Cathy Hohenegger

The Soil Moisture–Precipitation Feedback in Simulations with Explicit and Parameterized Convection

Abstract Moist convection is a key aspect of the extratropical summer climate and strongly affects the delicate balance of processes that determines the surface climate in response to larger-scale forcings. Previous studies using parameterized convection have found that the feedback between soil moisture and precipitation is predominantly positive (more precipitation over wet soils) over Europe. Here this feedback is investigated for one full month (July 2006) over the Alpine region using two different model configurations. The first one employs regional climate simulations performed with the Consortium for Small-Scale Modeling Model in Climate Mode (CCLM) on a grid spacing of 25 km. The second one uses the same model but integrated on a cloud-resolving grid of 2.2 km, allowing an explicit treatment of convection. Each configuration comprises one control and two sensitivity experiments. The latter start from perturbed soil moisture initial conditions. Comparison of the simulated soil moisture–precipitatio...

Predictability and Error Growth Dynamics in Cloud-Resolving Models

Abstract While the benefits of ensemble techniques over deterministic numerical weather predictions (NWP) are now widely recognized, the prospects of ensemble prediction systems (EPS) at high computational resolution are still largely unclear. Difficulties arise due to the poor knowledge of the mechanisms promoting rapid perturbation growth and propagation, as well as the role of nonlinearities. In this study, the dynamics associated with the growth and propagation of initial uncertainties is investigated by means of real-case high-resolution (cloud resolving) NWP integrations. The considered case is taken from the Mesoscale Alpine Programme intensive observing period 3 (MAP IOP3) and involves convection of intermediate intensity. To assess the underlying mechanisms and the degree of linearity upon the predictability of the flow, vastly different initial perturbation methodologies are compared, while all simulations use identical lateral boundary conditions to mimic a perfectly predictable synoptic-scale ...

Atmospheric Predictability at Synoptic Versus Cloud-Resolving Scales

The limited atmospheric predictability has been addressed by the development of ensemble prediction systems (EPS) that are now routinely applied for medium-range synoptic-scale numerical weather prediction (NWP). With the increase of computational power, interest is growing in the design of high-resolution (cloud resolving) NWP models and their associated short-range EPS. This development raises a series of fundamental questions, especially concerning the type of error growth and the validity of the tangent-linear approximation. To address these issues, a comparison between perturbed medium-range (10 day) synoptic-scale integrations (taken from the operational ECMWF EPS with a horizontal resolution of about 80 km) and short-range (1 day) high-resolution simulations (based on the Lokal Modell of the Consortium for Small-Scale Modeling with a grid spacing of 2.2 km) is conducted. The differences between the two systems are interpreted in a nondimensional sense and illustrated with the help of the Lorenz att...

Preconditioning Deep Convection with Cumulus Congestus

AbstractRecent studies have pushed forward the idea that congestus clouds, through their moistening of the atmosphere, could promote deep convection. On the other hand, older studies have tended to relate convective initiation to the large-scale forcing. These two views are here contrasted by performing a time-scale analysis. The analysis combines ship observations, large-eddy simulations, and 1 month of brightness temperature measurements with a focus on the tropical Atlantic and adjacent land areas.The time-scale analysis suggests that previous work may have overstated the importance of congestus moistening in the preconditioning of deep convection. It is found that cumuli congestus transition very rapidly to deep convection, in 2 h over land and 4 h over ocean. This is much faster than the time needed (10 h and longer) by congestus clouds to sufficiently moisten the atmosphere. Moreover, the majority of congestus clouds seem unable to grow into cumulonimbus and the probability of transition does not in...

The Formation of Wider and Deeper Clouds as a Result of Cold-Pool Dynamics

AbstractThis study investigates how precipitation-driven cold pools aid the formation of wider clouds that are essential for a transition from shallow to deep convection. In connection with a temperature depression and a depletion of moisture inside developing cold pools, an accumulation of moisture in moist patches around the cold pools is observed. Convective clouds are formed on top of these moist patches. Larger moist patches form with time supporting more and larger clouds. Moreover, enhanced vertical lifting along the leading edges of the gravity current triggered by the cold pool is found. The interplay of moisture aggregation and lifting eventually promotes the formation of wider clouds that are less affected by entrainment and become deeper. These mechanisms are corroborated in a series of cloud-resolving model simulations representing different atmospheric environments. A positive feedback is observed in that, in an atmosphere in which cloud and rain formation is facilitated, stronger downdrafts...

