Tropical cyclones (TCs) are identified and tracked in six recent reanalysis datasets and compared with those from the IBTrACS best-track archive. Results indicate that nearly every cyclone present in IBTrACS over the period 1979–2012 can be found in all six reanalyses using a tracking and matching approach. However, TC intensities are significantly underrepresented in the reanalyses compared to the observations. Applying a typical objective TC identification scheme, it is found that the largest uncertainties in TC identification occur for the weaker storms; this is exacerbated by uncertainties in the observations for weak storms and lack of consistency in operational procedures. For example, certain types of storms, such as tropical depressions, subtropical cyclones, and monsoon depressions, are not included in the best-track data for all reporting agencies. There are definite improvements in how well TCs are represented in more recent, higher-resolution reanalyses; in particular MERRA-2 is comparable with the NCEP-CFSR and JRA-55 reanalyses, which perform significantly better than the older MERRA reanalysis.

The coastal region of East Asia (EA) is one of the regions with the most frequent impacts from tropical cyclones (TCs). In this study, rainfall and moisture transports related to TCs are measured over EA, and the contribution of TCs to the regional water budget is compared with other contributors, especially the mean circulation of the EA summer monsoon (EASM). Based on ERA-Interim reanalysis (1979–2012), the trajectories of TCs are identified using an objective feature tracking method. Over 60% of TCs occur from July to October (JASO). During JASO, TC rainfall contributes 10%–30% of the monthly total rainfall over the coastal region of EA; this contribution is highest over the south/southeast coast of China in September. TCs make a larger contribution to daily extreme rainfall (above the 95th percentile): 50%–60% over the EA coast and as high as 70% over Taiwan Island. Compared with the mean EASM, TCs transport less moisture over EA. However, as the peak of the mean seasonal cycle of TCs lags two months behind that of the EASM, the moisture transported by TCs is an important source for the water budget over the EA region when the EASM withdraws. This moisture transport is largely performed by westward-moving TCs. These results improve understanding of the water cycle of EA and provide a useful test bed for evaluating and improving seasonal forecasts and coupled climate models.

Climate change presents risks both in terms of warming and increased variability that are heightened when compounded. It is thus notable that the simulations in the Coupled Model Intercomparison Project Phase 5 (CMIP5) showing greater Northern midlatitude continental warming also show a greater increase in monthly average temperature variance, particularly in Europe. European variability increases with warming at a rate of 0.40°C2/°C (95% C.I. [0.28, 0.50]), with local warming rates explaining 71% of the intermodel difference in variability changes. Coupling between warming and variance increases the probability of high temperatures compared to a scenario where variance is stable. If warming were to reach 6°C, the risk of monthly average temperature exceeding a 30°C threshold is 4 times greater in the increased‐variance scenario. Despite the simple scaling across models suggesting some common origin, changes in model temperature and variance potentially involve a range of mechanisms whose contributions remain unclear.

Atmospheric rivers (ARs) are filamentary corridors of enhanced atmospheric water vapor transport that can produce extreme precipitation in mid-latitude and polar regions, particularly when an AR undergoes topographic ascent (Nash et al., 2018;Neiman et al., 2008;Zhu & Newell, 1998). The magnitude and duration of the moisture flux directly relates to the intensity of precipitation with the highest precipitation rates being associated with strong, prolonged ARs (Eiras- Barca et al., 2021;Konrad & Dettinger, 2017;Prince et al., 2021;Ralph et al., 2019). Given the association between ARs and precipitation, the occurrence of ARs brings the potential for substantial environmental and socioeconomic impacts (Corringham et al., 2019). On the West Coast of the U.S., landfalling ARs are the primary cause of flooding with ∼90% of all floods occurring during ARs (Dettinger et al., 2011;Paltan et al., 2017). The occurrence of these hydrological extremes often results in damage to property and infrastructure, a noteworthy event being the damage to the Oroville Dam in northern California resulting in mass evacuations and financial damages exceeding USD$1 billion