A Dynamically Computed Convective Time Scale for the Kain–Fritsch Convective Parameterization Scheme

2015 ◽  
Vol 143 (6) ◽  
pp. 2105-2120 ◽  
Author(s):  
O. Russell Bullock ◽  
Kiran Alapaty ◽  
Jerold A. Herwehe ◽  
John S. Kain
Keyword(s):  
Time Scale ◽  
Radiation Effects ◽  
Convective Available Potential Energy ◽  
Wrf Model ◽  
Grid Cell ◽  
Grid Spacing ◽  
Convective Parameterization ◽  
Convective Clouds ◽  
Adjustment Time ◽  
Convective Adjustment

Abstract Many convective parameterization schemes define a convective adjustment time scale τ as the time allowed for dissipation of convective available potential energy (CAPE). The Kain–Fritsch scheme defines τ based on an estimate of the advective time period for deep convective clouds within a grid cell, with limits of 1800 and 3600 s, based on practical cloud-lifetime considerations. In simulations from the Weather Research and Forecasting (WRF) Model using 12-km grid spacing, the value of τ often defaults to the lower limit, resulting in relatively rapid thermodynamics adjustments and high precipitation rates. Herein, a new computation for τ in the Kain–Fritsch scheme is implemented based on the depth of the buoyant layer and the convective velocity scale. This new τ formulation is applied using 12- and 36-km model grid spacing in conjunction with a previous modification that takes into account the radiation effects of parameterized convective clouds. The dynamically computed convective adjustment time scale is shown to reduce the precipitation bias by approximately 15% while also providing improved simulations of inland rainfall from tropical storms.

Will Perturbing Soil Moisture Improve Warm-Season Ensemble Forecasts? A Proof of Concept

2006 ◽  
Vol 134 (11) ◽  
pp. 3174-3189 ◽  
Author(s):  
Christian Sutton ◽  
Thomas M. Hamill ◽  
Thomas T. Warner
Keyword(s):  
Soil Moisture ◽  
Surface Temperature ◽  
Land Surface ◽  
Short Range ◽  
Wrf Model ◽  
Warm Season ◽  
Ensemble Forecast ◽  
Grid Spacing ◽  
Ensemble Forecasts ◽  
Convective Parameterization

Abstract Current generation short-range ensemble forecast members tend to be unduly similar to each other, especially for components such as surface temperature and precipitation. One possible cause of this is a lack of perturbations to the land surface state. In this experiment, a two-member ensemble of the Advanced Research Weather Research and Forecasting (WRF) model (ARW) was run from two different soil moisture analyses. One-day forecasts were conducted for six warm-season cases over the central United States with moderate soil moistures, both with explicit convection at 5-km grid spacing and with parameterized convection at 20-km grid spacing. Since changing the convective parameterization has previously been demonstrated to cause significant differences between ensemble forecast members, 20-km simulations were also conducted that were initialized with the same soil moisture but that used two different convective parameterizations as a reference. At 5 km, the forecast differences due to changing the soil moisture were comparable to the differences in 20-km simulations with the same soil moisture but with a different convective parameterization. The differences of 20-km simulations from different soil moistures were occasionally large but typically smaller than the differences from changing the convective parameterization. Thus, perturbing the state of the land surface for this version of WRF/ARW was judged to be likely to increase the spread of warm-season operational short-range ensemble forecasts of precipitation and surface temperature when soil moistures are moderate in value, especially if the ensemble is comprised of high-resolution members with explicit convection.

scholarly journals Cloud-System-Resolving Model Simulations of Tropical Cloud Systems Observed during the Tropical Warm Pool-International Cloud Experiment

2010 ◽  
Vol 138 (1) ◽  
pp. 55-73 ◽  
Author(s):  
Kathrin Wapler ◽  
Todd P. Lane ◽  
Peter T. May ◽  
Christian Jakob ◽  
Michael J. Manton ◽  
...  
Keyword(s):  
Rain Rate ◽  
Model Performance ◽  
Wrf Model ◽  
Warm Pool ◽  
Cloud System ◽  
Weather Research And Forecasting ◽  
Grid Spacing ◽  
Model Simulations ◽  
Convective Clouds ◽  
Tropical Warm Pool

