Seasonal predictions based on two dynamical models

Abstract

Two dynamical models are used to perform a series of seasonal predictions. One model, referred to as GCM2, was designed as a general circulation model for climate studies, while the second one, SEF, was designed for numerical weather prediction. The seasonal predictions cover the 26‐year period 1969–1994. For each of the four seasons, ensembles of six forecasts are produced with each model, the six runs starting from initial conditions six hours apart. The sea surface temperature (SST) anomaly for the month prior to the start of the forecast is persisted through the three‐month prediction period, and added to a monthly‐varying climatological SST field.

The ensemble‐mean predictions for each of the models are verified independently, and the two ensembles are blended together in two different ways: as a simple average of the two models, denoted GCMSEF, and with weights statistically determined to minimize the mean‐square error (the Best Linear Unbiased Estimate (BLUE) method).

The GCMSEF winter and spring predictions show a Pacific/North American (PNA) response to a warm tropical SST anomaly. The temporal anomaly correlation between the zero‐lead GCMSEF mean‐seasonal predictions and observations of the 500‐hPa height field (Z₅₀₀) shows statistically significant forecast skill over parts of the PNA area for all seasons, but there is a notable seasonal variability in the distribution of the skill. The GCMSEF predictions are more skilful than those of either model in winter, and about as skilful as the better of the two models in the other seasons.

The zero‐lead surface air temperature GCMSEF forecasts over Canada are found to be skilful (a) over the west coast in all seasons except fall, (b) over most of Canada in summer, and (c) over Manitoba, Ontario and Quebec in the fall. In winter the skill of the BLUE forecasts is substantially better than that of the GCMSEF predictions, while for the other seasons the difference in skill is not statistically significant.

When the Z₅₀₀ forecasts are averaged over months two and three of the seasons (one‐month lead predictions), they show skill in winter over the north‐eastern Pacific, western Canada and eastern North America, a skill that comes from those years with strong SST anomalies of the El Niño/La Niña type. For the other seasons, predictions averaged over months two and three show little skill in Z₅₀₀ in the mid‐latitudes. In the tropics, predictive skill is found in Z₅₀₀ in all seasons when a strong SST anomaly of the El Niño/La Niña type is observed. In the absence of SST anomalies of this type, tropical forecast skill is still found over much of the tropics in months two and three of the northern hemisphere spring and summer, but not in winter and fall.     

On forecasting abnormal climatic events in the tropical Atlantic Ocean

Modelling and observational evidence indicate that interannual variabilities of dynamic height and sea surface temperature (SST) in the eastern part of the tropical Atlantic Ocean (Gulf of Guinea) are largely induced by preceding fluctuations in wind stress, mainly in the western equatorial basin. A wind-driven linear ocean model is used here to test the possibility of forecasting the abnormal dynamic heights. A control run of the model, forced by 1964–1993 wind stress monthly means, is first conducted. Yearly test runs (1964-1994) are subsequently performed from January to August by forcing the model with observed winds from January to May, and then by forcing with the May wind assumed to persist from June to August. During the last three decades the largest deviations of dynamic height simulated by the control run in the Gulf of Guinea in boreal summer would have been correctly forecast from wind data related only to conditions in May of each year. However, for weak climatic anomalies, the model may forecast overestimated values. For the most part (about 20 times during the last 30 years), the sign of the observed SST anomaly in the centre of the Gulf of Guinea during the boreal summer is identical to the sign of simulated anomalies of dynamic height deduced from both control and test runs. Along the eastern equatorial waveguide, the sea level forecasting skill slowly decreases from the first 2 weeks of June until the second 2 weeks of August, but remains high on both sides of the equator throughout boreal summer, as is expected from the adjustment in a linear ocean model. It is established that throughout the year in the Gulf of Guinea the accuracy of the 1-month forecast dynamic height anomaly provided by the simple linear method is greater than that of the 1-month forecast assuming persistence.     

