حساسیت‌سنجی میدان باد سطحی شبیه‌سازی‌شده ‌ توسط مدل WRF به شرایط اولیه و طرح‌واره‌های پارامترسازی لایه مرزی سیاره‌ای (مطالعه موردی: منطقه خلیج‌فارس)

نوع مقاله : مقاله پژوهشی‌

نویسندگان

1 پژوهشگاه ملی اقیانوس‌شناسی و علوم جوی، تهران، ایران

2 موسسه ژئوفیزیک دانشگاه تهران، تهران، ایران

چکیده

در این پژوهش عملکرد مدل WRF برای میدان باد سطحی و حساسیت این مدل نسبت به شرایط اولیه و مرزی و طرح‌واره­های لایه مرزی سیاره‌ای در طول چندین تاریخ منتخب به­صورت موردی روی خلیج فارس ارزیابی می­شود. به­دلیل وجود رویکردهای متفاوت در تولید و توسعه داده­های تحلیل و بازتحلیل (مانند سامانه داده‌گواری) و به‌کارگیری روش­های مختلف پارامترسازی در طرح‌واره­های لایه مرزی سیاره‌ای، این تحقیق برای شناسایی مناسب­ترین انتخاب از بین شرایط اولیه و مرزی متنوع و طرح‌واره­های مختلف لایه مرزی هدف­گذاری شده است. برای این منظور سه مجموعه داده (دو بازتحلیل و یک تحلیل) شامل ERA-Interim، NCEP-R2 و NCEP-FNL و شش طرح­واره لایه مرزی سیاره‌ای (دو غیر محلی و چهار  محلی) به همراه طرح‌واره­های سطحی مرتبط ب آنها انتخاب شده است. برای ارزیابی مدل از 22 ایستگاه هواشناسی همدیدی واقع در منطقه و مشاهدات دو ماهواره QuikSCAT و ASCAT استفاده می­شود. یافته­های این مطالعه نشان می­دهد وقتی شبیه­سازی باد مدل با ایستگاه­های هواشناسی همدیدی مقایسه می­شود، صرف­نظر از نوع طرح‌واره لایه مرزی، دو مجموعه داده ERA-Interim و NCEP-FNL که به­عنوان شرایط اولیه و مرزی استفاده می­شوند، عملکرد بهتری نسبت به NCEP-R2 دارند. با درنظرگرفتن طرح‌واره­ها، بهترین نتایج از ترکیب طرح‌واره YSU با داده­های شرط اولیه ERA-Interim برای سرعت باد و NCEP-FNL برای جهت باد استخراج می­شود. مقایسه خروجی مدل با داده­های باد دو ماهواره QuikSCAT و ASCAT نشان می­دهد تفاوت فاحشی بین پیکربندی­های مختلف دیده نمی­شود. باوجوداین، طرح‌واره­های YSU و ACM2 به­ترتیب منجر به تولید سرعت و جهت باد نزدیک به مشاهدات QuikSCAT می­شوند. همه پیکربندی­های مدل حاصل از تمام طرح‌واره­ها، تقریباً نتایج مشابهی در مقایسه با مشاهدات ASCAT دارند به­جز طرح‌واره YSU که میدان باد را اندکی بهتر از سایر طرح‌واره­ها شبیه­سازی می­کند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Sensitivity of the WRF model surface wind simulations to initial conditions and planetary boundary layer parameterization schemes (case study: over Persian Gulf)

نویسندگان [English]

  • Siavash Gholami 1
  • Sarmad Ghader 2
  • Hasan Khaleghi Zavareh 1
  • Parvin Ghafarian 1
1 Iranian National Institute for Oceanography and Atmospheric Science, Tehran, Iran
2 Institute of Geophysics, University of Tehran, Tehran, Iran
چکیده [English]

