Summer precipitation variability over South America on long and short intraseasonal timescales

A dipole pattern in convection between the South Atlantic convergence zone and the subtropical plains of southeastern South America characterizes summer intraseasonal variability over the region. The dipole pattern presents two main bands of temporal variability, with periods between 10 and 30Â days, and 30 and 90Â days; each influenced by different large-scale dynamical forcings. The dipole activity on the 30--90-day band is related to an eastward traveling wavenumber-1 structure in both OLR and circulation anomalies in the tropics, similar to that associated with the Madden--Julian oscillation. The dipole is also related to a teleconnection pattern extended along the South Pacific between Australia and South America. Conversely, the dipole activity on the 10--30-day band does not seem to be associated with tropical convection anomalies. The corresponding circulation anomalies exhibit, in the extratropics, the structure of Rossby-like wave trains, although their sources are not completely clear

The contribution of North Atlantic atmospheric circulation shifts to future wind speed projections for wind power over Europe

Wind power accounts for a large portion of the European energy mix (~17% of total power capacity). European power systems therefore have a significant - and growing - exposure to near-surface wind speed changes. Despite this, future changes in European wind climate remain relatively poorly studied (compared to, e.g., temperature or precipitation), and there is limited understanding of the differences shown by different general and regional circulation models (GCMs and RCMs). This study provides a step towards a process-based understanding of European wind speed changes by isolating the component associated with `large-scale' atmospheric circulation changes in the CMIP5 simulations. The component associated with the large-scale atmospheric circulation is found to explain cold season windiness projections in the free troposphere over Western Europe, with the changes reflecting the poleward shift of the North Atlantic jet. However, in most GCMs the projected wind speed changes near the surface are more negative than would be expected from the large-scale circulation alone. Thus, while the spread in CMIP5 21st century near surface wind speed projections is associated with divergent projections for the large-scale atmospheric circulation, there is a remarkably good agreement concerning a relative reduction in near-surface wind speeds. This analysis suggests that projected 21st century wind speed changes over Western Europe are the result of two distinct processes. The first is associated with changes in the large-scale atmospheric circulation, while the second is likely to be more local in its connection to the near-surface boundary layer. An improved process-based understanding of both is needed for enhancing confidence in wind-power projections on multi-decadal timescales

Sub-seasonal forecasts of demand and wind power and solar power generation for 28 European countries

Electricity systems are becoming increasingly exposed to weather. The need for high-quality meteorological forecasts for managing risk across all timescales has therefore never been greater. This paper seeks to extend the uptake of meteorological data in the power systems modelling community to include probabilistic meteorological forecasts at sub-seasonal lead-times. Such forecasts are growing in skill and are receiving considerable attention in power system risk management and energy trading. Despite this interest, these forecasts are rarely evaluated in power system terms and technical barriers frequently prohibit use by non-meteorological specialists. This paper therefore presents data produced through a new EU climate services program Subseasonal-to-seasonal forecasting for Energy (S2S4E). The data corresponds to a suite of well-documented, easy-to-use, self-consistent daily- and nationally aggregated time-series for wind power, solar power and electricity demand across 28 European countries. The data is accessible from http://dx.doi.org/10.17864/1947.275, (Gonzalez et al., 2020). The data includes a set of daily ensemble reforecasts from two leading forecast systems spanning 20-years (ECMWF, an 11 member ensemble, with twice weekly starts for 1996-2016, totalling 21,210 forecasts) and 11 years (NCEP, a 12 member lagged-ensemble, constructed to match the start dates from the ECMWF forecast. from 1999-2010, totalling 4608 forecasts). The reforecasts containing multiple plausible realisations of daily-weather and power data for up to 6 weeks in the future. To the authors’ knowledge, this is the first time fully calibrated and post-processed daily power system forecast set has been published, and this is the primary purpose of this paper. A brief review of forecast skill in each of the individual primary power system properties and a composite property is presented, focusing on the winter season. The forecast systems contain additional skill over climatological expectation for weekly-average forecasts at extended lead-times, though this skill depends on the nature of the forecast metric considered. This highlights the need for greater collaboration between the energy- and meteorological research communities to develop applications, and it is hoped that publishing these data and tools will support this

Nonannual tree rings in a climate-sensitive Prioria copaifera chronology in the Atrato River, Colombia

