Implementation of the WSM5 and WSM6 Single Moment Microphysics Scheme into the RAMS Model: Verification for the HyMeX-SOP1

Hindawi Publishing Corporation Advances in Meteorology Volume 2016, Article ID 5094126, 17 pages http://dx.doi.org/10.1155/2016/5094126 Research Article Implementation of the WSM5 and WSM6 Single Moment Microphysics Scheme into the RAMS Model: Verification for the HyMeX-SOP1 Stefano Federico ISAC-CNR, UOS of Rome, Via del Fosso del Cavaliere 100, 00133 Rome, Italy Correspondence should be addressed to Stefano Federico; Received 20 November 2015; Revised 16 March 2016; Accepted 7 April 2016 Academic Editor: Birgitte R. Furevik Copyright © 2016 Stefano Federico. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This paper shows the results of the implementation of two widely used bulk microphysics parameterizations (BMP) into the Regional Atmospheric Modeling System to improve the Quantitative Precipitation Forecast (QPF). The schemes are the WSM5 and WSM6 (WRF-single-moment-microphysics classes 5 and 6). The RAMS is run at high horizontal resolution (4 km) over the whole Italian territory and, to mimic the operational context, it is initialized by the analysis/forecast cycle issued at 12 UTC by the European Centre for Medium Weather Range Forecast (ECMWF). The performance of the BMP is analysed for the period of September 11 to October 31, 2012, which span most of the Special Observing Period 1 (SOP1) of the hydrological cycle in the Mediterranean experiment (HyMeX). For this period a database of daily precipitation of thousands of rain gauges over the Italian territory is available. In SOP1 few hazardous events occurred over Italy and, for one of them, the model performance is shown in detail. The potential improvement gained by combining the model outputs with different BMP in a single forecast is finally explored. 1. Introduction Numerical weather prediction of Quantitative Precipitation Forecast (QPF) has been continually improved over the last decades, thanks to the increasingly sophisticated physical schemes, improved data assimilation, and postprocessing techniques. Among the physical schemes, the microphysics parameterization plays an outstanding role for QPF [1]. The representation of cloud microstructure and processes in meteorological models can be done by sophisticated bin-resolving cloud models [2–6], which prognose multiple variables for specific intervals of each hydrometeor species size spectrum, or by simpler double and single moment schemes. Bin-resolving cloud models are complex and are very expensive in terms of computing time, deterring their use in the operational context, which is the target of this study. Double moment schemes are becoming more available [7–10] in meteorological models; however, their usage is still limited for the operational forecast because of their increased computational cost, caused by the prediction of the second moment, which, in most cases, is the number concentration. So, bulk microphysics schemes, which reduce the number of prognostic variables by assuming hydrometeor size spectra, are typically used in the operational context. The RAMS (Regional Atmospheric Modeling System) model is a fully compressible nonhydrostatic model developed at the Colorado State University ([11, 12], http://www .atmet.com/). Recently a 3D-Var [13] data assimilation system and the capability to simulate lightning [14] have been added to this model. There are several options for the physical parameterization of the PBL and for the short- and long-wave radiation schemes [11, 12]. However, for the single moment microphysics scheme (with the exception of pristine ice, for which a double moment scheme is always used) the only choice available is that reported in [15] (hereafter RM6). The aim of this paper is to show the performance of two widely used bulk microphysics parameterizations (BMP) implemented into the RAMS to improve the QPF and to compare their performance with RM6. 2 The two schemes, coded into RAMS, are the WRF(Weather Research and Forecasting System-) singlemoment-microphysics class 5 (WSM5) and WRF-singlemoment-microphysics class 6 (WSM6). Most of the BMP are based on the works [16, 17], which have been a central feature of mesoscale and general circulation models. An important problem of [16] was the excessive production of cloud ice at cold temperature. A revision of the ice microphysics processes was given in [18]. The most distinguishing features of the revised scheme were the following: (a) the ice number concentration is a function of temperature; (b) the ice crystal number concentration is a function of the ice amount. The microphysics scheme [18] was coded into WRF in two different configurations: (a) WSM3 (WRF-single-momentmicrophysics class 3), which predicts three categories of hydrometeors, vapour, cloud water/ice, and rain/snow, and (b) WSM5 (WRF-single-moment-microphysics class 5), which considers the hydrometeors, vapour, cloud water, cloud ice, rain, and snow. The WSM5 allows supercooled water to exist and allows a gradual melting of snow falling below the melting layer, a process occurring instantaneously in WSM3 when the snow falls below the 0∘ C level. The study [18] showed that the new microphysics scheme improved significantly the performance for high cloud ice amount, surface precipitation, and large scale mean temperature through a better representation of the ice cloud/radiation feedback. The WSM5 was further tested in [19], where two heavy precipitation events over Korea as well as regional climate experiments were considered (2 months of accumulated precipitation for the period July 1 to August 31, 2002) to test the performance of the WSM5 in terms of long-range forecast, showing good results for QPF in all cases. An extension of the WSM5 was proposed by [20], where the graupel was added as a prognostic variable to the WSM5 scheme and the scheme was referred to as WSM6. The WSM6 scheme was tested for an idealized 2D-thunderstorm and for a 3D real case of heavy precipitation occurred over Korea. The results of [20] show that the change in the hydrometeors prediction number had a negligible impact on the QPF for the coarse horizontal resolution (45 km), while they found a positive and nonnegligible impact, both for the quantitative precipitation at surface and for the temporal storm evolution, at fine (5 km) horizontal grid resolution. Even if decade-old, WSM5 and WSM6 are still widely used BMP of the WRF model [1]. The WSM5 and WSM6 performance are compared with the performance of the RM6 [15]. This scheme uses a generalized gamma size spectrum, rather than a Marshall-Palmer, considers ice-liquid mixed phase hydrometeors (graupel and hail), and introduces approximate solutions to the stochastic collection based on [21], which are used in place of continuous accretion approximations of [18–20]. Despite the continuously improved models’ per (...truncated)