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Weak but persistent synoptic-scale ascent may play a role in the initiation or maintenance of nocturnal convection over the central United States. An analytical model is used to explore the nocturnal low-level jets (NLLJ) and ascent that develop in an idealized diurnally varying frictional (Ekman) boundary layer in a neutrally stratified barotropic environment when the flow aloft is a zonally propagating Rossby wave. Steady-periodic solutions are obtained of the linearized Reynolds-averaged Boussinesq-approximated equations of motion on a beta plane with an eddy viscosity that is specified to increase abruptly at sunrise and decrease abruptly at sunset. Rayleigh damping terms are used to parameterize momentum loss due to radiation of inertia–gravity waves. The model-predicted vertical velocity is (approximately) proportional to the wavenumber and wave amplitude. There are two main modes of ascent in midlatitudes, an afternoon mode and a nocturnal mode. The latter arises as a gentle but persistent surge induced by the decrease of turbulence at sunset, the same mechanism that triggers inertial oscillations in the Blackadar theory of NLLJs. If the Rayleigh damping terms are omitted, the boundary layer depth becomes infinite at three critical latitudes, and the vertical velocity becomes infinite far above the ground at two of those latitudes. With the damping terms retained, the solution is well behaved. Peak daytime ascent in the model occurs progressively later in the afternoon at more southern locations (in the Northern Hemisphere) until the first (most northern) critical latitude is reached; south of that latitude the nocturnal mode is dominant.

 

Abstract The bow-and-arrow Mesoscale Convective System (MCS) has a unique structure with two convective lines resembling the shape of an archer’s bow and arrow. These MCSs and their arrow convection (located behind the MCS leading line) can produce hazardous winds and flooding extending over hundreds of kilometers, which are often poorly predicted in operational forecasts. This study examines the dynamics of a bow-and-arrow MCS observed over the Yangtze–Huai Plains of China, with a focus on the arrow convection provided. The analysis utilized backward trajectories and Lagrangian vertical momentum budgets to simulations employing the WRF‐ARW and CM1 models. Cells within the arrow in the WRF-ARW simulations of the MCS were elevated, initially forming as convectively unstable air within the low-level jet (LLJ), which gently ascended over the cold pool and converged with the MCS’s mesoscale convective vortex (MCV) at higher altitudes. The subsequent ascent in these cells was enhanced by dynamic pressure forcing due to the updraft being within a layer where the vertical shear changed with height due to the superposition of the LLJ and the MCV. These dynamic forcings initially played a larger role in the ascent than the parcel’s buoyancy. These findings were bolstered by idealized simulations employing the CM1 model. These results illustrate a challenge for accurately forecasting bow-and-arrow MCSs as the updraft magnitude depends on dynamical forcing associated with the interaction between vertical shear associated with the environment and due to convectively generated circulations. 

Abstract An analytical model is presented for the generation of a Blackadar-like nocturnal low-level jet in a broad baroclinic zone. The flow is forced from below (flat ground) by a surface buoyancy gradient and from above (free atmosphere) by a constant pressure gradient force. Diurnally varying mixing coefficients are specified to increase abruptly at sunrise and decrease abruptly at sunset. With attention restricted to a surface buoyancy that varies linearly with a horizontal coordinate, the Boussinesq-approximated equations of motion, thermal energy, and mass conservation reduce to a system of one-dimensional equations that can be solved analytically. Sensitivity tests with southerly jets suggest that (i) stronger jets are associated with larger decreases of the eddy viscosity at sunset (as in Blackadar theory); (ii) the nighttime surface buoyancy gradient has little impact on jet strength; and (iii) for pure baroclinic forcing (no free-atmosphere geostrophic wind), the nighttime eddy diffusivity has little impact on jet strength, but the daytime eddy diffusivity is very important and has a larger impact than the daytime eddy viscosity. The model was applied to a jet that developed in fair weather conditions over the Great Plains from southern Texas to northern South Dakota on 1 May 2020. The ECMWF Reanalysis v5 (ERA5) for the afternoon prior to jet formation showed that a broad north–south-oriented baroclinic zone covered much of the region. The peak model-predicted winds were in good agreement with ERA5 winds and lidar data from the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) central facility in north-central Oklahoma. 