FEM × DEM modelling of cohesive granular materials: Numerical homogenisation and multi-scale simulations

The article presents a multi-scale modelling approach of cohesive granular materials, its numerical implementation and its results. At microscopic level, Discrete Element Method (DEM) is used to model dense grains packing. At the macroscopic level, the numerical solution is obtained by a Finite Element Method (FEM). In order to bridge the micro- and macro-scales, the concept of Representative Elementary Volume (REV) is applied, in which the average REV stress and the consistent tangent operators are obtained in each macroscopic integration point as the results of DEM’s simulation. In this way, the numerical constitutive law is determined through the detailed modelling of the microstructure, taking into account the nature of granular materials. We first elaborate the principle of the computation homogenisation (FEM × DEM), then demonstrate the features of our multiscale computation in terms of a biaxial compression test. Macroscopic strain location is observed and discussed.     

The international conference “Vortices and coherent structures: from ocean to microfluids”, Vladivostok,Russia, 28–31 August 2017

The international conference “Vortices and coherent structures: from ocean to microfluids” was held at the Pacific Oceanological Institute of the Russian Academy of Sciences in Vladivostok (Russia) from August 28 to August 31, 2017. The event gathered experimentalists and theoreticians, oceanographers and physicists, with a common interest in observing and modelling fluid flows in different media, from the ocean to laboratory flows. It was a fruitful idea to bring together researchers from a variety of backgrounds to benefit from a vigorous discussion of concepts across different disciplines in oceanography and hydrodynamics.

     

Analysis of the interannual variability of annual daily extreme water levels in the St Lawrence River and Lake Ontario from 1918 to 2010

We compared the interannual variability of annual daily maximum and minimum extreme water levels in Lake Ontario and the St Lawrence River (Sorel station) from 1918 to 2010, using several statistical tests. The interannual variability of annual daily maximum extreme water levels in Lake Ontario is characterized by a positive long‐term trend showing two shifts in mean (1929–1930 and 1942–1943) and a single shift in variance (in 1958–1959). In contrast, for the St Lawrence River, this interannual variability is characterized by a negative long‐term trend with a single shift in mean, which occurred in 1955–1956. As for annual daily minimum extreme water levels, their interannual variability shows no significant long‐term change in trend. However, for Lake Ontario, the interannual variability of these water levels shows two shifts in mean, which are synchronous with those for maximum water levels, and a single shift in variance, which occurred in 1965–1966. These changes in trend and stationarity (mean and variance) are thought to be due to factors both climatic (the Great Drought of the 1930s) and human (digging of the Seaway and construction of several dams and locks during the 1950s). Despite this change in means and variance, the four series are clearly described by the generalized extreme value distribution. Finally, annual daily maximum and minimum extreme water levels in the St Lawrence and Lake Ontario are negatively correlated with Atlantic multidecadal oscillation over the period from 1918 to 2010. Copyright © 2013 John Wiley & Sons, Ltd.     

Wavelet filter analysis of splitting and coupling of seismic normal modes below 1.5 mHz with superconducting gravimeter records after the December 26, 2004 Sumatra earthquake

New generation superconducting gravimeters (SGs), which have been demonstrated to be better than the best seismometers STS-1 at frequencies below 1 mHz, can be accepted as the quietest vertical seismometers for observation of long-period earth free oscillations. Wavelet filtering with narrow band-pass frequency response as shown in this paper is very helpful in removing at- mospheric pressure effects from on gravity records in long-period seismic mode frequency bands. The processing of high quality SG records after the great Sumatra earthquake (Dec. 26, 2004) with wavelet filtering leads to clear observations of all coupled toroidal modes below 1.5 mHz except these for 0T5, 0T7 and 1T1; moreover 1T2 and 1T3 are, for the first time, unambiguously revealed in the vertical components of the free oscillations. The three well-resolved splitting singlets of overtones 2S1 are observed from a single SG record for the first time.