Equivalent Potential Temperature Research Articles

Climatology of thermodynamic indices and background synoptic conditions responsible for severe convection during pre‐ to post‐monsoon seasons over Indian region

AbstractTo investigate the mechanisms responsible for severe convection linked with a variety of mesoscale, synoptic systems over the Indian region, a preliminary analysis is conducted. Using IMD RSRW/Reanalysis (ERA5)/Lightning (TRMM LIS) products both local‐scale thermodynamics and large‐scale background conditions responsible for the major lightning hot spots in different seasons are investigated. In the pre‐monsoon season, high lightning activity over NE Indian region is due to moisture intrusion by south‐westerly at lower levels (warm air advection), along with mid‐level north westerlies (cold air advection) which favour the low‐level convergence and upper‐level divergence. SCS over south India are mainly attributed to wind discontinuity over the region. During monsoon season major lightning activity in NW India is due to the presence of heat low and the rest of the country less intense SCS activity is evident due to high wind shear conditions in connection with low‐level (westerly) and upper‐level (easterly jet stream). In the post‐monsoon season, major lightning in south India are due to the prevailing north‐easterlies and in north India, the activity is attributed to the passage of western disturbance (WD). Station plot analysis suggests the varied distribution of thermodynamic indices season/region‐wise due to the diverse background forcing. Correlation analysis between the lightning and thermodynamic indices suggests that more skillful indices are KI (~0.7 to 0.8), precipitable water (PPW) (~0.8) (pre‐monsoon, monsoon) and (PPW) (~0.8), convective available potential energy (CAPE) (~0.6) in post monsoon over respective lightning hot‐spot regions. Independent verification using Wyoming data/reanalysis for different case studies suggests that monitoring the monthly thresholds of highly correlated indices provides a helpful proxy to operationally forecast the severe convective systems (season/region). Mean Equivalent potential temperature, and mixing ratio in mixed layer has shown reasonable association with the lightning occurrence over all lightning hot spot regions which are implemented in the IMD GFS and IMD WRF models.

Understanding winter windstorm predictability over Europe

Abstract. Winter windstorms belong to the most damaging meteorological events in the extra-tropics. Their impact on society makes it essential to understand and improve seasonal forecasts of these extreme events. Skilful predictions on a seasonal timescale have been shown in previous studies by investigating hindcasts from various forecast centres. This study aims to explain storm forecast skill based on relevant dynamical factors. Therefore, a number of factors which are known to influence either windstorms directly or their synoptic relevant systems, mid-latitude cyclones, are investigated. These factors are analysed for their relation to windstorm forecast performance based on a reanalysis (ERA5) and the seasonal hindcast of the UK Met Office (Global Seasonal forecasting system version 5, GloSea5). Within GloSea5, relevant dynamical factors are (1) validated with respect to their physical connections to windstorms, (2) investigated with respect to the seasonal forecast skill of the factors themselves, and (3) assessed on the relevance and influence of their forecast performance to and on windstorm forecast skill. Although not all investigated factors reveal a clear and consistent influence on windstorm forecast skill over Europe, core factors like mean sea level pressure gradient, sea surface temperature, equivalent potential temperature and Eady growth rate show consistent results within these three steps: their physical connection is well represented in the model; these factors are skilfully predicted in storm-relevant regions, and, consequently, this skill leads to increased forecast skill of winter windstorms over Europe. This study thus explains existing forecast skill in winter windstorms but also indicates potential for further model developments to improve seasonal winter windstorm predictions.