Abstract There is a growing interest in the use of ground-based remote sensors for Numerical Weather Prediction (NWP), which is sparked by their potential to address the currently existing observation gap within the Planetary Boundary Layer (PBL). Nevertheless, open questions still exist regarding the relative importance of and synergy among various instrument types. To shed light on these important questions, the present study examines the forecast benefits associated with several different ground-based profiling networks using 10 diverse cases from the Plains Elevated Convection at Night (PECAN) field campaign. Aggregated verification statistics reveal that a combination of in situ and remote sensing profilers leads to the largest increase in forecast skill, both in terms of the parent mesoscale convective system and the explicitly resolved bore. These statistics also indicate that it is often advantageous to collocate thermodynamic and kinematic remote sensors. By contrast, the impacts of networks consisting of single profilers appear to be flow-dependent, with thermodynamic (kinematic) remote sensors being most useful in cases with relatively low (high) convective predictability. Deficiencies in the data assimilation method as well as inherent complexities in the governing moisture dynamics are two factors shown to limit the forecast value extracted from such networks. 

Raindrop size distributions (DSD) and rain rate have been estimated from polarimetric radar data using different approaches with the accuracy depending on the errors both in the radar measurements and the estimation methods. Herein, a deep neural network (DNN) technique was utilized to improve the estimation of the DSD and rain rate by mitigating these errors. The performance of this approach was evaluated using measurements from a two-dimensional video disdrometer (2DVD) at the Kessler Atmospheric and Ecological Field Station in Oklahoma as ground truth with the results compared against conventional estimation methods for the period 2006–17. Physical parameters (mass-/volume-weighted diameter and liquid water content), rain rate, and polarimetric radar variables (including radar reflectivity and differential reflectivity) were obtained from the DSD data. Three methods—physics-based inversion, empirical formula, and DNN—were applied to two different temporal domains (instantaneous and rain-event average) with three diverse error assumptions (fitting, measurement, and model errors). The DSD retrievals and rain estimates from 18 cases were evaluated by calculating the bias and root-mean-squared error (RMSE). DNN produced the best performance for most cases, with up to a 5% reduction in RMSE when model errors existed. DSD and rain estimated from a nearby polarimetric radar using the empirical and DNN methods were well correlated with the disdrometer observations; the rain-rate estimate bias of the DNN was significantly reduced (3.3% in DNN vs 50.1% in empirical). These results suggest that DNN has advantages over the physics-based and empirical methods in retrieving rain microphysics from radar observations.

 

This study used radar observations and a high‐resolution numerical simulation to explore the interactions between an mesoscale convective system (MCS), cold pool outflows, and atmospheric bores in a non‐uniform baroclinic environment. The bores were generated by a nocturnal MCS that occurred on 2–3 June 2017 over the southern North China Plain. The goal of this investigation is to determine how the structure of bores varied within this non‐uniform environment and whether and how the bores would maintain the MCS and alter its structure. To the southwest of the MCS, where there was large CAPE and a well‐mixed boundary layer, discrete convection initiation occurred behind a single radar fine line (RFL) maintaining the propagation of the MCS. To the southeast of the MCS, multiple RFLs were found suggesting the generation of an undular bore in an environment containing an intense nocturnal stable boundary layer with dry upper layers and little CAPE. Hydraulic and nonlinear theory were applied to the simulation of the MCS revealing that the differences in the bore evolution depended on both the characteristics of the cold pool and the variations in the ambient environment. Thus, the characteristics of the ambient environment and the associated differences in bore structure impacted the maintenance and organization of the MCS. This study implies the importance of an accurate representation of the low‐level ambient environment and the microphysics and kinematics within the MCS to accurately simulate and forecast cold pools, the generation and evolution of bores, and their impact on nocturnal MCSs.

