Assessing the impacts of different WRF precipitation physics in hurricane simulations

Weather and Forecasting

Volumn 27, Issue 4, 2012, Pages 1003-1016

  Nasrollahi, Nasrin ^a   Aghakouchak, Amir ^a   Li, Jialun ^a   Gao, Xiaogang ^a   Hsu, Kuolin ^a   Sorooshian, Soroosh ^a  

^a University of California at Irvine   (United States)

Author keywords

Cloud parameterizations; Convective parameterization, Numerical weather prediction forecasting; Numerical weather prediction forecasting

Indexed keywords

CUMULUS PARAMETERIZATION; EXTREME EVENTS; GRID SIZE; GROUND-BASED OBSERVATIONS; IMPACT MODEL; MICROPHYSICS; MODEL OUTPUTS; NUMERICAL WEATHER PREDICTION; NUMERICAL WEATHER PREDICTION MODELS; PARAMETERIZATION SCHEMES; PRECIPITATION PHYSICS; WEATHER RESEARCH AND FORECASTING MODELS;

HURRICANES; PARAMETERIZATION; PHYSICS; UNCERTAINTY ANALYSIS; WEATHER FORECASTING;

CLOUDS;

ACCURACY ASSESSMENT; CLIMATE MODELING; CLOUD MICROPHYSICS; CUMULUS; HURRICANE; MODEL TEST; NUMERICAL MODEL; PARAMETERIZATION; PRECIPITATION ASSESSMENT; PRECIPITATION INTENSITY; STORM TRACK; WEATHER FORECASTING;

EID: 84868315987     PISSN: 08828156     EISSN: 15200434     Source Type: Journal    
DOI: 10.1175/WAF-D-10-05000.1     Document Type: Article

References (43)

