scholarly journals Direct Bayesian model reduction of smaller scale convective activity conditioned on large scale dynamics

2021 ◽  
Author(s):  
Robert Polzin ◽  
Annette Müller ◽  
Henning Rust ◽  
Peter Névir ◽  
Péter Koltai
Keyword(s):  
Model Reduction ◽  
Bayesian Model ◽  
Large Scale ◽  
Convective Available Potential Energy ◽  
Probabilistic Approach ◽  
Vertical Motion ◽  
Total Probability ◽  
Convective Activity ◽  
Stochastic Representation ◽  
Probabilistic Relation

Abstract. We pursue a simplified stochastic representation of smaller scale convective activity conditioned on large scale dynamics in the atmosphere. For identifying a Bayesian model describing the relation of different scales we use a probabilistic approach (Gerber and Horenko, 2017) called Direct Bayesian Model Reduction (DBMR). The convective available potential energy (CAPE) is applied as large scale flow variable combined with a subgrid smaller scale time series for the vertical velocity. We found a probabilistic relation of CAPE and vertical up- and downdraft for day and night. The categorization is based on the conservation of total probability. This strategy is part of a development process for parametrizations in models of atmospheric dynamics representing the effective influence of unresolved vertical motion on the large scale flows. The direct probabilistic approach provides a basis for further research of smaller scale convective activity conditioned on other possible large scale drivers.

scholarly journals Uncertainty-Aware Deep Learning-Based Cardiac Arrhythmias Classification Model of Electrocardiogram Signals

Computers ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 82
Author(s):  
Ahmad O. Aseeri
Keyword(s):  
Deep Learning ◽  
Cardiac Arrhythmias ◽  
Large Scale ◽  
Clinical Decision Making ◽  
Probabilistic Approach ◽  
Classification Model ◽  
Gating Mechanism ◽  
Uncertainty Estimates ◽  
Wide Range

Deep Learning-based methods have emerged to be one of the most effective and practical solutions in a wide range of medical problems, including the diagnosis of cardiac arrhythmias. A critical step to a precocious diagnosis in many heart dysfunctions diseases starts with the accurate detection and classification of cardiac arrhythmias, which can be achieved via electrocardiograms (ECGs). Motivated by the desire to enhance conventional clinical methods in diagnosing cardiac arrhythmias, we introduce an uncertainty-aware deep learning-based predictive model design for accurate large-scale classification of cardiac arrhythmias successfully trained and evaluated using three benchmark medical datasets. In addition, considering that the quantification of uncertainty estimates is vital for clinical decision-making, our method incorporates a probabilistic approach to capture the model’s uncertainty using a Bayesian-based approximation method without introducing additional parameters or significant changes to the network’s architecture. Although many arrhythmias classification solutions with various ECG feature engineering techniques have been reported in the literature, the introduced AI-based probabilistic-enabled method in this paper outperforms the results of existing methods in outstanding multiclass classification results that manifest F1 scores of 98.62% and 96.73% with (MIT-BIH) dataset of 20 annotations, and 99.23% and 96.94% with (INCART) dataset of eight annotations, and 97.25% and 96.73% with (BIDMC) dataset of six annotations, for the deep ensemble and probabilistic mode, respectively. We demonstrate our method’s high-performing and statistical reliability results in numerical experiments on the language modeling using the gating mechanism of Recurrent Neural Networks.

scholarly journals Global climatology and trends in convective environments from ERA5 and rawinsonde data

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Mateusz Taszarek ◽  
John T. Allen ◽  
Mattia Marchio ◽  
Harold E. Brooks
Keyword(s):  
Large Scale ◽  
Climate Models ◽  
Global Climate ◽  
Convective Available Potential Energy ◽  
Global Climate Models ◽  
Convective Precipitation ◽  
The Past ◽  
The Tropics ◽  
Rawinsonde Data

