Wavelet Entropy Energy Measure (WEEM): A multiscale measure to grade a geophysical system's predictability

<p>Model-free gradation of predictability of a geophysical system is essential to quantify how much inherent information is contained within the system and evaluate different forecasting methods' performance to get the best possible prediction. We conjecture that Multiscale Information enclosed in a given geophysical time series is the only input source for any forecast model. In the literature, established entropic measures dealing with grading the predictability of a time series at multiple time scales are limited. Therefore, we need an additional measure to quantify the information at multiple time scales, thereby grading the predictability level. This study introduces a novel measure, Wavelet Entropy Energy Measure (WEEM), based on Wavelet entropy to investigate a time series's energy distribution. From the WEEM analysis, predictability can be graded low to high. The difference between the entropy of a wavelet energy distribution of a time series and entropy of wavelet energy of white noise is the basis for gradation. The metric quantifies the proportion of the deterministic component of a time series in terms of energy concentration, and its range varies from zero to one. One corresponds to high predictable due to its high energy concentration and zero representing a process similar to the white noise process having scattered energy distribution. The proposed metric is normalized, handles non-stationarity, independent of the length of the data. Therefore, it can explain the evolution of predictability for any geophysical time series (ex: precipitation, streamflow, paleoclimate series) from past to the present. WEEM metric's performance can guide the forecasting models in getting the best possible prediction of a geophysical system by comparing different methods. </p>

Geological and geophysical system “tectonics-seismicity” of the unique Khailinsk center of high-magnet swarm. South-west of the Koryak seismic belt

Хаилинский центр уникальное явление в Корякском сейсмическом поясе, который обрамляет на севере литосферную плиту Берингию. Он создан роем Хаилинского и Олюторского землетрясений и афтершоков с М 5,07,6. Центр лежит в погруженной глыбе литосферы Олюторского залива, созданной межглыбовыми СЗ разломами на бортах трога с глубиной 82 км в рельефе литосферы. На трог надвинуты морские террейны с максимальным прогибом горизонтов литосферы в их килях, через которые проходит колонна с гипоцентрами землетрясений. Высокомагнитудный рой землетрясений Хаилинского Центра имеет взаимно ортогональные эллипсы афтершоков при общих эпицентрах главных толчков. Хаилинское землетрясение не проявило традиции связи эллипса релаксации афтершоков с известной геологией афтершоков в плане и разрезе. События столь мощные, не увязанные с очевидной геологической структурой представляются очевидной новинкой в мировой горнодобывающей практике. Анализ Хаилинского и Олюторского событий выявил коллизию двух фактов: совпадение эпицентров и полную ортогональность облаков обоих землетрясений. Их исследование как элементов одной системы тектоника-сейсмичность определило геологическое пространство положения гипоцентров. Интерес к сейсмичности Хаилинского высокомагнитудного центра рассматривается как обращение в геологии окраины к уникальной малой литосферной плите Берингия в сейсмологии СВ Азии. В основу исследования системы тектоника-сейсмичность положена концепция сейсмогенной тектоники территории активной окраины континента СВ Азии и места в ней Хаилинского Центра высокомагнитудного роя (ХВЦ). Основы такого понимания сейсмичности окраины территории тектоники определены авторской Концепцией глыбово-клавишной структуры литосферы на активной окраине континента . Эпицентральная область Хаилинского и Олюторского землетрясений локализуется на площади локальной Тылговаямской впадины, причленённой к Вывенской впадине с юга на её висячем ЮВ крыле зоны Вывенского разлома The Khailinsk Center is a unique phenomenon in the Koryak seismic belt, which frames the Beringia lithospheric plate in the north. It was created by a swarm of Khailinsk and Olyutorsk earthquakes and aftershocks with M 5.07.6. The center lies in a submerged block of the lithosphere of the Olyutor Bay, created by interblock northwestern faults on the sides of the trough with a depth of 82 km in the relief of the lithosphere. Sea terranes with a maximum deflection of the lithosphere horizons in their keels, through which a column with earthquake hypocenters passes, are thrust onto the trough. The high-magnitude swarm of earthquakes of the Khailinsk Center has mutually orthogonal ellipses of aftershocks at common epicenters of the main shocks. The Khaili earthquake did not show the tradition of connecting the aftershock relaxation ellipse with the known aftershock geology in plan and section. Such powerful events that are not tied to an obvious geological structure seem an obvious novelty in world mining practice. An analysis of the Khailinsk and Olyutor events revealed a collision of two facts: the coincidence of the epicenters and the complete orthogonality of the clouds of both earthquakes. Their study as elements of one system tectonics-seismicity determined the geological space of the hypocenters position. The interest in the seismicity of the Khailinsk high-magnitude center is considered as an appeal in the geology of the outskirts to the unique small lithospheric plate Beringia in the seismology of NE Asia. The research basis of the tectonics-seismicity system is the concept of seismogenic tectonics in the territory of the active margin of the North Asian continent and the place of the Khailinsk Center for High Magnitude Swarm (KHC). The basics of such understanding of the seismicity in the outskirts of the territory tectonics are determined by the authors Concept of the block-key structure of the lithosphere on the active outskirts of the continent. The epicentral region of the Khailinsk and Olyutorsk earthquakes is localized on the area of the local Tylgovyamsk Depression, connected to the Vyvensk Depression from the south on its hanging SE wing of the Vyvensk Fault zone

