The increase in intense tropical cyclone (TC) activity across the western North Pacific (WNP) has often been attributed to a warming ocean. However, it is essential to recognize that the tropical WNP region already boasts high temperatures, and a marginal increase in oceanic warmth due to global warming does not exert a significant impact on the potential for TCs to intensify. Here we report that the weakened vertical wind shear is the primary driver behind the escalating trend in TC intensity within the summer monsoon trough of the tropical WNP, while local ocean surface and subsurface thermodynamic factors play a minor role. Through observational diagnoses and numerical simulations, we establish that this weakening of the vertical wind shear is very likely due to the increase in temperature of the Tibetan Plateau. With further warming of the Tibetan Plateau under the Representative Concentration Pathway 4.5 scenario, the projected TCs will likely become stronger.

This study characterizes major modes of variability in the spring and summer U.S. dryness, as measured by the seasonal total number of dry (no‐precipitation) days, and assesses the impact of the Pacific sea surface temperature. The most severe spring and summer dry conditions typically occur in the western United States. Maximum covariance analysis reveals that the Pacific Decadal Oscillation (PDO) is the primary driver of interannual variability in the U.S. dryness. El Niño–Southern Oscillation (ENSO) also contributes in part (especially during spring). Beyond the PDO and ENSO impact, interannual variations in spring dryness exhibit a meridional dipole structure, while variations during summer are related to a northwest‐southeast (NW‐SE) oriented dipole. The spring meridional dipole is associated with circulation anomalies resembling the West Pacific teleconnection pattern, while the summer NW‐SE dipole is a downstream manifestation of a quasi‐stationary wave train. A parallel analysis of Coupled Model Intercomparison Project's fifth phase models' historical simulations demonstrates that such models generally capture the relation between U.S. dryness and the PDO, albeit with varying degrees of accuracy. The models also show reasonable skill in simulating the residual meridional dipole in spring dryness variability but have difficulty representing the NW‐SE oriented dipole occurring during summer. The model shortcomings isolated here largely arise from a misrepresentation of the corresponding large‐scale circulation and moisture transport anomalies. These model biases suggest that great challenges exist in our ongoing pursuit of reliable projections of the U.S. hydroclimate variability.

Warm season dry spells over the central and eastern United States are classified into three canonical types via a hierarchical cluster analysis for the period 1950–2005. Four CMIP5 models exhibit diverging skill in representing the observed behavior, ranging from southern Great Plains dry spells that are reasonably simulated by all four models to southeastern U.S. dry spells that are only accurately captured by one model. A model’s skill in representing a particular dry spell cluster is positively correlated with the model’s ability to simulate the large-scale meteorological patterns (LMPs) accompanying the dry spell. The interannual variability and overall observed decreasing trend in dry spell days are represented with varying degrees of accuracy by the four models. The results 1) highlight existing shortcomings in the climate model representation of regional dry spells and 2) illustrate the importance of properly simulating the observed spectrum of LMPs in minimizing these shortcomings.

The Pacific–North America–North Atlantic sector in general experienced a dryer and warmer climate in summer during the past 40 years. These changes are partly associated with declining midlatitude synoptic variability in boreal summer, especially over the two ocean basins. A nonmodal instability analysis of the boreal summer background flow is conducted for two periods, 1979–94 and 2000–15, to understand dynamical processes potentially responsible for the observed decline of synoptic variability. The synoptic variability associated with fast, nonmodal growth of atmospheric disturbances shows a decline over northern midlatitudes in the later period, in both a barotropic model and a two-level quasigeostrophic model. These results highlight the importance of the changing summer background flow in contributing to the observed changes in synoptic variability. Also discussed are factors likely associated with background flow changes including sea surface temperature and sea ice change.

The Colorado River is one of the most important rivers in the southwestern U.S., with ~ 90% of the total flow originating from the Upper Colorado River Basin (UCRB). The UCRB April–July streamflow is well-correlated to the UCRB spring precipitation. It is known that the UCRB precipitation is linked to an El Niño-like sea surface temperature (SST) pattern, but the causal effect of the tropical Pacific SST on the UCRB spring precipitation is still uncertain. Here, we apply a Granger causality approach to understand the causal effect of the tropical Pacific averaged SST in previous three seasons (winter, fall, and summer) on the UCRB averaged precipitation in spring in observations and two climate models. In observations, only the winter SST has Granger causal effect (withp-value ~ 0.05) on spring precipitation, while historical simulations of the two climate models overestimate the causal effect for winter and fall (withp-value < 0.01 and < 0.05, respectively) due to model biases. Moreover, future projections of the two climate models show divergent causal effects, especially for the scenario with high anthropogenic emissions. The divergent projections indicate that (1) there are large uncertainties in model projections of the causal effect of the tropical Pacific SST on UCRB spring precipitation and (2) it is uncertain whether climate models can reliably capture changes in such causality. These uncertainties may result in large uncertainties in seasonal forecasts of the UCRB hydroclimate under global climate change.