AbstractGlobally, thunderstorms are responsible for a significant fraction of rainfall, and in the mid-latitudes often produce extreme weather, including large hail, tornadoes and damaging winds. Despite this importance, how the global frequency of thunderstorms and their accompanying hazards has changed over the past 4 decades remains unclear. Large-scale diagnostics applied to global climate models have suggested that the frequency of thunderstorms and their intensity is likely to increase in the future. Here, we show that according to ERA5 convective available potential energy (CAPE) and convective precipitation (CP) have decreased over the tropics and subtropics with simultaneous increases in 0–6 km wind shear (BS06). Conversely, rawinsonde observations paint a different picture across the mid-latitudes with increasing CAPE and significant decreases to BS06. Differing trends and disagreement between ERA5 and rawinsondes observed over some regions suggest that results should be interpreted with caution, especially for CAPE and CP across tropics where uncertainty is the highest and reliable long-term rawinsonde observations are missing.

scholarly journals Influence of the Upstream Terrain on the Formation of a Cold Frontal Snowband in Northeast China

2021 ◽  
Author(s):  
Na Li ◽  
Baofeng Jiao ◽  
Lingkun Ran ◽  
Zongting Gao ◽  
Shouting Gao
Keyword(s):  
Gravity Waves ◽  
Northeast China ◽  
Large Scale ◽  
Control Experiment ◽  
Vertical Motion ◽  
Near Surface ◽  
Inertial Instability ◽  
Two Factors ◽  
Negative Effect ◽  
Conditional Instability

AbstractWe investigated the influence of upstream terrain on the formation of a cold frontal snowband in Northeast China. We conducted numerical sensitivity experiments that gradually removed the upstream terrain and compared the results with a control experiment. Our results indicate a clear negative effect of upstream terrain on the formation of snowbands, especially over large-scale terrain. By thoroughly examining the ingredients necessary for snowfall (instability, lifting and moisture), we found that the release of mid-level conditional instability, followed by the release of low-level or near surface instabilities (inertial instability, conditional instability or conditional symmetrical instability), contributed to formation of the snowband in both experiments. The lifting required for the release of these instabilities was mainly a result of frontogenetic forcing and upper gravity waves. However, the snowband in the control experiment developed later and was weaker than that in the experiment without upstream terrain. Two factors contributed to this negative topographic effect: (1) the mountain gravity waves over the upstream terrain, which perturbed the frontogenetic circulation by rapidly changing the vertical motion and therefore did not favor the release of instabilities in the absence of persistent ascending motion; and (2) the decrease in the supply of moisture as a result of blocking of the upstream terrain, which changed both the moisture and instability structures leeward of the mountains. A conceptual model is presented that shows the effects of the instabilities and lifting on the development of cold frontal snowbands in downstream mountains.

scholarly journals Tropical Cyclone Count Forecasting Using a Dynamical Seasonal Prediction System: Sensitivity to Improved Ocean Initialization

2011 ◽  
Vol 24 (12) ◽  
pp. 2963-2982 ◽  
Author(s):  
Andrea Alessandri ◽  
Andrea Borrelli ◽  
Silvio Gualdi ◽  
Enrico Scoccimarro ◽  
Simona Masina
Keyword(s):  
Tropical Cyclone ◽  
Indian Ocean ◽  
Wind Shear ◽  
Large Scale ◽  
Initial Conditions ◽  
North Pacific Ocean ◽  
Convective Available Potential Energy ◽  
Seasonal Prediction ◽  
Boreal Summer ◽  
Prediction System

Abstract This study investigates the predictability of tropical cyclone (TC) seasonal count anomalies using the Centro Euro-Mediterraneo per i Cambiamenti Climatici–Istituto Nazionale di Geofisica e Vulcanologia (CMCC-INGV) Seasonal Prediction System (SPS). To this aim, nine-member ensemble forecasts for the period 1992–2001 for two starting dates per year were performed. The skill in reproducing the observed TC counts has been evaluated after the application of a TC location and tracking detection method to the retrospective forecasts. The SPS displays good skill in predicting the observed TC count anomalies, particularly over the tropical Pacific and Atlantic Oceans. The simulated TC activity exhibits realistic geographical distribution and interannual variability, thus indicating that the model is able to reproduce the major basic mechanisms that link the TCs’ occurrence with the large-scale circulation. TC count anomalies prediction has been found to be sensitive to the subsurface assimilation in the ocean for initialization. Comparing the results with control simulations performed without assimilated initial conditions, the results indicate that the assimilation significantly improves the prediction of the TC count anomalies over the eastern North Pacific Ocean (ENP) and northern Indian Ocean (NI) during boreal summer. During the austral counterpart, significant progresses over the area surrounding Australia (AUS) and in terms of the probabilistic quality of the predictions also over the southern Indian Ocean (SI) were evidenced. The analysis shows that the improvement in the prediction of anomalous TC counts follows the enhancement in forecasting daily anomalies in sea surface temperature due to subsurface ocean initialization. Furthermore, the skill changes appear to be in part related to forecast differences in convective available potential energy (CAPE) over the ENP and the North Atlantic Ocean (ATL), in wind shear over the NI, and in both CAPE and wind shear over the SI.