Predictability Mysteries in Cloud-Resolving Models

The rapid amplification of small-amplitude perturbations by the chaotic nature of the atmospheric dynamics intrinsically limits the skill of deterministic weather forecasts. In this study, limited-area cloudresolving numerical weather prediction (NWP) experiments are conducted to investigate the role of mesoscale processes in determining predictability. The focus is set on domain-internal error growth by integrating an ensemble of simulations using slightly modified initial conditions but identical lateral boundary conditions. It is found that the predictability of the three investigated cases taken from the Mesoscale Alpine Programme (MAP) differs tremendously. In terms of normalized precipitation spread, values between 0.05 (highly predictable) and 1 (virtually unpredictable) are obtained. Analysis of the derived ensemble spread demonstrates that the diabatic forcing associated with moist dynamics is the prime source of rapid error growth. However, in agreement with an earlier study it is found that the differentiation between convective and stratiform rain is unable to account for the distinctive precipitation spreads of the three cases. In particular, instability indices are demonstrated to be poor predictors of the predictability level. An alternate hypothesis is proposed and tested. It is inspired by the dynamical instability theory and states that significant loss of predictability only occurs over moist convectively unstable regions that are able to sustain propagation of energy against the mean flow. Using a linear analysis of gravity wave propagation, this hypothesis is shown to provide successful estimates of the predictability level for the three cases under consideration.

The Influence of Land Surface Heterogeneities on Cloud Size Development

AbstractThis study analyzes the effects of land surface heterogeneities at various horizontal scales on the transition from shallow to deep convection and on the cloud size distribution. An idealized case of midlatitude summertime convection is simulated by means of large-eddy simulations coupled to an interactive land surface. The transition is accelerated over heterogeneous surfaces. The simulation with an intermediate patch size of 12.8 km exhibits the fastest transition with a transition time two-thirds that over a homogeneous surface. A similar timing is observed for the precipitation onset whereas the total accumulated rainfall tends to increase with patch size. The cloud size distribution can be approximated by a power law with a scale break. The exponent of the power law is independent of the heterogeneity scale, implying a similar cloud cover between the simulations. In contrast, the scale break varies with patch size. The size of the largest clouds does not scale with the boundary layer height, ...

An Idealized Cloud-Resolving Framework for the Study of Midlatitude Diurnal Convection over Land

AbstractThis paper introduces an idealized cloud-resolving modeling (CRM) framework for the study of midlatitude diurnal convection over land. The framework is used to study the feedbacks among soil, boundary layer, and diurnal convection. It includes a setup with explicit convection and a full set of parameterizations. Predicted variables are constantly relaxed toward prescribed atmospheric profiles and soil conditions. The relaxation is weak in the lower troposphere and upper soil to allow the development of a realistic diurnal planetary boundary layer. The model is run to its own equilibrium (30 days).The framework is able to produce a realistic timing of the diurnal cycle of convection. It also confirms the development of deeper convection in a more unstably stratified atmosphere.With this relaxation method, the simulated “diurnal equilibrium convection” determines the humidity profile of the lower atmosphere, and the simulation becomes insensitive to the reference humidity profile. However, if a fast...

The Atlantic ITCZ bias in CMIP5 models

Precipitation over the tropical Atlantic in 24 atmospheric models is analyzed using an object-based approach, which clusters rainy areas in the models as precipitation objects and calculates their properties such as size, amplitude, and location. Based on the distribution of precipitation objects over land and over ocean, two classes of models emerge. The first class of models has a reasonable representation of objects over land but misplaces the ocean object westward, near the coast of Brazil, instead of the central Atlantic as observed. The second class of models show small-sized objects over land with intense precipitation values; for these models, the ocean object is located eastward, near the coast of Guinea. The Atlantic intertropical convergence zone structure in the models exhibits either the West or the East Atlantic bias. No model matches the observed precipitation distribution. The two distinct model behaviors in the mean state are traced to the coastal precipitation bias of the models in boreal spring. In this season, the two model groups place the main precipitation object on opposite coasts—one group puts it at the south coast of Brazil and the other group places it at the Gulf of Guinea. This west–east partitioning of precipitation is sustained in boreal summer, resulting in the West and East Atlantic bias in the annual mean. It is found that models with the East Atlantic bias tend to be high resolution models which rain excessively over the Gulf of Guinea starting from boreal spring.

Intensification of convective extremes driven by cloud–cloud interaction

Convective precipitation may change in a changing climate. Large eddy simulations of convection with a realistic diurnal cycle suggest that interactions between convective systems and precipitation extremes are influenced by temperature.