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Evaluation of the WRF physics ensemble using a multivariable integrated evaluation approach over the Haihe river basin in northern China

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Abstract

A crucial step in the application of the Weather Research and Forecasting (WRF) model to regional climate research is the selection of the proper combinations of physical parameterizations. In this study, we examined the performance of various parametrization schemes in the WRF model in terms of precipitation and temperature over the Haihe river basin in northern China. The WRF experiments were integrated with 13-km horizontal resolution and driven by ERA-INTERIM reanalysis data over the period from 1st June to 31st August, 2016. Fifty-eight members of physics combinations derived from five types of physics options were assessed against the available observational temperature and precipitation data by utilizing the multivariable integrated evaluation (MVIE) method. Our results indicated that the best combination of physical schemes consisted of CAM5.1 microphysics, MRF PBL, BMJ cumulus, CAM Longwave/Shortwave radiation, and Noah Land Surface schemes. The optimal setup’s differences with the observational data, temporally and spatially, were much smaller than other setups in terms of surface air temperature and precipitation, which proves that the optimal setup showed better performance than the other setups. Further analysis of the sensitivities of model outputs to different types of physics options suggests that the microphysics, planetary boundary layer (PBL), and cumulus schemes have a more significant impact on the model performances than the radiation scheme and Land Surface schemes.

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References

  • Argüeso D, Hidalgo Muñoz JM, Gámiz Fortis SR et al (2011) Evaluation of WRF parameterizations for climate studies over southern Spain using a multistep regionalization. J Clim 24(21):5633–5651

    Google Scholar 

  • Balzarini A, Angelini F, Ferrero L et al (2014) Sensitivity analysis of PBL schemes by comparing WRF model and experimental data. Geosci Model Develop Discuss 7:6133–6171

    Google Scholar 

  • Bastidas LA, Hogue TS, Sorooshian S et al (2006) Parameter sensitivity analysis for different complexity land surface models using multicriteria methods. J Geophys Res 111(D20):1–19

    Google Scholar 

  • Borge R, Alexandrov V, del Vas JJ, Lumbreras J, Encarnacio´ n R (2008) A comprehensive sensitivity analysis of the WRF model for air quality applications over the IberianPeninsula. Atmos. Environ. 42:8560–8574

    Google Scholar 

  • Budakoti S, Singh C, Pal PK (2019) Assessment of various cumulus parameterization schemes for the simulation of very heavy rainfall event based on optimal ensemble approach. Atmospheric Res 218:195–206

    Google Scholar 

  • Bukovsky MS, Karoly DJ (2009) Precipitation simulations using WRF as a nested regional climate model. J Appl Meteorol Clim 48:2152–2159

    Google Scholar 

  • 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 129:569–585

    Google Scholar 

  • Chen F, Liu C, Dudhia J et al (2014) A sensitivity study of high-resolution regional climate simulations to three land surface models over the western United States. J Geophys Res Atmospheres 119:7271–7291

    Google Scholar 

  • Christensen O, Gaertner M, Prego J et al (2001) Internal variability of regional climate models. Clim Dyn 17:875–887

    Google Scholar 

  • Cohen AE, Cavallo SM, Coniglio MC et al (2015) A review of planetary boundary layer parameterization schemes and their sensitivity in simulating southeastern U.S. cold season severe weather environments. Weather Forecast 30:150224120634008

    Google Scholar 

  • Collins WD, Rasch PJ, Boville BA et al (2006) The formulation and atmospheric simulation of the Community Atmosphere Model version 3 (CAM3). J Clim 19:2144–2161

    Google Scholar 

  • Crétat J, Pohl B, Richard Y et al (2012) Uncertainties in simulating regional climate of Southern Africa: sensitivity to physical parameterizations using WRF. Clim Dynam 38:613–634

    Google Scholar 

  • Denis B, Laprise R, Caya D et al (2002) Downscaling ability of one-way nested regional climate models: the big-brother experiment. Clim Dynam 18(627):646

    Google Scholar 

  • Dickinson RE, Errico RM, Giorgi F et al (1989) A regional climate model for the western United States. Clim Change 15:383–422