Atmospheric conditions conducive to thunderstorms with downbursts in Canada and a downburst precursor parameter

Thunderstorm winds are the costliest wind hazard in Canada, but they have not been well studied. This paper investigates atmospheric conditions prone to downbursts in Canada using a combination of reported downbursts from damage survey reports, ERA5 reanalysis data, lightning flash observations, radar imagery, and upper air measurements for the period of 2019–2023. We propose a novel Downburst Precursor Parameter (DPP) by integrating two low-correlated thermodynamic and kinematic parameters. DPP outperforms other existing instability indices in downburst diagnosis in Canada. Our spatial analysis reveals the absence of damaging downbursts west of the Rockies, while approximately half of all recorded damaging downbursts occurred in southeastern Canada. Squall lines and supercells are the most common types of downburst-generating storms in Canada. Furthermore, nearly two-thirds of storms are squall lines when a downburst is accompanied by lightning flashes, which occurred in ∼71% of all cases. The remaining ∼29% of downbursts without lightning are mostly dry downbursts, typically displaying a disorganized pattern of convective storms on a radar screen. The equivalent potential temperature difference between the surface and mid-level in the troposphere (∆θe) exceeds 13 K prior to 61% of damaging downbursts. This result indicates that ∆θe might be a useful downburst indicator in Canada despite lower values compared to many regions in the United States.

Analytical and adaptable initial conditions for dry and moist baroclinic waves in the global hydrostatic model OpenIFS (CY43R3)

Abstract. This article presents a description of an analytical, stable, and flexible initial background state for both dry and moist baroclinic wave simulation on an aquaplanet in order to test the dynamical core of numerical weather prediction models and study the dynamics and evolution of extratropical cyclones. The initial background state is derived from an analytical zonal wind speed field, or jet structure, and the hydrostatic primitive equations for moist adiabatic and frictionless flow in spherical coordinates. A baroclinic wave can develop if a perturbation is added to the zonal wind speed field. This new baroclinic wave configuration has been implemented in the Open Integrated Forecasting System (OpenIFS) CY43R3, a global numerical weather prediction model developed by the European Centre for Medium-Range Weather Forecasts. In total, seven parameters can be used to control the generation of the initial background state and hence the development of the baroclinic waves in the OpenIFS configuration file: the jet's width, the jet's height, the maximum zonal mean wind speed of the jet, the horizontal mean of the surface virtual temperature, the surface relative humidity, the lapse rate, and the surface roughness. Nine dry and nine moist initial background states have been generated to test their stability without perturbations. The meteorological stability of the initial states is investigated by examining the spatial distributions of the equivalent potential temperature, the absolute vorticity, and the Brunt–Väisälä frequency. Moreover, the root mean square error (RMSE) of the zonal wind speed has been computed to assess their numerical stability. Finally, six dry and six moist initial background state have been used with an unbalanced perturbation to ensure that the baroclinic life cycles that develop are physically realistic. The resulting baroclinic wave is shown to be sensitive to the jet's width. This configuration for baroclinic wave simulations will be used to create a large ensemble of baroclinic life cycles to study how extratropical cyclones may evolve in the future.

Remote Effects of double Typhoons on Record-breaking Rainfall: A case Study in North China

During 18–22 July 2021, an extreme precipitation event occurred in Henan, China, with maximum daily precipitation reached 657 mm, broking their historical records and resulting in severe disaster. This heavy rainstorm occurred with the background of two typhoon (In-fa and Cempaka) activities, but resent studies have only considered the effects of individual typhoons, ignoring their combined effects. The Dynamic Recycling Model and Weather Research and Forecasting Model were applied to investigate the contributions of two typhoons on water vapor transportation. Two transportation paths were determined: the eastern path for In-fa and the southwestern path for Cempaka. These paths contributed up to 78% of the total water vapor over Henan. Two typhoons jointly led to extreme precipitation, and Cempaka showed greater impact than In-fa on the vapor transportation. The precipitation was 39.0% of that in the control test when only Cempaka existed and 34.4% when only considering In-fa. The sensitivity results also indicate that Cempaka mainly induced the early stage of precipitation, while In-fa controlled the later stage. In addition to the effect of water vapor transportation, In-fa also influenced the local atmospheric stability. The pseudo equivalent potential temperature near the surface was 6 K higher when only In-fa existed relative to the scenario in which no typhoon was considered, indicating that In-fa strengthened the convective instability. Therefore, both Cempaka and In-fa contributed to this extreme precipitation event. Cempaka transferred more water vapor than In-fa, and In-fa acted to increase the instability. Their joint contribution amplified the precipitation intensity beyond the cumulative impact of individual effects.