Granitoid complexes and the Archean tectonic record in the southern part of northwestern Ontario

1979 ◽  
Vol 16 (10) ◽  
pp. 1965-1977 ◽  
Author(s):  
W. M. Schwerdtner ◽  
D. Stone ◽  
K. Osadetz ◽  
J. Morgan ◽  
G. M. Stott
Keyword(s):  
Large Scale ◽  
Vertical Motion ◽  
Strike Slip ◽  
Horizontal Motion ◽  
Tectonic Deformation ◽  
Northwestern Ontario ◽  
Greenstone Belts ◽  
Second Period ◽  
Transcurrent Faults ◽  
Regional Compression

Two principal, possibly overlapping, periods of tectonic deformation can be distinguished in the Archean of northwestern Ontario, a period of dominantly vertical-motion tectonics and a period of dominantly horizontal-motion tectonics. Gigantic diapirs of foliated to gneissic tonalite–granodiorite developed during the first period and appear to be responsible for the gross structure of, and the major folds within, the metavolcanic–metasedimentary masses ("greenstone belts"). These diapirs are most likely due to mechanical remobilization of early tabular batholiths which originally intruded the oldest supracrustal rocks presently exposed. Later massive to foliated, dioritic to granitic plutons that vary from concordant, crescentic plutons to partly discordant plutons of various shapes and sizes were emplaced into the diapirs.The second period of tectonic deformation is characterized by large-scale dextral shearing and the development of major transcurrent faults under northwesterly regional compression. The strike-slip motions of this period outlasted the late plutonism, and led to the development of mylonitic zones which cut all Archean granitoid plutons.

Model Reduction and Clusterization of Large-Scale Bidirectional Networks

2014 ◽  
Vol 59 (1) ◽  
pp. 48-63 ◽  
Author(s):  
Takayuki Ishizaki ◽  
Kenji Kashima ◽  
Jun-ichi Imura ◽  
Kazuyuki Aihara
Keyword(s):  
Model Reduction ◽  
Large Scale ◽  
Bidirectional Networks

scholarly journals Systematic Variation in Wintertime Precipitation in East Asia by MJO-Induced Extratropical Vertical Motion

2008 ◽  
Vol 21 (4) ◽  
pp. 788-801 ◽  
Author(s):  
Jee-Hoon Jeong ◽  
Baek-Min Kim ◽  
Chang-Hoi Ho ◽  
Yeon-Hee Noh
Keyword(s):  
East Asia ◽  
Large Scale ◽  
Diabatic Heating ◽  
Daily Precipitation ◽  
Lower Troposphere ◽  
Vertical Motion ◽  
Mean Value ◽  
Asian Countries ◽  
The Indian Ocean ◽  
Omega Equation

Abstract The variations in the wintertime precipitation over East Asia and the related large-scale circulation associated with the Madden–Julian oscillation (MJO) are examined. By analyzing the observed daily precipitation for the period 1974–2000, it is found that the MJO significantly modulates the distribution of precipitation over four East Asian countries; the precipitation rate difference between wet and dry periods over East Asia, when the centers of MJO convective activities are located over the Indian Ocean and western Pacific, respectively, reaches 3–4 mm day−1, which corresponds to the climatological winter-mean value. Composite analysis with respect to the MJO suggests that the MJO–precipitation relation is mostly explained by the strong vertical motion anomalies near an entrance region of the East Asia upper-tropospheric jet and moisture supply in the lower troposphere. To elucidate different dynamic origins of the vertical motion generated by the MJO, diagnostic analysis of a generalized omega equation is adopted. It is revealed that about half of the vertical motion anomalies in East Asia are induced by the quasigeostrophic forcings by the MJO, while diabatic heating forcings explain a very small fraction, less than 10% of total anomalies.

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