Persistent Anomaly Changes in High-Resolution Climate Simulations

Persistent anomalies (PAs) are associated with a variety of impactful weather extremes, prompting research into how their characteristics will respond to climate change. Previous studies, however, have not provided conclusive results, owing to the complexity of the phenomenon and to difficulties in general circulation model (GCM) representations of PAs. Here, we diagnose PA activity in ten years of current and projected future output from global, high-resolution (15-km mesh) time-slice simulations performed with the Model for Prediction Across Scales-Atmosphere (MPAS-A). These time slices span a range of ENSO states. They include high-resolution representations of sea-surface temperatures and GCM-based sea ice for present and future climates. Future projections, based on the RCP8.5 scenario, exhibit strong Arctic amplification and tropical upper warming, providing a valuable experiment with which to assess the impact of climate change on PA frequency. The MPAS-A present-climate simulations reproduce the main centers of observed PA activity, but with an eastward shift in the North Pacific and reduced amplitude in the North Atlantic. The overall frequency of positive PAs in the future simulations is similar to that in the present-day simulations, while negative PAs become less frequent. Although some regional changes emerge, the small, generally negative changes in PA frequency and meridional circulation index indicate that climate change does not lead to increased persistence of midlatitude flow anomalies or increased waviness in these simulations.

On spatial patterns of heat waves and cold spells from a large deviations perspective

<p></p><div> <div> <div><span>We analyse persistent temperature events, like heat waves or cold spells, by applying large deviation theory (LDT), and show that events with a long duration have also a substantial spatial extension. We point out that by using LDT one finds typical spatial patterns related to the persistent temperature extremes. Based on the output of a state-of-the-art climate model, we define the climatology of persistent heatwaves and cold spells in some key target regions of the planet by constructing empirically the corresponding rate functions for the surface temperature, and we assess the impact of increasing CO</span><sub>2</sub><span> concentration on such persistent anomalies. In particular, we notice the increasing hazard associated to heatwaves in a warmer climate. We show that two 2010 high impact events - summer Russian heatwave and winter Dzud in Mongolia – are associated with extended atmospheric patterns that are exceptional compared to the typical ones, but typical compared to the climatology of extreme events.</span></div> </div> </div>

Windows of Opportunity for Skillful Forecasts Subseasonal to Seasonal and Beyond

There is high demand and a growing expectation for predictions of environmental conditions that go beyond 0–14-day weather forecasts with outlooks extending to one or more seasons and beyond. This is driven by the needs of the energy, water management, and agriculture sectors, to name a few. There is an increasing realization that, unlike weather forecasts, prediction skill on longer time scales can leverage specific climate phenomena or conditions for a predictable signal above the weather noise. Currently, it is understood that these conditions are intermittent in time and have spatially heterogeneous impacts on skill, hence providing strategic windows of opportunity for skillful forecasts. Research points to such windows of opportunity, including El Niño or La Niña events, active periods of the Madden–Julian oscillation, disruptions of the stratospheric polar vortex, when certain large-scale atmospheric regimes are in place, or when persistent anomalies occur in the ocean or land surface. Gains could be obtained by increasingly developing prediction tools and metrics that strategically target these specific windows of opportunity. Across the globe, reevaluating forecasts in this manner could find value in forecasts previously discarded as not skillful. Users’ expectations for prediction skill could be more adequately met, as they are better aware of when and where to expect skill and if the prediction is actionable. Given that there is still untapped potential, in terms of process understanding and prediction methodologies, it is safe to expect that in the future forecast opportunities will expand. Process research and the development of innovative methodologies will aid such progress.

A New Variable-Threshold Persistent Anomaly Index: Northern Hemisphere Anomalies in the ERA-Interim Reanalysis

Persistent weather regimes characterized by anomalous temperature or precipitation are often associated with persistent anomalies (PAs) in the tropospheric geopotential height field. To identify PAs throughout the annual cycle, an earlier definition is modified to apply a seasonally varying magnitude threshold, based on a smoothed, daily varying climatological average of daily 500-hPa geopotential height variability. The modified index can be applied to a wide variety of analysis, reanalysis, or model-forecast gridded data. Here, the modified PA index is used to identify positive and negative Northern Hemisphere PAs in all seasons and to compute trends in PA frequency, strength, location, and duration, in the ECMWF ERA-Interim reanalysis dataset (1979–2016). Height data are detrended and anomalies are weighted with an inverse sine-of-latitude function. In addition to maxima in PA frequency identified previously (North Pacific, North Atlantic, and Russia), an additional summertime maximum appears in the Arctic; this feature has not been analyzed extensively. A composite of summertime positive Arctic PA events reveals an equivalent barotropic structure, similar to that documented for midlatitude PAs. Arctic PA frequency is greatest in summer; it exhibits no trend in frequency over the 38-yr ERA-Interim analysis period. In fact, no discernable trends in PA frequency, strength, or duration are evident in the analysis period for the primary PA regions, although there is a suggestion of a northward shift in positive PA activity in the North Pacific.

