On the projection of future fire danger conditions with various instantaneous/mean-daily data sources

Fire danger indices are descriptors of fire potential in a large area, and combine a few variables that affect the initiation, spread and control of forest fires. The Canadian Fire Weather Index (FWI) is one of the most widely used fire danger indices in the world, and it is built upon instantaneous values of temperature, relative humidity and wind velocity at noon, together with 24 hourly accumulated precipitation. However, the scarcity of appropriate data has motivated the use of daily mean values as surrogates of the instantaneous ones in several studies that aimed to assess the impact of global warming on fire. In this paper we test the sensitivity of FWI values to both instantaneous and daily mean values, analyzing their effect on mean seasonal fire danger (seasonal severity rating, SSR) and extreme fire danger conditions (90th percentile, FWI90, and FWI>30, FOT30), with a special focus on its influence in climate change impact studies. To this aim, we analyzed reanalysis and regional climate model (RCM) simulations, and compared the resulting instantaneous and daily mean versions both in the present climate and in a future scenario. In particular, we were interested in determining the effect of these datasets on the projected changes obtained for the mean and extreme seasonal fire danger conditions in future climate scenarios, as given by a RCM. Overall, our results warn against the use of daily mean data for the computation of present and future fire danger conditions. Daily mean data lead to systematic negative biases of fire danger calculations. Although the mean seasonal fire danger indices might be corrected to compensate for this bias, fire danger extremes (FWI90 and specially FOT30) cannot be reliably transformed to accommodate the spatial pattern and magnitude of their respective instantaneous versions, leading to inconsistent results when projected into the future. As a result, we advocate caution when using daily mean data and strongly recommend the application of the standard definition for its calculation as closely as possible. Threshold-dependent indices derived from FWI are not reliably represented by the daily mean version and thus can neither be applied for the estimation of future fire danger season length and severity, nor for the estimation of future extreme events.The research leading to these results has received funding from the European Union's Seventh Framework Programme (FP7/2007-2013) under grant agreement 243888 (FUME Project). J.F. acknowledges nancial support from the Spanish R&D&I programme through grant CGL2010-22158-C02 (CORWES project). The ESCENA project (200800050084265) of the Spanish \Strategic action on energy and climate change" provided the WRF RCM simulation used in this study. We acknowledge three anonymous referees for their useful comments that helped to improve the original manuscript

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Changes to the Fossil Record of Insects through Fifteen Years of Discovery

The first and last occurrences of hexapod families in the fossil record are compiled from publications up to end-2009. The major features of these data are compared with those of previous datasets (1993 and 1994). About a third of families (>400) are new to the fossil record since 1994, over half of the earlier, existing families have experienced changes in their known stratigraphic range and only about ten percent have unchanged ranges. Despite these significant additions to knowledge, the broad pattern of described richness through time remains similar, with described richness increasing steadily through geological history and a shift in dominant taxa, from Palaeoptera and Polyneoptera to Paraneoptera and Holometabola, after the Palaeozoic. However, after detrending, described richness is not well correlated with the earlier datasets, indicating significant changes in shorter-term patterns. There is reduced Palaeozoic richness, peaking at a different time, and a less pronounced Permian decline. A pronounced Triassic peak and decline is shown, and the plateau from the mid Early Cretaceous to the end of the period remains, albeit at substantially higher richness compared to earlier datasets. Origination and extinction rates are broadly similar to before, with a broad decline in both through time but episodic peaks, including end-Permian turnover. Origination more consistently exceeds extinction compared to previous datasets and exceptions are mainly in the Palaeozoic. These changes suggest that some inferences about causal mechanisms in insect macroevolution are likely to differ as well

Structure-From-Motion Photogrammetry to Support the Assessment of Collapse Risk in Alpine Glaciers

The application of Structure-from-Motion (SfM) Photogrammetry with ground-based and UAV camera stations may be exploited for modelling the topographic surface of Alpine glaciers. Multi-temporal repeated surveys lead to geometric models that may be applied to analyze the glacier retreat under global warming conditions. Thanks to the integration of point clouds obtained from ground-based and UAV imaging platforms, a complete 3D reconstruction also including vertical and sub-vertical surfaces may be achieved. These 3D models may be also exploited to understand the precursory signals of local collapse that might represent a risk for tourists and hikers visiting glaciers. In this paper a review on the application of SfM Photogrammetry in the field of glaciological studies is reported. The case of Forni Glacier in the Italian Alps is presented as emblematic study. Photogrammetric data sets obtained from measurement campaigns carried out in 2014, 2016, 2017 and 2018 have been processed using a common workflow. Attention is paid to a few crucial aspects, such as image orientation and calibration, dense surface matching, georeferencing and data fusion. In the end, the use of output point clouds to evaluate the risk of collapse in the Forni Glacier is addressed