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During spring migration, nocturnal migrants attempt to minimize their travel time to reach their breeding grounds early. However, how they behave and respond to unfavourable conditions during their springtime travels is much less understood. In this study, we reveal the effects of atmospheric factors on nocturnal bird migration under adverse conditions during spring and autumn, based on one of the most detailed bird migration studies globally, using radar data from 13 deployments over a period of seven years (2014–2020) in the Levant region. Using ERA5 reanalysis data, we found that migratory birds maintain similar ground speeds in both autumn and spring migrations, but during spring, when encountering unfavourable winds, they put more effort into maintaining their travel speed by increasing self-powered airspeed by 18%. Moreover, we report for the first time that spring migrants showed less selectivity to wind conditions and migrated even under unfavourable headwind and crosswind conditions. Interestingly, we discovered that temperature was the most important weather parameter, such that warm weather substantially increased migration intensities in both seasons. Our results enhance our understanding of bird migration over the Levant region, one of the world's largest and most important migration flyways, and the factors controlling it. This information is essential for predicting bird migration, which—especially under the ongoing anthropogenic changes—is of high importance. [ABSTRACT FROM AUTHOR]

Background: Exposure to heat during pregnancy has been associated with reduced fetal growth. Less is known about associations with cold and the potential for critical time windows of exposure. OBJECTIVES: We aimed to evaluate, in a national retrospective cohort, critical windows of susceptibility during pregnancy to extreme temperatures (low and high) and fetal growth, among 624,940 singleton term births in Israel during the period 2010-2014. Methods: Temperature exposures were estimated using a spatially refined gridded climate data set with a 1-h and 1- [km.sup.2] resolution. Percentiles of temperature were categorized by climatic zone for the entire pregnancy and by trimesters and weeks. Generalized additive models with the distributed lag nonlinear model framework were used to estimate unadjusted and adjusted associations between percentiles and categories of temperature and fetal growth markers: term [births after 36 weeks of gestational age (GA)] mean birth weight and term low birth weight (tLBW, term infants with birth weight below 2,500 g). Results: After adjustment, extreme temperatures (percentiles) during the entire pregnancy were associated with a lower mean birth weight {90th vs. 41st-50th percentile: -65 g; 95% CI: -72 g, -58 g}. Similar inverse U-shaped patterns were observed for all trimesters, with stronger associations for heat than for cold and for exposures during the third trimester. For heat, results suggest critical windows between 3-9 and 19-34 GA-weeks, with the strongest association estimated at 3 GA-weeks (temperature >90th vs. 41st-50th percentiles: -3.8 g; 95% CI: -7.1 g, -0.4 g). For cold, there was a consistent trend of null associations early in pregnancy and stronger inverse associations over time, with the strongest association at 36 GA-week ( Discussion: Findings from our study of term live births in Israel (2010-2014) suggest that exposure to extreme temperatures, especially heat, during specific time windows may result in reduced fetal growth. https://doi.org/10.1289/EHP8117, Background Increases in mean temperature and the frequency and intensity of extreme weather events due to climate change are expected to increase climate-related morbidity and mortality (Basagana 2018; IPCC 2014). [...]

Flash floods are among the most devastating and lethal natural hazards. In 2018, three flash-flood episodes resulted in 46 casualties in the deserts of Israel and Jordan alone. This paper presents the hydrometeorological analysis and forecasting of a substantial storm (25-27 Apr 2018) that hit an arid desert basin (Zin, ~ 1400 km2, southern Israel), claiming 12 human lives. Our aim was to: (a) spatially assess the severity of the storm, (b) quantify the time scale of the hydrological response, and (c) evaluate the available operational precipitation forecasting. Return periods of the storm's maximal rain intensities were derived locally, at 1-km2 resolution, using weather radar data and a novel statistical methodology. A high-resolution grid-based hydrological model was used to study the intra-basin flash-flood magnitudes, which were consistent with direct information from witnesses. The model was further used to examine the hydrological response to different forecast scenarios. A small portion of the basin (1-20 %) experienced extreme precipitation intensities (75- to 100-year return period), resulting in a local hydrological response of a high magnitude (10- to 50-year return period). Hillslope runoff, initiated minutes after the intense rainfall occurred, reached the streams and resulted in peak discharge within tens of minutes. Available deterministic operational precipitation forecasts poorly predicted the hydrological response in the studied basins (tens to hundreds of km2) mostly due to location inaccuracy. There was no gain from assimilating radar estimates in the numerical weather-prediction model. Therefore, we suggest using deterministic forecasts with caution as it might lead to fatal decision making. To cope with such errors a novel cost-effective methodology is applied by spatially shifting the forecasted precipitation fields. In this way, flash-flood occurrences were captured in most of the sub-basins, resulting in few false alarms. [ABSTRACT FROM AUTHOR]

In the absence of convection permitting numerical weather prediction (NWP) ensembles, the most recent deterministic NWP precipitation forecast is usually addressed. However, the exact intensity, location and timing of a deterministic precipitation forecast is not always reliable because of the chaotic nature and complexity of precipitation formation mechanisms. This study examines a way to optimize the use of precipitation forecasts for deterministic NWP models. More specifically, it suggests using a spatially smoothed time‐lagged ensemble (TLE) to obtain more reliable precipitation forecasts. A global NWP model (integrated forecast system—IFS) and a regional convection permitting NWP model (COSMO) over the Eastern Mediterranean during the period 2016–2018 were used for the analysis. First, the paper defines light, light–moderate and moderate intensities for 6 hr accumulated precipitation (6hAP) and investigates the corresponding definitions for 1 hr accumulated precipitation (1hAP). Next, fractional skill score (FSS) are used to estimate the optimal spatial smoothing scale of a deterministic precipitation forecast for the three intensity categories for the 6hAP and 1hAP. The FSS is also used to compare COSMO and IFS deterministic precipitation forecasts, and to analyse the skill degradation with the forecast range. It is quantitatively shown that the useful scale of precipitation forecasts is smaller for larger accumulation time intervals. Finally, precipitation forecasts for TLE are formed from successive smoothed deterministic forecasts and compared with the most recent deterministic forecast. It is found that, on average, TLEs have better skills for both 6hAP and 1hAP. The reason for this improvement in skill is illustrated using a case study as an example. [ABSTRACT FROM AUTHOR]

The growing importance of the planetary boundary layer (PBL) height detection is apparent in various fields, from air pollution analysis to weather prediction. In recent years micro-lidars such as ceilometers have been recognized as an efficient tool for such measurements. Here, the daytime summer PBL height is measured by eight ceilometers throughout Israel, along with with radiosonde profiles, the global IFS model, and the regional COSMO model. The analysis focused on three PBL height evaluation methods: the bulk Richardson method, the parcel method, and the wavelet covariance transform method. The best agreement between the PBL heights derived from a single radiosonde site on 33 summer days was found by the adjacent ceilometer (mean error = 12 m, RMSE = 97 m). Spatial analysis of the PBL heights derived from the models on 13 days in reference to five ceilometer measurement sites revealed COSMO evaluations by the bulk Richardson method (COSMOR) produced the best results for both flat (mean error = 19 m, RMSE = 203 m) and elevated terrain (mean error = -6 m, RMSE = 251 m). To improve COSMOR results, a regression tool was assimilated based on the PBL height difference between COSMOR and ceilometers. The regression is based on the altitude and distance from the shoreline for eight ceilometer sites. [ABSTRACT FROM AUTHOR]