In temperate climates, tree growth dormancy usually ensures the annual nature of tree rings, but in tropical environments, determination of annual periodicity can be more complex. The purposes of the work are as follows: (1) to generate a reliable tree‐ring width chronology for Prioria copaifera Griseb. (Leguminoceae), a tropical tree species dwelling in the Atrato River floodplains, Colombia; (2) to assess the climate signal recorded by the tree‐ring records; and (3) to validate the annual periodicity of the tree rings using independent methods. We used standard dendrochronological procedures to generate the P. copaifera tree‐ring chronology. We used Pearson correlations to evaluate the relationship of the chronology with the meteorological records, climate regional indices, and gridded precipitation/sea surface temperature products. We also evaluated 24 high‐precision 14C measurements spread over a range of preselected tree rings, with assigned calendar years by dendrochronological techniques, before and after the bomb spike in order to validate the annual nature of the tree rings. The tree‐ring width chronology was statistically reliable, and it correlated significantly with local records of annual and October–December (OND) streamflow and precipitation across the upper river watershed (positive), and OND temperature (negative). It was also significantly related to the Oceanic Niño Index, Pacific Decadal Oscillation, and the Southern Oscillation Index, as well as sea surface temperatures over the Caribbean and the Pacific region. However, 14C high‐precision measurements over the tree rings demonstrated offsets of up to 40 years that indicate that P. copaifera can produce more than one ring in certain years. Results derived from the strongest climate–growth relationship during the most recent years of the record suggest that the climatic signal reported may be due to the presence of annual rings in some of those trees in recent years. Our study alerts about the risk of applying dendrochronology in species with challenging anatomical features defining tree rings, commonly found in the tropics, without an independent validation of annual periodicity of tree rings. High‐precision 14C measurements in multiple trees are a useful method to validate the identification of annual tree rings

A new approach to extended-range multi-model forecasting: sequential learning algorithms

Multi-model combinations are a well established methodology in weather and climate prediction and their benefits have been widely discussed in the literature. Typical approaches involve combining the output of different numerical weather prediction (NWP) models using constant weighting factors, either uniformly distributed or determined through a prior skill assessment. This strategy, however, can lead to sub-optimal levels of skill as the performance of NWP models can vary with time (e.g., seasonally varying skill, changes in the forecasting system). Moreover, standard combination methods are not designed to incorporate predictions derived from sources other than NWP systems (e.g., climatological or time-series forecasts). New algorithms developed within the Machine Learning community provide the opportunity for `online prediction’ (also referred to as `sequential learning’). These methods consider a set of weighted predictors or `experts’ to produce subsequent predictions in which the combination or `mixture’ is updated at each step to optimize a loss or skill function. The predictors are highly flexible and can transparently combine both NWP- and statistically- derived forecasts. A set of these online prediction methods are tested and compared to standard multi-model combination techniques to assess their usefulness. The methods are general and can be applied to any model-derived predictand. A set of weather-sensitive European country-aggregate energy variables (electricity demand and wind power) are selected for demonstration purposes. Results show that these innovative methods exhibit significant skill improvements (i.e., between 5\% and 15\% improvement in the probabilistic skill) with respect to standard multi-model combination techniques for lead weeks up to 5. The incorporation of statistically-derived predictors (based on historical climate data) alongside NWP forecasts are also shown to contribute significant skill improvements in many cases

Patient and Provider Perspectives on How Trust Influences Maternal Vaccine Acceptance Among Pregnant Women in Kenya

Background Pregnant women and newborns are at high risk for infectious diseases. Altered immunity status during pregnancy and challenges fully vaccinating newborns contribute to this medical reality. Maternal immunization is a strategy to protect pregnant women and their newborns. This study aimed to find out how patient-provider relationships affect maternal vaccine uptake, particularly in the context of a lower middle- income country where limited research in this area exists. Methods We conducted semi-structured, in-depth narrative interviews of both providers and pregnant women from four sites in Kenya: Siaya, Nairobi, Mombasa, and Marsabit. Interviews were conducted in either English or one of the local regional languages. Results We found that patient trust in health care providers (HCPs) is integral to vaccine acceptance among pregnant women in Kenya. The HCP-patient relationship is a fiduciary one, whereby the patients’ trusts is primarily rooted in the provider’s social position as a person who is highly educated in matters of health. Furthermore, patient health education and provider attitudes are crucial for reinstating and fostering that trust, especially in cases where trust was impeded by rumors, community myths and misperceptions, and religious and cultural factors. Conclusion Patient trust in providers is a strong facilitator contributing to vaccine acceptance among pregnant women in Kenya. To maintain and increase immunization trust, providers have a critical role in cultivating a positive environment that allows for favorable interactions and patient health education. This includes educating providers on maternal immunizations and enhancing knowledge of effective risk communication tactics in clinical encounters

Pattern-based conditioning enhances sub-seasonal prediction skill of European national energy variables

