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Abstract This study extends the linear theory of Shapiro et al. (S18) for the onset of horizontal convergence and ascent in nocturnal boundary layers in baroclinic environments such as the U.S. Great Plains. In S18, the sudden decay of turbulence in a surface-based warm tongue at sunset triggers a surge of convergent inflow/ascent as well as a Blackadar-like nocturnal low-level jet. For conditions typical of broad warm-season surface-based baroclinic zones over the Great Plains, the S18 theory predicts that air parcels can rise 500 m–1 km before the onset of a descent phase. Such displacements may help sustain or initiate convection and play a role in the well-known nocturnal maximum in rainfall over the region. In this study, the Cloud Model 1 is used to examine the S18 predictions in a more realistic setting in which the nonlinear terms in the governing equations are retained, and the sudden shutdown of turbulence at sunset is replaced by a more gradual evening transition. A warm tongue arises in the simulated boundary layer over a 5-day period through a prescribed deficit in surface moisture which causes the greatest daytime heating in the domain center. As in S18, the simulations depict a surge of convergent flow, descent of the zone of peak ascent, replacement of the ascent zone by subsidence, peak vertical motion decreasing with latitude and warm tongue width, and the generation of free-atmosphere inertia–gravity waves. The divergence and vorticity fields are found to oscillate at the inertial frequency. 

Abstract 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 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 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 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. 

Abstract The THINICE field campaign, based from Svalbard in August 2022, provided unique observations of summertime Arctic cyclones, their coupling with cloud cover, and interactions with tropopause polar vortices and sea ice conditions. THINICE was motivated by the need to advance our understanding of these processes and to improve coupled models used to forecast weather and sea ice, as well as long-term projections of climate change in the Arctic. Two research aircraft were deployed with complementary instrumentation. The Safire ATR42 aircraft, equipped with the RALI (RAdar-LIdar) remote sensing instrumentation and in-situ cloud microphysics probes, flew in the mid-troposphere to observe the wind and multi-phase cloud structure of Arctic cyclones. The British Antarctic Survey MASIN aircraft flew at low levels measuring sea-ice properties, including surface brightness temperature, albedo and roughness, and the turbulent fluxes that mediate exchange of heat and momentum between the atmosphere and the surface. Long duration instrumented balloons, operated by WindBorne Systems, sampled meteorological conditions within both cyclones and tropospheric polar vortices across the Arctic. Several novel findings are highlighted. Intense, shallow low-level jets along warm fronts were observed within three Arctic cyclones using the Doppler radar and turbulence probes. A detailed depiction of the interweaving layers of ice crystals and supercooled liquid water in mixed-phase clouds is revealed through the synergistic combination of the Doppler radar, the lidar and in-situ microphysical probes. Measurements of near-surface turbulent fluxes combined with remote sensing measurements of sea ice properties are being used to characterize atmosphere-sea ice interactions in the marginal ice zone. 

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. 

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 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. 

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.