scholarly journals Identifying Relations Between Deep Convection and the Large‐Scale Atmosphere Using Explainable Artificial Intelligence

2022 ◽  
Author(s):  
M. H. Retsch ◽  
C. Jakob ◽  
M. S. Singh
Keyword(s):  
Artificial Intelligence ◽  
Large Scale ◽  
Deep Convection ◽  
Explainable Artificial Intelligence

scholarly journals An Explainable Artificial Intelligence Approach for Predicting Cardiovascular Outcomes using Electronic Health Records

2021 ◽  
Author(s):  
Sergiusz Wesolowski ◽  
Gordon Howard Lemmon ◽  
Edgar J Hernandez ◽  
Alex Ryan Henrie ◽  
Thomas A Miller ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Electronic Health Records ◽  
Large Scale ◽  
Cardiovascular Health ◽  
Cardiovascular Outcomes ◽  
Health Records ◽  
University Of Utah ◽  
Explainable Artificial Intelligence ◽  
Electronic Health ◽  
Discovery Method

Understanding the conditionally-dependent clinical variables that drive cardiovascular health outcomes is a major challenge for precision medicine. Here, we deploy a recently developed massively scalable comorbidity discovery method called Poisson Binomial based Comorbidity discovery (PBC), to analyze Electronic Health Records (EHRs) from the University of Utah and Primary Children's Hospital (over 1.6 million patients and 77 million visits) for comorbid diagnoses, procedures, and medications. Using explainable Artificial Intelligence (AI) methodologies, we then tease apart the intertwined, conditionally-dependent impacts of comorbid conditions and demography upon cardiovascular health, focusing on the key areas of heart transplant, sinoatrial node dysfunction and various forms of congenital heart disease. The resulting multimorbidity networks make possible wide-ranging explorations of the comorbid and demographic landscapes surrounding these cardiovascular outcomes, and can be distributed as web-based tools for further community-based outcomes research. The ability to transform enormous collections of EHRs into compact, portable tools devoid of Protected Health Information solves many of the legal, technological, and data-scientific challenges associated with large-scale EHR analyzes.

scholarly journals BattleNet: Capturing Advantageous Battlefield in RTS Games (Student Abstract)

2020 ◽  
Vol 34 (10) ◽  
pp. 13849-13850
Author(s):  
Donghyeon Lee ◽  
Man-Je Kim ◽  
Chang Wook Ahn
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Real Time ◽  
Large Scale ◽  
Outcome Predictor ◽  
Short Term ◽  
Rts Game

In a real-time strategy (RTS) game, StarCraft II, players need to know the consequences before making a decision in combat. We propose a combat outcome predictor which utilizes terrain information as well as squad information. For training the model, we generated a StarCraft II combat dataset by simulating diverse and large-scale combat situations. The overall accuracy of our model was 89.7%. Our predictor can be integrated into the artificial intelligence agent for RTS games as a short-term decision-making module.

scholarly journals Subseasonal Forecasts of the Northern Queensland Floods of February 2019: Causes and Forecast Evaluation

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 758
Author(s):  
Wayne Yuan-Huai Tsai ◽  
Mong-Ming Lu ◽  
Chung-Hsiung Sui ◽  
Yin-Min Cho
Keyword(s):  
Large Scale ◽  
Deep Convection ◽  
Austral Summer ◽  
Rainfall Event ◽  
Monsoon Depression ◽  
Forecast Skill ◽  
Sea Surface ◽  
Central Pacific ◽  
Percentile Rank ◽  
Extended Range

During the austral summer 2018/19, devastating floods occurred over northeast Australia that killed approximately 625,000 head of cattle and inundated over 3000 homes in Townsville. In this paper, the disastrous event was identified as a record-breaking subseasonal peak rainfall event (SPRE). The SPRE was mainly induced by an anomalously strong monsoon depression that was modulated by the convective phases of an MJO and an equatorial Rossby (ER) wave. The ER wave originated from an active equatorial deep convection associated with the El Niño warm sea surface temperatures near the dateline over the central Pacific. Based on the S2S Project Database, we analyzed the extended-range forecast skill of the SPRE from two different perspectives, the monsoon depression represented by an 850-hPa wind shear index and the 15-day accumulated precipitation characterized by the percentile rank (PR) and the ratio to the three-month seasonal (DJF) totals. The results of four S2S models of this study suggest that the monsoon depression can maintain the same level of skill as the short-range (3 days) forecast up to 8–10 days. For precipitation parameters, the conclusions are similar to the monsoon depression. For the 2019 northern Queensland SPRE, the model forecast was, in general, worse than the expectation derived from the hindcast analysis. The clear modulation of the ER wave that enhanced the SPRE monsoon depression circulation and precipitation is suspected as the main cause for the lower forecast skill. The analysis procedure proposed in this study can be applied to analyze the SPREs and their associated large-scale drivers in other regions.

scholarly journals Mesoscale Features Associated with Tropical Cyclone Formations in the Western North Pacific

2008 ◽  
Vol 136 (6) ◽  
pp. 2006-2022 ◽  
Author(s):  
Cheng-Shang Lee ◽  
Kevin K. W. Cheung ◽  
Jenny S. N. Hui ◽  
Russell L. Elsberry
Keyword(s):  
Tropical Cyclone ◽  
North Pacific ◽  
Western North Pacific ◽  
Large Scale ◽  
North Pacific Ocean ◽  
Deep Convection ◽  
Mesoscale Convective System ◽  
Convective System ◽  
Synoptic Patterns ◽  
The Mean