Relative distances between homology groups to assess persistent defects in time series

It is common to consider a data-intensive strategy to be an appropriate way to develop systemic analyses in biology and physiology. Therefore, options for data collection, sampling, standardization, visualization, and interpretation determine how causes are identified in time series to build mathematical models. However, there are often biases in the collected data that can affect the validity of the model: while collecting enough large datasets seems to be a good strategy for reducing the bias of the collected data, persistent and dynamical anomalies in the data structure can affect the overall validity of the model. In this work we present a methodology based on the definition of homological groups to evaluate persistent anomalies in the structure of the sampled time series. In this evaluation relevant patterns in the combination of different time series are clustered and grouped to customize the identification of causal relationships between parameters. We test this methodology on data collected from patients using mobile sensors to test the response to physical exercise in real-world conditions and outside the lab. With this methodology we plan to obtain a patient stratification of the time series to customize models in medicine.

A Lottery-Demand-Based Explanation of the Beta Anomaly

The low (high) abnormal returns of stocks with high (low) beta, which we refer to as the beta anomaly, is one of the most persistent anomalies in empirical asset pricing research. This article demonstrates that investors’ demand for lottery-like stocks is an important driver of the beta anomaly. The beta anomaly is no longer detected when beta-sorted portfolios are neutralized to lottery demand, regression specifications control for lottery demand, or factor models include a lottery demand factor. The beta anomaly is concentrated in stocks with low levels of institutional ownership and it exists only when the price impact of lottery demand is concentrated in high-beta stocks.

CHANGES IN BACKGROUND CONCENTRATIONS OF METALS IN THE SEDIMENTS OF MARSH-LAGOON LANDSCAPES OF THE WESTERN CASPIAN

The last 1978-1995 transgression of the Caspian Sea caused the development of marsh-lagoon system along the Western Caspian seashore. Due to salt marshes are very vulnerable to sea-level fluctuations, complex and dynamic system, they may be considered as a regional model of rapid environmental transformation. Changing conditions of migration in the soils of marsh-lagoon landscapes during the sea-level rise influenced on the migration of elements of variable valency, primarily Fe and Mn, but also Zn, Cu, Pb, Ni, Co, leading to their mobilization in slightly alkaline and neutral reducing conditions and subsequent deposition on the geochemical barriers. That led to the emergence of landscape-geochemical anomalies of Fe and heavy metals in the soils of salt marshes with a characteristic time of formation of any persistent anomalies during 5-10 years.

CHANGES IN BACKGROUND CONCENTRATIONS OF METALS IN THE SEDIMENTS OF MARSH-LAGOON LANDSCAPES OF THE WESTERN CASPIAN

The last 1978-1995 transgression of the Caspian Sea caused the development of marsh-lagoon system along the Western Caspian seashore. Due to salt marshes are very vulnerable to sea-level fluctuations, complex and dynamic system, they may be considered as a regional model of rapid environmental transformation. Changing conditions of migration in the soils of marsh-lagoon landscapes during the sea-level rise influenced on the migration of elements of variable valency, primarily Fe and Mn, but also Zn, Cu, Pb, Ni, Co, leading to their mobilization in slightly alkaline and neutral reducing conditions and subsequent deposition on the geochemical barriers. That led to the emergence of landscape-geochemical anomalies of Fe and heavy metals in the soils of salt marshes with a characteristic time of formation of any persistent anomalies during 5-10 years.

The Role of Standing Waves in Driving Persistent Anomalies of Upward Wave Activity Flux

Northern Hemisphere stratospheric polar vortex strength variability is known to be largely driven by persistent anomalies in upward wave activity flux. It has also been shown that attenuation and amplification of the stationary wave is the primary way in which wave activity flux varies. This study determines the structure of the wave anomalies that interfere with the climatological wave and drive this variability. Using a recently developed spectral decomposition it is shown that fixed-node standing waves are the primary drivers of the “linear interference” phenomenon. This is particularly true for the low-frequency component of the upward wave activity flux. The linear part of the flux is shown to be more persistent than the total flux and has significant tropospheric standing wave precursors that lead changes in the strength of the stratospheric polar vortex. Evidence is presented that current-generation high-top climate models are able to credibly simulate this variability in wave activity fluxes and the connection to polar vortex strength. Finally, the precursors to displacement and split sudden stratospheric warmings are examined. Displacement events are found to be preceded by about 25 days of anomalously high upward wave activity flux forced by standing waves amplifying the climatology. Split events have more short-lived wave activity flux precursors, which are dominated by the nonlinear part of the flux.