The Physics behind Precipitation Onset Bias in CMIP6 Models: The Pseudo-Entrainment Diagnostic and Trade-Offs between Lapse Rate and Humidity

Abstract Conditional instability and the buoyancy of plumes drive moist convection but have a variety of representations in model convective schemes. Vertical thermodynamic structure information from Atmospheric Radiation Measurement (ARM) sites and reanalysis (ERA5), satellite-derived precipitation (TRMM3b42), and diagnostics relevant for plume buoyancy are used to assess climate models. Previous work has shown that CMIP6 models represent moist convective processes more accurately than their CMIP5 counterparts. However, certain biases in convective onset remain pervasive among generations of CMIP modeling efforts. We diagnose these biases in a cohort of nine CMIP6 models with subdaily output, assessing conditional instability in profiles of equivalent potential temperature, θe, and saturation equivalent potential temperature, θes, in comparison to a plume model with different mixing assumptions. Most models capture qualitative aspects of the θes vertical structure, including a substantial decrease with height in the lower free troposphere associated with the entrainment of subsaturated air. We define a “pseudo-entrainment” diagnostic that combines subsaturation and a θes measure of conditional instability similar to what entrainment would produce under the small-buoyancy approximation. This captures the trade-off between larger θes lapse rates (entrainment of dry air) and small subsaturation (permits positive buoyancy despite high entrainment). This pseudo-entrainment diagnostic is also a reasonable indicator of the critical value of integrated buoyancy for precipitation onset. Models with poor θe/θes structure (those using variants of the Tiedtke scheme) or low entrainment runs of CAM5, and models with low subsaturation, such as NASA-GISS, lie outside the observational range in this diagnostic.

MJO Structure–Propagation Nexus and Impacts of Background Mean States in CMIP6 Models

Abstract Eastward propagation is an essential feature of the Madden–Julian oscillation (MJO). Yet, it remains a challenge to realistically simulate it by global climate system models, and the reasons are not fully understood. This study evaluates the capability of 20 Coupled Model Intercomparison Project phase 6 (CMIP6) models in simulating MJO’s eastward propagation and its intrinsic links with the dynamic–thermodynamic structures and the background mean states, aiming at better understanding the sources of the simulation errors. The metrics to evaluate the MJO internal dynamics consists of six parameters: 1) the east–west asymmetry in the low-level circulation, 2) the boundary layer moisture convergence propagation, 3) the vertical tilt of equivalent potential temperature or moist static energy, the vertical structures of 4) diabatic heating and 5) available potential energy generation, and 6) upper-level diabatic heating and divergence. We also gauge the performance of three MJO-related background mean-state fields, including precipitation, sea surface temperature, and low-level moist static energy. It is argued that these parameters are relevant internal and external factors that could affect MJO eastward propagation. We find that the boundary layer moisture convergence is most tightly coupled with the eastward propagation of MJO and controls the premoistening, destabilization, and the leading low-level diabatic heating and available potential energy generation. The CMIP6 models exhibit significant improvements against CMIP5 models in simulating MJO dynamic–thermodynamic structures and the mean states. The diagnostics in this study could help to identify the possible processes related to CMIP6 models’ shortcomings and shed light on how to improve simulation of MJO eastward propagation in the future.

Key ingredients in regional climate modelling for improving the representation of typhoon tracks and intensities

