménez, P., J. González-Rouco, J. Navarro, J. Montávez, and E. García-Bustamante, 2010b: Quality assurance of surface wind observations from automated weather stations. J. Atmos. Oceanic Technol., 27, 11011122, https://doi.org/10.1175/2010JTECHA1404.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Klink, K., 1999: Climatological mean and interannual variance of United States surface wind speed, direction and velocity. Int. J. Climatol., 19, 471488, https://doi.org/10.1002/(SICI)1097-0088(199904)19:5<471::AID-JOC367>3.0.CO;2-X.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lawrimore, J., M. Menne, B. Gleason, C. Williams, D. Wuertz, R. Vose, and J. Rennie, 2011: An overview of the Global Historical Climatology Network monthly mean temperature data set, version 3. J. Geophys. Res., 116, D19121, https://doi.org/10.1029/2011JD016187.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Loveland, T., B. Reed, J. Brown, D. Ohlen, Z. Zhu, L. Yang, and J. Merchant, 2000: Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int. J. Remote Sens., 21, 13031330, https://doi.org/10.1080/014311600210191.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Lucio-Eceiza, E. E., J. F. González-Rouco, J. Navarro, and H. Beltrami, 2017: Quality control of surface wind observations in north eastern North America. Part I: Data management issues. J. Atmos. Oceanic Technol., https://doi.org/10.1175/JTECH-D-16-0204.1, in press.

    • Search Google Scholar
    • Export Citation
  • Mardia, K. V., and P. E. Jupp, 2009: Directional Statistics. Wiley Series in Probability and Statistics, Vol. 494, John Wiley & Sons, 456 pp., https://doi.org/10.1002/9780470316979.

    • Crossref
    • Export Citation
  • Meek, D., and J. Hatfield, 1994: Data quality checking for single station meteorological databases. Agric. For. Meteor., 69, 85109, https://doi.org/10.1016/0168-1923(94)90083-3.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • MSC, 2013: MANOBS: Manual of surface weather observations. 7th ed. Amendment 18, Meteorological Service of Canada Tech. Rep. En56-238/2-2012E-PDF, 488 pp.

  • NCEP ADP OGSO, 1980: NCEP ADP operational global surface observations. National Center for Atmospheric Research Computational and Information Systems Laboratory Research Data Archive. Subset: February 1975–February 2007, accessed 1 January 2010, http://rda.ucar.edu/datasets/ds464.0/.

  • NCEP ADP OGSO, 2004: NCEP ADP global surface observational weather data, continuing from October 1999. National Center for Atmospheric Research Computational and Information Systems Laboratory Research Data Archive, accessed 1 January 2010, http://rda.ucar.edu/datasets/ds461.0/.

  • Petrovic, P., 2006: Detection of inhomogeneities in wind direction and speed data. Proc. Fifth Seminar for Homogenization and Quality Control in Climatological Databases, WCDMP-71, Budapest, Hungary, WCDMP, 83–90.

  • Plante, M., S.-W. Son, E. Atallah, J. Gyakum, and K. Grise, 2015: Extratropical cyclone climatology across eastern Canada. Int. J. Climatol., 35, 27592776, https://doi.org/10.1002/joc.4170.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Pryor, S. C., and Coauthors, 2009: Wind speed trends over the contiguous United States. J. Geophys. Res., 114, D14105, doi:10.1029/2008JD011416.

  • Shafer, M., C. Fiebrich, D. Arndt, S. Fredrickson, and T. Hughes, 2000: Quality assurance procedures in the Oklahoma Mesonetwork. J. Atmos. Oceanic Technol., 17, 474494, https://doi.org/10.1175/1520-0426(2000)017<0474:QAPITO>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Skamarock, W., and Coauthors, 2008: A description of the Advanced Research WRF version 3. NCAR Tech. Rep. NCAR/TN-475+STR, 113 pp., http://dx.doi.org/10.5065/D68S4MVH.

    • Crossref
    • Export Citation
  • Skey, S. G. P., K. Berger-North, and V. R. Swail, 1998: Measurement of winds and waves from a NOMAD buoy in high sea states. Preprints, Fifth Int. Workshop on Wave Hindcasting and Forecasting, Melbourne, FL, Environment Canada, 163–175, http://waveworkshop.org/5thWaves/C4.pdf.

  • Thomas, B. R., and V. R. Swail, 2011: Buoy wind inhomogeneities related to averaging method and anemometer type: Application to long time series. Int. J. Climatol., 31, 10401055, https://doi.org/10.1002/joc.2339.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Thomas, B. R., E. Kent, and V. Swail, 2005: Methods to homogenize wind speeds from ships and buoys. Int. J. Climatol., 25, 979995, https://doi.org/10.1002/joc.1176.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vautard, R., J. Cattiaux, P. Yiou, J.-N. Thépaut, and P. Ciais, 2010: Northern Hemisphere atmospheric stilling partly attributed to an increase in surface roughness. Nat. Geosci., 3, 756761, https://doi.org/10.1038/ngeo979.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Vejen, F., Ed., 2002: Quality control of meteorological observations: Automatic methods used in the Nordic countries. Norwegian Meteorological Institute KLIMA Tech. Rep. 8/2002, 109 pp.

