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4H–silicon carbide (SiC) shows the capability of hosting a large number of promising emitters for quantum technology. However, due to its high refractive index, the collection of photoluminescence emission is compromised for further applications. Here, we demonstrate a scalable approach of manufacturing solid-immersion lenses (SILs) on 4H–SiC. The procedure results in SILs with high effective NA. The fluorescence collection efficiency of single quantum emitters under the SILs shows 3.4 times enhancement confirmed by confocal microscopy of individual V 2 . [ABSTRACT FROM AUTHOR]

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VALUE is an open European collaboration to intercompare downscaling approaches for climate change research, focusing on different validation aspects (marginal, temporal, extremes, spatial, process‐based, etc.). Here we describe the participating methods and first results from the first experiment, using "perfect" reanalysis (and reanalysis‐driven regional climate model (RCM)) predictors to assess the intrinsic performance of the methods for downscaling precipitation and temperatures over a set of 86 stations representative of the main climatic regions in Europe. This study constitutes the largest and most comprehensive to date intercomparison of statistical downscaling methods, covering the three common downscaling approaches (perfect prognosis, model output statistics—including bias correction—and weather generators) with a total of over 50 downscaling methods representative of the most common techniques. Overall, most of the downscaling methods greatly improve (reanalysis or RCM) raw model biases and no approach or technique seems to be superior in general, because there is a large method‐to‐method variability. The main factors most influencing the results are the seasonal calibration of the methods (e.g., using a moving window) and their stochastic nature. The particular predictors used also play an important role in cases where the comparison was possible, both for the validation results and for the strength of the predictor–predictand link, indicating the local variability explained. However, the present study cannot give a conclusive assessment of the skill of the methods to simulate regional future climates, and further experiments will be soon performed in the framework of the EURO‐CORDEX initiative (where VALUE activities have merged and follow on). Finally, research transparency and reproducibility has been a major concern and substantive steps have been taken. In particular, the necessary data to run the experiments are provided at http://www.value‐cost.eu/data and data and validation results are available from the VALUE validation portal for further investigation: http://www.value‐cost.eu/validationportal. [ABSTRACT FROM AUTHOR]

To assess potential impacts of climate change for a specific location, one typically employs climate model simulations at the grid box corresponding to the same geographical location. For most of Europe, this choice is well justified. But, based on regional climate simulations, we show that simulated climate might be systematically displaced compared to observations. In particular in the rain shadow of mountain ranges, a local grid box is therefore often not representative of observed climate: the simulated windward weather does not flow far enough across the mountains; local grid boxes experience the wrong air masses and atmospheric circulation. In some cases, also the local climate change signal is deteriorated. Classical bias correction methods fail to correct these location errors. Often, however, a distant simulated time series is representative of the considered observed precipitation, such that a non-local bias correction is possible. These findings also clarify limitations of bias correcting global model errors, and of bias correction against station data. [ABSTRACT FROM AUTHOR]

To assess potential impacts of climate change for a specific location, one typically employs climate model simulations at the grid box corresponding to the same geographical location. But based on regional climate model simulations, we show that simulated climate might be systematically displaced compared to observations. In particular in the rain shadow of moutain ranges, a local grid box is therefore often not representative of observed climate: the simulated windward weather does not flow far enough across the mountains; local grid boxes experience the wrong airmasses and atmospheric circulation. In some cases, also the local climate change signal is deteriorated. Classical bias correction methods fail to correct these location errors. Often, however, a distant simulated time series is representative of the considered observed precipitation, such that a non-local bias correction is possible. These findings also clarify limitations of bias correcting global model errors, and of bias correction against station data. [ABSTRACT FROM AUTHOR]

Different ensemble-based data assimilation (DA) approaches for palaeoclimate reconstructions have been recently undertaken, but no systematic comparison among them has been attempted. We compare an off-line and an online ensemble-based method, with the testing period being the 17th century, which led into the Maunder Minimum. We use a low-resolution version of Max Planck Institute for Meteorology Earth System Model (MPI-ESM) to assimilate the Past Global Changes (PAGES) 2k continental temperature reconstructions. In the off-line approach, the ensemble for the entire simulation period is generated first and then the ensemble is used in combination with the empirical information to produce the analysis. In contrast, in the on-line approach, the ensembles are generated sequentially for sub-periods based on the analysis of previous sub-periods. Both schemes perform better than the simulations without DA. The on-line method would be expected to perform better if the assimilation led to states of the slow components of the climate system that are close to reality and the system had sufficient memory to propagate this information forward in time. In our comparison, which is based on analysing correlations and differences between the analysis and the proxy-based reconstructions, we find similar skill for both methods on the continental and hemispheric scales. This indicates either a lack of control of the slow components in our setup or a lack of skill in the information propagation on decadal timescales. Additional experiments are however needed to check whether the conclusions reached in this particular setup are valid in other cases. Although the performance of the two schemes is similar and the on-line method is more difficult to implement, the temporal consistency of the analysis in the on-line method makes it in general preferable. [ABSTRACT FROM AUTHOR]