Abstract. There is evidence of an increased frequency of rapid intensification events of tropical cyclones (TCs) in global offshore regions. This will not only result in increased peak wind speeds but may lead to more intense heavy precipitation events, leading to flooding in coastal regions. Therefore, high impacts are expected for urban agglomerations in coastal regions such as the densely populated Pearl River Delta (PRD) in China. Regional climate models (RCMs) such as the Weather Research and Forecasting (WRF) model are state-of-the-art tools commonly applied to predict TCs. However, typhoon simulations are connected with high uncertainties due to the high number of parameterization schemes of relevant physical processes (including possible interactions between the parameterization schemes) such as cumulus (CU) and microphysics (MP), as well as other crucial model settings such as domain setup, initial times, and spectral nudging. Since previous studies mostly focus on either individual typhoon cases or individual parameterization schemes, in this study a more comprehensive analysis is provided by considering four different typhoons of different intensity categories with landfall near the PRD, i.e. Typhoon Neoguri (2008), Typhoon Hagupit (2008), Typhoon Hato (2017), and Typhoon Usagi (2013), as well as two different schemes for CU and MP, respectively. Moreover, the impact of the model initialization and the driving data is studied by using three different initial times and two spectral nudging settings. Compared with the best-track reference data, the results show that the four typhoons show some consistency. For track bias, nudging only horizontal wind has a positive effect on reducing the track distance bias; for intensity, compared with a model explicitly resolving cumulus convection, i.e. without cumulus parameterization (CuOFF; nudging potential temperature and horizontal wind; late initial time), using the Kain–Fritsch scheme (KF; nudging only horizontal wind; early initial time) configuration shows relatively lower minimum sea level pressures and higher maximum wind speeds, which means stronger typhoon intensity. Intensity shows less sensitivity to two MP schemes compared with the CuOFF, nudging, and initial time settings. Furthermore, we found that compared with the CuOFF, using the KF scheme shows a relatively larger latent heat flux and higher equivalent potential temperature, providing more energy to typhoon development and inducing stronger TCs. This study could be used as a reference to configure WRF with the model's different combinations of schemes for historical and future TC simulations and also contributes to a better understanding of the performance of principal TC structures.

Evaporative controls on Antarctic precipitation: an ECHAM6 model study using innovative water tracer diagnostics

Abstract. Improving our understanding of the controls on Antarctic precipitation is critical for gaining insights into past and future polar and global environmental changes. Here we develop innovative water tracing diagnostics in the atmospheric general circulation model ECHAM6. These tracers provide new detailed information on moisture source locations and properties of Antarctic precipitation. In the preindustrial simulation, annual mean Antarctic precipitation originating from the open ocean has a source latitude range of 49–35∘ S, a source sea surface temperature range of 9.8–16.3 ∘C, a source 2 m relative humidity range of 75.6 %–83.3 %, and a source 10 m wind velocity (vel10) range of 10.1 to 11.3 m s−1. These results are consistent with estimates from existing literature. Central Antarctic precipitation is sourced from more equatorward (distant) sources via elevated transport pathways compared to coastal Antarctic precipitation. This has been attributed to a moist isentropic framework; i.e. poleward vapour transport tends to follow constant equivalent potential temperature. However, we find notable deviations from this tendency especially in the lower troposphere, likely due to radiative cooling. Heavy precipitation is sourced by longer-range moisture transport: it comes from 2.9∘ (300 km, averaged over Antarctica) more equatorward (distant) sources compared to the rest of precipitation. Precipitation during negative phases of the Southern Annular Mode (SAM) also comes from more equatorward moisture sources (by 2.4∘, averaged over Antarctica) compared to precipitation during positive SAM phases, likely due to amplified planetary waves during negative SAM phases. Moreover, source vel10 of annual mean precipitation is on average 2.1 m s−1 higher than annual mean vel10 at moisture source locations from which the precipitation originates. This shows that the evaporation of moisture driving Antarctic precipitation occurs under windier conditions than average. We quantified this dynamic control of Southern Ocean surface wind on moisture availability for Antarctic precipitation. Overall, the innovative water tracing diagnostics enhance our understanding of the controlling factors of Antarctic precipitation.

Global well-posedness of a model for precipitating convection with hydrostatic pressure under fast autoconversion and rain evaporation conditions

Moist convection in the tropical atmosphere involves the interaction of deep precipitating clouds that can be organized into different patterns and propagate long distances. Their modeling to predict their evolution can be done with PDE-based models but it requires the parametrization of different cloud micro-physical processes. Simplified models can maintain a balance between complexity and precision, and can still capture qualitative observations made in nature. In this work, we prove global existence and uniqueness of a model for precipitating turbulent convection. The model considers a moisture dynamics with phase changes. It assumes fast auto-conversion and rain evaporation together with a hydrostatic pressure approximation. We also show positivity of the variables associated to moisture and equivalent potential temperature. The existing literature is discussed and the new challenges in this model are highlighted.

