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Sedentary occupation of the southern Levantine coast spans from the Pre-Pottery Neolithic C to the Early Bronze Age Ib phase (c. 7000-3100 BC). Sites dating to the Early Pottery Neolithic (c. 6400-5500 BC) are scarce, however, potentially reflecting the effects of the 8.2ka climatic event. Here, the authors present the investigations at the submerged site of Habonim North off the Carmel Coast. Typological and radiocarbon dating indicate an Early Pottery Neolithic occupation and evidence for continuity of subsistence and economic strategies with both earlier and later Neolithic cultures. The results indicate the resilience of coastal communities in the face of significant climatic uncertainty and contribute to understanding human responses to environmental change. Keywords: Israel, Neolithic, climate change, sea-level rise, subsistence, resilience, Introduction The centuries leading up to the sixth millennium BC are perceived as a key period of development for Neolithic societies across southern Europe, the Aegean, Anatolia, Syria and Mesopotamia. [...]

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This article discusses the significance of absolute dating methods in archaeological research, with a focus on the city of Jerusalem. The article emphasizes the need for precise dating techniques, such as radiocarbon dating, to better understand the relationship between ancient texts and the archaeological record. The Jerusalem 14C project is presented as an example of applying radiometric dating in challenging urban environments, using Bayesian statistical methods and microarchaeology. The text also mentions the potential of other dating techniques, like archaeomagnetism, to enhance dating accuracy. The article highlights the importance of using multiple dating methods and advanced technologies to gain a deeper understanding of ancient texts and archaeological records. [Extracted from the article]

Wind power generation has had a profound impact on both the green power and traditional power sectors. As a result, wind power forecasting plays an immense role in effectively predicting and providing wind power generated for effective power dispatching for system operators. However, wind power forecasting is a challenging topic with accuracy issues between the predicted power and actual power generation at the point of common coupling. Furthermore, due to the variation of wind, effective dispatching through the utilisation of wind power production forecasting becomes a challenge. This issue is further compounded by the vast amount of data required to train and verify of these forecasting algorithms. This paper presents a fast acting post forecast weighing algorithm designed to evaluate the forecasted power output of a previously developed wind power forecasting package. The developed method is designed to gauge and improve the estimated output forecaster's approach in order to observe performance changes in the algorithm while using minimal data without changing the internal workings of the evaluated forecasting algorithm. [ABSTRACT FROM AUTHOR]

With the increase in penetration of wind generation on interconnected power systems, the importance of wind power ramp forecasting has continuously grown. Large power ramps caused by sudden weather changes raise more concerns due to their significant impact on the power system economics and stability. Correct wind power ramp forecasts can help the system operators and utility companies to tradeoff the risks when scheduling wind energy in the electricity market. In this paper, a day‐ahead wind power ramp forecasting algorithm is developed to provide probabilistic ramp forecasts for look‐ahead times up to 48 h using hourly wind speed forecasts from Environment Canada High Resolution Deterministic Prediction System (HRDPS). An image‐based similarity search strategy has been designed to build a direct link between the wind speed forecasts and the wind power ramp prediction, thus reducing the impact of the uncertainty from both the power production forecast model and the ramp identification process on the forecasting accuracy. A performance assessment and validation of the proposed ramp event forecasting method is conducted by using the forecast and operation data from six investigated wind farms across Canada. [ABSTRACT FROM AUTHOR]