Abstract Nested cloud-system-resolving model simulations of tropical convective clouds observed during the recent Tropical Warm Pool-International Cloud Experiment (TWP-ICE) are conducted using the Weather Research and Forecasting (WRF) model. The WRF model is configured with a highest-resolving domain that uses 1.3-km grid spacing and is centered over Darwin, Australia. The performance of the model in simulating two different convective regimes observed during TWP-ICE is considered. The first regime is characteristic of the active monsoon, which features widespread cloud cover that is similar to maritime convection. The second regime is a monsoon break, which contains intense localized systems that are representative of diurnally forced continental convection. Many aspects of the model performance are considered, including their sensitivity to physical parameterizations and initialization time, and the spatial statistics of rainfall accumulations and the rain-rate distribution. While the simulations highlight many challenges and difficulties in correctly modeling the convection in the two regimes, they show that provided the mesoscale environment is adequately reproduced by the model, the statistics of the simulated rainfall agrees reasonably well with the observations.

scholarly journals The Realization of Extreme Tornadic Storm Events under Future Anthropogenic Climate Change

2016 ◽  
Vol 29 (14) ◽  
pp. 5251-5265 ◽  
Author(s):  
Robert J. Trapp ◽  
Kimberly A. Hoogewind
Keyword(s):  
Climate Change ◽  
Convective Available Potential Energy ◽  
Wrf Model ◽  
Real Data ◽  
Anthropogenic Climate Change ◽  
Basic Question ◽  
Storm Events ◽  
The Mean ◽  
Atmospheric State ◽  
Convection Initiation

Abstract This research seeks to answer the basic question of how current-day extreme tornadic storm events might be realized under future anthropogenic climate change. The pseudo global warming (PGW) methodology was adapted for this purpose. Three contributions to the CMIP5 archive were used to obtain the mean 3D atmospheric state simulated during May 1990–99 and May 2090–99. The climate change differences (or Δs) in temperature, relative humidity, pressure, and winds were added to NWP analyses of three high-end tornadic storm events, and this modified atmospheric state was then used for initial and boundary conditions for real-data WRF Model simulations of the events at high resolution. Comparison of an ensemble of these simulations with control simulations (CTRL) facilitated assessment of PGW effects. In contrast to the robust development of supercellular convection in each CTRL, the combined effects of increased convective inhibition (CIN) and decreased parcel lifting under PGW led to a failure of convection initiation in many of the experiments. Those experiments that had sufficient matching between the CIN and lifting tended to generate stronger convective updrafts than CTRL, although not in proportion to the projected higher levels of convective available potential energy (CAPE) under PGW. In addition, the experiments with enhanced updrafts also tended to have enhanced vertical rotation. In fact, such supercellular convection was even found in simulations that were driven with PGW-reduced environmental wind shear. Notably, the PGW modifications did not induce a change in the convective morphology in any of the PGW experiments with significant convective storminess.

scholarly journals The Impacts of Horizontal Grid Spacing and Cumulus Parameterization on Subseasonal Prediction in a Global Convection-Permitting Model

2020 ◽  
Vol 148 (12) ◽  
pp. 4747-4765
Author(s):  
Nicholas J. Weber ◽  
Clifford F. Mass ◽  
Daehyun Kim
Keyword(s):  
Global Model ◽  
Forecast Skill ◽  
Cumulus Parameterization ◽  
Madden Julian Oscillation ◽  
Grid Spacing ◽  
Variable Resolution ◽  
Channel Simulation ◽  
Convective Parameterization ◽  
Tropical Precipitation ◽  
The Tropics

AbstractMonthlong simulations targeting four Madden–Julian oscillation events made with several global model configurations are verified against observations to assess the roles of grid spacing and convective parameterization on the representation of tropical convection and midlatitude forecast skill. Specifically, the performance of a global convection-permitting model (CPM) configuration with a uniform 3-km mesh is compared to that of a global 15-km mesh with and without convective parameterization, and of a variable-resolution “channel” simulation using 3-km grid spacing only in the tropics with a scale-aware convection scheme. It is shown that global 3-km simulations produce realistic tropical precipitation statistics, except for an overall wet bias and delayed diurnal cycle. The channel simulation performs similarly, although with an unrealistically higher frequency of heavy rain. The 15-km simulations with and without cumulus schemes produce too much light and heavy tropical precipitation, respectively. Without convection parameterization, the 15-km global model produces unrealistically abundant, short-lived, and intense convection throughout the tropics. Only the global CPM configuration is able to capture eastward-propagating Madden–Julian oscillation events, and the 15-km runs favor stationary or westward-propagating convection organized at the planetary scale. The global 3-km CPM exhibits the highest extratropical forecast skill aloft and at the surface, particularly during week 3 of each hindcast. Although more cases are needed to confirm these results, this study highlights many potential benefits of using global CPMs for subseasonal forecasting. Furthermore, results show that alternatives to global convection-permitting resolution—using coarser or spatially variable resolution—feature compromises that may reduce their predictive performance.