Precipitation and Moisture Transport of the 2021 Shimokita Heavy Precipitation: A Transformed Extratropical Cyclone from Typhoon#9

This study examines the heavy rainfall event that occurred in the Shimokita Peninsula, Japan, on 9–10 August 2021, resulting from an extra-tropical cyclone that developed from Typhoon#9 (EC9). The objective of this study is to elucidate the relationship between moisture transport and heavy rainfall and to verify the role of EC9. The authors created intensive hourly precipitation data over the Aomori Prefecture and analyzed them together with moisture fields. In most locations where the landslide disaster occurred, there were two precipitation peaks: at 9 UTC and 18 UTC on 9 August. The wind shear was strong from the lower to the upper troposphere with easterly winds in the lower troposphere and warm moist air from south for the first peak. A strong horizontal gradient of equivalent potential temperature, a northerly in lower troposphere, and moisture convergence over Shimokita Peninsula indicate the existence of the stationary front for the latter peak (18 UTC). The heavy precipitation and moisture convergence that caused the Shimokita event were identified by the stationary front of EC9 around the latter peak (15 UTC of 9th–06 UTC of 10 August). The precipitation distribution, which has a precipitation peak northeast of the EC center, is a typical typhoon-turned extratropical cyclone (EC) precipitation distribution.

A CloudSat–CALIPSO view of cloud and precipitation in the occluded quadrants of extratropical cyclones

AbstractUsing 10 years of satellite‐borne radar and lidar observations coupled with a novel method for automated occlusion identification, composite transects of cloud and precipitation across occluded thermal ridges of extratropical cyclones are, for the first time, constructed. These composites confirm that occluded sectors are characterized by the most extensive cloud cover and heaviest precipitation in any of the frontal regions of the cyclone. Hydrometeor frequency in occluded sectors is sensitive to the cyclone's ascent strength but not to the mean precipitable water in the cyclone's environment. This result is in contrast to the strong relationships between hydrometeor frequency and both precipitable water and ascent strength as previously reported in warm frontal regions. In both hemispheres, cloud and precipitation increase with the maximum value of the equivalent potential temperature at 700 hPa within the occluded thermal ridge, until a threshold is reached. For very large values of maximum equivalent potential temperature, hydrometeors become less frequent while precipitation rates increase. It is suggested that this conjunction is a by‐product of an increase in the frequency of convection in those instances. While in the Northern Hemisphere occluded sectors exhibit deeper and wider cloud structures than their Southern Hemisphere counterparts, their hydrometeor occurrence frequencies are less. The differences in maximum equivalent potential temperature of the thermal ridges in both hemispheres does not appear to explain the more frequent hydrometeors in the Southern Hemisphere. These relationships offer new perspectives on the interplay between cloud processes and cyclone evolution, as well as new observational constraints for process evaluation of Earth system models.

The Potential Roles of Preexisting Airmass Boundaries on a Tornadic Supercell Observed by TORUS on 28 May 2019

Abstract On 28 May 2019, a tornadic supercell, observed as part of Targeted Observation by UAS and Radars of Supercells (TORUS) produced an EF-2 tornado near Tipton, Kansas. The supercell was observed to interact with multiple preexisting airmass boundaries. These boundaries and attendant air masses were examined using unoccupied aircraft system (UAS), mobile mesonets, radiosondes, and dual-Doppler analyses derived from TORUS mobile radars. The cool-side air mass of one of these boundaries was found to have higher equivalent potential temperature and backed winds relative to the warm-side air mass; features associated with mesoscale air masses with high theta-e (MAHTEs). It is hypothesized that these characteristics may have facilitated tornadogenesis. The two additional boundaries were produced by a nearby supercell and appeared to weaken the tornadic supercell. This work represents the first time that UAS have been used to examine the impact of preexisting airmass boundaries on a supercell, and it provides insights into the influence environmental heterogeneities can have on the evolution of a supercell.

