@article {hess-26-1439-2022,
	title = {Coastal and orographic effects on extreme precipitation revealed by weather radar observations},
	journal = {Hydrology and Earth System Sciences},
	volume = {26},
	year = {2022},
	pages = {1439{\textendash}1458},
	doi = {10.5194/hess-26-1439-2022},
	url = {https://hess.copernicus.org/articles/26/1439/2022/},
	author = {Marra, F. and Armon, M. and Morin, E.}
}
@article {Nevo2022,
	title = {Flood forecasting with machine learning models in an operational framework},
	journal = {Hydrology and Earth System Sciences},
	volume = {26},
	year = {2022},
	month = {8},
	pages = {4013-4032},
	publisher = {Copernicus GmbH},
	abstract = {Google{\textquoteright}s operational flood forecasting system was developed to provide accurate real-time flood warnings to agencies and the public with a focus on riverine floods in large, gauged rivers. It became operational in 2018 and has since expanded geographically. This forecasting system consists of four subsystems: data validation, stage forecasting, inundation modeling, and alert distribution. Machine learning is used for two of the subsystems. Stage forecasting is modeled with the long short-term memory (LSTM) networks and the linear models. Flood inundation is computed with the thresholding and the manifold models, where the former computes inundation extent and the latter computes both inundation extent and depth. The manifold model, presented here for the first time, provides a machine-learning alternative to hydraulic modeling of flood inundation. When evaluated on historical data, all models achieve sufficiently high-performance metrics for operational use. The LSTM showed higher skills than the linear model, while the thresholding and manifold models achieved similar performance metrics for modeling inundation extent. During the 2021 monsoon season, the flood warning system was operational in India and Bangladesh, covering flood-prone regions around rivers with a total area close to 470 000 km2, home to more than 350 000 000 people. More than 100 000 000 flood alerts were sent to affected populations, to relevant authorities, and to emergency organizations. Current and future work on the system includes extending coverage to additional flood-prone locations and improving modeling capabilities and accuracy.},
	issn = {16077938},
	doi = {10.5194/HESS-26-4013-2022},
	author = {Sella Nevo and Efrat Morin and Adi Gerzi Rosenthal and Asher Metzger and Chen Barshai and Dana Weitzner and Dafi Voloshin and Frederik Kratzert and Gal Elidan and Gideon Dror and Gregory Begelman and Grey Nearing and Guy Shalev and Hila Noga and Ira Shavitt and Liora Yuklea and Moriah Royz and Niv Giladi and Nofar Peled Levi and Ofir Reich and Oren Gilon and Ronnie Maor and Shahar Timnat and Tal Shechter and Vladimir Anisimov and Yotam Gigi and Yuval Levin and Zach Moshe and Zvika Ben-Haim and Avinatan Hassidim and Yossi Matias}
}
@article {Armon2022,
	title = {Reduced Rainfall in Future Heavy Precipitation Events Related to Contracted Rain Area Despite Increased Rain Rate},
	journal = {Earth{\textquoteright}s Future},
	volume = {10},
	year = {2022},
	pages = {1{\textendash}19},
	abstract = {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 21 st 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{\textquoteright} 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 synoptic evolution 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. Plain Language Summary Heavy precipitation events are large storms that can recharge freshwater reservoirs, but can also lead to hazardous outcomes such as flash floods. Therefore, understanding the impacts of climate change on such storms is critical. Here, a weather model similar to those used in weather forecasts is used to simulate heavy precipitation events in the eastern Mediterranean. A large collection of storms is simulated in pairs: (1) historic storms, selected for their high impact, and (2) the same storms placed in a global warming scenario projected for the end of the 21 st century. Using these simulations we ask how present-day storms would look like were they to occur at the warmer end of the 21 st century. The future storms are found to produce much less rainfall compared to their historic counterparts. This decrease in rainfall is attributed mainly to the reduction in the area covered by storms{\textquoteright} rainfall, and happens despite increasing rainfall intensities. These results suggest that the region will be drier in the future with larger dry areas during storms; however, over short durations, it would rain more intensely over contracted areas-increasing local hazards associated with heavy precipitation events.},
	issn = {2328-4277},
	doi = {10.1029/2021ef002397},
	author = {Armon, Moshe and Marra, Francesco and Enzel, Yehouda and Rostkier-Edelstein, Dorita and Garfinkel, Chaim I. and Adam, Ori and Dayan, Uri and Efrat Morin}
}
@article {Elbaum2022,
	title = {Uncertainty in Projected Changes in Precipitation Minus Evaporation: Dominant Role of Dynamic Circulation Changes and Weak Role for Thermodynamic Changes},
	journal = {Geophysical Research Letters},
	volume = {49},
	year = {2022},
	month = {6},
	pages = {e2022GL097725},
	publisher = {John Wiley \& Sons, Ltd},
	abstract = {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 drive 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.},
	keywords = {CMIP5/6, hydroclimate changes, subtropical drying},
	issn = {1944-8007},
	doi = {10.1029/2022GL097725},
	url = {https://onlinelibrary.wiley.com/doi/full/10.1029/2022GL097725 https://onlinelibrary.wiley.com/doi/abs/10.1029/2022GL097725 https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL097725},
	author = {Eilat Elbaum and Chaim I. Garfinkel and Ori Adam and Efrat Morin and Dorita Rostkier-Edelstein and Uri Dayan}
}
