The representation of turbulent mixing within the lower troposphere is needed to accurately portray the vertical thermodynamic and kinematic profiles of the atmosphere in mesoscale model forecasts. For mesoscale models, turbulence is mostly a subgrid-scale process, but its presence in the planetary boundary layer (PBL) can directly modulate a simulation's depiction of mass fields relevant for forecast problems. The primary goal of this work is to review the various parameterization schemes that the Weather Research and Forecasting Model employs in its depiction of turbulent mixing (PBL schemes) in general, and is followed by an application to a severe weather environment. Each scheme represents mixing on a local and/or nonlocal basis. Local schemes only consider immediately adjacent vertical levels in the model, whereas nonlocal schemes can consider a deeper layer covering multiple levels in representing the effects of vertical mixing through the PBL. As an application, a pair of cold season severe weather events that occurred in the southeastern United States are examined. Such cases highlight the ambiguities of classically defined PBL schemes in a cold season severe weather environment, though characteristics of the PBL schemes are apparent in this case. Low-level lapse rates and storm-relative helicity are typically steeper and slightly smaller for nonlocal than local schemes, respectively. Nonlocal mixing is necessary to more accurately forecast the lower-tropospheric lapse rates within the warm sector of these events. While all schemes yield overestimations of mixed-layer convective available potential energy (MLCAPE), nonlocal schemes more strongly overestimate MLCAPE than do local schemes.

Long-lived coherent vortices located near the tropopause are often found over polar regions. Although these vortices are a commonly observed feature of the Arctic, and can have lifetimes longer than one month, little is known about the mechanisms that control their evolution. This paper examines mechanisms of intensity change for a cyclonic tropopause polar vortex (TPV) using an Ertel potential vorticity (EPV) diagnostic framework. Results from a climatology of intensifying cyclonic TPVs suggest that the essential dynamics are local to the vortex, rather than a consequence of larger-scale processes. This fact motivates a case study using a numerical model to investigate the role of diabatic mechanisms in the growth and decay of a particular cyclonic vortex. A component-wise breakdown of EPV reveals that cloud-top radiational cooling is the primary diabatic mechanism that intensifies the TPV during the growth phase. Increasing amounts of moisture become entrained into the vortex core at later times near Hudson Bay, allowing the destruction of potential vorticity near the tropopause due to latent heat release to become comparable to the radiational tendency to create potential vorticity.1 Assuming adiabatic and inviscid flow, PV and potential temperature are both conserved following the fluid motion. Thus, the existence of closed PV contours on potential temperature surfaces implies the existence of closed contours of potential temperature on PV surfaces.

Tropopause polar vortices are coherent circulation features based on the tropopause in polar regions. They are a common feature of the Arctic, with typical radii less than 1500 km and lifetimes that may exceed 1 month. The Arctic is a particularly favorable region for these features due to isolation from the horizontal wind shear associated with the midlatitude jet stream, which may destroy the vortical circulation. Intensification of cyclonic tropopause polar vortices is examined here using an Ertel potential vorticity framework to test the hypothesis that there is an average tendency for diabatic effects to intensify the vortices due to enhanced upper-tropospheric radiative cooling within the vortices. Data for the analysis are derived from numerical simulations of a large sample of observed cyclonic vortices over the Canadian Arctic. Results show that there is on average a net tendency to create potential vorticity in the vortex, and hence intensify cyclones, and that the tendency is radiatively driven. While the effects of latent heating are considerable, they are smaller in magnitude, and all other diabatic processes have a negligible effect on vortex intensity.

Characterized by radii as large as 800 km and lifetimes up to months, cyclonic tropopause polar vortices (TPVs) are coherent circulation features over the Arctic that are important precursors for surface cyclogenesis in high and middle latitudes. TPVs have been shown to be maintained by radiative processes over the Arctic owing to limited amounts of latent heating. This study explores the hypothesis that a downward extension of dry stratospheric air associated with TPVs results in an increase in longwave radiative cooling that intensifies the vortex. Idealized numerical modeling experiments are performed to isolate physical interactions, beginning with radiative forcing in a dry atmosphere and culminating with multiple physical interactions between radiation and clouds that more accurately represent the observed environment of TPVs. Results show that longwave radiative cooling associated with a rapid decrease in water vapor concentration near the tropopause is primarily responsible for observed TPV intensification. These enhanced water vapor gradients result from a lower tropopause within the vortex that places dry stratospheric air above relatively moist tropospheric air. Cloud-top radiative cooling enhances this effect and also promotes the maintenance of clouds by destabilizing the region near cloud top. Shortwave radiation and latent heating offset the longwave intensification mechanism. Heating from shortwave radiation reduces the cloud water mixing ratio by preferentially warming levels above cloud tops.