Severe Convective Storms in Limited Instability Organized by Pattern and Distribution

Abstract Severe convection occurring in high-shear, low-CAPE (HSLC) environments is a common cool-season threat in the southeastern United States. Previous studies of HSLC convection document the increased operational challenges that these environments present compared to their high-CAPE counterparts, corresponding to higher false-alarm ratios and lower probability of detection for severe watches and warnings. These environments can exhibit rapid destabilization in the hours prior to convection, sometimes associated with the release of potential instability. Here, we use self-organizing maps (SOMs) to objectively identify environmental patterns accompanying HSLC cool-season severe events and associate them with variations in severe weather frequency and distribution. Large-scale patterns exhibit modest variation within the HSLC subclass, featuring strong surface cyclones accompanied by vigorous upper-tropospheric troughs and northward-extending regions of instability, consistent with prior studies. In most patterns, severe weather occurs immediately ahead of a cold front. Other convective ingredients, such as lower-tropospheric vertical wind shear, near-surface equivalent potential temperature (θe) advection, and the release of potential instability, varied more significantly across patterns. No single variable used to train SOMs consistently demonstrated differences in the distribution of severe weather occurrence across patterns. Comparison of SOMs based on upper and lower quartiles of severe occurrence demonstrated that the release of potential instability was most consistently associated with higher-impact events in comparison to other convective ingredients. Overall, we find that previously developed HSLC composite parameters reasonably identify high-impact HSLC events. Significance Statement Even when atmospheric instability is not optimal for severe convective storms, in some situations they can still occur, presenting increased challenges to forecasters. These marginal environments may occur at night or during the cool season, when people are less attuned to severe weather threats. Here, we use a sorting algorithm to classify different weather patterns accompanying such storms, and we distinguish which specific patterns and weather system features are most strongly associated with severe storms. Our goals are to increase situational awareness for forecasters and to improve understanding of the processes leading to severe convection in marginal environments.

Diverging Behaviors of Simulated Tropical Cyclones in Moderate Vertical Wind Shear

Abstract As a follow-on to a previous study that examined the tilt and precession evolution of tropical cyclones (TCs) in a critical shear regime, this study examines the processes leading to the subsequent divergent evolutions in tilt and intensity. The control experiment fails to resume its precession and reintensify, while the perturbed experiments with enhanced upper-level inner-core vorticity resume the precession after a precession hiatus period. In the control experiment, a mesoscale negative absolute vorticity region forms at the upper levels due to tilting in strong downtilt convection. This upper-level, negative-vorticity region is inertially unstable, causing the inward acceleration of upper-level radial inflow. This upper-level inflow subsequently becomes negatively buoyant due to diabatic cooling and descends, bringing midlevel, low equivalent potential temperature (θE) air into the inner-core TC boundary layer, significantly disrupting the low-level TC circulation. Consequently, the disrupted TC vortex in the control is unable to recover. The upper-level negative vorticity region is absent in the perturbed experiments due to weaker downtilt convection, preventing the emergence of the disruptive inner-core downdraft. The weaker downtilt convection is caused by several factors. First, a stronger circulation aloft advects hydrometeors farther downwind, resulting in greater separation of the cooling-driven downdraft from the convective updraft region, and thus weaker dynamically forced lifting at low levels. Second, the mean θE of the low-level air feeding downtilt convection is smaller. Third, there is stronger and deeper adiabatic descent uptilt, causing more low-θE air diluting the downtilt updraft region. These results show how the full vortex structure is important to diverging TC evolutions in moderately sheared environments.

