Circulations atmosphériques et anomalies de fonte à la surface de la calotte glaciaire du Groenland

peer reviewedWith the aim to study the impact of the 500hPa general circulation on the Greenland ice sheet surface melt simulated by the regional climate model MAR, we developed a new Circulation Type Classification (CTC) based on the 500hPa geopotential height from the ECMWF (re)analysis over the period 1958-2007. This CTC shows that the dominant mode of the regional atmospheric variability around the Greenland is linked to the North Atlantic Oscillation (NAO) and that the surface anomalies are highly correlated to the general circulation. It explains also why a record surface melt was observed during the summer 2007. The 27th August of 2003, where the temperature was 10°C higher than the normal, is the consequence of an almost unique 500 hPa circulation in the 50 last years.Pour étudier les impacts de la circulation atmosphérique à 500hPa sur la fonte estivale à la surface de la calotte du Groenland simulée par le modèle du climat MAR, nous avons mis au point une nouvelle classification automatique des types de circulations atmosphériques appliquée à la période qui s'étend de 1958 à 2007. Cette classification, basée sur la hauteur géopotentielle à 500hPa issue des (ré)analyses du Centre Européen, permet de montrer que le mode dominant de la variabilité atmosphérique au Groenland est lié à l'Oscillation Nord-Atlantique (NAO) et que la fonte à la surface de la calotte est hautement corrélée à la circulation générale. Cette classification explique pourquoi une fonte record fut enregistrée durant l'été 2007. De même, le caractère exceptionnel du 27 août 2003, où la température moyenne au Groenland était près de 10°C supérieure à la moyenne 1958-2007, est clairement une conséquence d'une circulation à 500hPa presque unique durant les 50 dernières années de l'histoire climatique du Groenland

Automatic 1958-2007 daily weather pattern classification applied to an analysis of climatic conditions of wildfires in eastern Belgium

The daily atmospheric circulation patterns classification is founded on a 100 km regular grid centred on Belgium. The geopotential heights of 500, 850 and 1000 hPa levels were extracted from the ERA-40 database on the period 1958-2002 and from ECMWF operational analysis until the end of year 2007. The classification was based on a similarity index calculated on the orientation of exaggerated slopes of different daily geopotential fields. Wildfire occurrences were analyzed in April and September (which are the two months with the most frequent wildfire-days in Belgium) together with monthly frequencies and persistences of daily atmospheric circulation pattern classes as well as with yearly variability of weather climate conditions.CEC- DG12-SRD- Wildfires modelisation - Contract nr EV5V-CT91-001

Wavelet-Induced Mode Extraction procedure: Application to climatic data

The Wavelet-Induced Mode Extraction procedure (WIME) was developed drawing inspiration from Empirical Mode Decomposition. The concept involves decomposing the signal into modes, each presenting a characteristic frequency, using continuous wavelet transform. This method has yielded intriguing results in climatology. We improved the algorithm to take into account new parameters (noise, concavity, permissive zone evolution, border effects) and applied it to several climate signals. This version applied to ONI yields to impressive results: we detect 6 main periods and reconstruct the signal with a 94% correlation. This correlation grows as the niño/niña event gets stronger.13. Climate actio

The 1958–2009 Greenland ice sheet surface melt and the mid-tropospheric atmospheric circulation

peer reviewedaudience: researcherIn order to assess the impact of the mid-tropospheric circulation over the Greenland ice sheet (GrIS) on surface melt, as simulated by the regional climate model MAR, an automatic Circulation type classification (CTC) based on 500 hPa geopotential height from reanalyses is developed. General circulation correlates significantly with the surface melt anomalies for the summers in the period 1958–2009. The record surface melt events observed during the summers of 2007–2009 are linked to the exceptional persistence of atmospheric circulations favouring warm air advection. The CTC emphasizes that summer 500 hPa circulation patterns have changed since the beginning of the 2000s; this process is partly responsible for the recent warming observed over the GrIS

Analyse de la variabilité naturelle du climat : application à l’aide des ondelettes

Ce travail a pour but de mettre en évidence des cycles méconnus et cachés de la transformée de Fourier dans les séries temporelles liées au climat. Les périodes recherchées, à l’aide de l’outil ondelettes développé à l’Institut de Mathématique de l’Université de Liège, sont de l’ordre de quelques dizaines de mois

Étude fréquentielle de données via la transformée en ondelette : application aux cycles climatiques

