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Julian F. Quinting
and
Christian M. Grams

Abstract

The physical and dynamical processes associated with warm conveyor belts (WCBs) importantly affect midlatitude dynamics and are sources of forecast uncertainty. Moreover, WCBs modulate the large-scale extratropical circulation and can communicate and amplify forecast errors. Therefore, it is desirable to assess the representation of WCBs in numerical weather prediction (NWP) models in particular on the medium to subseasonal forecast range. Most often, WCBs are identified as coherent bundles of Lagrangian trajectories that ascend in a time interval of 2 days from the lower to the upper troposphere. Although this Lagrangian approach has advanced the understanding of the involved processes significantly, the calculation of trajectories is computationally expensive and requires NWP data at a high spatial [O(~1)], vertical [O(~10hPa)], and temporal resolution [O(~36h)]. In this study, we present a statistical framework that derives footprints of WCBs from coarser NWP data that are routinely available. To this end, gridpoint-specific multivariate logistic regression models are developed for the Northern Hemisphere using meteorological parameters from ERA-Interim data as predictors and binary footprints of WCB inflow, ascent, and outflow based on a Lagrangian dataset as predictands. Stepwise forward selection identifies the most important predictors for these three WCB stages. The logistic models are reliable in replicating the climatological frequency of WCBs as well as the footprints of WCBs at instantaneous time steps. The novel framework is a first step toward a systematic evaluation of WCB representation in large datasets such as subseasonal ensemble reforecasts or climate projections.

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Ángel F. Adames
and
Yi Ming

Abstract

The mechanisms that lead to the propagation of anomalous moisture and moist static energy (MSE) in monsoon low and high pressure systems, collectively referred to as synoptic-scale monsoonal disturbances (SMDs), are investigated using daily output fields from GFDL’s atmospheric general circulation model, version 4.0 (AM4.0). On the basis of linear regression analysis of westward-propagating rainfall anomalies of time scales shorter than 15 days, it is found that SMDs are organized into wave trains of three to four individual cyclones and anticyclones. These events amplify over the Bay of Bengal, reach a maximum amplitude over the eastern coast of India, and dissipate as they approach the Arabian Sea. The structure and propagation of the simulated SMDs resemble those documented in observations. It is found that moisture and MSE anomalies exhibit similar horizontal structures in the simulated SMDs, indicating that moisture is the leading contributor to MSE. Propagation of the moisture anomalies is governed by vertical moisture advection, while the MSE anomalies propagate because of horizontal advection of dry static energy by the anomalous winds. By combining the budgets, we interpret the propagation of the moisture anomalies in terms of lifting that is forced by horizontal dry static energy advection, that is, ascent along sloping isentropes. This process moistens the lower free troposphere, producing an environment that is more favorable to deep convection. Ascent driven by radiative heating is of primary importance to the maintenance of the moisture anomalies.

Open access
Yi-Hung Kuo
,
Kathleen A. Schiro
, and
J. David Neelin

Abstract

Convective transition statistics, which describe the relation between column-integrated water vapor (CWV) and precipitation, are compiled over tropical oceans using satellite and ARM site measurements to quantify the temperature and resolution dependence of the precipitation–CWV relation at fast time scales relevant to convection. At these time scales, and for precipitation especially, uncertainties associated with observational systems must be addressed by examining features with a variety of instrumentation and identifying robust behaviors versus instrument sensitivity at high rain rates. Here the sharp pickup in precipitation as CWV exceeds a certain critical threshold is found to be insensitive to spatial resolution, with convective onset occurring at higher CWV but at lower column relative humidity as bulk tropospheric temperature increases. Mean tropospheric temperature profiles conditioned on precipitation show vertically coherent structure across a wide range of temperature, reaffirming the use of a bulk temperature measure in defining the convective transition statistics. The joint probability distribution of CWV and precipitation develops a peak probability at low precipitation for CWV above critical, with rapidly decreasing probability of high precipitation below and near critical, and exhibits systematic changes under spatial averaging. The precipitation pickup with CWV is reasonably insensitive to time averaging up to several hours but is smoothed at daily time scales. This work demonstrates that CWV relative to critical serves as an effective predictor of precipitation with only minor geographic variations in the tropics, quantifies precipitation-related statistics subject to different spatial–temporal resolution, and provides a baseline for model comparison to apply these statistics as observational constraints on precipitation processes.

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Fiaz Ahmed
and
J. David Neelin

Abstract

The tropical precipitation–moisture relationship, characterized by rapid increases in precipitation for modest increases in moisture, is conceptually recast in a framework relevant to plume buoyancy and conditional instability in the tropics. The working hypothesis in this framework links the rapid onset of precipitation to integrated buoyancy in the lower troposphere. An analytical expression that relates the buoyancy of an entraining plume to the vertical thermodynamic structure is derived. The natural variables in this framework are saturation and subsaturation equivalent potential temperatures, which capture the leading-order temperature and moisture variations, respectively. The use of layer averages simplifies the analytical and subsequent numerical treatment. Three distinct layers, the boundary layer, the lower free troposphere, and the midtroposphere, adequately capture the vertical variations in the thermodynamic structure. The influence of each environmental layer on the plume is assumed to occur via lateral entrainment, corresponding to an assumed mass-flux profile. The fractional contribution of each layer to the midlevel plume buoyancy (i.e., the layer weight) is estimated from TRMM 3B42 precipitation and ERA-Interim thermodynamic profiles. The layer weights are used to “reverse engineer” a deep-inflow mass-flux profile that is nominally descriptive of the tropical atmosphere through the onset of deep convection. The layer weights—which are nearly the same for each of the layers—constitute an environmental influence function and are also used to compute a free-tropospheric integrated buoyancy measure. This measure is shown to be an effective predictor of onset in conditionally averaged precipitation across the global tropics—over both land and ocean.

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