Fair scores for ensemble forecasts Ferro, C. A. T.
Quarterly journal of the Royal Meteorological Society,
July 2014 Part B, Letnik:
140, Številka:
683
Journal Article
Recenzirano
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The notion of fair scores for ensemble forecasts was introduced recently to reward ensembles with members that behave as though they and the verifying observation are sampled from the same ...distribution. In the case of forecasting binary outcomes, a characterization is given of a general class of fair scores for ensembles that are interpreted as random samples. This is also used to construct classes of fair scores for ensembles that forecast multicategory and continuous outcomes. The usual Brier, ranked probability and continuous ranked probability scores for ensemble forecasts are shown to be unfair, while adjusted versions of these scores are shown to be fair. A definition of fairness is also proposed for ensembles with members that are interpreted as being dependent and it is shown that fair scores exist only for some forms of dependence.
Decadal predictions have a high profile in the climate science community and beyond, yet very little is known about their skill. Nor is there any agreed protocol for estimating their skill. This ...paper proposes a sound and coordinated framework for verification of decadal hindcast experiments. The framework is illustrated for decadal hindcasts tailored to meet the requirements and specifications of CMIP5 (Coupled Model Intercomparison Project phase 5). The chosen metrics address key questions about the information content in initialized decadal hindcasts. These questions are: (1) Do the initial conditions in the hindcasts lead to more accurate predictions of the climate, compared to un-initialized climate change projections? and (2) Is the prediction model’s ensemble spread an appropriate representation of forecast uncertainty on average? The first question is addressed through deterministic metrics that compare the initialized and uninitialized hindcasts. The second question is addressed through a probabilistic metric applied to the initialized hindcasts and comparing different ways to ascribe forecast uncertainty. Verification is advocated at smoothed regional scales that can illuminate broad areas of predictability, as well as at the grid scale, since many users of the decadal prediction experiments who feed the climate data into applications or decision models will use the data at grid scale, or downscale it to even higher resolution. An overall statement on skill of CMIP5 decadal hindcasts is not the aim of this paper. The results presented are only illustrative of the framework, which would enable such studies. However, broad conclusions that are beginning to emerge from the CMIP5 results include (1) Most predictability at the interannual-to-decadal scale, relative to climatological averages, comes from external forcing, particularly for temperature; (2) though moderate, additional skill is added by the initial conditions over what is imparted by external forcing alone; however, the impact of initialization may result in overall worse predictions in some regions than provided by uninitialized climate change projections; (3) limited hindcast records and the dearth of climate-quality observational data impede our ability to quantify expected skill as well as model biases; and (4) as is common to seasonal-to-interannual model predictions, the spread of the ensemble members is not necessarily a good representation of forecast uncertainty. The authors recommend that this framework be adopted to serve as a starting point to compare prediction quality across prediction systems. The framework can provide a baseline against which future improvements can be quantified. The framework also provides guidance on the use of these model predictions, which differ in fundamental ways from the climate change projections that much of the community has become familiar with, including adjustment of mean and conditional biases, and consideration of how to best approach forecast uncertainty.
Ensemble post‐processing methods are used in operational weather forecasting to form probability distributions that represent forecast uncertainty. Several such methods have been proposed in the ...literature, including logistic regression, ensemble dressing, Bayesian model averaging and non‐homogeneous Gaussian regression. We conduct an imperfect model experiment with the Lorenz 1996 model to investigate the performance of these methods, especially when forecasting the occurrence of rare extreme events. We show how flexible bias‐correction schemes can be incorporated into these post‐processing methods, and that allowing the bias correction to depend on the ensemble mean can yield considerable improvements in skill when forecasting extreme events. In the Lorenz 1996 setting, we find that ensemble dressing, Bayesian model averaging and non‐homogeneous Gaussian regression perform similarly, while logistic regression performs less well.
Extreme value analysis of observed daily temperature anomalies from a new quasi‐global data set indicates that extreme daily maximum and minimum temperatures (>98.5 or <1.5 percentile) have warmed ...for most regions since 1950. Changes in extreme anomalous daily temperatures are determined by fitting extreme value distributions with time‐varying parameters. Changes in the distribution of anomaly exceedances above a high threshold are found to be statistically significant at the 10% level for most land areas when compared with a time‐invariant distribution and with the unforced natural variability produced by a coupled climate model. The largest positive trends in the location parameter of the extreme distribution are found in Canada and Eurasia where daily maximum temperatures have typically warmed by 1 to 3°C since 1950. The total area exhibiting positive trends is significantly greater than can be attributed to unforced natural variability. For most regions, positive trend magnitudes are larger and cover a greater area for daily minimum temperatures than for maximum temperatures. The comparatively small areas of cooling are found to be consistent with unforced natural climate variability. The North Atlantic Oscillation (NAO) is found to have a significant influence on extreme winter daily temperatures for many areas, with a negative NAO of one standard deviation reducing expected extreme winter daily temperatures by ∼2°C over Eurasia but increasing temperatures over northeastern North America.