In this work‎, ‎sensitivity and performance of the Weather Research and Forecasting (WRF) model for surface wind field simulations are evaluated under several initial and‎ boundary conditions‎, ‎along with‎ ‎different planetary boundary layer (PBL) schemes during several dates over the Persian Gulf region‎. Since there are differences between production approaches and development periods of analysis and reanalysis data (namely‎, ‎assimilation system) on the one hand‎, ‎and‎ differences in applied method for PBL parameterization by any scheme on the other hand‎, ‎this paper aims to identify a suitable set up among the whole configurations which‎ are under examination‎. ‎To this end‎, ‎three datasets (two reanalyses and one analysis) including‎, ‎ERA-Interim‎, ‎NCEP-R2‎, ‎and NCEP-FNL and six PBL‎ schemes (two local and four nonlocal) including ACM2‎, ‎BouLac‎, ‎MYJ‎, ‎MYNN‎, ‎QNSE‎, ‎and YSU accompanied by their relevant surface-layer schemes are used‎. To assess the WRF model wind simulations, available observational wind data including 22 synoptic weather stations located in the region and‎ observations of QuikSCAT and ASCAT satellites are employed‎.
Findings of this study indicate that when the wind simulations are compared with synoptic weather stations observations‎, ‎irrespective of the type of PBL scheme‎, ‎ERA-Interim and‎ NCEP-FNL datasets exhibit better performance in comparison with the NCEP-R2 and ‎when PBL schemes are also considered‎, ‎results show that combination of YSU scheme and‎ ERA-Interim reanalysis data leads to a better estimate of wind speed and combination of YSU and NCEP-FNL data generates less error for wind direction‎. Moreover‎, ‎comparison of model wind simulations and observations of QuikSCAT and ASCAT satellites shows that there are no substantial differences between various‎ configurations‎. ‎However‎, ‎using YSU and ACM2 scheme‎s, ‎WRF model generates speed and direction of the wind close to the observations of QuikSCAT‎. Although all tests have almost similar results as ASCAT satellite observations‎, ‎YSU scheme estimates are slightly better than other schemes.
Overall, the results of this study revealed that the major difference between WRF wind simulations and measured winds arises from the choice of initial conditions data and it does not depend on different PBL schemes. Consequently, changing initial and boundary conditions data has a noticeable impact on the model wind results. Thus, in future studies, emphasis must be more on reanalysis and analysis datasets and the option of WRF PBL parameterization schemes should be the second priority.
Due to the fairly good similarity of the model surface wind with QuikSCAT and ASCAT observations, the choice of WRF model simulations as offshore wind database can be a valid available alternative instead of QuikSCAT and ASCAT wind, particularly when meeting their limitation in spatial resolution (swath data) or temporal sampling.

کلیدواژه‌ها [English]

