A single column simulation-based decomposition of the tropical upper tropospheric warming

An atmospheric global climate model (GCM) and its associated single-column model are used to study the tropical upper tropospheric warming and elucidate how different processes drive this warming. In this modeling framework, on average the direct radiative process accounts for 13% of the total warming. The radiation increases the atmospheric lapse rate and triggers more convection, which further produces 74% of the total warming. The rest 13% is attributable to the circulation adjustment. The relative importance of these processes differs in different regions. In the deep tropics, the radiative-convective adjustment produces the most significant warming and accounts for almost 100% of the total warming. In the subtropics, the radiative-convective adjustment accounts for 73% of the total warming and the circulation adjustment plays a more important role than in the deep tropics, especially at the levels above 200 hPa. When the lateral boundary conditions, i.e. the temperature and water vapor advections, are held fixed in single-column simulations, the tropospheric relative humidity significantly increases in the radiative-convective adjustment in response to the surface warming. This result, in contrast to the relative humidity conservation behavior in the GCM, highlights the importance of circulation adjustment in maintaining the constant relative humidity. The tropical upper tropospheric warming in both the full GCM and the single-column simulations is found to be less strong than the warming predicted by reference moist adiabats. This evidences that the sub-moist-adiabat warming occurs even without the dilution effect of the large-scale circulation adjustment.

Dependence of predictability of precipitation in the northwestern Mediterranean coastal region on the strength of synoptic control

The weather-regime-dependent predictability of precipitation in the convection-permitting kilometric-scale AROME-EPS is examined for the entire HyMeX-SOP1 employing the convective adjustment timescale. This diagnostic quantifies variations in synoptic forcing on precipitation and is associated with different precipitation characteristics, forecast skill and predictability. During strong synoptic control, which dominates the weather on 80 % of the days in the 2-month period, the domain-integrated precipitation predictability assessed with the normalized ensemble standard deviation is above average, the wet bias is smaller and the forecast quality is generally better. In contrast, the pure spatial forecast quality of the most intense precipitation in the afternoon, as quantified with its 95th percentile, is superior during weakly forced synoptic regimes. The study also considers a prominent heavy-precipitation event that occurred during the NAWDEX field campaign in the same region, and the predictability during this event is compared with the events that occurred during HyMeX. It is shown that the unconditional evaluation of precipitation widely parallels the strongly forced weather type evaluation and obscures forecast model characteristics typical for weak control.

Dependence of Predictability of Precipitation in the Northwestern Mediterranean Coastal Region on the Strength of Synoptic Control

The weather regime dependent predictability of precipitation in the convection permitting kilometric scale AROME-EPS is examined for the entire HyMeX SOP1 employing the convective adjustment timescale. This diagnostic quantifies variations in synoptic forcing on precipitation and is associated with different precipitation characteristics, forecast skill and predictability. During strong synoptic control, which is dominating the weather on 80 % of the days in the 2-months period, the domain integrated precipitation predictability assessed with the normalized ensemble standard deviation is above average, the wet bias is smaller and the forecast quality is generally better. In contrast, the spatial forecast quality of most intense precipitation in the afternoon, as quantified with its 95th percentiles, is superior during weakly forced synoptic regimes. The study also considers a prominent heavy precipitation event that occurred during the NAWDEX field campaign in the same region, and the predictability during this event is compared with the events that occurred during HyMeX. It is shown that the unconditional evaluation of precipitation widely parallels the strongly forced weather type evaluation and obscures forecast model characteristics typical for weak control.

Asymptotic Models for Tropical Intraseasonal Oscillations and Geostrophic Balance

In the tropics, rainfall is coupled with waves in the form of, for example, convectively coupled equatorial waves (CCEWs) and the Madden–Julian oscillation (MJO). In perhaps the simplest viewpoint of CCEWs, the effects of moisture and convective adjustment can predict the basic aspects of their propagation and structure: reduced propagation speeds and reduced meridional length scales. Here, a similar simple viewpoint is investigated for the MJO’s propagation and structure. To do this investigation, budget analyses of a model MJO are first presented to illustrate and motivate the asymptotic scaling assumptions. Asymptotic models are then derived for the MJO. In brief, the structure of the asymptotic MJO is described by a tropical geostrophic balance, and the slow propagation arises from the dynamics of moist static energy. To be specific, if the moist static energy has a background vertical gradient that is asymptotically weak (i.e., a moist stability that is nearly neutral), then it supports a slowly propagating wave. Beyond these main aspects, other processes also have an influence, such as eddy diffusion of moisture. In comparing the simple viewpoints of CCEWs and the MJO, one main difference is in the propagation speeds: relative to a dry wave speed of 50 m s−1, the MJO has a speed of 5 m s−1, resulting from a reduction factor of 0.1 related to moist stability, whereas the basic CCEW speed is 15 m s−1, resulting from a reduction factor of the square root of 0.1, related to the square root of the moist stability.