Raw output from deterministic numerical weather prediction models is typically subject to systematic biases. Although ensemble forecasts provide invaluable information regarding the uncertainty in a ...prediction, they themselves often misrepresent the weather that occurs. Given their widespread use, the need for high‐quality wind‐speed forecasts is well‐documented. Several statistical approaches have therefore been proposed to recalibrate ensembles of wind‐speed forecasts, including a heteroscedastic truncated regression approach. An extension to this method that utilises the prevailing atmospheric flow is implemented here in a quasigeostrophic simulation study and on Global Ensemble Forecasting System (GEFS) reforecast data, in the hope of alleviating errors owing to changes in the synoptic‐scale atmospheric state. When the wind speed depends strongly on the underlying weather regime, the resulting forecasts have the potential to provide substantial improvements in skill relative to conventional post‐processing techniques. This is particularly pertinent at longer lead times, where there is more improvement to be gained over current methods, and in weather regimes associated with wind speeds that differ greatly from climatology. In order to realise this potential, an accurate prediction of the future atmospheric regime is required.
Surface winds are closely related to the prevailing atmospheric circulation and hence recently developed statistical post‐processing methods that utilise weather regimes are applied here to wind‐speed forecasts. Regime‐dependent post‐processing approaches are compared with standard methods of calibrating wind‐speed ensembles in a quasigeostrophic simulation study and using reforecast data. If an accurate prediction of the regime is available, then noticeable improvements over current post‐processing methods are observed at locations where wind speed is heavily affected by the underlying regime.
The objective of this study was to verify the flight radius and the influence of the climatic season and period of the day on the external activity of Melipona rufiventris bees. The forager bees were ...released at different distances to evaluate the flight radius. The following were considered for external activities in the four different seasons of the year (Winter, Autumn, Spring, Summer): the entry with no apparent load was considered as nectar/water, entry with defined and opaque mass in the corbicula was considered as pollen, the entry with undefined and shiny mass in the corbicula was considered as resin/clay or bee exit no load and removal of debris, mass trapped by the jaws. Assessments were performed between 6 am and 6 pm each month. M. rufiventris can reach distances of 2 500 meters, however the return decreases as the distance increases. The species performs all activities in and out of the colony during all seasons of the year and periods between 6 am and 6 pm but reduce nectar/water collection and exit from the box without apparent load and with debris between 6:00 am and 10 am in winter. It is concluded that distances greater than 1 500 meters hinder the external activity of bees which is influenced by air temperature, air humidity, time of day, season of the year and food availability.
Background and Purpose
Reperfusion therapy is the standard of care for ischaemic stroke; however, there is a need to identify new therapeutic targets able to ameliorate cerebral damage. Neutrophil β1 ...adrenoceptors (β1AR) have been linked to neutrophil migration during exacerbated inflammation. Given the central role of neutrophils in cerebral damage during stroke, we hypothesize that β1AR blockade will improve stroke outcomes.
Experimental Approach
Rats were subjected to middle cerebral artery occlusion–reperfusion to evaluate the effect on stroke of the selective β1AR blocker metoprolol (12.5 mg·kg−1) when injected i.v. 10 min before reperfusion.
Key Results
Magnetic resonance imaging and histopathology analysis showed that pre‐reperfusion i.v. metoprolol reduced infarct size. This effect was accompanied by reduced cytotoxic oedema at 24 h and vasogenic oedema at 7 days. Metoprolol‐treated rats showed reduced brain neutrophil infiltration and those which infiltrated displayed a high proportion of anti‐inflammatory phenotype (N2, YM1+). Additional inflammatory models demonstrated that metoprolol specifically blocked neutrophil migration via β1AR and excluded a significant effect on the glia compartment. Consistently, metoprolol did not protect the brain in neutrophil‐depleted rats upon stroke. In patients suffering an ischaemic stroke, β1AR blockade by metoprolol reduced circulating neutrophil–platelet co‐aggregates.
