Site adaptation with machine learning for a Northern Europe gridded global solar irradiance product

Gridded global horizontal irradiance(GHI)databases are fundamental for analysing solar energy applications’technical and economic aspects,particularly photovoltaic applications.Today,there exist numerous gridded GHI databases whose quality has been thoroughly validated against ground-based irradiance measurements.Nonetheless,databases that generate data at latitudes above 65˚are few,and those available gridded irradiance products,which are either reanalysis or based on polar orbiters,such as ERA5,COSMO-REA6,or CM SAF CLARA-A2,generally have lower quality or a coarser time resolution than those gridded irradiance products based on geostationary satellites.Amongst the high-latitude gridded GHI databases,the STRÅNG model developed by the Swedish Meteorological and Hydrological Institute(SMHI)is likely the most accurate one,providing data across Sweden.To further enhance the product quality,the calibration technique called"site adaptation"is herein used to improve the STRÅNG dataset,which seeks to adjust a long period of low-quality gridded irradiance estimates based on a short period of high-quality irradiance measurements.This study introduces a novel approach for site adaptation of solar irradiance based on machine learning techniques,which differs from the conventional statistical methods used in previous studies.Seven machine-learning algorithms have been analysed and compared with conventional statistical approaches to identify Sweden’s most accurate algorithms for site adaptation.Solar irradiance data gathered from three weather stations of SMHI is used for training and validation.The results show that machine learning can substantially improve the STRÅNG model’s accuracy.However,due to the spatiotemporal heterogeneity in model performance,no universal machine learning model can be identified,which suggests that site adaptation is a location-dependant procedure.

Thinking in three's: Changing surgical patient safety practices in the complex modern operating room

The three surgical patient safety events, wrong site surgery, retained surgical items (RSI) and surgical fires are rare occurrences and thus their effects on the complex modern operating room (OR) are difficult to study. The likelihood of occurrence and the magnitude of risk for each of these surgical safety events are undefined. Many providers may never have a personal experience with one of these events and training and education on these topics are sparse. These circumstances lead to faulty thinking that a provider won't ever have an event or if one does occur the provider will intuitively know what to do. Surgeons are not preoccupied with failure and tend to usually consider good outcomes, which leads them to ignore or diminish the importance of implementing and following simple safety practices. These circumstances contribute to the persistent low level occurrence of these three events and to the difficulty in generating sufficient interest to resource solutions. Individual facilities rarely have the time or talent to understand these events and develop lasting solutions. More often than not, even the most well meaning internal review results in a new line to a policy and some rigorous enforcement mandate. This approach routinely fails and is another reason why these problems are so persistent. Vigilance actions alone havebeen unsuccessful so hospitals now have to take a systematic approach to implementing safer processes and providing the resources for surgeons and other stake-holders to optimize the OR environment. This article discusses standardized processes of care for mitigation of injury or outright prevention of wrong site surgery, RSI and surgical fires in an action-oriented framework illustrating the strategic elements important in each event and focusing on the responsibilities for each of the three major OR agents-anesthesiologists, surgeons and nurses. A Surgical Patient Safety Checklist is discussed that incorporates the necessary elements to bring these team members together and influence the emergence of a safer OR.