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Steven M. Cavallo, Jimy Dudhia, and Chris Snyder

Abstract

An upper-level cold bias in potential temperature tendencies of 10 K day−1, 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 ±0.5 K day−1. Corresponding bias reductions are also seen, particularly near the tropopause.

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Steven M. Cavallo and Gregory J. Hakim

Abstract

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.

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Steven M. Cavallo and Gregory J. Hakim

Abstract

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.

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Steven M. Cavallo and Gregory J. Hakim

Abstract

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.

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Steven M. Cavallo, Judith Berner, and Chris Snyder

Abstract

Accurate predictions in numerical weather models depend on the ability to accurately represent physical processes across a wide range of scales. This paper evaluates the utility of model time tendencies, averaged over many forecasts at a given lead time, to diagnose systematic forecast biases in the Advanced Research version of the Weather Research and Forecasting (WRF) Model during the 2010 North Atlantic hurricane season using continuously cycled ensemble data assimilation (DA). Erroneously strong low-level heating originates from the planetary boundary layer parameterization as a consequence of using fixed sea surface temperatures, impacting the upward surface sensible heat fluxes. Warm temperature bias is observed with a magnitude 0.5 K in a deep tropospheric layer centered 700 hPa, originating primarily from the Kain–Fritsch convective parameterization.

This study is the first to diagnose systematic forecast bias in a limited-area mesoscale model using its forecast tendencies. Unlike global models where relatively fewer time steps typically encompass a DA cycling period, averaging all short-term forecast tendencies can require potentially large data. It is shown that 30-min averaging intervals can sufficiently represent the systematic model bias in this modeling configuration when initializing forecasts from an ensemble member that is generated using a DA system with an identical model configuration. However, the number of time steps before model error begins to dominate initial condition (IC) errors may vary between modeling configurations. Model and IC error are indistinguishable in short-term forecasts when initialized from the ensemble mean, a global analysis from a different model, and an ensemble member using a different parameterization.

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Steven M. Cavallo and Gregory J. Hakim

Abstract

Tropopause polar vortices (TPVs) are commonly observed, coherent circulation features of the Arctic with typical radii as large as approximately 800 km. Intensification of cyclonic TPVs has been shown to be dominated by infrared radiation. Here the hypothesis is tested that while radiation alone may not be essential for TPV genesis, radiation has a substantial impact on the long-term population characteristics of cyclonic TPVs.

A numerical model is used to derive two 10-yr climatologies of TPVs for both winter and summer: a control climatology with radiative forcing and an experimental climatology with radiative forcing withheld. Results from the control climatology are first compared to those from the NCEP–NCAR reanalysis project (NNRP), which indicates sensitivity to both horizontal grid resolution and the use of polar filtering in the NNRP. Smaller horizontal grid resolution of 60 km in the current study yields sample-mean cyclonic TPV radii that are smaller by a factor of ~2 compared to NNRP, and vortex track densities in the vicinity of the North Pole are considerably larger compared to NNRP. The experimental climatologies show that winter (summer) vortex maximum amplitude is reduced by 22.3% (38.0%), with a net tendency to weaken without radiation. Moreover, while the number and lifetime of cyclonic TPVs change little in winter without radiation, the number decreases 12% and the mean lifetime decreases 19% during summer without radiation. These results suggest that dynamical processes are primarily responsible for the genesis of the vortices, and that radiation controls their maximum intensity and duration during summer, when the destructive effect of ambient shear is weaker.

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Sarah M. Borg, Steven M. Cavallo, and David D. Turner

Abstract

Tropopause polar vortices (TPVs) are long-lived, coherent vortices that are based on the dynamic tropopause and characterized by potential vorticity anomalies. TPVs exist primarily in the Arctic, with potential impacts ranging from surface cyclone generation and Rossby wave interactions to dynamic changes in sea ice. Previous analyses have focused on model output indicating the importance of clear-sky and cloud-top radiative cooling in the maintenance and evolution of TPVs, but no studies have focused on local observations to confirm or deny these results. This study uses cloud and atmospheric state observations from Summit Station, Greenland, combined with single-column experiments using the Rapid Radiative Transfer Model to investigate the effects of clear-sky, ice-only, and all-sky radiative cooling on TPV intensification. The ground-based observing system combined with temperature and humidity profiles from the European Centre for Medium-Range Weather Forecasts’s fifth major global reanalysis dataset, which assimilates the twice-daily soundings launched at Summit, provides novel details of local characteristics of TPVs. Longwave radiative contributions to TPV diabatic intensity changes are analyzed with these resources, starting with a case study focusing on observed cloud properties and associated radiative effects, followed by a composite study used to evaluate observed results alongside previously simulated results. Stronger versus weaker vertical gradients in anomalous clear-sky radiative heating rates, contributing to Ertel potential vorticity changes, are associated with strengthening versus weakening TPVs. Results show that clouds are sometimes influential in the intensification of a TPV, and composite results share many similarities to modeling studies in terms of atmospheric state and radiative structure.

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Christopher P. Riedel, Steven M. Cavallo, and David B. Parsons

Abstract

Due in part to sparse conventional observation coverage in the Antarctic region, atmospheric studies in this part of the globe often rely more heavily on numerical models. Model representation of atmospheric processes in the Antarctic remains inferior to representation in the Northern Hemisphere midlatitudes. Poor representation may be related to inaccurate model analyses that do not optimally utilize the limited observation network. Here, the ensemble Kalman filter (EnKF) data assimilation (DA) technique is employed in lieu of variational DA techniques to investigate impacts on model analysis accuracy. This DA technique [provided by the Data Assimilation Research Testbed (DART)] is coupled with a polar-modified, mesoscale numerical model that together compose Antarctic-DART (A-DART). A-DART is cycled with DA and run over a 1-month period, assimilating only conventional observations. Results show relatively good agreement between A-DART and observations. Comparison with radiosonde temperature and geostationary satellite wind observations shows large differences between RMSE and ensemble spread in the upper troposphere. The analysis increment shows large values in the eastern Atlantic–western Indian Oceans associated with geostationary satellite wind observations. Further evaluation determines that geostationary satellite wind observations may be biased in this region. Overall, this baseline demonstration of ensemble-based modeling applied in the Antarctic produced short-term forecasts that were competitive with two operational modeling systems while assimilating on the O(106) fewer observations. A-DART is capable of assimilating additional observations for a variety of applications. This study highlights the capability of applying this ensemble-based DA technique for process and forecast studies in an observation-sparse region.

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Ariel E. Cohen, Steven M. Cavallo, Michael C. Coniglio, and Harold E. Brooks

Abstract

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.

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Ariel E. Cohen, Steven M. Cavallo, Michael C. Coniglio, Harold E. Brooks, and Israel L. Jirak

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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.

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