Abstract
Numerical weather prediction (NWP) models can complement the satellite technology in simulating the cloud properties, especially in extreme storm events, when gathering new data becomes more than essential for accurate weather forecasting. In this study, we investigate the capability of the Weather Research and Forecasting (WRF) model to realistically simulate some important cloud properties in high-resolution grids, such as cloud phase (e.g., liquid or ice) and cloud water path. The sensitivity of different combinations of physics parameterizations to the simulated cloud fields is studied. The experiment is conducted on a super typhoon event by configuring the WRF model in two domains, with two-way nesting, allowing bidirectional information exchange between the parent and the nest. In order to do the assessment, the simulated cloud fields are compared against MODIS-derived cloud properties from one overpass scene. While the simulations have been able to capture the spatial distribution of cloud properties reasonably well, produced cloud quantities such as ice water path has been significantly overestimated when compared to the MODIS optical cloud information. The microphysics parameterizations are found to be more sensitive than the planetary boundary layer (PBL) parameterizations.
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Bougeault P, Lacarrere P (1989) Parameterization of orography-induced turbulence in a mesobeta-scale model. Mon Weather Rev 117(8):1872–1890. doi:10.1175/1520-0493(1989)117<1872:pooiti>2.0.co;2
Chen F, Dudhia J (2001) Coupling an advanced land surface-hydrology model with the Penn State-NCAR MM5 modeling system. Part I: model implementation and sensitivity. Mon Weather Rev 129(4):569–585. doi:10.1175/1520-0493(2001)129<0569:caalsh>2.0.co;2
Dai Q, Han DW, Rico-Ramirez MA, Islam T (2013) The impact of raindrop drift in a three-dimensional wind field on a radar-gauge rainfall comparison. Int J Remote Sens 34(21):7739–7760. doi:10.1080/01431161.2013.826838
Hong S-Y, Lim J-OJ (2006) The WRF single-moment 6-class microphysics scheme (WSM6). J Korean Meteor Soc 42(2):129–151
Hong SY, Dudhia J, Chen SH (2004) A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon Weather Rev 132(1):103–120. doi:10.1175/1520-0493(2004)132<0103:aratim>2.0.co;2
Hong SY, Noh Y, Dudhia J (2006) A new vertical diffusion package with an explicit treatment of entrainment processes. Mon Weather Rev 134(9):2318–2341. doi:10.1175/mwr3199.1
Ishak A, Remesan R, Srivastava P, Islam T, Han DW (2013) Error correction modelling of wind speed through hydro-meteorological parameters and mesoscale model: a hybrid approach. Water Resour Manag 27(1):1–23. doi:10.1007/s11269-012-0130-1
Islam T, Rico-Ramirez MA, Han DW, Bray M, Srivastava PK (2013) Fuzzy logic based melting layer recognition from 3 GHz dual polarization radar: appraisal with NWP model and radio sounding observations. Theor Appl Climatol 112(1–2):317–338. doi:10.1007/s00704-012-0721-z
Islam T, Rico-Ramirez M, Srivastava P, Dai Q, Han D, Gupta M, Zhuo L (2014a) CLOUDET: a cloud detection and estimation algorithm for passive microwave imagers and sounders aided by naïve Bayes classifier and multilayer perceptron. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing PP (99)
Islam T, Rico-Ramirez MA, Han DW, Srivastava PK (2014b) Sensitivity associated with bright band/melting layer location on radar reflectivity correction for attenuation at C-band using differential propagation phase measurements. Atmos Res 135:143–158. doi:10.1016/j.atmosres.2013.09.003
Islam T, Srivastava P, Rico-Ramirez M, Dai Q, Gupta M, Singh S (2014c) Tracking a tropical cyclone through WRF–ARW simulation and sensitivity of model physics. Nat Hazards:1–23. doi:10.1007/s11069-014-1494-8
Islam T, Srivastava PK, Rico-Ramirez MA, Dai Q, Han DW, Gupta M (2014d) An exploratory investigation of an adaptive neuro fuzzy inference system (ANFIS) for estimating hydrometeors from TRMM/TMI in synergy with TRMM/PR. Atmos Res 145:57–68. doi:10.1016/j.atmosres.2014.03.019
Kain JS (2004) The kain-fritsch convective parameterization: an update. J Appl Meteorol 43(1):170–181. doi:10.1175/1520-0450(2004)043<0170:tkcpau>2.0.co;2
