Surface wind regionalization in complex terrain
| dc.contributor.author | Jiménez, P. A. | |
| dc.contributor.author | González Rouco, Jesús Fidel | |
| dc.contributor.author | Montávez, J. P. | |
| dc.contributor.author | Navarro, J. | |
| dc.contributor.author | García Bustamante, E. | |
| dc.contributor.author | Valero Rodríguez, Francisco | |
| dc.date.accessioned | 2023-06-20T11:12:17Z | |
| dc.date.available | 2023-06-20T11:12:17Z | |
| dc.date.issued | 2008-01 | |
| dc.description | © 2008 American Meteorological Society. We thank the Sección de Evaluación de Recursos Agrarios del Departamento de Agricultura, Ganadería y Alimentación of the Navarra Government for providing us with the wind dataset used in this study and the ECMWF for the free access to the ERA-40 data. We also thank Drs. M. Montoya and C. Raible for useful discussions, suggestions, and comments during this work, as well as Prof. M. Cornide for providing a first version of the code to calculate the spectral densities. The authors are indebted to the three reviewers for their comments, which helped to improve the quality of the original manuscript considerably. This work was partially funded by Project CGL2005- 06966-C07/CLI. JFGR was supported by a Ramón y Cajal fellowship. | |
| dc.description.abstract | Daily wind variability in the Comunidad Foral de Navarra in northern Spain was studied using wind observations at 35 locations to derive subregions with homogeneous temporal variability. Two different methodologies based on principal component analysis were used to regionalize: 1) cluster analysis and 2) the rotation of the selected principal components. Both methodologies produce similar results and lead to regions that are in general agreement with the topographic features of the terrain. The meridional wind variability is similar in all subregions, whereas zonal wind variability is responsible for differences between them. The spectral analysis of wind variability within each subregion reveals a dominant annual cycle and the varying presence of higher-frequency contributions in the subregions. The valley subregions tend to present more variability at high frequencies than do higher-altitude sites. Last, the influence of large-scale dynamics on regional wind variability is explored by studying connections between wind in each subregion and sea level pressure fields. The results of this work contribute to the characterization of wind variability in a complex terrain region and constitute a framework for the validation of mesoscale model wind simulations over the region. | |
| dc.description.department | Depto. de Física de la Tierra y Astrofísica | |
| dc.description.faculty | Fac. de Ciencias Físicas | |
| dc.description.refereed | TRUE | |
| dc.description.sponsorship | Programa Ramón y Cajal (MEC) | |
| dc.description.sponsorship | Ministerio de Educación y Ciencia (MEC), España | |
| dc.description.status | pub | |
| dc.eprint.id | https://eprints.ucm.es/id/eprint/36431 | |
| dc.identifier.doi | 10.1175/2007JAMC1483.1 | |
| dc.identifier.issn | 1558-8424 | |
| dc.identifier.officialurl | http://dx.doi.org/10.1175/2007JAMC1483.1 | |
| dc.identifier.relatedurl | http://journals.ametsoc.org/ | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/51826 | |
| dc.issue.number | 1 | |
| dc.journal.title | Journal of applied meteorology and climatology | |
| dc.language.iso | eng | |
| dc.page.final | 325 | |
| dc.page.initial | 308 | |
| dc.publisher | American Meteorological Society | |
| dc.relation.projectID | CGL2005- 06966-C07/CLI | |
| dc.rights.accessRights | open access | |
| dc.subject.cdu | 52 | |
| dc.subject.keyword | Principal components | |
| dc.subject.keyword | United-States | |
| dc.subject.keyword | Cluster-analysis | |
| dc.subject.keyword | Daily rainfall | |
| dc.subject.keyword | Precipitation variability | |
| dc.subject.keyword | Classification | |
| dc.subject.keyword | Patterns | |
| dc.subject.keyword | Field | |
| dc.subject.keyword | Rotation | |
| dc.subject.keyword | Stations | |
| dc.subject.ucm | Astrofísica | |
| dc.subject.ucm | Astronomía (Física) | |
| dc.title | Surface wind regionalization in complex terrain | |
| dc.type | journal article | |
| dc.volume.number | 47 | |
| dcterms.references | Anderberg, M. R., 1973: Cluster Analysis for Applications. Academic Press, 359 pp. Bärring, L., 1988: Regionalization of daily rainfall in Kenya by means of common factor analysis. J. Climatol., 8, 371–389. Belserene, E. P., 1988: Rhythms of a variable star. Sky and Telescope, Vol. 76, September, p. 288. Bloomfield, P., 1976: Fourier Analysis of Time Series: An Introduction. Wiley, 258 pp. Blumen, W., Ed., 1990: Atmospheric Processes over Complex Terrain. Meteor. Monogr., No. 45, Amer. Meteor. Soc., 323 pp. Bonell, M., and G. Sumner, 1992: Autumn and winter daily precipitation areas in Wales, 1982–1983 to 1986–1987. Int. J. Climatol., 12, 77–102. Cattell, R. B., 1966: The scree test for the number of factors. Multivariate Behav. Res., 1, 245–276. Cheng, E. D., 1998: Macroscopic extreme wind regionalization. J. Wind Eng. Ind. Aerodyn., 77–78, 13–21. Comrie, A. C., and E. C. Glenn, 1998: Principal componentsbased regionalization of precipitation regimes across the southwest United States and northern Mexico, with an application to monsoon precipitation variability. Climate Res., 10, 201–215. Deeming, T. J., 1975: Fourier analysis with unequally-spaced data. Astrophys. Space Sci., 36, 137–158. DeGaetano, A. T., 1997: A quality-control routine for hourly wind observations. J. Atmos. Oceanic Technol., 14, 308–317. Dyer, T. G. J., 1975: The assignment of rainfall stations into homogeneous groups: An application of principal component analysis. Quart. J. Roy. Meteor. Soc., 101, 1005–1013. Fovell, R. G., and M.