Machine-learning-based investigation of the variables affecting summertime lightning occurrence over the Southern Great Plains

Abstract. Lightning is affected by many factors, many of which are not routinely measured, well understood, or accounted for in physical models. Several commonly used machine learning (ML) models have been applied to analyze the relationship between Atmospheric Radiation Measurement (ARM) data and lightning data from the Earth Networks Total Lightning Network (ENTLN) in order to identify important variables affecting lightning occurrence in the vicinity of the Southern Great Plains (SGP) ARM site during the summer months (June, July, August and September) of 2012 to 2020. Testing various ML models, we found that the random forest model is the best predictor among common classifiers. When convective clouds were detected, it predicts lightning occurrence with an accuracy of 76.9 % and an area under the curve (AUC) of 0.850. Using this model, we further ranked the variables in terms of their effectiveness in nowcasting lightning and identified geometric cloud thickness, rain rate and convective available potential energy (CAPE) as the most effective predictors. The contrast in meteorological variables between no-lightning and frequent-lightning periods was examined for hours with CAPE values conducive to thunderstorm formation. Besides the variables considered for the ML models, surface variables and mid-altitude variables (e.g., equivalent potential temperature and minimum equivalent potential temperature, respectively) have statistically significant contrasts between no-lightning and frequent-lightning hours. For example, the minimum equivalent potential temperature from 700 to 500 hPa is significantly lower during frequent-lightning hours compared with no-lightning hours. Finally, a notable positive relationship between the intracloud (IC) flash fraction and the square root of CAPE (CAPE) was found, suggesting that stronger updrafts increase the height of the electrification zone, resulting in fewer flashes reaching the surface and consequently a greater IC flash fraction.

Factors Associated with the Downshear Reformation of Tropical Cyclones

Abstract The conditions associated with tropical cyclones undergoing downshear reformation are explored for the North Atlantic basin from 1998 to 2020. These storms were compared to analog tropical cyclones with similar intensity, vertical wind shear, and maximum potential intensity, but did not undergo downshear reformation. Storm-centered, shear-relative composites were generated using ERA5 and GridSat-B1 data. Downshear reformation predominately occurs for tropical cyclones of tropical storm intensity embedded in moderate vertical wind shear. A comparison between composites suggests that reformed storms are characterized by greater low-level and midtropospheric relative humidity downshear, larger surface latent heat fluxes downshear and left of shear, and larger low-level equivalent potential temperatures and CAPE right of shear. These factors increase thermodynamic favorability, building a reservoir of potential energy and decreasing dry air entrainment, promoting sustained convection downshear, and favoring the development of a new center. Significance Statement The development of a new low-level circulation center in tropical cyclones that replaces the original center, called downshear reformation, can affect the structure and intensity of storms, representing a challenge in forecasting tropical cyclones. While there have been a handful of case studies on downshear reformation, this study aims to more comprehensively understand the conditions that favor downshear reformation by comparing a large set of North Atlantic tropical cyclones that underwent reformation with a similar set of tropical cyclones that did not undergo reformation. Tropical cyclones that undergo reformation have a moister environment, larger surface evaporation, and higher low-level instability in specific regions that help sustain deep, downshear convection that favors the development of a new center.

Prediction of Convective Available Potential Energy and Equivalent Potential Temperature using a Coupled WRF and Deep Learning for Typhoon Identification

To predict typhoons in the western North Pacific Ocean, it is required to predict the determinants of typhoon activities. The formation of the typhoon can be controlled by Convective Available Potential Energy (CAPE) and Equivalent Potential Temperature (theta-e). To predict the variables, a mesoscale numerical model of Weather Research and Forecasting (WRF) can be used. However, the output of WRF needs to improve to obtain a more accurate CAPE and theta-e prediction. This study uses a coupled WRF model and Deep Learning (DL) Multilayer Perceptron Regressor approach to increase CAPE and theta-e prediction skills. Simulation with dataset scenarios with WRF outputs as predictors and sounding data as predictors are developed and tested to obtain the most appropriate package of deep learning simulation. The study found that coupled models provide increased mean accuracy of theta-e and CAPE, namely 16.6% and 32.0% higher than using original WRF, respectively. This study also shows the difference of skill scores in the spatial distribution of CAPE and theta-e of WRF result and its coupled model.

