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Aided by progress in the theoretical understanding, new knowledge on tropical rainfall annual cycle changes under global warming background has been advanced in the past decade. In this review, we focus on recent advances in understanding the changes of tropical rainfall annual cycle, including its four distinct features: amplitude, pattern shift, phase and wet/dry season length changes. In a warming climate, the amplitude of tropical rainfall annual cycle is enhanced, more evidently over ocean, while the phase of tropical rainfall annual cycle is delayed, mainly over land. The former is explained by the wet-get-wetter mechanism and the latter is explained by the enhanced effective atmospheric heat capacity and increased convective barrier. The phase delay over land has already emerged in the past four decades. The pattern shift under warming is marked by two features: equatorward shift of the inter-tropical convergence zone throughout the year and the land-to-ocean precipitation shift in the rainy season. The former is explained by the upped-ante mechanism and/or related to the enhanced equatorial warming in a warmer world. The latter is suggested to be caused by the opposite land and ocean surface temperature annual cycle changes in the tropics. Over tropical rainforest regions such as Amazon and Congo Basin, the dry season has lengthened in the recent decades, but the fundamental reason is still unclear. Despite the notable progress of the last decade, many gaps remain in understanding the mechanism, quantifying and attributing the emergence, narrowing the inter-model uncertainty, and evaluating the impact of tropical rainfall annual cycle changes, motivating future work guided by some directions proposed in this review.

Seasonal snow is an integral part of the global water supply and storage system. Snow droughts impact ecological, agricultural, and urban systems by altering the amount and timing of meltwater delivery. These droughts are characterized by a lack of on-the-ground snow (snow water equivalent, SWE) that can be caused by low total precipitation (dry drought) or low proportion of precipitation falling as snowfall (warm drought), often combined with an early melt. The standardized SWE index (SWEI) ranks the current status of SWE for a given location compared to a baseline condition and identifies the existence, but not the cause, of snow drought. In this work, we use estimates of SWE, temperature, and precipitation from nine coupled model intercomparison project phase 6 (CMIP6) models to quantify the frequency, severity, and type of snow droughts globally for historical and future scenarios. Compared to a historical baseline (1850–1900) total snow drought frequency more than doubles under socio-economic pathway (SSP)2-4.5 and SSP5-8.5; all of the increase in snow drought frequency comes from an increase in warm droughts. The probability distribution of future SWEI in major snowy basins around the world are likely to be centered on more negative values, which corresponds to more severe drought and, with only moderate changes in distribution spread, more frequent drought. CMIP6 simulations pinpoint snow drought as an emerging global threat to water resources and highlight the need to explore higher resolution future models that better capture complex mountain topography, wildland fires, and snow-forest interactions.

Surface ozone is substantially affected by climate change through the modulation of key meteorological parameters such as temperature. While the changes in temperature under a warming climate manifest in changes of both the mean and higher-order statistical moments, their individual role in ozone concentration changes has not been broadly investigated. To address this gap, we use a novel approach to isolate the impacts of mean warming and changes in higher-order moments of temperature on ozone over the southeastern U.S. (SEUS) and western U.S. (WUS) by the mid-21st century based on simulations under Technology Driver Model A1B and B2 scenarios from a regional modeling framework (Weather Research and Forecasting model coupled with Chemistry (WRF/Chem)). Mean warming generally dominates the impacts of climate change on ozone, and higher-order moment temperature changes can also counteract 25% of the ozone exceedance of 70 ppbv over SEUS, and may offset 48% of the mean warming induced increase of ozone exceedance in heat waves during 2046–2055 under A1B. The opposite changes in the higher-order moments over SEUS and WUS lead to opposite impacts on ozone exceedance in the two regions. Our results suggest that improving prediction of both the mean and higher-order temperature changes may be crucial to constraining the future changes in ozone concentration to better inform air quality policy.

Temperature and water vapor have been considered as important factors affecting ozone concentrations, however, their synergistic effect on ozone, as well as its response to a warming climate remains unclear. Here, numerical experiments with different combinations of climate and emissions highlighted opposite changes of annual ozone over the contiguous U.S. under scenarios with high vs. low ozone precursor emissions in the future with warming. Comparing the occurrence of heat waves on higher vs. lower ozone days, we found significant suppression of the heat wave exacerbation of ozone by anthropogenic emissions reductions. Variations of ozone with temperature ( T ) and water vapor ( Q ) over the western U.S. and southeastern U.S. in the simulations are clearly revealed through the construction of an O _3 - T-Q diagram. Based on the diagram, we further identified a T -dominant regime at higher temperatures where ozone increases with temperature increase, and a Q -dominant regime at lower temperatures where ozone decreases with temperature increase due to the negative effect of water vapor. With larger anthropogenic emission reductions, ozone may increase at a lower rate with temperature in the T -dominant regime, or even decrease with temperature in the Q -dominant regime. Our results show that with large emission reductions, substantial ozone pollution due to warming and increasing heat waves may be counteracted by water vapor, partly turning the ‘climate penalty’ on ozone into ‘climate benefit’. Hence controlling anthropogenic emissions may be an increasingly important strategy in a warmer and wetter climate to improve air quality and public health.