  • von Storch, H., and R. W. Zwiers, 2003: Statistical Analysis in Climate Research. Cambridge University Press, 484 pp., https://doi.org/10.1017/CBO9780511612336.

    • Crossref
    • Export Citation
  • Wade, C. G. N., 1987: A quality control program for surface mesometeorological data. J. Atmos. Oceanic Technol., 4, 435453, https://doi.org/10.1175/1520-0426(1987)004<0435:AQCPFS>2.0.CO;2.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wan, H., and X. L. Wang, 2006: Canadian special metadata database for climate data homogenization. Environment Canada Internal Rep., 29 pp.

  • Wan, H., X. L. Wang, and V. R. Swail, 2010: Homogenization and trend analysis of Canadian near-surface wind speeds. J. Climate, 23, 1209, https://doi.org/10.1175/2009JCLI3200.1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • WMO, 1950: Provisional guide to international meteorological instrument and observing practice. World Meteorological Organization Tech. Rep. WMO-8, chapter 6.4, 68 pp.

  • WMO, 1969: Measurement of surface wind. Guide to meteorological instruments and methods of observation, 3rd ed. Secretariat of the World Meteorological Organization Tech. Rep. WMO-8, chapter 6.4, 10 pp.

  • WMO, 1983: Measurement of surface wind. Guide to meteorological instruments and methods of observation, 5th ed. Secretariat of the World Meteorological Organization Tech. Rep. WMO-8, chapter 6.6.2, 14 pp.

  • WMO, 2008: Guide to meteorological instruments and methods of observation. 7th ed. World Meteorological Organization Tech. Rep. WMO-8, 716 pp.

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Quality Control of Surface Wind Observations in Northeastern North America. Part II: Measurement Errors

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  • 1 Facultad de Ciencias Físicas, Universidad Complutense Madrid, and Instituto de Geociencias, Universidad Complutense de Madrid–Consejo Superior de Investigaciones Científicas, Madrid, Spain
  • | 2 División de Energías Renovables, CIEMAT, Madrid, Spain
  • | 3 Climate and Atmospheric Sciences Institute, St. Francis Xavier University, Antigonish, Nova Scotia, Canada
  • | 4 Global Forecasters S.L., Madrid, Spain
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Abstract

A quality control (QC) process has been developed and applied to an observational database of surface wind speed and wind direction in northeastern North America. The database combines data from three datasets of different initial quality, including a total of 526 land stations and buoys distributed over the provinces of eastern Canada and five adjacent northeastern U.S. states. The data span from 1953 to 2010. The first part of the QC deals with data management issues and is developed in a companion paper. Part II, presented herein, is focused on the detection of measurement errors and deals with low-variability errors, like the occurrence of unrealistically long calms, and high-variability problems, like rapid changes in wind speed; some types of biases in wind speed and wind direction are also considered. About 0.5% (0.16%) of wind speed (wind direction) records have been flagged. Additionally, 15.87% (1.73%) of wind speed (wind direction) data have been corrected. The most pervasive error type in terms of affected sites and erased data corresponds to unrealistic low wind speeds (89% of sites affected with 0.35% records removed). The amount of detected and corrected/removed records in Part II (~9%) is approximately two orders of magnitude higher than that of Part I. Both management and measurement errors are shown to have a discernible impact on the statistics of the database.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Etor E. Lucio-Eceiza, eelucio@fis.ucm.es

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-16-0204.1

Abstract

A quality control (QC) process has been developed and applied to an observational database of surface wind speed and wind direction in northeastern North America. The database combines data from three datasets of different initial quality, including a total of 526 land stations and buoys distributed over the provinces of eastern Canada and five adjacent northeastern U.S. states. The data span from 1953 to 2010. The first part of the QC deals with data management issues and is developed in a companion paper. Part II, presented herein, is focused on the detection of measurement errors and deals with low-variability errors, like the occurrence of unrealistically long calms, and high-variability problems, like rapid changes in wind speed; some types of biases in wind speed and wind direction are also considered. About 0.5% (0.16%) of wind speed (wind direction) records have been flagged. Additionally, 15.87% (1.73%) of wind speed (wind direction) data have been corrected. The most pervasive error type in terms of affected sites and erased data corresponds to unrealistic low wind speeds (89% of sites affected with 0.35% records removed). The amount of detected and corrected/removed records in Part II (~9%) is approximately two orders of magnitude higher than that of Part I. Both management and measurement errors are shown to have a discernible impact on the statistics of the database.

© 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Etor E. Lucio-Eceiza, eelucio@fis.ucm.es

This article has a companion article which can be found at http://journals.ametsoc.org/doi/abs/10.1175/JTECH-D-16-0204.1

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