Conclusions and Implications
Our findings describe that β1AR blockade ameliorates cerebral damage by targeting neutrophils, identifying a novel therapeutic target to improve outcomes in patients with stroke. This therapeutic strategy is in the earliest stages of the translational pathway and should be further explored.
Before the invention of modern, large-scale engineering projects, terrace systems were rarely built in single phases of construction, but instead developed gradually, and could even be said to have ...evolved. Understanding this process of landscape change is therefore important in order to fully appreciate how terrace systems were built and functioned, and is also pivotal to understanding how the communities that farmed these systems responded to changes; whether these are changes to the landscape brought about by the farming practices themselves, or changes to social, economic or climatic conditions. Combining archaeological stratigraphy, soil micromorphology and geochemistry, this paper presents a case-study from the historic and extensive terraced landscape at Konso, southwest Ethiopia, and demonstrates – in one important river valley at least – that the original topsoil and much of the subsoil was lost prior to the construction of hillside terraces. Moreover, the study shows that alluvial sediment traps that were built adjacent to rivers relied on widespread hillside soil erosion for their construction, and strongly suggests that these irrigated riverside fields were formerly a higher economic priority than the hillside terraces themselves; a possibility that was not recognised by numerous observational studies of farming in this landscape. Research that takes into account how terrace systems change through time can thus provide important details of whether the function of the system has changed, and can help assess how the legacies of former practices impact current or future cultivation.
•The study combines stratigraphy, geochemistry, micromorphology and pyrolysis GC/MS.•Riverside fields were built by trapping sediment produced by hillside soil erosion.•Hillside terraces were built initially for protecting the valuable riverside fields.•Slope soil erosion has been an agronomic resource for system maintenance.•Understanding landscape evolution is essential for successful long-term management.
Background: Opioid use in patients with renal impairment can lead to increased adverse effects. Opioids differ in their effect in renal impairment in both efficacy and tolerability. This systematic ...literature review forms the basis of guidelines for opioid use in renal impairment and cancer pain as part of the European Palliative Care Research Collaborative’s opioid guidelines project.
Objective: The objective of this study was to identify and assess the quality of evidence for the safe and effective use of opioids for the relief of cancer pain in patients with renal impairment and to produce guidelines.
Search strategy: The Cochrane Database of Systematic Reviews, Cochrane Central Register of Controlled Trials, MedLine, EMBASE and CINAHL were systematically searched in addition to hand searching of relevant journals.
Selection criteria: Studies were included if they reported a clinical outcome relevant to the use of selected opioids in cancer-related pain and renal impairment. The selected opioids were morphine, diamorphine, codeine, dextropropoxyphene, dihydrocodeine, oxycodone, hydromorphone, buprenorphine, tramadol, alfentanil, fentanyl, sufentanil, remifentanil, pethidine and methadone. No direct comparator was required for inclusion. Studies assessing the long-term efficacy of opioids during dialysis were excluded.
Data collection and analysis: This is a narrative systematic review and no meta-analysis was performed. The Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach was used to assess the quality of the studies and to formulate guidelines.
Main results: Fifteen original articles were identified. Eight prospective and seven retrospective clinical studies were identified but no randomized controlled trials. No results were found for diamorphine, codeine, dihydrocodeine, buprenorphine, tramadol, dextropropoxyphene, methadone or remifentanil.
Conclusions: All of the studies identified have a significant risk of bias inherent in the study methodology and there is additional significant risk of publication bias. Overall evidence is of very low quality. The direct clinical evidence in cancer-related pain and renal impairment is insufficient to allow formulation of guidelines but is suggestive of significant differences in risk between opioids.
Recommendations: Recommendations regarding opioid use in renal impairment and cancer pain are made on the basis of pharmacokinetic data, extrapolation from non-cancer pain studies and from clinical experience. The risk of opioid use in renal impairment is stratified according to the activity of opioid metabolites, potential for accumulation and reports of successful or harmful use. Fentanyl, alfentanil and methadone are identified, with caveats, as the least likely to cause harm when used appropriately. Morphine may be associated with toxicity in patients with renal impairment. Unwanted side effects with morphine may be satisfactorily dealt with by either increasing the dosing interval or reducing the 24 hour dose or by switching to an alternative opioid.
The importance of temperature in the determination of the yield of an annual crop (groundnut;
Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used ...with a crop model (GLAM) to examine crop growth under simulated current (1961–1990) and future (2071–2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments.
The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change.
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