Adverse impact of terrain steepness on thermally driven initiation of orographic convection

Abstract. Diurnal mountain winds precondition the environment for deep moist convection through horizontal and vertical transport of heat and moisture. They also play a key role in convection initiation, especially in strongly inhibited environments, by lifting air parcels above the level of free convection. Despite its relevance, the impact of these thermally driven circulations on convection initiation has yet to be examined systematically. Using idealized large-eddy simulations (Δx=50 m) with the Weather Research and Forecasting (WRF) model, we study the effect of cross-valley circulations on convection initiation under synoptically undisturbed and convectively inhibited conditions, considering quasi-2D mountain ranges of different heights and widths. In particular, we contrast convection initiation over relatively steep mountains (20 % average slope) and less steep ones (10 %). One distinctive finding is that, under identical environmental conditions, relatively steep mountain ranges lead to a delayed onset and lower intensity of deep moist convection, although they cause stronger thermal updrafts at ridge tops. The temporal evolution of convective indices, such as convective inhibition and convective available potential energy, shows that destabilization over the steeper mountains is slower, presumably due to lower low-level moisture. Analysis of the ridgetop moisture budget reveals the competing effects of moisture advection by the mean thermally driven circulation and turbulent moisture transport. In general, at mountaintops, the divergence of the turbulent moisture flux offsets the convergence of the advective moisture flux almost entirely. Due to the stronger ridgetop updraft, the mean advective moistening over the steeper mountains is higher; nevertheless, the total moistening is lower and the width of the updraft zone is narrower on average. Thus, buoyant updrafts over the steeper mountains are more strongly affected by the turbulent entrainment of environmental air, which depletes their moisture and cloud water content and makes them less effective at initiating deep convection. Saturated updrafts over less steep mountains, on the other hand, gain more moisture from the vapor flux at cloud base, leading to significantly higher moisture accumulation. The lower entrainment rates in these simulations are revealed by the fact that equivalent potential temperature in the cloud decreases less strongly with height than over steeper terrain. The precipitation efficiency, a measure of how much of the condensed water eventually precipitates, is considerably larger over the less steep mountains, also due to lower total condensation compared with the steeper simulations. The relationship between mountain size and precipitation amount depends on the thermodynamic profile. It is nearly linear in cases with low initial convective inhibition but more complex otherwise. The weaker convection over steeper mountains is a robust finding, valid over a range of background environmental stability and mountain sizes.

On the Collective Importance of Model Physics and Data Assimilation on Mesoscale Convective System and Precipitation Forecasts over Complex Terrain

Abstract Forecasting mesoscale convective systems (MCSs) and precipitation over complex terrain is an ongoing challenge even for convective-permitting numerical models. Here, we show the value of combining mesoscale constraints to improve short-term MCS forecasts for two events during the North American monsoon season in 2013, including the following: 1) the initial specification of moisture, via GPS-precipitable water vapor (PWV) data assimilation (DA); 2) kinematics via modification of cumulus parameterization; and 3) microphysics via modification of cloud microphysics parameterization. A total of five convective-permitting Weather Research and Forecasting (WRF) Model experiments is conducted for each event to elucidate the impact of these constraints. Results show that combining GPS-PWV DA with a modified Kain–Fritsch scheme and double-moment microphysics provides relatively the best forecast of both North American monsoon MCSs and convective precipitation in terms of timing, location, and intensity relative to available precipitation and cloud-top temperature observations. Additional examination on the associated reflectivity, vertical wind field, equivalent potential temperature, and hydrometeor distribution of MCS events show the added value of each individual constraint to forecast performance. Significance Statement Forecasting thunderstorm clouds and rain over mountainous regions is challenging because of limitations in having radar and rain gauges and in resolving physical drivers in forecast models. We examine the value of considering all possible constraints by incorporating moisture into these models, and correcting physics in the model treatment of cumulus and cloud microphysics parameterizations. This study demonstrates that assimilating moisture and using modified Kain–Fritsch and double-moment microphysics schemes provides the best thunderstorm cloud and rain forecasts in terms of timing, location, and intensity. Each correction improves key properties of these storms such as vertical wind, along with distribution of water in various phases. We highlight the need to improve our efforts on effectively integrating these constraints into current and future forecasts.