Abstract The mesoscale features of 124 tropical cyclone formations in the western North Pacific Ocean during 1999–2004 are investigated through large-scale analyses, satellite infrared brightness temperature (TB), and Quick Scatterometer (QuikSCAT) oceanic wind data. Based on low-level wind flow and surge direction, the formation cases are classified into six synoptic patterns: easterly wave (EW), northeasterly flow (NE), coexistence of northeasterly and southwesterly flow (NE–SW), southwesterly flow (SW), monsoon confluence (MC), and monsoon shear (MS). Then the general convection characteristics and mesoscale convective system (MCS) activities associated with these formation cases are studied under this classification scheme. Convection processes in the EW cases are distinguished from the monsoon-related formations in that the convection is less deep and closer to the formation center. Five characteristic temporal evolutions of the deep convection are identified: (i) single convection event, (ii) two convection events, (iii) three convection events, (iv) gradual decrease in TB, and (v) fluctuating TB, or a slight increase in TB before formation. Although no dominant temporal evolution differentiates cases in the six synoptic patterns, evolutions ii and iii seem to be the common routes taken by the monsoon-related formations. The overall percentage of cases with MCS activity at multiple times is 63%, and in 35% of cases more than one MCS coexisted. Most of the MC and MS cases develop multiple MCSs that lead to several episodes of deep convection. These two patterns have the highest percentage of coexisting MCSs such that potential interaction between these systems may play a role in the formation process. The MCSs in the monsoon-related formations are distributed around the center, except in the NE–SW cases in which clustering of MCSs is found about 100–200 km east of the center during the 12 h before formation. On average only one MCS occurs during an EW formation, whereas the mean value is around two for the other monsoon-related patterns. Both the mean lifetime and time of first appearance of MCS in EW are much shorter than those developed in other synoptic patterns, which indicates that the overall formation evolution in the EW case is faster. Moreover, this MCS is most likely to be found within 100 km east of the center 12 h before formation. The implications of these results to internal mechanisms of tropical cyclone formation are discussed in light of other recent mesoscale studies.

scholarly journals Atmospheric Conditions Associated with Labrador Sea Deep Convection: New Insights from a Case Study of the 2006/07 and 2007/08 Winters

2016 ◽  
Vol 29 (14) ◽  
pp. 5281-5297 ◽  
Author(s):  
Who M. Kim ◽  
Stephen Yeager ◽  
Ping Chang ◽  
Gokhan Danabasoglu
Keyword(s):  
North America ◽  
North Atlantic ◽  
Large Scale ◽  
Initial Conditions ◽  
Deep Convection ◽  
La Niña ◽  
Labrador Sea ◽  
Atmospheric Conditions ◽  
Circulation Anomaly ◽  
La Nina

Abstract Deep convection in the Labrador Sea (LS) resumed in the winter of 2007/08 under a moderately positive North Atlantic Oscillation (NAO) state. This is in sharp contrast with the previous winter with weak convection, despite a similar positive NAO state. This disparity is explored here by analyzing reanalysis data and forced-ocean simulations. It is found that the difference in deep convection is primarily due to differences in large-scale atmospheric conditions that are not accounted for by the conventional NAO definition. Specifically, the 2007/08 winter was characterized by an atmospheric circulation anomaly centered in the western North Atlantic, rather than the eastern North Atlantic that the conventional NAO emphasizes. This anomalous circulation was also accompanied by anomalously cold conditions over northern North America. The controlling influence of these atmospheric conditions on LS deep convection in the 2008 winter is confirmed by sensitivity experiments where surface forcing and/or initial conditions are modified. An extended analysis for the 1949–2009 period shows that about half of the winters with strong heat losses in the LS are associated with such a west-centered circulation anomaly and cold conditions over northern North America. These are found to be accompanied by La Niña–like conditions in the tropical Pacific, suggesting that the atmospheric response to La Niña may have a strong influence on LS deep convection.

scholarly journals On interpreting studies of tracer transport by deep cumulus convection and its effects on atmospheric chemistry

2008 ◽  
Vol 8 (20) ◽  
pp. 6037-6050 ◽  
Author(s):  
M. G. Lawrence ◽  
M. Salzmann
Keyword(s):  
Atmospheric Chemistry ◽  
Large Scale ◽  
Deep Convection ◽  
Convective Transport ◽  
Advective Transport ◽  
Tracer Transport ◽  
Transport Models ◽  
Mass Fluxes ◽  
Split Treatment ◽  
The Mean

Abstract. Global chemistry-transport models (CTMs) and chemistry-GCMs (CGCMs) generally simulate vertical tracer transport by deep convection separately from the advective transport by the mean winds, even though a component of the mean transport, for instance in the Hadley and Walker cells, occurs in deep convective updrafts. This split treatment of vertical transport has various implications for CTM simulations. In particular, it has led to a misinterpretation of several sensitivity simulations in previous studies in which the parameterized convective transport of one or more tracers is neglected. We describe this issue in terms of simulated fluxes and fractions of these fluxes representing various physical and non-physical processes. We then show that there is a significant overlap between the convective and large-scale mean advective vertical air mass fluxes in the CTM MATCH, and discuss the implications which this has for interpreting previous and future sensitivity simulations, as well as briefly noting other related implications such as numerical diffusion.

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