75 research outputs found
Dansgaard-Oeschger events: tipping points in the climate system
Dansgaard-Oeschger events are a prominent mode of variability in the records
of the last glacial cycle. Various prototype models have been proposed to
explain these rapid climate fluctuations, and no agreement has emerged on which
may be the more correct for describing the paleoclimatic signal. In this work,
we assess the bimodality of the system reconstructing the topology of the
multi--dimensional attractor over which the climate system evolves. We use
high-resolution ice core isotope data to investigate the statistical properties
of the climate fluctuations in the period before the onset of the abrupt
change. We show that Dansgaard-Oeschger events have weak early warning signals
if the ensemble of events is considered. We find that the statistics are
consistent with the switches between two different climate equilibrium states
in response to a changing external forcing (e.g. solar, ice sheets...), either
forcing directly the transition or pacing it through stochastic resonance.
These findings are most consistent with a model that associates
Dansgaard-Oeschger with changing boundary conditions, and with the presence of
a bifurcation point.Comment: Final typeset version freely available at: Clim. Past, 9, 323-333,
2013 www.clim-past.net/9/323/2013/ doi:10.5194/cp-9-323-201
A reappraisal of the thermal growing season length across Europe
Growing season length (GSL) indices derived from surface air temperature are frequently used in climate monitoring applications. The widely used Expert Team on Climate Change Detection and Indices (ETCCDI) definition aims to give a broadly applicable measure of the GSL that is indicative of the duration of the mild part of the year. In this paper longâterm trends in that index are compared with an alternative measure calculated using a time series decomposition technique (empirical ensemble mode decomposition [EEMD]). It is demonstrated that the ETCCDI index departs from the mildâseason definition as its start and end dates are determined by temperature events operating within the synoptic timescale; this raises the interâannual variance of the index. The EEMDâderived index provides a less noisy and more realistic index of the GSL by filtering out the synopticâscale variance and capturing the annualâcycle and longer timescale variability. Longâterm trends in the GSL are comparable between the two indices, with an average increase in length of around 5 days/decade observed for the period 1965â2016. However, the results using the EEMD index display a more coherent picture of significant trends than has been previously observed. Furthermore, the EEMDâderived growing season parameters are more closely related to variations in seasonalâmean hemisphericâscale atmospheric circulation patterns, with around 57% of the interâannual variation in the start of the growing season being connected to the North Atlantic Oscillation and East Atlantic patterns, and around 55% of variation in the end of the growing season being associated with East Atlantic/west Russiaâtype patterns
Surface wind over Europe: Data and variability
This work improves the characterization and knowledge of the surface wind climatology over Europe with the development of an observational database with unprecedented quality control (QC), the European Surface Wind Observational database (EuSWiO). EuSWiO includes more than 3,829 stations with sub-daily resolution for wind speed and direction, with a number of sites spanning the period of 1880â2017, a few hundred time series starting in the 1930s and relatively good spatial coverage since the 1970s. The creation of EuSWiO entails the merging of eight different data sets and its submission to a common QC. About 5% of the total observations were flagged, correcting a great part of the extreme and unrealistic values, which have a discernible impact on the statistics of the database. The daily wind variability was characterized by means of a classification technique, identifying 11 independent subregions with distinct temporal wind variability over the 2000â2015 period. Significant decreases in the wind speed during this period are found in five regions, whereas two regions show increases. Most regions allow for extending the analysis to earlier decades. Caution in interpreting long-term trends is needed as wind speed data have not been homogenized. Nevertheless, decreases in the wind speed since the 1980s can be noticed in most of the regions. This work contributes to a deeper understanding of the temporal and spatial surface wind variability in Europe. It will allow from meteorological to climate and climate change studies, including potential applications to the analyses of extreme events, wind power assessments or the evaluation of reanalysis or model-data comparison exercises at continental scales
Linking Unserved Energy to Weather Regimes
The integration of renewable energy sources into power systems is expected to
increase significantly in the coming decades. This can result in critical
situations related to the strong variability in space and time of weather
patterns. During these critical situations the power system experiences a
structural shortage of energy across multiple time steps and regions, leading
to Energy Not Served (ENS) events. Our research explores the relationship
between six weather regimes that describe the large scale atmospheric flow and
ENS events in Europe by simulating future power systems. Our results indicate
that most regions have a specific weather regime that leads to the highest
number of ENS events. However, ENS events can still occur during any weather
regime, but with a lower probability.
In particular, our findings show that ENS events in western and central
European countries often coincide with either the positive Scandinavian
Blocking (SB+), characterised by cold air penetrating Europe under calm weather
conditions from north-eastern regions, or North Atlantic Oscillation (NAO+)
weather regime, characterised by westerly flow and cold air in the southern
half of Europe. Additionally, we found that the relative impact of one of these
regimes reaches a peak 10 days before ENS events in these countries. In
Scandinavian and Baltic countries, on the other hand, our results indicate that
the relative prevalence of the negative Atlantic Ridge (AR-) weather regime is
higher during and leading up to the ENS event.Comment: Rogier H. Wuijts and Laurens P. Stoop contributed equally to this
wor
Building long homogeneous temperature series across Europe: a new approach for the blending of neighboring series
Long and homogeneous series are a necessary requirement for reliable climate analysis. Relocation of measuring equipment from one station to another, such as from the city center to a rural area or a nearby airport, is one of the causes of discontinuities in these long series which may affect trend estimates. In this paper an updated procedure for the composition of long series, by combining data from nearby stations, is introduced. It couples an evolution of the blending procedure already implemented within the European Climate Assessment and Dataset (which combines data from stations no more than 12.5 km apart from each other) with a duplicate removal, alongside the quantile matching homogenization procedure. The ECA&D contains approximately 3000 homogenized series for each temperature variable prior to the blending procedure, around 820 of these are longer than 60 years; the process of blending increases the number of long series to more than 900. Three case studies illustrate the effects of the homogenization on single blended series, showing the effectiveness of separate adjustments on extreme and mean values (Geneva), on cases where blending is complex (Rheinstetten) and on series which are completed by adding relevant portions of GTS synoptic data (Siauliai). Finally, a trend assessment on the whole European continent reveals the removal of negative and very large trends, demonstrating a stronger spatial consistency. The new blended and homogenized data-set will allow a more reliable use of temperature series for indices calculation and for the calculation of gridded data-sets, and will be available for users on www.ecad.eu
A multidecadal assessment of climate indices over Europe
Monitoring and management of several environmental and socioeconomic sectors require climate data that can be summarized using a set of standard and meaningful climate metrics. This study describes a newly developed gridded dataset for the whole of Europe, which employed a set of 125 climate indices spanning different periods based on data availability, but mainly 1950â2017 and 1979â2017. This dataset comprehensively summarizes climate variability in Europe for a wide range of climate variables and conditions, including air temperature, precipitation, biometeorology, aridity, continentality, drought, amongst others. Climate indices were computed at different temporal scales (i.e. monthly, seasonal and annual) and mapped at a grid interval of 0.25°. We intend to update these indices on an annual basis. This dataset is freely available to research and end-user communities
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