Intraseasonal teleconnections leading to heat waves in central Chile

Author(s):  
Martín Jacques‐Coper ◽  
Daniel Veloso‐Aguila ◽  
Christian Segura ◽  
Amanda Valencia
Keyword(s):  
2021 ◽  
Author(s):  
Martín Jacques-Coper ◽  
Alan Demortier ◽  
Deniz Bozkurt

<p>This study explores the main drivers of heat wave (HW) events in central Chile using state-of-the-art reanalysis data (ERA5) and observations during the extended austral summer season (November to March) for the period 1979-2018. Frequency and intensity aspects of the HW events are considered using the total number of HW events per season and the amplitude, respectively. We first contrast ERA5 with several surface meteorological stations in central Chile to evaluate its ability to capture daily maximum temperature variability and the HW events. We then use synoptic- and large-scale fields and teleconnection patterns to address the most favorable conditions of the HW events from a climatological perspective, as well as for the extreme January 2017 HW event that swept central Chile with temperature records and wildfires. ERA5 tends to capture temperature extremes and the HW events at the inland stations; on the contrary, it has difficulties in capturing the maximum temperature variability at the coastal stations, which is plausible given the complex terrain features and confined coastal climate zone (only ~7% of all grid boxes within central Chile). The HW composite based on ERA5 reveals a mid-level trough-ridge dipole pattern exhibiting a blocking anticyclone on the surface over a large part of southwest South America. Relatively dry and warm easterly flow appears to accompany the anomalous warming in a large part of central Chile. The temporal evolution of the HW events yields a wave-like propagation pattern and enhancement of trough-ridge pattern along the South Pacific. This meridional dipole pattern is found to be largely associated with the Pacific South American pattern. In addition, the Madden-Julian Oscillation (MJO) appears to be a key component of the HW events in central Chile. In particular, while active MJO phases 2 and 7 promote sub-seasonal patterns that favor the South Pacific dipole mode, synoptic anomalies can superimpose on them and favor the formation of a migrating anticyclone over central-southern Chile and coastal lows over central Chile. Agreeing with the climatological findings, the extreme January 2017 HW analysis suggests that an eastward migratory mid-latitude trough-ridge pattern associated with the MJO phase 2 was at work. We highlight that, in addition to large- and synoptic-scale features, sub-synoptic processes such as coastal lows can have an important role in shaping the HW events and can lead to amplification of temperature extremes during the HW events.</p>


2021 ◽  
Author(s):  
Alan Demortier ◽  
Deniz Bozkurt ◽  
Martín Jacques-Coper

2020 ◽  
Vol 82 ◽  
pp. 149-160
Author(s):  
N Kargapolova

Numerical models of the heat index time series and spatio-temporal fields can be used for a variety of purposes, from the study of the dynamics of heat waves to projections of the influence of future climate on humans. To conduct these studies one must have efficient numerical models that successfully reproduce key features of the real weather processes. In this study, 2 numerical stochastic models of the spatio-temporal non-Gaussian field of the average daily heat index (ADHI) are considered. The field is simulated on an irregular grid determined by the location of weather stations. The first model is based on the method of the inverse distribution function. The second model is constructed using the normalization method. Real data collected at weather stations located in southern Russia are used to both determine the input parameters and to verify the proposed models. It is shown that the first model reproduces the properties of the real field of the ADHI more precisely compared to the second one, but the numerical implementation of the first model is significantly more time consuming. In the future, it is intended to transform the models presented to a numerical model of the conditional spatio-temporal field of the ADHI defined on a dense spatio-temporal grid and to use the model constructed for the stochastic forecasting of the heat index.


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