1. AghaKouchak, A., A. Bárdossy, and E. Habib, 2010a: Conditional simulation of remotely sensed rainfall data using a non-Gaussian v-transformed copula.Adv.WaterResour., 33, 624-634.
2. AghaKouchak, A., A. Bárdossy, and E. Habib, 2010b: Copula-based uncertainty modeling: Application to multi-sensor precipitation estimates. Hydrol. Processes, 24, 2111-2124.
3. AghaKouchak, A., E. Habib, and A. Bárdossy, 2010c: Modeling radar rainfall estimation uncertainties: Random error model. J. Hydrol. Eng., 15, 265-274.
4. AghaKouchak, A., N. Nasrollahi, J. Li, B. Imam, and S. Sorooshian, 2011: Geometrical characterization of precipitation patterns. J. Hydrometeor., 12, 274-285.
5. Arnaud, P., C. Bouvier, L. Cisner, and R. Dominguez, 2002: Influence of rainfall spatial variability on flood prediction. J. Hydrol., 260, 216-230.
6. Chen, F., and J. Dudhia, 2001: Coupling an advanced land surface- hydrology model with the Penn State-NCAR MM5 modeling system. Part I: Model implementation and sensitivity. Mon. Wea. Rev., 129, 569-585.
7. Ciach, G., W. Krajewski, and G. Villarini, 2007: Product-errordriven uncertainty model for probabilistic quantitative precipitation estimation with NEXRADdata. J. Hydrometeor., 8, 1325-1347.
8. Corradini, C., and V. Singh, 1985: Effect of spatial variability of effective rainfall on direct runoff by geomorphologic approach. J. Hydrol., 81, 27-43.
9. Dudhia, J., 1989: Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale twodimensional model. J. Atmos. Sci., 46, 3077-3107.
10. Ferrier, B. S., 1994: A double-moment multiple-phase four-class bulk ice scheme. Part I: Description. J. Atmos. Sci., 51, 249-280.
11. Fiener, P., and K. Auerswald, 2009: Spatial variability of rainfall on a sub-kilometre scale. Earth Surf. Processes Landforms, 34, 848-859.
12. Fovell, R., 2006: Impact of microphysics on hurricane track and intensity forecasts. Seventh WRF Users' Workshop, Boulder, CO, National Center of Atmospheric Research, 3.2. [Available online at http://www.mmm.ucar.edu/wrf/users/workshops/WS2006/abstracts/Session03/3_2_Fovell.pdf.]
13. Fovell, R., K. Corbosiero, and H.-C. Kuo, 2010: Influence of cloudradiative feedback on tropical cyclone motion symmetric contributions. Preprints, 29th Conf. on Hurricanes and Tropical Meteorology, Tucson, AZ, Amer. Meteor. Soc., 13C.5. [Available online at http://ams.confex.com/ams/pdfpapers/168859.pdf.]
14. Gallus, W., Jr., 1999: Eta simulations of three extreme rainfall events: Impacts of resolution and choice of convective scheme. Wea. Forecasting, 14, 405-426.
15. Goodrich, D., J. Faures, D. Woolhiser, L. Lane, and S. Sorooshian, 1995: Measurement and analysis of small-scale convective storm rainfall variability. J. Hydrol., 173, 283-308.
16. Grell, G., and D. Devenyi, 2002: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29, 1693-1696.
17. Hong, S.-Y., and J. Dudhia, 2003: Testing of a new non-local boundary layer vertical diffusion scheme in numerical weather prediction applications. Preprints, 20th Conf. on Weather Analysis and Forecasting/16th Conf. on Numerical Weather Prediction, Seattle, WA, Amer. Meteor. Soc., 17.3. [Available online at http://ams.confex.com/ams/pdfpapers/72744.pdf.]
18. Hong, S.-Y., J. Dudhia, and S.-H. Chen, 2004: A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation. Mon. Wea. Rev., 132, 103-120.
19. Hong, Y., K. Hsu, H. Moradkhani, and S. Sorooshian, 2006: Uncertainty quantification of satellite precipitation estimation and Monte Carlo assessment of the error propagation into hydrologic response. Water Resour. Res., 42, W08421, doi:10.1029/2005WR004398.
20. Janjić, Z., 1994: The step-mountain eta coordinate model: Further development of the convection, viscous sublayer, and turbulence closure schemes. Mon. Wea. Rev., 122, 927-945.
21. Jankov, I., P. Schultz, C. Anderson, and S. Koch, 2007: The impact of different physical parameterizations and their interactions on cold season QPF in the American River basin. J. Hydrometeor., 8, 1141-1151.
22. Kain, J., 2004: The Kain-Fritsch convective parameterization: An update. J. Appl. Meteor., 43, 170-181.
23. Kain, J.,,and J. Fritsch, 1990:Aone-dimensional entraining/detraining plume model and its application in convective parameterization. J. Atmos. Sci., 47, 2784-2802.
24. Kain, J., and J. Fritsch, 1993: Convective parameterization for mesoscale models: The Kain-Fritsch scheme. The Representation of Cumulus Convection in Numerical Models, Meteor. Monogr., No. 46, Amer. Meteor. Soc., 165-170.
25. Kessler, E., 1969: On the Distribution and Continuity of Water Substance in Atmospheric Circulation. Meteor. Monogr., No. 32, Amer. Meteor. Soc., 84 pp.
26. Krajewski, W., and J. Smith, 2002: Radar hydrology: Rainfall estimation. J. Hydrol., 25, 1387-1394.
27. Li, X., and Z. Pu, 2009: Sensitivity of numerical simulations of the early rapid intensification of Hurricane Emily to cumulus parameterization schemes in different model horizontal resolutions. J. Meteor. Soc. Japan, 87, 403-421.
28. Lin, Y., and K. Mitchell, 2005: The NCEP stage II/IV hourly precipitation analyses: Development and applications. Preprints, 19th Conf. on Hydrology, San Diego, CA, Amer. Meteor. Soc., 1.2. [Available online at http://ams.confex.com/ams/pdfpapers/83847.pdf.]
29. Lin, Y.-L., R. Rarley, and H. Orville, 1983: Bulk parameterization of the snow field in a cloud model. J. Climate Appl. Meteor., 22, 1065-1092.
30. Lowrey, M., and Z. Yang, 2008: Assessing the capability of a regional-scale weather model to simulate extreme precipitation patterns and flooding in central Texas. Wea. Forecasting, 23, 1102-1126.
31. Mlawer, E., S. Taubman, P. Brown, and M. Iacono, 1997: Radiative transfer for inhomogeneous atmospheres: RRTM, a validated correlated-k model for the longwave. J. Geophys. Res., 102 (D14), 16 663-16 682.
32. Mölders, N., 2008: Suitability of the Weather Research and Forecasting (WRF) model to predict the June 2005 fire weather for interior Alaska. Wea. Forecasting, 23, 953-973.
33. NHC, 2007: November 2005 Atlantic tropical weather summary. NOAA/National Hurricane Center, 33 pp. [Available online at http://www.nhc.noaa.gov/pdf/TCR-AL182005_Rita.pdf.]
34. Olson, D. A., N. Junker, and B. Korty, 1995: Evaluation of 33 years of quantitative precipitation forecasting. Wea. Forecasting, 10, 498-511.
35. Seed, A., and R. Srikanthan, 1999: A space and time model for design storm rainfall. J. Geophys. Res., 104 (D24), 31 623-31 630.
36. Seo, D.-J., J. Breidenbach, and D. Miller, 1999: Real-time adjustments of mean field and range-dependent biases in WSR-88d rainfall estimation. Preprints, 15th Int. Conf. on Interactive Information and Processing Systems (IIPS) for Meteorology, Oceanography, and Hydrology, Dallas, TX, Amer. Meteor. Soc., 5.20.
37. Skamarock, W. C., andM. L. Weisman, 2009: The impact of positivedefinitemoisture transport onNWPprecipitation forecasts. Mon. Wea. Rev., 137, 488-494.
38. Skamarock, W. C., J. Klemp, J. Dudhia, D. Gill, D. Barker, W. Wang, and J. Powers, 2007: A description of the advanced research WRF version 2. NCAR Tech. Note NCAR/TN-4681STR, 88 pp
39. Steiner, M., and J. Smith, 2000: Reflectivity, rain rate, and kinetic energy flux relationships based on raindrop spectra. J. Appl. Meteor., 39, 1923-1940.
40. Vie, B., O. Nuissier, and V. Ducrocq, 2011: Cloud-resolving ensemble simulations of Mediterranean heavy precipitation events: Uncertainty on initial condition and lateral boundary condition. Mon. Wea. Rev., 139, 403-419.
41. Wang, W., and N. Seaman, 1997: A comparison study of convective schemes in a mesoscale model. Mon. Wea. Rev., 125, 252-278.
42. Wang, X., Z. Zhong, J. Hu, and H. Yuan, 2010: Effect of lateral boundary scheme on the simulation of tropical cyclone track in regional climate model RegCM3. Asia-Pac. J. Atmos. Sci., 46, 221-230.
43. Zhang, F., A. Odins, and J. Nielsen-Gammon, 2006: Mesoscale predictability of an extreme warm-season precipitation event. Wea. Forecasting, 21, 149-166.