Understanding the climate requires a complex study of time series connected to weather parameters. The climatologist frequently applies signal processing tools and often uses the harmonic analysis and the Fourier transform. This article is dedicated to the description of a new tool, elaborated by mathematicians, which completes the outfit of intruments intended for signal analysis. The scale spectrum, which synthetizes a part of the information supplied by the wavelet transform, possesses the property to reveal pseudo-cycles which evolves around an average period. When applied to air surface temperature time series obtained from more than one hundred weather stations, to reanalysis data and to climatic indices which characterize the tropospheric flows, the wavelet transforms and the scale spectra reveal cycles with periods close to 30 months and 42 months. The Solar parameters analysis also leads to the existence of pseudo-cycles with frequencies corresponding to those found in the temperature time series and climatic indices.La compréhension du climat nécessite une étude approfondie des séries temporelles des paramètres du temps qui ont été mesurés dans le passé. Le climatologue recourt aux techniques du traitement du signal et il utilise souvent l’analyse harmonique et la transformée de Fourier. Cet article est consacré à la description d’un nouvel outil, élaboré par les mathématiciens, qui complète la panoplie d’instruments destinés à l’analyse du signal. Le spectre d’échelle, qui synthétise une partie de l’information fournie par la transformée en ondelette, possède la propriété de déceler des cycles dont la période évolue, dans le temps, de part et d’autre d’une période moyenne. Appliqué aux séries temporelles de températures de surface de l’air mesurées dans une centaine de stations météorologiques, aux données proposées par les réanalyses et aux principaux indices climatiques qui caractérisent les flux troposphériques, le spectre d’échelle a révélé des cycles dont les périodes sont proches de 30 et de 42 mois. L’analyse des données relatives à l’activité solaire conclut également à la présence de cycles dont les fréquences correspondent à celles relevées dans les séries de données de températures et dans celles des indices du climat

Multi-Months Cycles Observed in Climatic Data

Climatic variations happen at all time scales and since the origins of these variations are usually of very complex nature, climatic signals are indeed chaotic data. The identification of the cycles induced by the natural climatic variability is therefore a knotty problem, yet the knowing of these cycles is crucial to better understand and explain the climate (with interests for weather forecasting and climate change projections). Due to the non-stationary nature of the climatic time series, the simplest Fourier-based methods are inefficient for such applications (see e.g. Titchmarsh (1948)). This maybe explains why so few systematic spectral studies have been performed on the numerous datasets allowing to describe some aspects of the climate variability (e.g. climatic indices, temperature data). However, some recent studies (e.g. Matyasovszky (2009); Paluš & Novotná (2006)) show the existence of multi-year cycles in some specific climatic data. This shows that the emergence of new tools issued from signal analysis allows to extract sharper information from time series. Here, we use a wavelet-based methodology to detect cycles in air-surface temperatures obtained from worldwide weather stations, NCEP/NCAR reanalysis data, climatic indices and some paleoclimatic data. This technique reveals the existence of universal rhythms associated with the periods of 30 and 43 months. However, these cycles do not affect the temperature of the globe uniformly. The regions under the influence of the AO/NAO indices are influenced by a 30 months period cycle, while the areas related to the ENSO index are affected by a 43 months period cycle; as expected, the corresponding indices display the same cycle. We next show that the observed periods are statistically relevant. Finally, we consider some mechanisms that could induce such cycles. This chapter is based on the results obtained in Mabille & Nicolay (2009); Nicolay et al. (2009; 2010)

A statistical validation for the cycles found in air temperature data using a Morlet wavelet-based method

Recently, new cycles, associated with periods of 30 and 43 months, respectively, have been observed by the authors in surface air temperature time series, using a wavelet-based methodology. Although many evidences attest the validity of this method applied to climatic data, no systematic study of its efficiency has been carried out. Here, we estimate confidence levels for this approach and show that the observed cycles are significant. Taking these cycles into consideration should prove helpful in increasing the accuracy of the climate model projections of climate change and weather forecast

Multy-year cycles observed in air temperature data and proxy series

First, palaeoclimatic time series are analyzed under the lens of the continuous wavelet transform. Two cycles, of period 30 and 43 months respectively, are detected in millennial temperature reconstructions. These rhythms correspond to the ones detected in weather station temperature records in a previous study of the authors. It is then showed that most parts of the globe are affected by at least one of the two cycles. Their relationship with the main climatic indices is also investigated, as well as the statistical significance of the observations