ABSTRACT:

Medicanes, hurricane-like cyclonic systems in the Mediterranean Sea, are becoming an increasingly severe problem for many Mediterranean countries because climate projections suggest a higher risk under anthropogenic forcing even under an intermediate scenario. Due to the small size of these weather systems, high-resolution data are required to better resolve their structure and evolution. Here we investigate medicanes from the perspective of precipitation using the high-resolution (0.25
) ERA-5 reanalysis data released by European Centre for Medium-Range Weather Forecasts. Overall, we identify a total of 59 medicanes from ERA-5 data during 1979–2017, with marked year-to-year variability. These storms tend to occur mostly between September and March. Overall, the intensity of medicanes (i.e., maximum wind) is lower than that of tropical cyclones, and this is also true for precipitation. The composite precipitation of medicanes increases from the centre to 0.8
and then decreases. During 1979–2017, many regions along the Mediterranean Sea experienced over 20 extreme precipitation events (i.e., days) which were caused by medicanes, accounting for 2–5% of all the extreme precipitation events.

ABSTRACT:

This study examines the climatology and structure of rainfall associated with tropical cyclones (TCs) based on the atmosphere-only Coupled Model Intercomparison Project Phase 6 (CMIP6) HighResMIP runs of the PRocess-based climate sIMulation: AdVances in high resolution modelling and European climate Risk Assessment (PRIMAVERA) Project during 1979-2014. We evaluate how the spatial resolution of climate models with a variety of dynamic cores and parameterization schemes affects the representation of TC rainfall. These HighResMIP atmosphere-only runs that prescribe historical sea surface temperatures and radiative forcings can well reproduce the observed spatial pattern of TC rainfall climatology, with high-resolution models generally performing better than the low-resolution ones. Overall, the HighResMIP atmosphere-only runs can also reproduce the observed percentage contribution of TC rainfall to total amounts, with an overall better performance by the high-resolution models. The models perform better over ocean than over land in simulating climatological total TC rainfall, TC rainfall proportion and TC rainfall per TC in terms of spatial correlation. All the models in the HighResMIP atmosphere-only runs underestimate the observed composite TC rainfall structure over both land and ocean, especially in their lower resolutions. The underestimation of rainfall composites by the HighResMIP atmosphere-only runs is also supported by the radial profile of TC rainfall. Overall, the increased spatial resolution generally leads to an improved model performance in reproducing the observed TC rainfall properties.

ABSTRACT:

Among the many impacts of COVID-19, the pandemic led to improved air quality conditions in the countries under quarantine. In particular, there was a remarkable reduction in aerosols due to the shutdown of industries and drastically reduced traffic in many Asian countries between late January and March 2020; similarly, California experienced a large reduction in aerosols due to the state’s lockdown in response to COVID-19. Meanwhile, the western United States, particularly the coastal areas from Washington to California, received much less precipitation than normal during the same period. Is it possible that this reduction in precipitation was driven by the reduced aerosols due to the coronavirus? Here we show that the reduction in aerosols resulted in higher temperatures (up to ~0.5℃) and generally lower snow amounts, but cannot explain the observed low precipitation amounts over this region. In addition to an assessment of the effects of coronavirus-related reduction in aerosols on precipitation across the western United States, our findings also provide basic information on the potential impacts different mitigation efforts aimed at reducing anthropogenic aerosols would have on the regional climate.

ABSTRACT:

Atlantic tropical cyclones (TCs) can cause significant societal and economic impacts, as 2019’s Dorian serves to remind us of these storms’ destructiveness. Decades of effort to understand and predict Atlantic TC activity have improved seasonal forecast skill, but large uncertainties still remain, in part due to an incomplete understanding of the drivers of TC variability. Here we identify an association between the East Asian Subtropical Jet Stream (EASJ) during July-October and the frequency of Atlantic TCs (wind speed ≥ 34 knot) and hurricanes (wind speed ≥ 64 knot) during August-November based on observations for 1980-2018. This strong association is tied to the impacts of EASJ on a stationary Rossby wave train emanating from East Asia and the tropical Pacific to the North Atlantic, leading to changes in vertical wind shear in the Atlantic Main Development Region (80°W-20°W, 10°N-20°N).

ABSTRACT:

Tropical Cyclones (TCs) generate extreme precipitation with severe impacts across large coastal and inland areas, calling for accurate frequency estimation methods. Statistical approaches that take into account the physical mechanisms responsible for these extremes can help reducing the estimation uncertainty. Here we formulate a mixed-population Metastatistical Extreme Value Distribution explicitly incorporating non-TC and TC-induced rainfall and evaluate its implications on long series of daily rainfall for six major U.S. urban areas impacted by these storms. We find statistically significant differences between the distributions of TCand non-TC-related precipitation; moreover, including mixtures of distributions improves the estimation of the probability of extreme precipitation where TCs occur more frequently. These improvements are greater when rainfall aggregated over duration longer than one day are considered.