Using Ensemble Data Assimilation to Explore the Environmental Controls on the Initiation and Predictability of Moist Convection

Atmospheric deep moist convection has emerged as one of the most challenging topics for numerical weather prediction, due to its chaotic process of development and multi-scale physical interactions. This study examines the dynamics and predictability of a weakly organized linear convective system using convection permitting EnKF analysis and forecasts with assimilating all-sky satellite radiances from a water vapor sensitive band of the Advanced Baseline Imager on GOES-16. The case chosen occurred over the Gulf of Mexico on 11 June 2017 during the NASA Convective Processes Experiment (CPEX) field campaign. Analysis of the water vapor and dynamic ensemble covariance structures revealed that meso-α (2000-200 km) and meso-β (200-20 km) scale initial features helped to constrain the general location of convection with a few hours of lead time, contributing to enhancing convective activity, but meso-γ (20-2 km) or even smaller scale features with less than 30-minute lead time were identified to be essential for capturing individual convective storms. The impacts of meso-α scale initial features on the prediction of particular individual convective cells were found to be classified into two regimes; in a relatively dry regime, the meso-α scale environment needs to be moist enough to support the development of the convection of interest, but in a relatively wet regime, a drier meso-α scale environment is preferable to suppress the surrounding convective activity. This study highlights the importance of high-resolution initialization of moisture fields for the prediction of a quasi-linear tropical convective system, as well as demonstrating the accuracy that may be necessary to predict convection exactly when and where it occurs.

Quasi-idealized numerical simulations of processes involved in orogenic convection initiation over the Sierras de Córdoba mountains

The Sierras de Córdoba (SDC) mountain range in Argentina is a hotspot of deep moist convection initiation (CI). Radar climatology indicates that 44% of daytime CI events that occur near the SDC in spring and summer seasons and that are not associated with the passage of a cold front or an outflow boundary involve a northerly LLJ, and these events tend to preferentially occur over the southeast quadrant of the main ridge of the SDC. To investigate the physical mechanisms acting to cause CI, idealized convection-permitting numerical simulations with a horizontal grid spacing of 1 km were conducted using CM1. The sounding used for initializing the model featured a strong northerly LLJ, with synoptic conditions resembling those in a previously postulated conceptual model of CI over the region, making it a canonical case study. Differential heating of the mountain caused by solar insolation in conjunction with the low-level northerly flow sets up a convergence line on the eastern slopes of the SDC. The southern portion of this line experiences significant reduction in convective inhibition, and CI occurs over the SDC southeast quadrant. Thesimulated storm soon acquires supercellular characteristics, as observed. Additional simulations with varying LLJ strength also show CI over the southeast quadrant. A simulation without background flow generated convergence over the ridgeline, with widespread CI across the entire ridgeline. A simulation with mid- and upper-tropospheric westerlies removed indicates that CI is minimally influenced by gravity waves. We conclude that the low-level jet is sufficient to focus convection initiation over the southeast quadrant of the ridge.

Implementation of the Unified Representation of Deep Moist Convection in the CWBGFS

This study implements the unified parameterization (UP) in the Central Weather Bureau Global Forecast System (CWBGFS) based on the relaxed Arakawa–Schubert scheme (RAS) at a horizontal resolution of 15 km. The new cumulus parameterization that incorporates the UP framework is called URAS. The UP generalizes the representation of moist convection between the parameterized and the explicitly resolved processes according to the process-dependent convective updraft fraction (σ). Short-term hindcasts are performed to investigate the impacts of the UP on the simulated precipitation variability and organized convective systems over the Maritime Continent when multiple scales of convection occurred. The result shows that σ is generally larger when convective systems develop, which adaptively reduces the parameterized convection and increases the spatial variation of moisture. In the URAS experiment, the moisture hotspots within organized convective systems contribute to the enhanced local circulation and the more significant variability of precipitation. Consequently, the URAS has a more realistic precipitation spectrum, an improved relationship between the maximum precipitation and the horizontal scale of the convective systems, and an improved column water vapor–precipitation relationship.

Diurnal Cycle of Tropical Oceanic Mesoscale Cold Pools

Tropical convection regimes range from deep organized to shallow convective systems. Mesoscale processes such as cold pools within tropical convective systems can play a significant role in the evolution of convection over land and open ocean. Although cold pools are widely observed, their diurnal properties are not well understood over tropical oceans and land. The oceanic cold pool identification metric applied herein uses the gradient feature (GF) technique and is compared with diurnally-resolved buoy-identified thermal cold pools. This study provides a first-ever diurnal climatology of GF number, area, and attributed TRMM 3B42 precipitation using a space-borne scatterometer (RapidScat). Buoy data over the Pacific, Atlantic, and Indian Ocean have been used to validate and examine the RapidScat-identified diurnal cycle of GF number and precipitation. Buoy-observed cold pool duration, precipitation, temperature, and wind speed is analyzed to understand the in situ cold pool properties over tropical oceans. GF- and buoy-observed cold pool number and precipitation exhibits a similar bimodal diurnal variability with a morning and afternoon maxima, thus establishing confidence in using GF as a proxy to observe cold pools over tropical oceans. The morning peak is attributed to cold pools associated with deep moist convection while the afternoon peak is related to shallower clouds in relatively drier environments resulting in smaller cold pools over global tropical oceans.