Milbrandt JA, Yau MK (2005a) A multimoment bulk microphysics parameterization. Part I: analysis of the role of the spectral shape parameter. J Atmos Sci 62(9):3051–3064. doi:10.1175/jas3534.1
Milbrandt JA, Yau MK (2005b) A multimoment bulk microphysics parameterization. Part II: a proposed three-moment closure and scheme description. J Atmos Sci 62(9):3065–3081. doi:10.1175/jas3535.1
Minnis P, Sun-Mack S, Young DF, Heck PW, Garber DP, Chen Y, Spangenberg DA, Arduini RF, Trepte QZ, Smith WL, Ayers JK, Gibson SC, Miller WF, Hong G, Chakrapani V, Takano Y, Liou KN, Xie Y, Yang P (2011) CERES edition-2 cloud property retrievals using TRMM VIRS and terra and aqua MODIS data-part I: algorithms. IEEE Trans Geosci Remote Sens 49(11):4374–4400. doi:10.1109/tgrs.2011.2144601
Nakanishi M, Niino H (2006) An improved mellor-yamada level-3 model: its numerical stability and application to a regional prediction of advection fog. Bound-Layer Meteorol 119(2):397–407. doi:10.1007/s10546-005-9030-8
Otkin JA, Greenwald TJ (2008) Comparison of WRF model-simulated and MODIS-derived cloud data. Mon Weather Rev 136(6):1957–1970. doi:10.1175/2007mwr2293.1
Platnick S, King MD, Ackerman SA, Menzel WP, Baum BA, Riedi JC, Frey RA (2003) The MODIS cloud products: algorithms and examples from terra. IEEE Trans Geosci Remote Sens 41(2):459–473. doi:10.1109/tgrs.2002.808301
Pleim JE (2007) A combined local and nonlocal closure model for the atmospheric boundary layer. Part I: model description and testing. J Appl Meteorol Climatol 46(9):1383–1395. doi:10.1175/jam2539.1
Skamarock WC, Klemp JB (2008) A time-split nonhydrostatic atmospheric model for weather research and forecasting applications. J Comput Phys 227(7):3465–3485. doi:10.1016/j.jcp.2007.01.037
Srivastava PK, Han DW, Rico-Ramirez MA, Al-Shrafany D, Islam T (2013) Data fusion techniques for improving soil moisture deficit using SMOS satellite and WRF-NOAH land surface model. Water Resour Manag 27(15):5069–5087. doi:10.1007/s11269-013-0452-7
Srivastava PK, Han D, Rico-Ramirez MA, O’Neill P, Islam T, Gupta M (2014a) Assessment of SMOS soil moisture retrieval parameters using tau–omega algorithms for soil moisture deficit estimation. Journal of Hydrology 519, Part A (0):574–587. doi:http://dx.doi.org/10.1016/j.jhydrol.2014.07.056
Srivastava PK, Han DW, Rico-Ramirez MA, Islam T (2014b) Sensitivity and uncertainty analysis of mesoscale model downscaled hydro-meteorological variables for discharge prediction. Hydrol Process 28(15):4419–4432. doi:10.1002/hyp.9946
Sukoriansky S, Galperin B, Perov V (2005) Application of a new spectral theory of stably stratified turbulence to the atmospheric boundary layer over sea ice. Bound-Layer Meteorol 117(2):231–257. doi:10.1007/s10546-004-6848-4
Tao WK, Simpson J, McCumber M (1989) An ice water saturation adjustment. Mon Weather Rev 117(1):231–235. doi:10.1175/1520-0493(1989)117<0231:aiwsa>2.0.co;2
Thompson G, Field PR, Rasmussen RM, Hall WD (2008) Explicit forecasts of winter precipitation using an improved bulk microphysics scheme. Part II: implementation of a new snow parameterization. Mon Weather Rev 136(12):5095–5115. doi:10.1175/2008mwr2387.1
Acknowledgments
The authors would like to acknowledge the European Centre for Medium-Range Weather Forecasts (2009), ERA-Interim Project, http://rda.ucar.edu/datasets/ds627.0/, Research Data Archive at the National Center for Atmospheric Research, Computational and Information Systems Laboratory, Boulder, CO. The MODIS data used in this study were acquired as part of the NASA’s Earth-Sun System Division and archived and distributed by the MODIS Adaptive Processing System (MODAPS). Portion of the research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (NASA).
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Islam, T., Srivastava, P.K. & Dai, Q. High-resolution WRF simulation of cloud properties over the super typhoon Haiyan: physics parameterizations and comparison against MODIS. Theor Appl Climatol 126, 427–435 (2016). https://doi.org/10.1007/s00704-015-1575-y
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DOI: https://doi.org/10.1007/s00704-015-1575-y