Different ensemble-based data assimilation (DA) approaches for palaeoclimate reconstructions have been recently followed, but no systematic comparison among them has been attempted. We compare an off-line and an on-line ensemble-based method, with the testing period being the 17th century, which led into the Maunder Minimum. We use a low-resolution version of Max Planck Institute for Meteorology's model MPI-ESM, to assimilate the PAGES 2K continental temperature reconstructions. In the off-line approach the ensemble for the entire simulation period is generated first and then the ensemble is used in combination with the empirical information to produce the analysis. In contrast, in the on-line approach the ensembles are generated sequentially for sub-periods based on the analysis of previous sub-periods. Both schemes perform better than the simulations without DA. The on-line method would be expected to perform better if the assimilation led to states of the slow components of the climate system that are close to reality and the system had sufficient memory to propagate this information forward in time. In our comparison, which is based on analysing correlations and differences between the analysis and the proxy-based reconstructions, we find similar skill for both methods on continental and the hemispheric scales. This indicates either a lack of control of the slow components in our setup or a lack of information propagation on decadal timescales. Although the skill is similar and the on-line method is more difficult to implement, the temporal consistency of the analysis in on-line method makes it in general preferable. [ABSTRACT FROM AUTHOR]

Climate proxy data provide noisy, and spatially incomplete information on some aspects of past climate states, whereas palaeosimulations with climate models provide global, multi-variable states, which may however differ from the true states due to unpredictable internal variability not related to climate forcings, as well as due to model deficiencies. Using data assimilation for combining the empirical information from proxy data with the physical understanding of the climate system represented by the equations in a climate model is in principle a promising way to obtain better estimates for the climate of the past. Data assimilation has been used for a long time in weather forecasting and atmospheric analyses to control the states in atmospheric General Circulation Models such that they are in agreement with observation from surface, upper air, and satellite measurements. Here we discuss the similarities and the differences between the data assimilation problem in palaeoclimatology and in weather forecasting, and present and conceptually compare three data assimilation methods that have been developed in recent years for applications in palaeoclimatology. All three methods (selection of ensemble members, Forcing Singular Vectors, and Pattern Nudging) are illustrated by examples that are related to climate variability over the extratropical Northern Hemisphere during the last millennium. In particular it is shown that all three methods suggest that the cold period over Scandinavia during 1790-1820 is linked to anomalous northerly or easterly atmospheric flow, which in turn is related to a pressure anomaly that resembles a negative state of the Northern Annular Mode. [ABSTRACT FROM AUTHOR]

Climate proxy data provide noisy, and spatially incomplete information on some aspects of past climate states, whereas palaeosimulations with climate models provide global, multi-variable states, which may however differ from the true states due to unpredictable internal variability not related to climate forcings, as well as due to model deficiencies. Using data assimilation for combining the empirical information from proxy data with the physical understanding of the climate system represented by the equations in a climate model is in principle a promising way to obtain better estimates for the climate of the past. Data assimilation has been used for a long time in weather forecasting and atmospheric analyses to control the states in atmospheric General Circulation Models such that they are in agreement with observation from surface, upper air, and satellite measurements. Here we discuss the similarities and the differences between the data assimilation problem in palaeoclimatology and in weather forecasting, and present and conceptually compare three data assimilation methods that have been developed in recent years for applications in palaeoclimatology. All three methods (selection of ensemble members, Forcing Singular Vectors, and Pattern Nudging) are illustrated by examples that are related to climate variability over the extratropical Northern Hemisphere during the last millennium. In particular it is shown that all three methods suggest that the cold period over Scandinavia during 1790-1820 is linked to anomalous northerly or easterly atmospheric flow, which in turn is related to a pressure anomaly that resembles a negative state of the Northern Annular Mode. [ABSTRACT FROM AUTHOR]

In 9 Goettingen minipigs we studied the effect of E. coli bacteremia on effective pulmonary capillary pressure and the longitudinal distribution of pulmonary vascular resistance. Precapillary pressure gradient (dPa) was calculated as the difference between mean pulmonary artery pressure (MPP) and effective pulmonary capillary pressure (Pc) (dPa = MPP-Pc), postcapillary pressure gradient (dPv) as the difference between Pc and left atrial pressure (dPv = Pc-LAP). The disturbance of pulmonary gas exchange was quantified by the AaDO2 quotient 1-PaO2/PAO2. Live E. coli infusion resulted in hypodynamic circulatory failure. Cardiac index fell from 3.7 +/- 0.81 . min-1.m-2 to 2.2 +/- 0.71 .min-1.m-2 after bacteremia lasting for 3.5 h. Simultaneously venous pulmonary vascular resistance rose from 25% of total pulmonary vascular resistance before to 32% after 3.5 h bacteremia, thus raising Pc from 11 mmHg to 16 mmHg. The degree of respiratory insufficiency was correlated with changes of MPP, dPa and dPv: 1-PaO2/PAO2 = 0.2 + 0.035.dPv (r = 0.829). Our results show, that the longitudinal distribution of pulmonary vascular resistance changes during septicemia, thus raising Pc. This may be an important factor in the genesis of septic pulmonary failure. [ABSTRACT FROM AUTHOR]

We report a patient undergoing redo cardiac surgery for combined replacement of the aortic and mitral valves. During the course of the operation, a Swan-Ganz catheter - positioned preoperatively - was accidentally fixed to the wall of the pulmonary artery. As this did not interfere with cardiac output measurement or the pulmonary artery pressure wave form, the fixation was not noticed until an attempt was made to remove the catheter. Fluoroscopy revealed both the catheter's immobility and the location of the suture fixation. The patient required a sternotomy to remove the catheter. In order to avoid this complication, the indications for pulmonary artery catheters during cardiac surgery should be carefully considered. If catheters are inserted, their mobility should by all means be ensured before the chest is closed. [ABSTRACT FROM AUTHOR]