Deep Convective Adjustment of Temperature and Moisture

Simple process models and complex climate models are remarkably sensitive to the time scale of convective adjustment τ, but this parameter remains poorly constrained and understood. This study uses the linear-range slope of a semiempirical relationship between precipitation and a lower-free-tropospheric buoyancy measure BL. The BL measure is a function of layer-averaged moist enthalpy in the boundary layer (150-hPa-thick layer above surface), and temperature and moisture in the lower free troposphere (boundary layer top to 500 hPa). Sensitivity parameters with units of time quantify the BL response to its component perturbations. In moist enthalpy units, BL is more sensitive to temperature than equivalent moisture perturbations. However, column-integrated moist static energy conservation ensures that temperature and moisture are equally altered during the adjustment process. Multiple adjusted states with different temperature–moisture combinations exist; the BL sensitivity parameters govern the relationship between adjusted states, and also combine to yield a time scale of convective adjustment ~2 h. This value is comparable to τ values used in cumulus parameterization closures. Disparities in previously reported values of τ are attributed to the neglect of the temperature contribution to precipitation, and to averaging operations that include data from both precipitating and nonprecipitating regimes. A stochastic model of tropical convection demonstrates how either averaging operations or neglected environmental influences on precipitation can yield τ estimates longer than the true τ value built into the model. The analysis here culminates in construction of a precipitation closure with both moisture and temperature adjustment (q–T closure), suitable for use in both linearized and nonlinear, intermediate-complexity models.

A 1D RCE Study of Factors Affecting the Tropical Tropopause Layer and Surface Climate

There are discrepancies between global climate models regarding the evolution of the tropical tropopause layer (TTL) and also whether changes in ozone impact the surface under climate change. We use a 1D clear-sky radiative–convective equilibrium model to determine how a variety of factors can affect the TTL and how they influence surface climate. We develop a new method of convective adjustment, which relaxes the temperature profile toward the moist adiabat and allows for cooling above the level of neutral buoyancy. The TTL temperatures in our model are sensitive to CO2 concentration, ozone profile, the method of convective adjustment, and the upwelling velocity, which is used to calculate a dynamical cooling rate in the stratosphere. Moreover, the temperature response of the TTL to changes in each of the above factors sometimes depends on the others. The surface temperature response to changes in ozone and upwelling at and above the TTL is also strongly amplified by both stratospheric and tropospheric water vapor changes. With all these influencing factors, it is not surprising that global models disagree with regard to TTL structure and evolution and the influence of ozone changes on surface temperatures. On the other hand, the effect of doubling CO2 on the surface, including just radiative, water vapor, and lapse-rate feedbacks, is relatively robust to changes in convection, upwelling, or the applied ozone profile.

Nonuniqueness in a Single-Column Model for Moist Convection

We investigate a moist atmospheric column convection model by considering the atmosphere as a single vertical column of air parcels, each of which contains water vapor. The moist convective adjustment of both air and water mass in the column is considered from an (unstable) initial state to a statically stable final configuration of parcels. Two variations of an algorithm based upon swapping neighboring parcels are compared: after swapping, no parcels remain supersaturated. The results of these algorithms are compared directly with those of the adjustment algorithm of Cheng et al., which adjusts an atmospheric column to achieve the global maximum of a relevant cost functional. Two examples are considered: in the first, the algorithms adjust to similar arrangements, showing that the global maximum of the functional is the dynamically preferred state, while in the second, the algorithms adjust to significantly different states. Thus, we identify a nonuniqueness to the solution to the adjustment problem in terms of local and global cost functional maximizers. We then discuss the relevance of this nonuniqueness to numerical prediction in weather and climate models.

Roles of the Moisture and Wave Feedbacks in Shaping the Madden–Julian Oscillation

This study investigates the moisture and wave feedbacks in the Madden–Julian oscillation (MJO) dynamics by applying the general three-way interaction theoretical model. The three-way interaction model can reproduce observed large-scale characteristics of the MJO in terms of horizontal quadrupole-vortex structure, vertically tilted structure led by planetary boundary layer (PBL) convergence, slow eastward propagation with a period of 30–90 days, and planetary-scale circulation. The moisture feedback effects can be identified in this model by using diagnostic thermodynamic and momentum equations, and the wave feedback effects are investigated by using a diagnostic moisture equation. The moisture feedback is found to be responsible for producing the MJO dispersive modes when the convective adjustment process is slow. The moisture feedback mainly acts to reduce the frequency and growth rate of the short waves, while leaving the planetary waves less affected, so neglecting the moisture feedback is a good approximation for the wavenumber-1 MJO. The wave feedback is shown to slow down the eastward propagation and increase the growth rate of the planetary waves. The wave feedback becomes weak when the convective adjustment time increases, so neglecting the wave feedback is a good approximation for the MJO dynamics during a slow adjustment process. Sensitivities of these two feedbacks to other parameters are also discussed. These theoretical findings suggest that the two feedback processes, and thus the behaviors of the simulated MJO mode, should be sensitive to the parameters used in cumulus parameterizations.