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Tropical cyclones (TCs) are one of the most severe weather hazards in the tropics, causing many human deaths and substantial property loss. Therefore, it is always urgent to significantly reduce systematic errors that may hinder the accurate forecast of TC activity. To evaluate the ability of the Euro-Mediterranean Center for Climate Change (CMCC) forecast system to represent TC activity and to verify the feasibility of TCs forecast, we use a new version of the CMCC Seasonal Prediction System (SPS3.5), which configures with high spatial resolution (0.5 degrees) in the atmospheric component and a large (40) number of ensemble members. We compared SPS3.5 hindcasts from 1998 to 2016 July-September with observed TC tracks derived from the International Best Track Archive for Climate Stewardship (IBTrACS). To identify storms and track their trajectories in SPS3.5, we use the Geophysical Fluid Dynamics Laboratory (GFDL) Tropical Cyclone tracking algorithm and set strict thresholds to ensure the authenticity of the captured TCs. We find that the SPS3.5 system captures the spatial distributions in the North Hemisphere (R~0.8) well, although it underestimates TCs' number magnitude, which relates to the model resolution and thresholds. TCs spatial distribution is best captured over the Pacific, where the largest peak season (August) is covered by our dataset, while lower-skill is shown over the North Atlantic Ocean and the North Indian Ocean. For TC variability, the model performs well only in the Western North Pacific (R up to 0.6). We also investigate the relationship between TCs' intensity and interannual variability with ENSO., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Aspects of low-frequency variability of the atmospheric circulation in the Euro-Atlantic domain, such as the frequency of wintertime blocking and the North Atlantic Oscillation, have been found to exhibit significant predictability in large-ensemble seasonal and decadal forecasts. Part of this predictability arguably stems from the realistic initialization of the North Atlantic ocean, which influences the atmospheric circulation through air–sea interaction. Yet, various model deficiencies, such as systematic model biases and the misrepresentation of coupled processes may be limiting the emergence of the associated predictable signals. We present results from three recent studies indicating that increasing model resolution (typically moving to 0.25° in the ocean and 0.5° in the atmosphere) is crucial for mitigating various such deficiencies. Specifically, we show that: (i) increasing model resolution in a multi-model ensemble of coupled historical HighResMIP simulations leads to mitigating certain long-standing extratropical SST biases that contribute to the under-representation of European blocking, (ii) increasing the atmospheric model resolution in a multi-model set of historical HighResMIP simulations forced with observed sea surface temperatures allows for the realistic representation of the atmospheric circulation response to interannual Gulf Stream variability, expectedly important for predictability, and (iii) increasing model resolution in a multi-model ensemble of coupled HighResMIP simulations improves the realism of extratropical North Atlantic atmosphere–ocean variability through mitigating oceanic biases that control the variability of the deep ocean circulation at multi-annual and longer timescales. Current work focuses on evaluating how such model deficiencies affect seasonal and decadal predictability., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

