Seasonal Prediction of Arabian Sea Marine Heatwaves

Marine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (Sardinella longiceps)

Decadal Prediction of Marine Heatwaves in MPI‐ESM

Marine Heatwaves (MHW) are SST extremes that can have devastating impacts on marine ecosystems and can influence circulation patterns in the ocean and the atmosphere. Here, we present a first attempt to study the decadal predictability of MHW in an ensemble of decadal hindcasts based on the Max Planck Institute Earth System Model. For the global mean we find significant skill for the multiyear MHW trends but we cannot predict the interannual to decadal variability of MHW. In the Subpolar North Atlantic, we can predict the interannual to decadal variability of MHW days and frequency up to lead year 8. We demonstrate that in the Subpolar North Atlantic, any increase in SST is accompanied by more MHW and vice versa. Thereby we gain additional information about the decadal evolution of SST that go beyond predicting the yearly mean SST.Plain Language Summary: Marine Heatwaves (MHW) are periods with extremely warm ocean temperatures that can be disruptive for many marine ecosystems. Here, we provide an attempt to predict the evolution of MHW in the global ocean for the following two to ten years. With this analysis we improve our understanding of the predictability of surface temperatures in the global ocean. We find that there are strong regional differences in the predictability of MHW. One region where MHW can be predicted successfully is the Subpolar North Atlantic. We show that an increase in mean ocean temperature also results in an increase in MHW.Key Points: Global mean multiyear trends for Marine Heatwaves (MHW) days and frequency can be skillfully predicted for the following two to eight years. In the Subpolar North Atlantic, yearly characteristics MHW days and frequency are predictable up to leadyear eight. Any increase in SST in the Subpolar North Atlantic is accompanied by an increase in MHW and vice versa.Copernicus Climate Change ServiceDeutsche Forschungsgemeinschafthttp://hdl.handle.net/hdl:21.14106/f2fdc61b13828ed5284f4e4ab41e63f8a84c6e5

The impact of classroom management strategies on at-risk students’ behavior in biology class. A case study

Der gezielte Einsatz von Classroom-Management-Strategien kann die Beschulung von Schülerinnen und Schülern mit herausforderndem Verhalten begünstigen. Verschiedene Metaanalysen belegen, dass der Einsatz von Classroom-Management-Strategien im Unterricht positive Effekte auf das Verhalten der Lernenden hat. Die zentrale Fragestellung dieser Untersuchung ist, ob der gezielte Einsatz von Classroom-Management-Strategien zu einer Reduktion des Störverhaltens und einer Verbesserung des Lern- und Arbeitsverhaltens bei Lernenden unter besonderen Risikobedingungen im Biologieunterricht führt. Die zugrundeliegende Fördermaßnahme für einen inklusiven Biologieunterricht berücksichtigt in ihrer Konzeption neben fachlichen und sonderpädagogischen Aspekten insbesondere die Grundlagen eines effektiven Classroom Managements. Die Evaluation erfolgte mit Hilfe einer experimentellen Einzelfallstudie im A-B-Design. Es ergeben sich für das Lern- und Arbeitsverhalten anhand der Non-Overlap-Indices moderate bis große Interventionseffekte. Für den Bereich Störverhalten lassen sich bei allen drei Schülern moderate Effekte feststellen. Die Befunde stützen somit den aktuellen Forschungsstand und erweitern diesen für den inklusiven Biologieunterricht. (DIPF/Orig.)Target-oriented applications of classroom management strategies (Emmer & Evertson, 2009) can facilitate the education of pupils with challenging behaviours. Several meta analyses (Hattie, 2012; Korpershoek, Harms, de Boer, van Kuijk & Doolaard, 2016; Marzano, 2000) prove that classroom management strategies have positive effects on the pupils’ behaviour. The central question of this study is whether a specific teaching unit leads to a reduction of disturbing behaviour and to an improvement of the learning and working behaviour among pupils under special risk conditions. The teaching unit of inclusive biology lessons incorporates subject-related and special educational aspects with a certain focus on classroom management. The evaluation was carried out as an experimental single-case study with an A-B design (Jain & Spieß, 2012). Based on the non-overlap indices pupils show moderate to large intervention effects with regard to their learning and working behaviour. In disruptive behaviour, moderate effects can be observed among all three students. Our findings support the current state of research. (DIPF/Orig.

Seasonal Prediction of Arabian Sea Marine Heatwaves

AbstractMarine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (Sardinella longiceps).Plain Language Summary: Marine heatwaves (MHWs) are prolonged extreme events associated with exceptionally high ocean water temperatures. Such events impose heat stress on marine life, and thus predicting such events is beneficial for management applications. In this work we show that the occurrence of MHWs in summer in the Arabian Sea can be skilfully predicted seven month in advance. Our prediction system benefits from the information of sea surface temperature anomalies in the eastern Pacific Ocean in the preceding winter, among other aspects. Our predictions suggest potential for using climate information in fisheries management in this region.Key Points: Summer marine heatwaves in the Arabian Sea are predictable seven months in advance The prediction skill in summer is mainly associated with a preceding El Niño event in winter Probabilistic predictions of Arabian Sea area under heatwave can be tailored to benefit fisheries DFGUniversität Hamburg http://dx.doi.org/10.13039/501100005711Cedars‐Sinai Medical Center http://dx.doi.org/10.13039/100013015Marine Institute http://dx.doi.org/10.13039/501100001627Copernicus Climate Change ServiceAigéin, Aeráid, agus athrú AtlantaighEUhttp://dx.doi.org/10.7289/V5SQ8XB5http://hdl.handle.net/hdl:21.14106/f2fdc61b13828ed5284f4e4ab41e63f8a84c6e52http://hdl.handle.net/hdl:21.14106/27e73ed39cd59d2033e018a494e342383db53a0

Seasonal Prediction of Arabian Sea Marine Heatwaves

Marine heatwaves are known to have a detrimental impact on marine ecosystems, yet predicting when and where they will occur remains a challenge. Here, using a large ensemble of initialized predictions from an Earth System Model, we demonstrate skill in predictions of summer marine heatwaves over large marine ecosystems in the Arabian Sea seven months ahead. Retrospective forecasts of summer (June to August) marine heatwaves initialized in the preceding winter (November) outperform predictions based on observed frequencies. These predictions benefit from initialization during winters of medium to strong El Niño conditions, which have an impact on marine heatwave characteristics in the Arabian Sea. Our probabilistic predictions target spatial characteristics of marine heatwaves that are specifically useful for fisheries management, as we demonstrate using an example of Indian oil sardine (Sardinella longiceps)