IAMAS: a century of international cooperation in atmospheric sciences

The International Association of Meteorology and Atmospheric Sciences (IAMAS) was founded in 1919 as the Section of Meteorology of the International Union of Geodesy and Geophysics (IUGG). Significant advances over human history, particularly during the 19th century, in the gathering, communication, assembly and analysis of observations of the changing weather and in theoretical understanding of the fundamental physical relationships and processes governing atmospheric circulation had been driven by the need for improved weather and climate forecasts to support the expansion of global trade, better public warnings of extreme weather, and safer and more effective military operations. Since its foundation, in parallel and cooperation with intergovernmental development under the auspices of what is now the World Meteorological Organization (WMO), IAMAS and its 10 international commissions have provided the international organizational framework for the convening of the general and scientific assemblies and other meetings that bring together expert scientists from around the world to further advance scientific understanding and prediction of the behaviour of the atmosphere and its connections to and effects on other components of the Earth's intercoupled geophysical system.

Estimating the state of a geophysical system with sparse observations: time delay methods to achieve accurate initial states for prediction

The problem of forecasting the behavior of a complex dynamical system through analysis of observational time-series data becomes difficult when the system expresses chaotic behavior and the measurements are sparse, in both space and/or time. Despite the fact that this situation is quite typical across many fields, including numerical weather prediction, the issue of whether the available observations are "sufficient" for generating successful forecasts is still not well understood. An analysis by Whartenby et al. (2013) found that in the context of the nonlinear shallow water equations on a β plane, standard nudging techniques require observing approximately 70 % of the full set of state variables. Here we examine the same system using a method introduced by Rey et al. (2014a), which generalizes standard nudging methods to utilize time delayed measurements. We show that in certain circumstances, it provides a sizable reduction in the number of observations required to construct accurate estimates and high-quality predictions. In particular, we find that this estimate of 70 % can be reduced to about 33 % using time delays, and even further if Lagrangian drifter locations are also used as measurements.

Geophysical fluid dynamics: whence, whither and why?

This article discusses the role of geophysical fluid dynamics (GFD) in understanding the natural environment, and in particular the dynamics of atmospheres and oceans on Earth and elsewhere. GFD, as usually understood, is a branch of the geosciences that deals with fluid dynamics and that, by tradition, seeks to extract the bare essence of a phenomenon, omitting detail where possible. The geosciences in general deal with complex interacting systems and in some ways resemble condensed matter physics or aspects of biology, where we seek explanations of phenomena at a higher level than simply directly calculating the interactions of all the constituent parts. That is, we try to develop theories or make simple models of the behaviour of the system as a whole. However, these days in many geophysical systems of interest, we can also obtain information for how the system behaves by almost direct numerical simulation from the governing equations. The numerical model itself then explicitly predicts the emergent phenomena—the Gulf Stream, for example—something that is still usually impossible in biology or condensed matter physics. Such simulations, as manifested, for example, in complicated general circulation models, have in some ways been extremely successful and one may reasonably now ask whether understanding a complex geophysical system is necessary for predicting it. In what follows we discuss such issues and the roles that GFD has played in the past and will play in the future.