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1. Introduction The problem of mesoscale predictability in numerical weather forecasts is becoming increasingly important as computational resources allow the simulation of progressively finer-scale atmospheric features. It is also of societal importance, as the accurate prediction and localization of severe weather, including flash flooding and tornadoes, is vital to saving lives and property. Nearly 50 years ago, Edward Lorenz proposed the idea that certain deterministic fluid systems with
1. Introduction The problem of mesoscale predictability in numerical weather forecasts is becoming increasingly important as computational resources allow the simulation of progressively finer-scale atmospheric features. It is also of societal importance, as the accurate prediction and localization of severe weather, including flash flooding and tornadoes, is vital to saving lives and property. Nearly 50 years ago, Edward Lorenz proposed the idea that certain deterministic fluid systems with
500 hPa along with positive values of unfiltered 950-hPa ζ . The 950-hPa circulation in the EnKF-MADIS forecast remains weak after initialization ( Fig. 5c ) and lags behind the midlevel circulation in the days leading up to the genesis time. Likewise, the 950-hPa circulation in the EnKF-PREDICT simulation moves closer to the 500-hPa cyclone and intensifies with time. The forecast from this analysis also contains a noticeably higher number of mesoscale vorticity anomalies 24 h into the simulation
500 hPa along with positive values of unfiltered 950-hPa ζ . The 950-hPa circulation in the EnKF-MADIS forecast remains weak after initialization ( Fig. 5c ) and lags behind the midlevel circulation in the days leading up to the genesis time. Likewise, the 950-hPa circulation in the EnKF-PREDICT simulation moves closer to the 500-hPa cyclone and intensifies with time. The forecast from this analysis also contains a noticeably higher number of mesoscale vorticity anomalies 24 h into the simulation
1. Introduction Current-generation numerical weather prediction (NWP) models now are capable of routinely capturing the evolution of large-scale synoptic weather systems but remain challenged in forecasting meso- and convective-scale weather phenomena such as squall lines and tornadic thunderstorms. It is of great interest to assess the predictability of these mesoscale severe weather systems, what their predictability limits are, and how to improve our forecasts, particularly with respect to
1. Introduction Current-generation numerical weather prediction (NWP) models now are capable of routinely capturing the evolution of large-scale synoptic weather systems but remain challenged in forecasting meso- and convective-scale weather phenomena such as squall lines and tornadic thunderstorms. It is of great interest to assess the predictability of these mesoscale severe weather systems, what their predictability limits are, and how to improve our forecasts, particularly with respect to
accuracy of track forecasting has been attributed primarily to improved prediction of synoptic- to planetary-scale circulation using global numerical prediction models ( Rappaport et al. 2009 ; McAdie and Lawrence 2000 ). In contrast, the lack of systematic improvement for the intensity forecast is not well understood. It has been hypothesized that progress has been limited by outstanding challenges of numerical prediction of mesoscale processes and multiscale interactions, in particular regarding the
accuracy of track forecasting has been attributed primarily to improved prediction of synoptic- to planetary-scale circulation using global numerical prediction models ( Rappaport et al. 2009 ; McAdie and Lawrence 2000 ). In contrast, the lack of systematic improvement for the intensity forecast is not well understood. It has been hypothesized that progress has been limited by outstanding challenges of numerical prediction of mesoscale processes and multiscale interactions, in particular regarding the
Prediction Scheme (SHIPS) for the Atlantic basin . Wea. Forecasting , 9 , 209 – 220 , https://doi.org/10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2 . 10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2 Ek , M. B. , K. E. Mitchell , Y. Lin , E. Rogers , P. Grunmann , V. Koren , G. Gayno , and J. D. Tarpley , 2003 : Implementation of Noah land surface model advancements in the National Centers for Environmental Prediction operational mesoscale Eta model . J. Geophys. Res. , 108
Prediction Scheme (SHIPS) for the Atlantic basin . Wea. Forecasting , 9 , 209 – 220 , https://doi.org/10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2 . 10.1175/1520-0434(1994)009<0209:ASHIPS>2.0.CO;2 Ek , M. B. , K. E. Mitchell , Y. Lin , E. Rogers , P. Grunmann , V. Koren , G. Gayno , and J. D. Tarpley , 2003 : Implementation of Noah land surface model advancements in the National Centers for Environmental Prediction operational mesoscale Eta model . J. Geophys. Res. , 108