    Google Scholar 

  • Ding Y, Wang Z, Sun Y (2008) Inter-decadal variation of the summer precipitation in East China and its association with decreasing Asian summer monsoon. Part I: observed evidences. Int J Climatol 228:1139–1161

    Google Scholar 

  • Ding Y, Wang Z, Sun Y (2010) Inter-decadal variation of the summer precipitation in East China and its association with decreasing Asian summer monsoon. Part I: observed evidences. Int J Climtol 28(9):1139–1161

    Google Scholar 

  • Duan Y, Ma Z, Yang Q (2017) Characteristics of consecutive dry days variations in China. Theoret Appl Climatol 130(1–2):711–711

    Google Scholar 

  • Eaton B (2011) User’s guide to the community atmosphere model CAM-5.1. NCAR. http://www.cesm.ucar.edu/models/cesm1.0/cam.

  • Ek MB, Mitchell KE, Lin Y, Rogers E, Grunmann P, Koren V, Gayno G, Tarpley JD (2003) Implementation of Noah land surface model advancements in the National Centers for Environmental Prediction operational mesoscale Eta model. J Geophys Res 108:8851

    Google Scholar 

  • Evans JP, Ekström M, Ji F (2012) Evaluating the performance of a WRF physics ensemble over South-East Australia. Clim Dyn 39:1241–1258

    Google Scholar 

  • Fernández J, Montávez JP, Sáenz J et al (2007) Sensitivity of the MM5 mesoscale model to physical parameterizations for regional climate studies: annual cycle. J Geophys Res Atmos 112(D4):D04101

    Google Scholar 

  • Ferreira JA, Carvalho AC, Carvalheiro L et al (2014) On the influence of physical parameterisations and domains configuration in the simulation of an extreme precipitation event. Dyn Atmos Oceans 68:35–55

    Google Scholar 

  • Gallus JS, Bresch J (2006) Comparison of impacts of WRF dynamic core, physics package, and initial conditions on warm season rainfall forecasts. Mon Weather Rev 134:2632

    Google Scholar 

  • Giannaros C, Melas D, Giannaros TM (2019) On the short-term simulation of heat waves in the Southeast Mediterranean: sensitivity of the WRF model to various physics schemes. Atmos Res 218:99–116

    Google Scholar 

  • Gillett NP, Thompson DWJ (2003) Simulation of recent Southern Hemisphere climate change. Science 302:273–275

    Google Scholar 

  • Giorgi F (2006) Regional climate modeling: status and perspectives. J Physique IV 139:101–118

    Google Scholar 

  • Giorgi F, Bi X (2000) A study of internal variability of a regional climate model. J Geophys Res 105:29503–29516

    Google Scholar 

  • Gleckler PJ, Taylor KE, Doutriaux C (2008) Performance metrics for climate models. J Geophys Res 113:D06104

    Google Scholar 

  • Hasan MA, Islam AKMS (2018) Evaluation of microphysics and cumulus schemes of WRF for forecasting of heavy monsoon rainfall over the southeastern hilly region of Bangladesh. Pure Applied Geophys 175:4537–4566

    Google Scholar 

  • He J, Yang XH, Li JQ et al (2015) Spatiotemporal variation of meteorological droughts based on the daily comprehensive drought index in the Haihe River basin, China. Nat Hazards 75:199–217

    Google Scholar 

  • Hong SY, Pan HL (1996) Nonlocal boundary layer vertical diffusion in a medium-range forecast model. Mon Weather Rev 124:2322–2339

    Google Scholar 

  • Hu XM, Nielsen-Gammon JW, Zhang F (2010) Evaluation of three planetary boundary layer schemes in the WRF model. J Appl Meteorol Climatol 49:1831–1844

    Google Scholar 

  • Huang F, Xu Z, Guo W (2018) Evaluating vector winds in the Asian-Australian monsoon region simulated by 37 CMIP5 models. Clim Dyn 53(1–2):491–507

    Google Scholar 

  • Huang F, Xu Z, Guo W (2020) The linkage between CMIP5 climate models’ abilities to simulate precipitation and vector winds. Clim Dyn 54(11–12):4953–4970

