Water volume estimates of shallow desert lakes are the basis for water balance calculations, important both for water resource management and paleohydrology/climatology. Water volumes are typically inferred from bathymetry mapping; however, being shallow, ephemeral and remote, bathymetric surveys are scarce in such lakes. We propose a new, remote-sensing based, method to derive the bathymetry of such lakes using the relation between water occurrence, during >30-yr of optical satellite data, and accurate elevation measurements from the new Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2). We demonstrate our method at three locations where we map bathymetries with ~0.3 m error. This method complements other remotely sensed, bathymetry-mapping methods as it can be applied to: (a) complex lake systems with sub-basins, (b) remote lakes with no in-situ records, and (c) flooded lakes. The proposed method can be easily implemented in other shallow lakes as it builds on publically accessible global data sets.

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.

The metastatistical extreme value approach proved promising in the frequency analysis of daily precipitation from ordinary events, outperforming traditional methods based on sampled extremes. However, sub-daily applications are currently restrained as it is not known if ordinary events can be consistently examined over durations, and it is not clear to what extent their entire distributions represent extremes. We propose here a unified definition of ordinary events across durations, and suggest the simplified metastatistical extreme value formulation for dealing with extremes emerging from the tail, rather than the entire distributions, of ordinary events. This unified framework provides robust estimates of extreme quantiles (≤10% error on the 100-year from a 26-year long record), and allows scaling representations in which ordinary and extreme events share the scaling exponent. Future applications could improve our knowledge of sub-daily extreme precipitation and help investigating the impact of local factors and climatic forcing on their frequency.

Soil erosion is a worldwide agricultural and environmental problem that threatens food security and ecosystem viability. In arable environments, the primary cause of soil loss is short and intense storms that are characterized with high spatiotemporal variability. The complex nature of these erosive events imposes a great challenge for erosion modeling and risk analysis. Accurate high-resolution measurement of rain intensity is often lacking or sparsely available. As a result, many studies rely on coarser-resolution rainfall data that often fail to address the impact of intra-storm properties. In this study, based on a novel statistical method, we quantify the discrete and cumulative multiannual impact of rainstorm regime on runoff and soil erosion to better understand the most important rainstorm properties on erosion rate and amount, and, to provide storm-scale risk analyses. Central to our analyses is the coupling of a processes-based crop-land erosion model, Dynamic Water Erosion Prediction Project (DWEPP), with a stochastic rainfall generator that produces localized rainfall statistics at 5-min resolution (CoSMoS). To our knowledge, this is the first study that calibrated DWEPP runoff and sediment at the plot-scale on cropland. The model had an acceptable fit with measured event runoff and sediment data collected in northern Israel (NSE = 0.79 - 0.82). We then generated 300-year stochastic simulations of event-based runoff and sediment yield and used them to estimate erosion risk and calibrate a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. Results indicate that in the study area, high erosion rate events are characterized by intense rain bursts of short duration (shorter than the usually adopted erosivity index of 30-min), and not necessary by events of large volume accumulation or long duration. On these bases, we proposed an optimal rainfall erosivity index that combines intra-storm properties for the study area. As changes in rainstorm properties are expected under a changing climate, we expect our methodology to be a valuable tool for investigating the global concerns about future changes in soil erosion rate.

Orographic impact on extreme sub-daily precipitation is critical for risk management but remains insufficiently understood due to complicated atmosphere-orography interactions and large uncertainties. We investigate the problem adopting a framework able to reduce uncertainties and isolate the systematic interaction of Mediterranean cyclones with a regular orographic barrier. The average decrease with elevation reported for hourly extremes is found enhanced at sub-hourly durations. Tail heaviness of 10-minute intensities is negligibly affected by orography, suggesting self-similarity of the distributions at the convective scale. Orography decreases the tail heaviness at longer durations, with a maximum impact around hourly scales. These observations are explained by an orographically-induced redistribution of precipitation towards stratiform-like processes, and by the succession of convective cores in multi-hour extremes. Our results imply a breaking of scale-invariance at sub-hourly durations, with important implications for natural hazards management in mountainous areas.