scholarly journals More on the Scale Dependence of the Predictability of Precipitation Patterns: Extension to the 2009–13 CAPS Spring Experiment Ensemble Forecasts

2017 ◽  
Vol 145 (9) ◽  
pp. 3625-3646 ◽  
Author(s):  
Madalina Surcel ◽  
Isztar Zawadzki ◽  
M. K. Yau ◽  
Ming Xue ◽  
Fanyou Kong
Keyword(s):  
Large Scale ◽  
Forecast Error ◽  
Quasi Equilibrium ◽  
Relative Role ◽  
Ensemble Forecasts ◽  
Adjustment Time ◽  
Convective Adjustment ◽  
Microphysical Parameterization ◽  
Microphysical Parameterization Scheme

This paper analyzes the scale and case dependence of the predictability of precipitation in the Storm-Scale Ensemble Forecast (SSEF) system run by the Center for Analysis and Prediction of Storms (CAPS) during the NOAA Hazardous Weather Testbed Spring Experiments of 2008–13. The effect of different types of ensemble perturbation methodologies is quantified as a function of spatial scale. It is found that uncertainties in the large-scale initial and boundary conditions and in the model microphysical parameterization scheme can result in the loss of predictability at scales smaller than 200 km after 24 h. Also, these uncertainties account for most of the forecast error. Other types of ensemble perturbation methodologies were not found to be as important for the quantitative precipitation forecasts (QPFs). The case dependences of predictability and of the sensitivity to the ensemble perturbation methodology were also analyzed. Events were characterized in terms of the extent of the precipitation coverage and of the convective-adjustment time scale [Formula: see text], an indicator of whether convection is in equilibrium with the large-scale forcing. It was found that events characterized by widespread precipitation and small [Formula: see text] values (representative of quasi-equilibrium convection) were usually more predictable than nonequilibrium cases. No significant statistical relationship was found between the relative role of different perturbation methodologies and precipitation coverage or [Formula: see text].

scholarly journals Comparison of Simulated Precipitation over East Asia in Two Regional Models with Hydrostatic and Nonhydrostatic Dynamical Cores

2016 ◽  
Vol 144 (10) ◽  
pp. 3579-3590 ◽  
Author(s):  
Jihyeon Jang ◽  
Song-You Hong
Keyword(s):  
Wrf Model ◽  
Local Maximum ◽  
Weather Research And Forecasting ◽  
Model Program ◽  
Grid Spacing ◽  
Dynamical Core ◽  
Simulated Precipitation ◽  
Precipitation Area ◽  
Hydrostatic Limit ◽  
Regional Forecasts

This study examines the characteristics of a nonhydrostatic dynamical core compared to a corresponding hydrostatic dynamical core in the Regional Model Program (RMP) of the Global/Regional Integrated Model system (GRIMs), a spectral model for regional forecasts, focusing on simulated precipitation over Korea. This kind of comparison is also executed in the Weather Research and Forecasting (WRF) finite-difference model with the same physics package used in the RMP. Overall, it is found that the nonhydrostatic dynamical core experiment accurately reproduces the heavy rainfall near Seoul, South Korea, on a 3-km grid, relative to the results from the hydrostatic dynamical core in both models. However, the characteristics of nonhydrostatic effects on the simulated precipitation differ between the RMP and WRF Model. The RMP with the nonhydrostatic dynamical core improves the local maximum, which is exaggerated in the hydrostatic simulation. The hydrostatic simulation of the WRF Model displaces the major precipitation area toward the mountainous region along the east coast of the peninsula, which is shifted into the observed area in the nonhydrostatic simulation. In the simulation of a summer monsoonal rainfall, these nonhydrostatic effects are negligible in the RMP, but the simulated monsoonal rainfall is still influenced by the dynamical core in the WRF Model even at a 27-km grid spacing. One of the reasons for the smaller dynamical core effect in the RMP seems to be the relatively strong horizontal diffusion, resulting in a smaller grid size of the hydrostatic limit.

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