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We test the application of a rare event simulation (RES) algorithm to accelerate the sampling of extreme winter rainfall over Europe in a climate model. The genealogical particle analysis algorithm, an ensemble method that interrupts the simulation at intermediate times to clone realizations in which an extreme event is developing, is applied to the intermediate complexity general circulation model PlaSim. We show that the algorithm strongly reduces the numerical effort required to estimate probabilities of extremes, demonstrating the potential of RES of seasonal precipitation extremes. Plain Language Summary: Rare events, such as winters with a lot of rainfall, can have a high impact. High rainfall can cause floods, risking lives, and damaging property. To plan for such events, we want to know what the probability is to experience a lot of rainfall in any given year. One way to make an estimate is to run climate models and look at the proportion of winters having rainfall above a high threshold. This method can be very costly and time‐consuming, as climate models require powerful computers and we need to run them for a long time until we see a few winters with very high rainfall. In this article, we apply algorithms to speed up such model simulations. Instead of keeping the model running for a long time, we run a large number of copies at the same time. At regular intervals, we check which simulations are producing a lot of rain. These we copy, while others are terminated. Even though we have made high rainfall more likely than it should be, we can still estimate what the correct probabilities of high rainfall are. We show that this method saves time running our computer model, while still giving accurate results. Key Points: A rare event simulation algorithm is applied to a climate model, generating a large ensemble of realizations with high winter rainfall over EuropeThe algorithm generates the ensemble at a significantly lower numerical effort compared to conventional brute‐force simulationThe ensemble allows to estimate probabilities of high threshold exceedances more accurately [ABSTRACT FROM AUTHOR]

In this study, we examined the sensitivity of tropical cyclone (TC) characteristics and precipitation to the Cordillera Mountain Range (CMR) in Luzon, Philippines. Using the Weather Research and Forecasting (WRF) model, we simulated eight TCs with four different CMR orographic elevations: Control, Flat, Reduced, and Enhanced. We found that at significance level α = 0.05 , TC intensity significantly weakened as early as 21 h prior to landfall in the Enhanced experiment relative to the Control, whereas there was little change in the Flat and Reduced experiments. However, throughout the period when the TC crossed Luzon, we found no significant differences for TC movement speed and position in the different orographic elevations. When a TC made landfall, associated precipitation over the CMR increased as the mountain height increased. We further investigated the underpinning processes relevant to the effect of the CMR on precipitation by examining the effects of mountain slope, incoming perpendicular wind speed, and the moist Froude Number ( F w ). Compared with other factors, TC precipitation was most strongly correlated with the strength of approaching winds multiplied by the mountain slope, i.e., stronger winds blowing up steeper mountain slopes caused higher amounts of precipitation. We also found that individually, F w , mountain height, and upslope wind speeds were poor indicators of orographically induced precipitation. The effects of mountain range on TC rainfall varied with TC cases, highlighting the complexity of the mountain, wind, and rainfall relationship. [ABSTRACT FROM AUTHOR]

The Philippines is exposed to tropical cyclones (TCs) throughout the year due to its location in the western North Pacific. While these TCs provide muchneeded precipitation for the country's hydrological cycle, extreme precipitation from TCs may also cause damaging hazards such as floods and landslides. This study examines the relationship between TC extreme precipitation and TC characteristics, including movement speed, intensity and season, for westward-moving TCs crossing Luzon, northern Philippines. We measure extreme precipitation by the weighted precipitation exceedance (WPE), calculated against a 95th percentile threshold, which considers both the magnitude and spatial extent of TC-related extreme precipitation. WPE has a significant, moderate positive relationship with TC intensity with a non-significant, weak negative relationship with movement speed. When TCs are classified by intensity 1 day before landfall (or pre-landfall), Typhoons (1-min maximum sustained wind speed ≥64 knots) tend to yield higher WPE than non-Typhoons (<64 knots). On the other hand, when TCs are classified by pre-landfall speed, slow TCs (movement speed <11.38 knots) tend to yield higher WPE than fast TCs (movement speed ≥11.38 knots). However, the relationship between prelandfall TC intensity and WPE is more pronounced during June–September while there is no significant difference between the WPE of the southwest monsoon (June–September) and northeast monsoon (October–December) seasons. These results suggest that it is important to consider the pre-landfall cyclone movement speed, intensity and season to anticipate extreme precipitation of incoming TCs. A decision table considering these factors is devised to aid in TC extreme precipitation forecasting. [ABSTRACT FROM AUTHOR]

The diurnal cycle of precipitation over the Central Himalaya is governed by a complex interaction between the diurnal cycle of tropical convection and local orographic flow. Understanding this interaction is crucial for model evaluation, where the simulation of such processes is highly sensitive to model resolution and choice of parametrisation schemes. In this study, the mean diurnal cycle is computed using gridded satellite data–Integrated Multi‐satellitE Retrievals for Global Precipitation Measurement (GPM) (IMERG) data and is shown to be bimodal, with one peak in the late afternoon (1700 India Standard Time (IST)) and a stronger one in the early morning (0200 IST). This structure is an artefact of compositing, as individual days are associated with single peaks. The late‐afternoon "convective" peak is shown to be linked to the diurnal cycle of tropical convection, whereas the nocturnal "katabatic" peak is shown to be triggered by nocturnal downslope flow converging with the background monsoon circulation. As such, the katabatic peak is strongly favoured by an active monsoon trough, which provides greater southeasterly moisture flux to the foothills, resulting in increased low‐level moisture flux convergence upon interaction with the katabatic northerlies. When the trough is less active, precipitation is brought to the region by mesoscale convective systems, ranging in scale from tens to thousands of kilometres, resulting in convective peaks. We hypothesise that these convective afternoon peaks are enhanced by anabatic flow. It is shown that the Boreal Summer Intraseasonal Oscillation does not play a significant role in modulating either the timing or the amplitude of the diurnal cycle; however, low‐pressure systems do: either by intensifying the trough (and hence the katabatic peak), or, when further north, by providing deep convection (hence supporting the convective peak). Two reanalyses and a separate 17‐km model with parametrised convection capture both peaks, but overestimate the magnitude of the convective peak and underestimate the magnitude of the katabatic peak. [ABSTRACT FROM AUTHOR]

The west coast of India, dominated by the Western Ghats mountain range, is among the rainiest places in the Tropics. The interaction between the land–sea contrast of the coast, the monsoonal westerlies, and the oblique mountains is subject to complex intraseasonal variability, which has not previously been explored in depth. This study investigates that variability from the perspective of the land–sea contrast, using empirical orthogonal function analysis to discern regimes of onshore and offshore rainfall over southwest India and the eastern Indian Ocean. Locally, it is found that the rainfall is most sensitive to midtropospheric humidity: when this is anomalously high, deep convection is encouraged; when this is anomalously low, it is suppressed. A moisture‐tracking algorithm is employed to determine the primary sources of the anomalously wet and dry midtropospheric air. There are important secondary contributions from low‐level vorticity and cross‐shore moisture flux. The dominant control on intraseasonal variability in coastal precipitation is found to be the Boreal Summer Intraseasonal Oscillation (BSISO): over 75% of the strongest offshore events occur during phases 3 and 4; and about 40% of the strongest onshore events occur during phases 5 and 6. The location of monsoon low‐pressure systems is also shown to be important in determining the magnitude and location of coastal rainfall. [ABSTRACT FROM AUTHOR]