    Google Scholar 

  • Janjic ZI (1994) The step-mountain eta coordinate model: Further developments of the convection, viscous sublayer and turbulence closure schemes. Mon Wea Rev 122:927–945

    Google Scholar 

  • Janjic ZI (2000) Comments on “Development and Evaluation of a Convection Scheme for Use in Climate Models.” J Atmos Sci 57:3686

    Google Scholar 

  • Jerez S, Montavez JP, Jimenez-Guerrero P et al (2013) A multi-physics ensemble of present-day climate regional simulations over the Iberian Peninsula. Clim Dyn 40:3023–3046

    Google Scholar 

  • Koren V, Schaake JC, Mitchell KE, Duan QY, Chen F, Baker JM (1999) A parameterization of snowpack and frozen ground intended for NCEP weather and climate models. J Geophys Res 104:19569–19585

    Google Scholar 

  • Landman WA, Seth A, Camargo SJ (2005) The effect of regional climate model domain choice on the simulation of tropical cyclone-like vortices in the southwestern Indian Ocean. J Climate 18:1263–1274

    Google Scholar 

  • Li W, Guo W, Xue Y et al (2016) Sensitivity of a regional climate model to land surface parameterization schemes for East Asian summer monsoon simulation. Clim Dyn 47:2293–2308

    Google Scholar 

  • Li Y, Li Z, Zhang Z et al (2019) High-resolution regional climate modeling and projection over western canada using a weather research forecasting model with a pseudo-global warming approach. Hydrol Earth Syst Sci 23(11):4635–4659

    Google Scholar 

  • Li MX, Ma Z (2015) Soil moisture drought detection and multi-temporal variability across China. Sci China-Earth Sci 58(10):1798–1813

    Google Scholar 

  • Liu CH, Ikeda K, Rasmussen R et al (2017) Continental-scale convection-permitting modeling of the current and future climate of North America. Clim Dyn 49(1–2):71–95

    Google Scholar 

  • Ma ZG, Fu C (2006) Some evidences of drying trend over North China from 1951 to 2004. Chin Sci Bull 51(23):2913–2925

    Google Scholar 

  • Ma ZG, Fu C (2007) Evidences of drying trend in the global during the later half of 20th century and their relationship with large-scale climate background. Sci China Ser D-Earth Sci 50(5):776–788

    Google Scholar 

  • Mooney PA, Mulligan FJ, Fealy R (2013) Evaluation of the sensitivity of the Weather Research and Forecasting Model to parameterization schemes for regional climates of Europe over the period 1990–95. J Clim 26:1002–1017

    Google Scholar 

  • Osborn TJ (2004) Simulating the winter North Atlantic Oscillation: the roles of internal variability and greenhouse gas forcing. Clim Dyn 22:605–623

    Google Scholar 

  • Perkins SE, Pitman AJ, Holbrook NJ et al (2007) Evaluation of the AR4 climate models’ simulated daily maximum temperature, minimum temperature, and precipitation over Australia using probability density functions. J Clim 20:4356

    Google Scholar 

  • Pieri AB, Von Hardenberg J, Parodi A et al (2015) Sensitivity of precipitation statistics to resolution, microphysics, and convective parameterization: a case study with the high-resolution WRF climate model over Europe. J Hydrometeorol 16:1857–1872

    Google Scholar 

  • Quan J, Di Z, Duan Q et al (2016) An evaluation of parametric sensitivities of different meteorological variables simulated by the WRF model. Quart J Royal Meteorolog Soc 142:2925–2934

    Google Scholar 

  • Ratnam JV, Kumar KK (2005) Sensitivity of the simulated monsoons of 1987 and 1988 to convective parameterization schemes in MM5. J Clim 18:2724–2743

    Google Scholar 

  • Schaefer JT (1990) The critical success index as an indicator of warning skill. Wea Forecast 5:570–575

    Google Scholar 

  • Seth A, Giorgi F (1998) The effects of domain choice on summer precipitation simulation and sensitivity in a regional climate model. J Clim 11:2698–2712

    Google Scholar 

  • Stergiou I, Tagaris E, Sotiropoulou RE (2017) Sensitivity Assessment of WRF Parameterizations over Europe. Proceedings 1(5):119.