that these may be a more important source of uncertainty than perturbations on the smallest resolved scales in very-high-resolution mesoscale models. In particular, recent work ( Durran and Gingrich 2014 ; Durran and Weyn 2016 ; WD17 ) has highlighted a little-known result in Lorenz (1969) suggesting that initial large-scale errors can be as detrimental to forecasts as initial small-scale errors of the same absolute amplitude. Morss et al. (2009) used a similar strategy of imposing initial
that these may be a more important source of uncertainty than perturbations on the smallest resolved scales in very-high-resolution mesoscale models. In particular, recent work ( Durran and Gingrich 2014 ; Durran and Weyn 2016 ; WD17 ) has highlighted a little-known result in Lorenz (1969) suggesting that initial large-scale errors can be as detrimental to forecasts as initial small-scale errors of the same absolute amplitude. Morss et al. (2009) used a similar strategy of imposing initial
, which results in the loss of mesoscale predictability within hours ( Zhang et al. 2003 , 2007 ; Selz and Craig 2015 ; Durran and Weyn 2016 ; Weyn and Durran 2017 ). The practical consequence of this behavior is the well-known difficulty to forecast convective phenomena, such as tropical cyclones ( Sippel and Zhang 2008 ; Judt et al. 2016 ) and severe convective storms (e.g., Hawblitzel et al. 2007 ; Zhang et al. 2015 ). Because of their restricted domains, however, regional models cannot
, which results in the loss of mesoscale predictability within hours ( Zhang et al. 2003 , 2007 ; Selz and Craig 2015 ; Durran and Weyn 2016 ; Weyn and Durran 2017 ). The practical consequence of this behavior is the well-known difficulty to forecast convective phenomena, such as tropical cyclones ( Sippel and Zhang 2008 ; Judt et al. 2016 ) and severe convective storms (e.g., Hawblitzel et al. 2007 ; Zhang et al. 2015 ). Because of their restricted domains, however, regional models cannot
: Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine Programme . Quart. J. Roy. Meteor. Soc. , 133 , 831 – 846 , doi:10.1002/qj.65 . Romero , R. , C. A. Doswell III , and C. Ramis , 2000 : Mesoscale numerical study of two cases of long-lived quasi-stationary convective systems over eastern Spain . Mon. Wea. Rev. , 128 , 3731 – 3751 , doi:10.1175/1520-0493(2001)129<3731:MNSOTC>2.0.CO;2 . Rotach , M. W. , and Coauthors , 2009 : MAP D
: Quantitative precipitation forecasting in the Alps: The advances achieved by the Mesoscale Alpine Programme . Quart. J. Roy. Meteor. Soc. , 133 , 831 – 846 , doi:10.1002/qj.65 . Romero , R. , C. A. Doswell III , and C. Ramis , 2000 : Mesoscale numerical study of two cases of long-lived quasi-stationary convective systems over eastern Spain . Mon. Wea. Rev. , 128 , 3731 – 3751 , doi:10.1175/1520-0493(2001)129<3731:MNSOTC>2.0.CO;2 . Rotach , M. W. , and Coauthors , 2009 : MAP D
each grid size (Δ) describe how the resolved and parameterized turbulence should be represented at each grid size. This section provides brief descriptions of the LES model [the Weather Research and Forecasting Model (WRF)], the experimental setup and characteristics of the benchmark simulations, and the reference data obtained from the simulations. a. Model description WRF is used as an LES model. WRF calculates the fully compressible and nonhydrostatic governing equations that are formulated
each grid size (Δ) describe how the resolved and parameterized turbulence should be represented at each grid size. This section provides brief descriptions of the LES model [the Weather Research and Forecasting Model (WRF)], the experimental setup and characteristics of the benchmark simulations, and the reference data obtained from the simulations. a. Model description WRF is used as an LES model. WRF calculates the fully compressible and nonhydrostatic governing equations that are formulated
. Heymsfield et al. (2001) showed CBs overshooting the tropopause by 2 km adjacent to the developing eye of Hurricane Bonnie (1998), and later, shortly before the storm reached maximum intensity, they found deep mesoscale subsidence extending from z = 15 km at cloud top downward and radially inward along the eye–eyewall interface. They hypothesized that this downdraft, originating as compensating subsidence of stratospheric air and being maintained by evaporative and sublimative cooling of hydrometeors
. Heymsfield et al. (2001) showed CBs overshooting the tropopause by 2 km adjacent to the developing eye of Hurricane Bonnie (1998), and later, shortly before the storm reached maximum intensity, they found deep mesoscale subsidence extending from z = 15 km at cloud top downward and radially inward along the eye–eyewall interface. They hypothesized that this downdraft, originating as compensating subsidence of stratospheric air and being maintained by evaporative and sublimative cooling of hydrometeors