Southeast U.S. cold season severe weather events can be difficult to predict because of the marginality of the supporting thermodynamic instability in this regime. The sensitivity of this environment to prognoses of instability encourages additional research on ways in which mesoscale models represent turbulent processes within the lower atmosphere that directly influence thermodynamic profiles and forecasts of instability. This work summarizes characteristics of the southeast U.S. cold season severe weather environment and planetary boundary layer (PBL) parameterization schemes used in mesoscale modeling and proceeds with a focused investigation of the performance of nine different representations of the PBL in this environment by comparing simulated thermodynamic and kinematic profiles to observationally influenced ones. It is demonstrated that simultaneous representation of both nonlocal and local mixing in the Asymmetric Convective Model, version 2 (ACM2), scheme has the lowest overall errors for the southeast U.S. cold season tornado regime. For storm-relative helicity, strictly nonlocal schemes provide the largest overall differences from observationally influenced datasets (underforecast). Meanwhile, strictly local schemes yield the most extreme differences from these observationally influenced datasets (underforecast) in a mean sense for the low-level lapse rate and depth of the PBL, on average. A hybrid local–nonlocal scheme is found to mitigate these mean difference extremes. These findings are traced to a tendency for local schemes to incompletely mix the PBL while nonlocal schemes overmix the PBL, whereas the hybrid schemes represent more intermediate mixing in a regime where vertical shear enhances mixing and limited instability suppresses mixing.

Real-time analyses and forecasts using an ensemble Kalman filter (EnKF) and the Advanced Hurricane Weather Research and Forecasting Model (AHW) are evaluated from the 2009 North Atlantic hurricane season. This data assimilation system involved cycling observations that included conventional in situ data, tropical cyclone (TC) position, and minimum SLP and synoptic dropsondes each 6 h using a 96-member ensemble on a 36-km domain for three months. Similar to past studies, observation assimilation systematically reduces the TC position and minimum SLP errors, except for strong TCs, which are characterized by large biases due to grid resolution. At 48 different initialization times, an AHW forecast on 12-, 4-, and 1.33-km grids is produced with initial conditions drawn from a single analysis member. Whereas TC track analyses and forecasts exhibit a pronounced northward bias, intensity forecast errors are similar to (lower than) the NWS Hurricane Weather Research Model (HWRF) and GFDL forecasts for forecast lead times #60 h (.60 h), with the largest track errors associated with the weakest systems, such as Tropical Storm (TS) Erika. Several shortcomings of the data assimilation system are addressed through postseason sensitivity tests, including using the maximum 800-hPa circulation to identify the TC position during assimilation and turning off the quality control for the TC minimum SLP observation when the initial intensity is far too weak. In addition, the improved forecast of TS Erika relative to HWRF is shown to be related to having initial conditions that are more representative of a sheared TC and not using a cumulus parameterization.

Arctic cyclones are an extremely common, year-round phenomenon, with substantial influence on sea ice. However, few studies address the heterogeneity in the spatial patterns in the atmosphere and sea ice during Arctic cyclones. We investigate these spatial patterns by compositing on cyclones from 1985-2016 using a novel, cyclone-centered approach that reveals conditions as functions of bearing and distance from cyclone centers. An axisymmetric, cold core model for the structure of Arctic cyclones has previously been proposed, however, we show that the structure of Arctic cyclones is comparable to those in the mid-latitudes, with cyclonic surface winds, a warm, moist sector to the east of cyclones and a cold, dry sector to the west. There is no consensus on the impact of Arctic cyclones on sea ice, as some studies have shown that Arctic cyclones lead to sea ice growth and others to sea ice loss. Instead, we find that sea ice decreases to the east of Arctic cyclones and increases to the west, with the greatest changes occurring in the marginal ice zone. Using a sea ice model forced with prescribed atmospheric reanalysis, we reveal the relative importance of the dynamic and thermodynamic forcing of Arctic cyclones on sea ice. The dynamic and thermodynamic responses of sea ice concentration to cyclones are comparable in magnitude, however dynamic processes dominate the response of sea ice thickness and are the primary driver of the east-west difference in the sea ice response to cyclones.

An upper-level cold bias in potential temperature tendencies of 10 K day 21 , strongest at the top of the model, is observed in Weather Research and Forecasting (WRF) model forecasts. The bias originates from the Rapid Radiative Transfer Model longwave radiation physics scheme and can be reduced substantially by 1) modifying the treatment within the scheme by adding a multilayer buffer between the model top and top of the atmosphere and 2) constraining stratospheric water vapor to remain within the estimated climatology in the stratosphere. These changes reduce the longwave heating rate bias at the model top to 60.5 K day 21 . Corresponding bias reductions are also seen, particularly near the tropopause.