  • Skamarock WC, et al. (2008) A description of the Advanced Research WRF version 3. NCAR Tech. Note NCAR/TN–4751STR. pp 113.

  • Taylor KE (2001) Summarizing multiple aspects of model performance in a single diagram. J Geophys Res: Atmos 106:7183–7192

    Google Scholar 

  • Tegoulias I, Kartsios S, Pytharoulis I et al (2017) The influence of WRF parameterisation schemes on high resolution simulations over Greece Perspectives on Atmospheric Sciences. Springer, Cham, pp 3–8

    Google Scholar 

  • Tian J, Liu J, Wang J et al (2017) A spatio-temporal evaluation of the WRF physical parameterisations for numerical rainfall simulation in semi-humid and semi-arid catchments of Northern China. Atmos Res 191:141–155

    Google Scholar 

  • Troen IB, Mahrt L (1986) A simple model of the atmospheric boundary layer; sensitivity to surface evaporation. Boundary-Layer Meteorol 37:129–148

    Google Scholar 

  • Von Storch H, Langenberg H, Feser F (2000) A spectral nudging technique for dynamical downscaling purposes. Mon Wea Rev 128:3664–3673

    Google Scholar 

  • Wang H (2001) The weakening of the Asian monsoon circulation after the end of 1970’s. Adv Atmos Sci 18(3):376–386

    Google Scholar 

  • Wang D, Yu X, Jia G et al (2019) Sensitivity analysis of runoff to climate variability and land-use changes in the Haihe Basin mountainous area of north China. Agric Ecosys Environ 269:193–203

    Google Scholar 

  • Wang Y, Leung LR, McGregor JL et al (2004) Regional climate modeling: progress, challenges, and prospects. J Meteor Soc Japan Ser II 82:1599–1628

    Google Scholar 

  • Willmott CJ, Ackleson SG, Davis RE et al (1985) Statistics for the evaluation and comparison of models. J Geophys Res Oceans 90:8995–9005

    Google Scholar 

  • Xie B, Fung JCH, Chan A et al (2012) Evaluation of nonlocal and local planetary boundary layer schemes in the WRF model. J Geophys Res Atmos. https://doi.org/10.1029/2011JD017080

    Article  Google Scholar 

  • Xu Z, Hou Z, Han Y et al (2016) A diagram for evaluating multiple aspects of model performance in simulating vector fields. Geosci Model Devel 9:4365–4380

    Google Scholar 

  • Xu Z, Han Y, Fu C (2017) Multivariable integrated evaluation of model performance with the vector field evaluation diagram. Geosci Model Devel Discuss 10:1–31

    Google Scholar 

  • Xu Z, Han Y (2020) Short communication comments on ‘DISO: A rethink of Taylor diagram.’ Int J Climatol 40(4):2506–2510

    Google Scholar 

  • Yáñez-Morroni G, Gironás J, Caneo M et al (2018) Using the Weather Research and Forecasting (WRF) model for precipitation forecasting in an Andean region with complex topography. Atmosphere 9:304

    Google Scholar 

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Acknowledgements

This study was jointly sponsored by the National Key Research and Development Program of China (2017YFC1501804) and the National Natural Science Foundation of China (Grant No.41875116). The authors would like to acknowledge two anonymous reviewers for their insightful suggestions that inspired this work.

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Authors and Affiliations

  1. Key Laboratory of Regional Climate and Environment for Temperate East Asia, RCE-TEA, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China

    Danqiong Dai, Liang Chen, Zhuguo Ma & Zhongfeng Xu

  2. University of Chinese Academy of Sciences, Beijing, China

    Danqiong Dai, Liang Chen & Zhuguo Ma

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  1. Danqiong Dai
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Correspondence to Liang Chen.

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Dai, D., Chen, L., Ma, Z. et al. Evaluation of the WRF physics ensemble using a multivariable integrated evaluation approach over the Haihe river basin in northern China. Clim Dyn 57, 557–575 (2021). https://doi.org/10.1007/s00382-021-05723-x

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