Evaluation and Comparison of Two Deep Convection Parameterization Schemes at Convection-Permitting Resolution

Coarse-grained results from a large-eddy simulation (LES) using the Weather Research and Forecast Model (WRF) were compared in this study with the WRF simulations at a typical convection-permitting horizontal grid spacing of 3 km for an idealized case of deep moist convection. The purpose of this comparison is to identify major differences at the subgrid process level between two widely-used deep convection parameterization schemes in the WRF model. It is shown that there are considerable differences in subgrid process representations between the two schemes due to different parameterization formulations and underlying assumptions. The two schemes not only differ in trigger function, subgrid cloud model, and closure assumptions but also disagree with the coarse-grained LES results in terms of vertical mass flux profiles. Thus, it is difficult to discern which scheme is more advantageous over the other at the subgrid process level. The conclusions from this study highlight the importance of establishing benchmarks using observations and LES to develop and evaluate convection parameterization schemes suitable for models at convection-permitting resolution.

Investigating the impact of land surface characteristics on monsoon dynamics with idealized model simulations and theories

Monsoons emerge over a range of land surface conditions and exhibit varying physical characteristics over the seasonal cycle, from onset to withdrawal. Systematically varying the moisture and albedo parameters over land in an idealized modeling framework allows one to analyze the physics underlying the successive stages of monsoon development. To this end we implement an isolated South American continent with reduced heat capacity but no topography in an idealized moist general circulation model. Irrespective of the local moisture availability, the seasonal cycles of precipitation and circulation over the South American monsoon sector are distinctly monsoonal with the default surface albedo. The dry land case (zero evaporation) is characterized by a shallow overturning circulation with vigorous lower-tropospheric ascent, transporting water vapor from the ocean. By contrast, with bucket hydrology or unlimited land moisture the monsoon features deep moist convection that penetrates the upper troposphere. A series of land albedo perturbation experiments indicates that the monsoon strengthens with the net column energy flux and the near-surface moist static energy with all land moisture conditions. When the land-ocean thermal contrast is strong enough, inertial instability alone is sufficient for producing a shallow but vigorous circulation and converging a large amount of moisture from the ocean even in the absence of land moisture. Once the land is sufficiently moist, convective instability takes hold and the shallow circulation deepens. These results have implications for monsoon onset and intensification, and may elucidate the seasonal variations in how surface warming impacts tropical precipitation over land.

Evaluating the conservation of energy variables in simulations of deep moist convection

It is often assumed in parcel theory calculations, numerical models, and cumulus parameterizations that moist static energy (MSE) is adiabatically conserved. However, the adiabatic conservation of MSE is only approximate because of the assumption of hydrostatic balance. Two alternative variables are evaluated here: MSE −IB and MSE +KE, wherein IB is the path integral of buoyancy (B) and KE is kinetic energy. Both of these variables relax the hydrostatic assumption and are more precisely conserved than MSE. This article quantifies the errors that result from assuming that the aforementioned variables are conserved in large eddy simulations (LES) of both disorganized and organized deep convection. Results show that both MSE −IB and MSE +KE better predict quantities along trajectories than MSE alone. MSE −IB is better conserved in isolated deep convection, whereas MSE −IB and MSE +KE perform comparably in squall line simulations. These results are explained by differences between the pressure perturbation behavior of squall lines and isolated convection. Errors in updraft B diagnoses are universally minimized when MSE−IB is assumed to be adiabatically conserved, but only when moisture dependencies of heat capacity and temperature dependency of latent heating are accounted for. When less accurate latent heat and heat capacity formulae were used, MSE−IB yielded poorer B predictions than MSE due to compensating errors. Our results suggest that various applications would benefit from using either MSE −IB or MSE +KE instead of MSE with properly formulated heat capacities and latent heats.

