We present a multidisciplinary study of the microphysics, mesoscale and synoptic conditions of a rare radiation-fog event in the central and southern regions of Israel during January 3-6, 2021. The fog developed during nighttime from south to central coastal areas and dissipated at morning. The synoptic conditions were dominated by Red Sea Troughs at the surface without cyclonic upper air circulation, suitable for radiation fog development. In-situ measurements were combined with satellite imagery, high resolution (1-km grid size) Weather Research and Forecast model (WRF) with Real-Time Four-Dimensional Data Assimilation (RTFDDA) forecasts and post-processing algorithms including machine learning (ML) to analyze this event and to evaluate its numerical forecasting. The micro-physical analysis involved measurements of droplet size distribution and visibility range, allowing the calculation of liquid-water content and effective diameter of fog droplets. The measured visibility range was 90 m. The droplet diameter main mode was 1-2 micrometers, followed by another one around 6 micrometers. Typical liquid-water content values were 0.01-0.025 g/m3. WRF-RTFDDA mesoscale forecasts, post-processed by simple thresholds-based and ML algorithms, largely succeeded in predicting the temporal and spatial development of the dense fog. They proved useful in distinguishing between near-surface fog and elevated fog/low clouds, a distinction not possible from satellite imagery only. Clear patches at coastal areas covered in part by urban landuse were observed both in satellite imagery and model forecasts. WRF-RTFDDA forecasts proved their usefulness in forecasting this massive fog and low clouds events and in providing alerts to operational users and field campaign deployments.

Heavy precipitation events (HPEs) can lead to deadly and costly natural disasters and are critical to the hydrological budget in regions where rainfall variability is high and water resources depend on individual storms. Thus, reliable projections of such events in the future are needed. To provide high-resolution projections under the RCP8.5 scenario for HPEs at the end of the 21st century and to understand the changes in sub-hourly to daily rainfall patterns, weather research and forecasting (WRF) model simulations of 41 historic HPEs in the eastern Mediterranean are compared with “pseudo global warming” simulations of the same events. This paper presents the changes in rainfall patterns in future storms, decomposed into storms’ mean conditional rain rate, duration, and area. A major decrease in rainfall accumulation (-30% averaged across events) is found throughout future HPEs. This decrease results from a substantial reduction of the rain area of storms (-40%) and occurs despite an increase in the mean conditional rain intensity (+15%). The duration of the HPEs decreases (-9%) in future simulations. Regionally maximal 10-min rain rates increase (+22%), whereas over most of the region, long-duration rain rates decrease. The consistency of results across events, driven by varying synoptic conditions, suggests that these changes have low sensitivity to the specific large-scale flow during the events. Future HPEs in the eastern Mediterranean will therefore likely be drier and more spatiotemporally concentrated, with substantial implications on hydrological outcomes of storms.

Projections of extreme precipitation based on modern climate models suffer from large uncertainties. Specifically, unresolved physics and natural variability limit the ability of climate models to provide actionable information on impacts and risks at the regional, watershed and city scales relevant for practical applications. Here we show that the interaction of precipitating systems with local features can constrain the statistical description of extreme precipitation. These observational constraints can be used to project local extremes of low yearly exceedance probability (e.g., 100-year events) using synoptic-scale information from climate models, which is generally represented more accurately than the local-scales, and without requiring climate models to explicitly resolve extremes. The novel approach offers a path for improving the predictability of local statistics of extremes in a changing climate, independent of pending improvements in climate models at regional and local scales.

End of century projections from Coupled Model Intercomparison Project (CMIP) models show a decrease in precipitation over subtropical oceans that often extends into surrounding land areas, but with substantial intermodel spread. Changes in precipitation are controlled by both thermodynamical and dynamical processes, though the importance of these processes for regional scales and for intermodel spread is not well understood. The contribution of dynamic and thermodynamic processes to the model spread in regional precipitation minus evaporation (P-E) is computed for 48 CMIP models. The intermodel spread is dominated essentially everywhere by the change of the dynamic term, including in most regions where thermodynamic changes dominate the multi-model mean response. The dominant role of dynamic changes is insensitive to zonal averaging which removes any influence of stationary wave changes, and is also evident in subtropical oceanic regions. Relatedly, intermodel spread in P-E is generally unrelated to climate sensitivity.