Regime transitions of Australian climate and climate extremes

Systematic changes, since the beginning of the 20th century, in average and extreme Australian rainfall and temperatures indicate that Southern Australian climate has undergone regime transitions into a drier and warmer state. South-west Western Australia (SWWA) experienced the most dramatic drying trend with average streamflow into Perth dams, in the last decade, just 20 % of that before the 1960s and extreme, decile 10, rainfall reduced to near zero. In south-eastern Australia (SEA) systematic decreases in average and extreme cool season rainfall became evident in the late 1990s with a halving of the area experiencing average decile 10 rainfall in the early 21st century compared with that for the 20th century. The shift in annual surface temperatures over SWWA and SEA, and indeed for Australia as a whole, has occurred primarily over the last 20 years with the percentage area experiencing extreme maximum temperatures in decile 10 increasing to an average of more than 45 % since the start of the 21st century compared with less than 3 % for the 20th century mean. Average maximum temperatures have also increased by circa 1 °C for SWWA and SEA over the last 20 years. The climate changes are associated with atmospheric circulation shifts and are indicative of second order regime transitions, apart from extreme temperatures for which the dramatic increases are suggestive of first order transitions.

A study of capturing Atlantic meridional overturning circulation (AMOC) regime transition through observation-constrained model parameters

The multiple equilibria are an outstanding characteristic of the Atlantic meridional overturning circulation (AMOC) that has important impacts on the Earth climate system appearing as regime transitions. The AMOC can be simulated in different models, but the behavior deviates from the real world due to the existence of model errors. Here, we first combine a general AMOC model with an ensemble Kalman filter to form an ensemble coupled model data assimilation and parameter estimation (CDAPE) system and derive the general methodology to capture the observed AMOC regime transitions through utilization of observational information. Then we apply this methodology designed within a “twin” experiment framework with a simple conceptual model that simulates the transition phenomenon of AMOC multiple equilibria as well as a more physics-based MOC box model to reconstruct the “observed” AMOC multiple equilibria. The results show that the coupled model parameter estimation with observations can significantly mitigate the model deviations, thus capturing regime transitions of the AMOC. This simple model study serves as a guideline when a coupled general circulation model is used to incorporate observations to reconstruct the AMOC historical states and make multi-decadal climate predictions.

Assessing model performance by weather regime transitions

<p>Having the ability to stratify a model’s performance by weather type is not only beneficial to a weather forecaster when making decisions, but it is also important for end users, whether they be scientists looking to improve the model, or a customer wishing to know the value of a forecast under a specific set of circumstances.</p><p>At the MET Office, Decider is a tool which assigns a dominant weather type to a set of ensemble members, to predict the probability of a weather type occurring. The weather type is chosen from either a set of 30 or 8 sub-types, where a weather type is pre-determined objectively by clustering a 154 year record of sea level pressure anomaly fields.  </p><p>There is also a record of daily weather type classifications derived from analysis fields and so information of model performance for these weather types could be invaluable in reducing model error if combined with the predictions from Decider.</p><p>Early trials of assessing model performance by weather type revealed that larger errors occur when the weather type persisted for a single day, rather than longer timescales, and so this suggests that it would be beneficial to examine weather type transition periods.</p><p>To examine this, we expand the weather type methodology to include multiple time periods. The current methodology uses 12Z analyses to identify the weather type, and so we first assess model performance as a sensitivity study to the analysis time.</p><p>Transition days are identified when the weather type changes during a pre-defined validation period, which allows separation into either night/day weather type transitions, or a change in weather type over a full 24-hour period.</p><p>We will present early results of this work and demonstrate the impact of model performance when stratifying by regime transitions.</p>

Retroactivity induced operating regime transition in an enzymatic futile cycle

Activated phosphorylation-dephosphorylation biochemical reaction cycles are a class of enzymatic futile cycles. A futile cycle such as a single MAPK cascade governed by two underlying enzymatic reactions permits Hyperbolic (H), Signal transducing (ST), Threshold-hyperbolic (TH) and Ultrasensitive (U) operating regimes that characterize input-output behaviour. Retroactive signalling caused by load due to sequestration of phosphorylated or unphosphorylated form of the substrate in a single enzymatic cascade without explicit feedback can introduce two-way communication, a feature not possible otherwise. We systematically characterize the operating regimes of a futile cycle subject to retroactivity in either of the substrate forms. We demonstrate that increasing retroactivity strength, which quantifies the downstream load, can trigger five possible regime transitions. Retroactivity strength is a reflection of the fraction of the substrate sequestered by its downstream target. Remarkably, the minimum required retroactivity strength to evidence any sequestration triggered regime transition demands 23% of the substrate bound to its downstream target. This minimum retroactivity strength corresponds to the transition of the dose-response curve from ST to H regime. We show that modulation of the saturation and unsaturation levels of the enzymatic reactions by retroactivity is the fundamental mechanism governing operating regime transition.

Detection of dynamical regime transitions with lacunarity as a multiscale recurrence quantification measure

We propose lacunarity as a novel recurrence quantification measure and illustrate its efficacy to detect dynamical regime transitions which are exhibited by many complex real-world systems. We carry out a recurrence plot-based analysis for different paradigmatic systems and nonlinear empirical data in order to demonstrate the ability of our method to detect dynamical transitions ranging across different temporal scales. It succeeds to distinguish states of varying dynamical complexity in the presence of noise and non-stationarity, even when the time series is of short length. In contrast to traditional recurrence quantifiers, no specification of minimal line lengths is required and geometric features beyond linear structures in the recurrence plot can be accounted for. This makes lacunarity more broadly applicable as a recurrence quantification measure. Lacunarity is usually interpreted as a measure of heterogeneity or translational invariance of an arbitrary spatial pattern. In application to recurrence plots, it quantifies the degree of heterogeneity in the temporal recurrence patterns at all relevant time scales. We demonstrate the potential of the proposed method when applied to empirical data, namely time series of acoustic pressure fluctuations from a turbulent combustor. Recurrence lacunarity captures both the rich variability in dynamical complexity of acoustic pressure fluctuations and shifting time scales encoded in the recurrence plots. Furthermore, it contributes to a better distinction between stable operation and near blowout states of combustors.

How do borders influence migration? Insights from open and closed border regimes in the three Guianas

The ways border regimes affect migration patterns remain ambiguous. Closed borders may constrain migration but also encourage migrants to pursue alternative migration channels and destinations. While open borders may be associated with higher migration, oftentimes they promote circulation and return. To clarify how different border regimes influence migration patterns, this article examines the impact of open and closed border regimes on migration outcomes in Guyana, Suriname and French Guiana in the 1950s–1980s period, when all three gained independence or non-sovereign status and colonial ties were strong. The article proposes a conceptual schematic model that can accommodate varied post-colonial political and border regime transitions and explains changes in the timing, destination and composition of migration. The analysis finds that, counterintuitively, closed borders can lead to high emigration while open borders can encourage people to stay. The proposed model also illustrates the relevance of three dimensions of time: thehistorical juncture, thesequence of changeand thetime span. In sum, rather than preventing migration, border regimes yield important effects that lead to migration diversification.