Low-level Mesoscale and Cloud-scale Interactions Promoting Deep Convection Initiation

Data from scanning radars, radiosondes, and vertical profilers deployed during three field campaigns are analyzed to study interactions between cloud-scale updrafts associated with initiating deep moist convection and the surrounding environment. Three cases are analyzed in which the radar networks permitted dual-Doppler wind retrievals in clear air preceding and during the onset of surface precipitation. These observations capture the evolution of: i) the mesoscale and boundary layer flow, and ii) low-level updrafts associated with deep moist convection initiation (CI) events yielding sustained or short-lived precipitating storms.The elimination of convective inhibition did not distinguish between sustained and unsustained CI events, though the vertical distribution of convective available potential energy may have played a role. The clearest signal differentiating the initiation of sustained versus unsustained precipitating deep convection was the depth of the low-level horizontal wind convergence associated with the mesoscale flow feature triggering CI, a sharp surface wind shift boundary or orographic upslope flow. The depth of the boundary layer relative to the height of the LFC failed to be a consistent indicator of CI potential. Widths of the earliest detectable low-level updrafts associated with sustained precipitating deep convection were ~3-5 km, larger than updrafts associated with surrounding boundary layer turbulence (~1-3-km wide). It is hypothesized that updrafts of this larger size are important for initiating cells to survive the destructive effects of buoyancy dilution via entrainment.

The behavior of high-CAPE (convective available potential energy) summer convection in large-domain large-eddy simulations with ICON

Current state-of-the-art regional numerical weather prediction (NWP) models employ kilometer-scale horizontal grid resolutions, thereby simulating convection within the grey zone. Increasing resolution leads to resolving the 3D motion field and has been shown to improve the representation of clouds and precipitation. Using a hectometer-scale model in forecasting mode on a large domain therefore offers a chance to study processes that require the simulation of the 3D motion field at small horizontal scales, such as deep summertime moist convection, a notorious problem in NWP. We use the ICOsahedral Nonhydrostatic weather and climate model in large-eddy simulation mode (ICON-LEM) to simulate deep moist convection and distinguish between scattered, large-scale dynamically forced, and frontal convection. We use different ground- and satellite-based observational data sets, which supply information on ice water content and path, ice cloud cover, and cloud-top height on a similar scale as the simulations, in order to evaluate and constrain our model simulations. We find that the timing and geometric extent of the convectively generated cloud shield agree well with observations, while the lifetime of the convective anvil was, at least in one case, significantly overestimated. Given the large uncertainties of individual ice water path observations, we use a suite of observations in order to better constrain the simulations. ICON-LEM simulates a cloud ice water path that lies between the different observational data sets, but simulations appear to be biased towards a large frozen water path (all frozen hydrometeors). Modifications of parameters within the microphysical scheme have little effect on the bias in the frozen water path and the longevity of the anvil. In particular, one of our convective days appeared to be very sensitive to the initial and boundary conditions, which had a large impact on the convective triggering but little impact on the high frozen water path and long anvil lifetime bias. Based on this limited set of sensitivity experiments, the evolution of locally forced convection appears to depend more on the uncertainty of the large-scale dynamical state based on data assimilation than of microphysical parameters. Overall, we judge ICON-LEM simulations of deep moist convection to be very close to observations regarding the timing, geometrical structure, and cloud ice water path of the convective anvil, but other frozen hydrometeors, in particular graupel, are likely overestimated. Therefore, ICON-LEM supplies important information for weather forecasting and forms a good basis for parameterization development based on physical processes or machine learning.

When the trigger of deep convection gets tricky in idealized climate simulations

<p><span>On the evening on July 2, 2011 a severe cloud burst occurred in the Copenhagen area. During the late afternoon deep moist convection developed over nearby Skåne (the southernmost part of Sweden) in an airstream from east-northeast. In the early evening the DMC passed over Øresund to Copenhagen, where it created a severe flash flood. Between 90 and 135 mm of precipitation in less than 2 hours was recorded ooding cellars, streets, and key roads. The deluge caused 6 billion Danish kroner in damage. Although that such extreme events are rare, the impacts on society is important and should be understood under a warmer climate. Although regional climate models have recently reached the convection permitting resolution, reproducing such events is still challenging.</span></p><p><span>Several studies suggest that extreme precipitations should increase under a future warmer climate using transient simulation or a pseudo-warming approach. It is still unclear how such event would behave under warmer or colder synoptic conditions. Using a forecast-ensemble method, but keeping a climate perspective, this study assesses the risk rising from such an event under otherwise almost identical, but warmer or colder conditions. With this set-up, we find that the development of the system that resulted in observed downpour exhibit quite a sensitivity to the initial conditions and contrary to a linear thinking, the risk of flooding is decreasing as the climate warms due to the inhibition of the CAPE by the additional lapse-rate anomalies used in this study. We therefore propose that the PGW method should be used with caution and that extreme precipitation events also in transient simulations of future climates need to be studied in detailed to address the limitations to models ability to produce those most extreme and by nature inherently rare events.</span></p>