  • surface wind
  • WRF
  • initial/boundary conditions
  • Persian Gulf
  • PBL scheme
غلامی، س.، قادر، س.، خالقی زواره، ح. و غفاریان، پ.، 1397، ارزیابی پیش­یابی میدان باد توسط مدل WRF تحت‌تأثیر شرایط اولیه و مرزی متفاوت در منطقه خلیج فارس: مقایسه با داده­های همدیدی و ماهواره­های QuikSCAT و ASCAT: مجله فیزیک زمین و فضا، 44(1)، 227-243.
Banks, R. F., Tiana-Alsina, J., Baldasano, J. M., Rocadenbosch, F., Papayannis, A., Solomos, S., and Tzanis, C. G., 2016, Sensitivity of boundary-layer variables to PBL schemes in the WRF model based on surface meteorological observations, lidar, and radiosondes during the HygrA-CD campaign: Atmospheric Research, 176, 185–201.
Blackadar, A. K., 1976, Modeling the nocturnal boundary layer: paper presented at Third Symposium on Atmospheric Turbulence, Diffusion and Air Quality, American Meteorological Society, Raleigh, NC.
Borge, R., Alexandrov, V., José del Vas, J., Lumbreras, J., and Rodríguez, E., 2008, A comprehensive sensitivity analysis of the WRF model for air quality applications over the Iberian Peninsula: Atmospheric Environment, 42(37), 8560–8574.
Bougeault, P., and Lacarrere, P., 1989, Parameterization of orography-induced turbulence in a mesobeta-scale model: Monthly Weather Review, 117(8), 1872–1890.
Bouniol, D., Lemaitre, Y., and Protat, A., 2002, Upper-and lower-troposphere coupling processes involved in the FASTEX IOP16 frontal cyclone: Quarterly Journal of the Royal Meteorological Society, Wiley Online Library, 128(582), 1211–1228.
Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Matsui, N., Allan, R. J., Yin, X., Gleason, B. E., Vose, R. S., Rutledge, G., Bessemoulin, P., 2011, The twentieth century reanalysis project: Quarterly Journal of the Royal Meteorological Society, Wiley Online Library, 137(654), 1–28.
Coniglio, M. C., Correia Jr., J., Marsh, P. T., and Kong, F., 2013, Verification of convection-allowing WRF model forecasts of the planetary boundary layer using sounding observations: Weather and Forecasting, 28(3), 842–862.
Deppe, A. J., Gallus Jr., W. A., and Takle, E. S., 2013, A WRF ensemble for improved wind speed forecasts at turbine height: Weather and Forecasting, 28(1),  212–228.
Dudhia, J., 1993, A nonhydrostatic version of the Penn State–NCAR mesoscale model: Validation tests and simulation of an Atlantic Cyclone: Monthly Weather Review, 121(5), 1493–1513.
Easterling, D. R., Anderson, D. M., Cohen, S. J., Gutowski, W. J., Holland, G. J., Kunkel, K. E., Peterson, T. C., Pulwarty, R. S., Stouffer, R. J., and Wehner, M. F., 2008, Measures to improve our understanding of weather and climate extremes: weather and climate extremes in a changing climate. Regions of focus: North America, Hawaii, Caribbean, and US Pacific Islands, A report by the US Climate Change Science Program and the Subcommittee on Global Change Research, Washington DC. Available from http://downloads. climatescience. gov/sap/sap3-3/sap3-3-final-Chapter4.pdf.
Floors, R., Vincent, C. L., Gryning, S. E., Peña, A., and Batchvarova, E., 2013, The wind profile in the coastal boundary layer: Wind lidar measurements and numerical modelling: Boundary-Layer Meteorology, 147(3), 469–491.
Hong, S. Y., Noh, Y., and Dudhia, J., 2006, A new vertical diffusion package with an explicit treatment of entrainment processes: Monthly Weather Review, 134(9), 2318–2341.
Hong, S. Y., and Pan, H. L., 1996, Nonlocal boundary layer vertical diffusion in a medium-range forecast model: Monthly Weather Review, 124(10), 2322–2339.
Janjic, Z. I., 1990, The Step-Mountain coordinate: physical package: Monthly Weather Review, 118(7), 1429–1443.
Janjic, Z. I., 1994, The Step-Mountain Eta coordinate model: Further developments of the convection, viscous sublayer, and turbulence closure schemes: Monthly Weather Review, 122(5), 927–945.
Janjić, Z. I., 1996, The surface layer in the NCEP Eta Model, paper presented at 11th Conference on Numerical Weather Prediction: American Meteorological Society, Norfolk, Va. Preprints.