 

Abstract Our world is rapidly changing. Societies are facing an increase in the frequency and intensity of high impact and extreme weather and climate events. These extremes together with exponential population growth and demographic shifts (e.g., urbanization, increase in coastal populations) are increasing the detrimental societal and economic impact of hazardous weather and climate events. Urbanization and our changing global economy have also increased the need for accurate projections of climate change and improved predictions of disruptive and potentially beneficial weather events on km-scales. Technological innovations are also leading to an evolving and growing role of the private sector in the weather and climate enterprise. This article discusses the challenges faced in accelerating advances in weather and climate forecasting and proposes a vision for key actions needed across the private, public, and academic sectors. Actions span: i) Utilizing the new observational and computing ecosystems; ii) Strategies to advance earth system models; iii) Ways to benefit from the growing role of artificial intelligence; iv) Practices to improve the communication of forecast information and decision support in our age of internet and social media; and v) Addressing the need to reduce the relatively large, detrimental impacts of weather and climate on all nations and especially on low income nations. These actions will be based on a model of improved cooperation between the public, private, and academic sectors. This article represents a concise summary of the White Paper on the Future of Weather and Climate Forecasting (2021) put together by the World Meteorological Organizations’s Open Consultative Platform. 

Abstract This study investigates a nocturnal mesoscale convective system (MCS) observed during the Plains Elevated Convection At Night (PECAN) field campaign. A series of wavelike features were observed ahead of this MCS with extensive convective initiation (CI) taking place in the wake of one of these disturbances. Simulations with the WRF-ARW Model were utilized to understand the dynamics of these disturbances and their impact on the MCS. In these simulations, an “elevated bore” formed within an inversion layer aloft in response to the layer being lifted by air flowing up and over the cold pool. As the bore propagated ahead of the MCS, the lifting created an environment more conducive to deep convection allowing the MCS to discretely propagate due to CI in the bore’s wake. The Scorer parameter was somewhat favorable for trapping of this wave energy, although aspects of the environment evolved to be consistent with the expectations for an n = 2 mode deep tropospheric gravity wave. A bore within an inversion layer aloft is reminiscent of disturbances predicted by two-layer hydraulic theory, contrasting with recent studies that suggest bores are frequently initiated by the interaction between the flow within stable nocturnal boundary layer and convectively generated cold pools. Idealized simulations that expand upon this two-layer approach with orography and a well-mixed layer below the inversion suggest that elevated bores provide a possible mechanism for daytime squall lines to remove the capping inversion often found over the Great Plains, particularly in synoptically disturbed environments where vertical shear could create a favorable trapping of wave energy. 

Using data from the 6 July 2015 PECAN case study, this paper provides the first objective assessment of how the assimilation of ground-based remote sensing profilers affects the forecasts of bore-driven convection. To account for the multiscale nature of the phenomenon, data impacts are examined separately with respect to (i) the bore environment, (ii) the explicitly resolved bore, and (iii) the bore-initiated convection. The findings from this work suggest that remote sensing profiling instruments provide considerable advantages over conventional in situ observations, especially when the retrieved data are assimilated at a high temporal frequency. The clearest forecast improvements are seen in terms of the predicted bore environment where the assimilation of kinematic profilers reduces a preexisting bias in the structure of the low-level jet. Data impacts with respect to the other two forecast components are mixed in nature. While the assimilation of thermodynamic retrievals from the Atmospheric Emitted Radiance Interferometer (AERI) results in the best convective forecast, it also creates a positive bias in the height of the convectively generated bore. Conversely, the assimilation of wind profiler data improves the characteristics of the explicitly resolved bore, but tends to further exacerbate the lack of convection in the control forecasts. Various dynamical diagnostics utilized throughout this study provide a physical insight into the data impact results and demonstrate that a successful prediction of bore-driven convection requires an accurate depiction of the internal bore structure as well as the ambient environment ahead of it.

 

Abstract There has been a recent wave of attention given to atmospheric bores in order to understand how they evolve and initiate and maintain convection during the night. This surge is attributable to data collected during the 2015 Plains Elevated Convection at Night (PECAN) field campaign. A salient aspect of the PECAN project is its focus on using multiple observational platforms to better understand convective outflow boundaries that intrude into the stable boundary layer and induce the development of atmospheric bores. The intent of this article is threefold: 1) to educate the reader on current and future foci of bore research, 2) to present how PECAN observations will facilitate aforementioned research, and 3) to stimulate multidisciplinary collaborative efforts across other closely related fields in an effort to push the limitations of prediction of nocturnal convection.