Sub-seasonal forecasts are becoming more widely used in the energy sector to inform high-impact, weather-dependent decisions. Using pattern-based methods (such as weather regimes) is also becoming commonplace, although until now an assessment of how pattern-based methods perform compared to gridded model output has not been completed. We compare four methods to predict weekly-mean anomalies of electricity demand and demand-net-wind across 28 European countries. At short lead times (days 0-10) grid-point forecasts have higher skill than pattern-based methods across multiple metrics. However, at extended lead times (day 12+) pattern-based methods can show greater skill than grid-point forecasts. All methods have relatively low skill at weekly-mean national impact forecasts beyond day 12, particularly for probabilistic skill metrics. We therefore develop a method of pattern-based conditioning, which is able to provide windows of opportunity for prediction at extended lead times: when at least 50% of the ensemble members of a forecast agree on a specific pattern, skill increases significantly. The conditioning is valuable for users interested in particular thresholds for decision making, as it combines the dynamical robustness in the large-scale flow conditions from the pattern-based methods with local information present in the grid-point forecasts

Seasonal cycle of precipitation variability in South America on intraseasonal timescales

The seasonal cycle of the intraseasonal (IS) variability of precipitation in South America is described through the analysis of bandpass filtered outgoing longwave radiation (OLR) anomalies. The analysis is discriminated between short (10--30 days) and long (30--90 days) intraseasonal timescales. The seasonal cycle of the 30--90-day IS variability can be well described by the activity of first leading pattern (EOF1) computed separately for the wet season (October--April) and the dry season (May--September). In agreement with previous works, the EOF1 spatial distribution during the wet season is that of a dipole with centers of actions in the South Atlantic Convergence Zone (SACZ) and southeastern South America (SESA), while during the dry season, only the last center is discernible. In both seasons, the pattern is highly influenced by the activity of the Madden--Julian Oscillation (MJO). Moreover, EOF1 is related with a tropical zonal-wavenumber-1 structure superposed with coherent wave trains extended along the South Pacific during the wet season, while during the dry season the wavenumber-1 structure is not observed. The 10--30-day IS variability of OLR in South America can be well represented by the activity of the EOF1 computed through considering all seasons together, a dipole but with the stronger center located over SESA. While the convection activity at the tropical band does not seem to influence its activity, there are evidences that the atmospheric variability at subtropical-extratropical regions might have a role. Subpolar wavetrains are observed in the Pacific throughout the year and less intense during DJF, while a path of wave energy dispersion along a subtropical wavetrain also characterizes the other seasons. Further work is needed to identify the sources of the 10--30-day-IS variability in South America

Implementation of a provider-focused intervention for maximizing human papillomavirus (HPV) vaccine uptake in young cancer survivors receiving follow-up care in pediatric oncology practices: Protocol for a cluster-randomized trial of the HPV PROTECT intervention

BACKGROUND: Childhood cancer survivors are at high risk for developing new cancers (such as cervical and anal cancer) caused by persistent infection with the human papillomavirus (HPV). HPV vaccination is effective in preventing the infections that lead to these cancers, but HPV vaccine uptake is low among young cancer survivors. Lack of a healthcare provider recommendation is the most common reason that cancer survivors fail to initiate the HPV vaccine. Strategies that are most successful in increasing HPV vaccine uptake in the general population focus on enhancing healthcare provider skills to effectively recommend the vaccine, and reducing barriers faced by the young people and their parents in receiving the vaccine. This study will evaluate the effectiveness and implementation of an evidence-based healthcare provider-focused intervention (HPV PROTECT) adapted for use in pediatric oncology clinics, to increase HPV vaccine uptake among cancer survivors 9 to 17 years of age. METHODS: This study uses a hybrid type 1 effectiveness-implementation approach. We will test the effectiveness of the HPV PROTECT intervention using a stepped-wedge cluster-randomized trial across a multi-state sample of pediatric oncology clinics. We will evaluate implementation (provider perspectives regarding intervention feasibility, acceptability and appropriateness in the pediatric oncology setting, provider fidelity to intervention components and change in provider HPV vaccine-related knowledge and practices [e.g., providing vaccine recommendations, identifying and reducing barriers to vaccination]) using a mixed methods approach. DISCUSSION: This multisite trial will address important gaps in knowledge relevant to the prevention of HPV-related malignancies in young cancer survivors by testing the effectiveness of an evidence-based provider-directed intervention, adapted for the pediatric oncology setting, to increase HPV vaccine initiation in young cancer survivors receiving care in pediatric oncology clinics, and by procuring information regarding intervention delivery to inform future implementation efforts. If proven effective, HPV PROTECT will be readily disseminable for testing in the larger pediatric oncology community to increase HPV vaccine uptake in cancer survivors, facilitating protection against HPV-related morbidities for this vulnerable population. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04469569, prospectively registered on July 14, 2020