Janjić, Z. I., 2002, Nonsingular Implementation of the Mellor-Yamada Level 2.5 Scheme in the NCEP Meso model: NCEP Office Note, 437, p. 61. Available at: http://www.emc.ncep.noaa.gov/officenotes/newernotes/on437.pdf.
Jimenez, P. A., Dudhia, J., Gonzalez-Rouco, J. F., Navarro, J., Montavez, J. P., and Garcia-Bustamante, E., 2012, A revised scheme for the WRF surface layer formulation: Monthly Weather Review, 140(3), 898–918.
Kalnay, E., Kanamitsu, M., Kistler, R., Collins, W., Deaven, D., Gandin, L., Iredell, M., Saha, S., White, G., Woollen, J., Zhu, Y., Chelliah, M., Ebisuzaki, W., Higgins, W., Janowiak, J., Mo, K., Ropelewski, C., Wang, J., Leetmaa, A., Reynolds, R., Jenne, R., and Joseph, D., 1996, The NCEP/NCAR 40-year reanalysis project: Bulletin of the American Meteorological Society, 77(3), 437–471.
Kosovic, B., and Curry, J. A., 2000, A large eddy simulation study of a quasi-steady, stably stratified atmospheric boundary layer: Journal of the Atmospheric Sciences, 57(8), 1052–1068.
Laprise, R., De Elia, R., Caya, D., Biner, S., Lucas-Picher, P. H., Diaconescu, E., Leduc, M., Alexandru, A., Separovic, L., 2008, Challenging some tenets of regional climate modelling: Meteorology and Atmospheric Physics, Springer, 100(1–4), 3–22.
Mellor, G. L., and Yamada, T., 1974, A hierarchy of turbulence closure models for planetary boundary layers: Journal of the Atmospheric Sciences, 31(7), 1791–1806.
Mellor, G. L., and Yamada, T., 1982, Development of a turbulence closure model for geophysical fluid problems: Reviews of Geophysics, 20(4), 851–875.
Nakanishi, M., and Niino, H., 2004, An improved Mellor-Yamada level-3 model with condensation physics: Its design and verification: Boundary-Layer Meteorology, 112(1), 1–31.
Nakanishi, M., and Niino, H., 2006, An improved Mellor-Yamada level-3 model: Its numerical stability and application to a regional prediction of advection fog: Boundary-Layer Meteorology, 119(2), 397–407.
Perrone, T. J., 1979, Winter Shamal in the Persian Gulf: Naval environmental prediction research facility menterey, Technical Report.
Pleim, J. E., and Chang, J. S., 1992, A non-local closure model for vertical mixing in the convective boundary layer: Atmospheric environment, Part A, General Topics, 26(6), 965–981.
Pleim, J. E., 2007a, A combined local and nonlocal closure model for the atmospheric boundary layer, Part I: Model description and testing: Journal of Applied Meteorology and Climatology, 46(9), 1383–1395.
Pleim, J. E., 2007b, A combined local and nonlocal closure model for the atmospheric boundary layer, Part II: Application and evaluation in a mesoscale meteorological model: Journal of Applied Meteorology and Climatology, 46(9), 1396–1409.
Rauscher, S. A., Coppola, E., Piani, C., and Giorgi, F., 2010, Resolution effects on regional climate model simulations of seasonal precipitation over Europe: Climate Dynamics, Springer, 35(4), 685–711.
Shin, H. H., and Hong, S. Y., 2011, Intercomparison of planetary boundary-layer parametrizations in the WRF model for a single day from CASES-99: Boundary-Layer Meteorology, 139(2), 261–281.
Skamarock, W. C., Klemp, J. B., Dudhi, J., Gill, D. O., Barker, D. M., Duda, M. G., Huang, X. Y., Wang, W., and Powers, J. G., 2008, A description of the advanced research WRF Version 3: NCAR Technical note-475+STR.
Sukoriansky, S., 2008, Implementation of the Quasi-Normal Scale Elimination (QNSE) model of stably stratified turbulence in WRF: Report on WRF-DTC Visit.
Sukoriansky, S., Galperin, B., and Perov, V., 2005, Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice: Boundary-Layer Meteorology, 117(2), 231–257.
Wang, W., Bruyére, C., Duda, M., Dudhia, J., Gill, D., Kavulich, M., Keene, K., Lin, H. C., Michalakes, J., Rizvi, S. and Others, 2014, ARW Version 3 Modeling System User’s Guide January 2014: National Center for Atmospheric Research, Boulder, CO, http://www2.mmm.ucar.edu/wrf/users/docs/user_guide_V3/contents.html.
Wilks, D. S., 2011, Forecast verification: Academic Press, 100, 301–394.
Xie, B., Fung, J. C. H., Chan, A., and Lau, A., 2012, Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model: Journal of Geophysical Research Atmospheres, 117(12), 1–26.