-Y. C. Fovell, 1993: Climate zones of the conterminous United States defined using cluster analysis. J. Climate, 6, 2103–2135. Graybeal, D. Y., 2006: Relationships among daily mean and maximum wind speeds, with application to data quality assurance. Int. J. Climatol., 26, 29–43. Green, M., L. O. Myrup, and R. G. Flocchini, 1992: A method for classification of wind field patterns and its application to Southern California. Int. J. Climatol., 12, 111–135. Gregory, S., 1975: On the delimitation of regional patterns of recent climatic fluctuations. Weather, 30, 276–288. Hardy, D., and J. J. Walton, 1978: Principal components analysis of vector wind measurements. J. Appl. Meteor., 17, 1153–1162. Johnson, S. C., 1967: Hierarchical clustering schemes. Psychometrika, 32, 241–254. Kaihatu, J. M., R. A. Handler, G. O. Marmorino, and L. K. Shay, 1998: Empirical orthogonal function analysis of ocean surface currents using complex and real-vector methods. J. Atmos. Oceanic Technol., 15, 927–941. Kaufmann, P., and R. O. Weber, 1996: Classification of mesoscale wind fields in the MISTRAL field experiment. J. Appl. Meteor., 35, 1963–1979. ——, and ——, 1998: Directional correlation coefficient for channeled flow and application to wind data over complex terrain. J. Atmos. Oceanic Technol., 15, 89–97. ——, and C. D. Whiteman, 1999: Cluster-analysis classification of wintertime wind patterns in the Grand Canyon region. J. Appl. Meteor., 38, 1131–1147. Klink, K., and C. J. Willmott, 1989: Principal components of the surface wind field in the United States: A comparison of analyses based upon wind velocity, direction, and speed. Int. J. Climatol., 9, 293–308. Ludwig, F. L., J. Horel, and C. D. Whiteman, 2004: Using EOF analysis to identify important surface wind patterns in mountain valleys. J. Appl. Meteor., 43, 969–983. Mass, C. F., and Y.-H. Kuo, 1998: Regional real-time numerical weather prediction: Current status and future potential. Bull. Amer. Meteor. Soc., 79, 253–263. McGowan, H. A., and A. P. Sturman, 1996: Interacting multiscale wind systems within an alpine basin, Lake Tekapo, New Zealand. Meteor. Atmos. Phys., 58, 165–177. Meek, D. W., and J. L. Hatfield, 1994: Data quality checking for single station meteorological databases. Agric. For. Meteor., 69, 85–109. Milligan, G. W., 1980: An examination of the effect of six types of error perturbation on fifteen clustering algorithms. Psychometrika, 45, 325–342. Preisendorfer, R. W., 1988: Principal Component Analysis in Meteorology and Oceanography. Elsevier, 425 pp. Richman, M. B., 1986: Rotation of principal components. Int. J. Climatol., 6, 293–335. Rife, D. L., C. A. Davis, Y. Liu, and T. T. Warner, 2004: Predictability of low-level winds by mesoscale meteorological models. Mon. Wea. Rev., 132, 2553–2569. Romero, R., C. Ramis, J. A. Guijarro, and G. Sumner, 1999a: Daily rainfall affinity areas in Mediterranean Spain. Int. J. Climatol., 19, 557–578. ——, G. Sumner, C. Ramis, and A. Genovés, 1999b: A classification of the atmospheric circulation patterns producing significant daily rainfall in the Spanish Mediterranean area. Int. J. Climatol., 19, 765–785. Simmons, A. J., and J. K. Gibson, 2000: The ERA-40 Project Plan. ECMWF ERA-40 Project Rep. Series 1, Reading, United Kingdom, 63 pp. Sotillo, M. G., C. Ramis, R. Romero, S. Alonso, and V. Homar, 2003: Role of orography in the spatial distribution of precipitation over the Spanish Mediterranean zone. Climate Res., 23, 247–261. Steinacker, R., and Coauthors, 2006: A mesoscale data analysis and downscaling method over complex terrain. Mon. Wea. Rev., 134, 2758–2771. Stewart, J. Q., C. D. Whiteman, W. J. Steenburgh, and X. Bian, 2002: A climatological study of thermally driven wind systems of the U.S. Intermountain West. Bull. Amer. Meteor. Soc., 83, 699–708. Stooksbury, D. E., and P. J. Michaels, 1991: Cluster analysis of southeastern U.S. climate stations. Theor. Appl. Climatol., 44, 143–150. von Storch, H., 1995: Inconsistencies at the interface of climate impact studies and global climate research. Meteor. Z., 4, 72–80. ——, and F. W. Zwiers, 1999: Statistical Analysis in Climate Research. Cambridge University Press, 484 pp. Weber, R. O., and P. Kaufmann, 1995: Automated classification scheme for wind fields. J. Appl. Meteor., 34, 1133–1141. White, D., M. Richman, and B. Yarnal, 1991: Climate regionalization and rotation of principal components. Int. J. Climatol., 11, 1–25. Whiteman, C. D., 2000: Mountain Meteorology: Fundamentals and Applications. Oxford University Press, 355 pp. ——, and J. C. Doran, 1993: The relationship between overlying synoptic-scale flows and winds within a valley. J. Appl. Meteor., 32, 1669–1682. Wilks, D. S., 1995: Statistical Methods in the Atmospheric Sciences: An Introduction. Academic Press, 467 pp. Xoplaki, E., J. F. González Rouco, J. Luterbacher, and H. Wanner, 2004: Wet season Mediterranean precipitation variability: Influence of large-scale dynamics and trends. Climate Dyn., 23, 63–78. | |
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