Jerold A. Herwehe

An Observation-Based Investigation of Nudging in WRF for Downscaling Surface Climate Information to 12-km Grid Spacing

AbstractPrevious research has demonstrated the ability to use the Weather Research and Forecasting model (WRF) and contemporary dynamical downscaling methods to refine global climate modeling results to a horizontal grid spacing of 36 km. Environmental managers and urban planners have expressed the need for even finer resolution in projections of surface-level weather to take into account local geophysical and urbanization patterns. In this study, WRF as previously applied at 36-km grid spacing is used with 12-km grid spacing with one-way nesting to simulate the year 2006 over the central and eastern United States. The results at both resolutions are compared with hourly observations of surface air temperature, humidity, and wind speed. The 12- and 36-km simulations are also compared with precipitation data from three separate observation and analysis systems. The results show some additional accuracy with the refinement to 12-km horizontal grid spacing, but only when some form of interior nudging is appl...

Improving High-Resolution Weather Forecasts Using the Weather Research and Forecasting (WRF) Model with an Updated Kain–Fritsch Scheme

AbstractEfforts to improve the prediction accuracy of high-resolution (1–10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale awareness for improving high-resolution short-term precipitation forecasts in the WRF Model. To address these issues, the authors introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain–Fritsch (KF) convective parameterization scheme in the WRF Model. These changes include subgrid-scale cloud–radiation interactions, a dynamic adjustment time scale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lift...

Increasing the credibility of regional climate simulations by introducing subgrid‐scale cloud‐radiation interactions

The radiation schemes in the Weather Research and Forecasting (WRF) model have previously not accounted for the presence of subgrid-scale cumulus clouds, thereby resulting in unattenuated shortwave radiation, which can lead to overly energetic convection and overpredicted surface precipitation. This deficiency can become problematic when applying WRF as a regional climate model (RCM). Therefore, modifications were made to the WRF model to allow the Kain–Fritsch (KF) convective parameterization to provide subgrid-scale cloud fraction and condensate feedback to the rapid radiative transfer model–global (RRTMG) shortwave and longwave radiation schemes. The effects of these changes are analyzed via 3 year simulations using the standard and modified versions of WRF, comparing the modeled results with the North American Regional Reanalysis (NARR) and Climate Forecast System Reanalysis data, as well as with available data from the Surface Radiation Network and Clouds and Earths Radiant Energy System. During the summer period, including subgrid cloudiness estimated by KF in the RRTMG reduces the surface shortwave radiation, leading to less buoyant energy, which is reflected in a smaller diabatic convective available potential energy, thereby alleviating the overly energetic convection. Overall, these changes have reduced the overprediction of monthly, regionally averaged precipitation during summer for this RCM application, e.g., by as much as 49 mm for the southeastern U.S., to within 0.7% of the NARR value of 221 mm. These code modifications have been incorporated as an option available in the latest version of WRF (v3.6).

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

AbstractMany 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 ti...