As an important element in the regional containment of the COVID-19 pandemic a PCR testing laboratory with a cooperative character was founded in spring 2021 to screen for SARS-CoV-2 in the Nuremberg region, Germany. The aim was to detect asymptomatic infections in day care facilities for children, schools, and companies. The laboratory used an established RT-PCR protocol and analyzed approximately 18,500 pools of up to 25 pooled samples each from gargles or swabs ("lollipops") from up to 135 facilities between July 2021 and June 2022. Usually, the participating facilities were informed about positive pools within a few hours. Retention samples from positive pools were usually analyzed on the same day, and the results were reported to the facilities as well as the German Electronic Reporting and Information System (DEMIS). In the laboratory results, both the local incidences and the transition from the Delta- to the Omicron surge in early 2022 were well reflected. It is plausible that about 4,800 secondary infections could be prevented from the approximately 1,570 positive individual samples detected in conjunction with appropriate isolation measures. Such a PCR laboratory, which is characterized by short response times and high flexibility, can thus provide valuable services for regional surveillance of infection incidence. Als ein wichtiger Baustein zur regionalen Eindämmung der COVID-19 Pandemie wurde im Frühjahr 2021 ein PCR-Testlabor mit genossenschaftlichem Charakter zum Screening auf SARS-CoV-2 in der Region Nürnberger Land gegründet. Ziel war die Detektion asymptomatischer Infektionen in Kindertagesstätten, Schulen und Unternehmen. Das Labor nutzte ein etabliertes RT-PCR Verfahren und analysierte zwischen Juli 2021 und Juni 2022 aus bis zu 135 Einrichtungen rund 18.500 Pools mit je bis zu 25 vereinigten Proben aus Gurgelaten bzw. Abstrichtupfern ("Lollis"). In der Regel wurden die teilnehmenden Einrichtungen innerhalb weniger Stunden über positive Pools informiert, Rückstellproben positiver Pools wurden meist noch am selben Tag analysiert und die Ergebnisse an die Einrichtungen sowie das Deutsche Elektronische Melde- und Informationssystem (DEMIS) gemeldet. In den Laborergebnissen bildeten sich über den Zeitraum Juli 2021 bis Juni 2022 sowohl die lokalen Inzidenzen als auch der Übergang von der Delta- zur Omikron-Welle Anfang 2022 gut ab. Es ist plausibel, dass sich bei den ca. 1.570 detektierten positiven Einzelproben in Verbindung mit geeigneten Isolationsmaßnahmen etwa 4.800 Sekundärinfektionen verhindern ließen. Ein solches PCR-Labor, das sich durch kurze Antwortzeiten und hohe Flexibilität auszeichnet, kann somit wertvolle Dienste für die regionale Überwachung des Infektionsgeschehens leisten.

Starting to resolve the oceanic mesoscale in climate models is a step change in model fidelity. This study examines how certain obstinate biases in the midlatitude North Atlantic respond to increasing resolution (from 1° to 0.25° in the ocean) and how such biases in sea surface temperature (SST) affect the atmosphere. Using a multimodel ensemble of historical climate simulations run at different horizontal resolutions, it is shown that a severe cold SST bias in the central North Atlantic, common to many ocean models, is significantly reduced with increasing resolution. The associated bias in the time-mean meridional SST gradient is shown to relate to a positive bias in low-level baroclinicity, while the cold SST bias causes biases also in static stability and diabatic heating in the interior of the atmosphere. The changes in baroclinicity and diabatic heating brought by increasing resolution lead to improvements in European blocking and eddy-driven jet variability. Across the multimodel ensemble a clear relationship is found between the climatological meridional SST gradients in the broader Gulf Stream Extension area and two aspects of the atmospheric circulation: the frequency of high-latitude blocking and the southern-jet regime. This relationship is thought to reflect the two-way interaction (with a positive feedback) between the respective oceanic and atmospheric anomalies. These North Atlantic SST anomalies are shown to be important in forcing significant responses in the midlatitude atmospheric circulation, including jet variability and the storm track. Further increases in oceanic and atmospheric resolution are expected to lead to additional improvements in the representation of Euro-Atlantic climate.

Seasonal predictions leverage on predictable or persistent components of the Earth system that can modify the state of the atmosphere. The land surface provides predictability through various mechanisms, including snow cover, with particular reference to Autumn snow cover over the Eurasian continent. The snow cover alters the energy exchange between surface and atmosphere and induces a diabatic cooling that in turn can affect the atmosphere locally and remotely. Lagged relationships between snow cover in Eurasia and atmospheric modes of variability in the Northern Hemisphere have been documented but are deemed to be non-stationary and climate models typically do not reproduce observed relationships with consensus. The role of the snow in recent dynamical seasonal forecasts is therefore unclear. Here we assess the role of Autumn Eurasian snow cover in a set of five operational seasonal forecasts with large ensemble size and high resolution and with the help of targeted idealised simulations. Forecast systems reproduce realistically regional changes of the surface energy balance. Retrospective forecasts and idealised sensitivity experiments identify a coherent change of the circulation in the Northern Hemisphere. The main features of the atmospheric response are a wave-train downstream over the Pacific and North America and a signal in the Arctic. The latter does not emerge in reanalysis data but is compatible with a lagged but weak and fast feedback from the snow to the Arctic Oscillation.