Land aridity is often characterized by the aridity index (AI), which does not account for land surface water-energy interactions that are crucially important in determining regional climate. Such interactions can be captured by the evaporative fraction (EF, ratio of evapotranspiration to available energy) regimes. As EF is subject to energy and water limitations in humid and dry areas, respectively, EF regimes may be used to characterize land aridity to account for the influence of complex land characteristics and their impact on water availability. Here, we propose a simple framework to characterize land aridity by statistically ranking the coupling strength between EF and surface energy and water terms. The framework is demonstrated using gridded data and compared with AI over the U.S. and China. Results show that regionalization of aridity zones based on EF regimes and a two-tiered classification scheme may provide information such as surface energy and water variability complementary to the background aridity depicted by AI, with implications for extreme events.

Soil erosion delivers enormous amounts of macro-nutrients including nitrogen (N) and phosphorus (P) from land to rivers, potentially sustaining water column bioavailable nutrient levels for decades. In this study, we represent erosional N and P fluxes in the Energy Exascale Earth System Model (E3SM) and apply the model to the continental United States. We estimate that during 1991–2019 soil erosion delivers 775 Gg yr ^−1 (1 Gg = 10 ^9 g) of particulate N (PN) and 328 Gg yr ^−1 of particulate P (PP) on average to the drainage basins of the northern Gulf of Mexico, including the Mississippi/Atchafalaya River and other rivers draining to the Texas Gulf and the Eastern Gulf. Our model simulation shows that in these rivers PP is the dominant P constituent and over 55% of P exported by erosion comes from soil P pools that could become bioavailable within decades. More importantly, we find that during 1991–2019 erosional N and P fluxes increase at rates of about 15 Gg N yr ^−1 and 6 Gg P yr ^−1 , respectively, due to increased extreme rains in the Mississippi/Atchafalaya river basin, and this intensification of erosional N and P fluxes drive the significant increase of riverine PN and PP yields to the northern Gulf of Mexico. With extreme rains projected to increase with warming, erosional nutrient fluxes in the region would likely continue to rise in the future, thus complicating the effort of reducing eutrophication in the inland and coastal waters.

This study investigated the anthropogenic influence on the temporal variability of annual precipitation for the period 1950–2005 as simulated by the CMIP5 models. The temporal variability of both annual precipitation amount (PRCPTOT) and intensity (SDII) was first measured using a metric of statistical dispersion called the Gini coefficient. Comparing simulations driven by both anthropogenic and natural forcing (ALL) with simulations of natural forcing only (NAT), we quantified the anthropogenic contributions to the changes in temporal variability at global, continental and sub-continental scales as a relative difference of the respective Gini coefficients of ALL and NAT. Over the period of 1950–2005, our results indicate that anthropogenic forcing have resulted in decreased uniformity (i.e. increase in unevenness or disparity) in annual precipitation amount and intensity at global as well as continental scales. In addition, out of the 21 sub-continental regions considered, 14 (PRCPTOT) and 17 (SDII) regions showed significant anthropogenic influences. The human impacts are generally larger for SDII compared to PRCTOT, indicating that the temporal variability of precipitation intensity is generally more susceptible to anthropogenic influence than precipitation amount. The results highlight that anthropogenic activities have changed not only the trends but also the temporal variability of annual precipitation, which underscores the need to develop effective adaptation management practices to address the increased disparity.

Despite the importance of surface water to people and ecosystems, few studies have explored detectable changes in surface water supply in a changing climate, given its large natural variability. Here we analyze runoff projections from the Variable Infiltration Capacity hydrological model driven by 97 downscaled and bias-corrected Coupled Model Intercomparison Project Phase 5 climate projections over the conterminous United States (CONUS). Our results show that more than 40% of the CONUS land area will experience significant changes in the probability distribution functions (i.e. PDFs) of summer and winter runoff by the end of the 21st century, which may pose great challenges to future surface water supply. Sub-basin mean runoff PDFs are projected to change significantly after 2040s depending on the emission scenarios, with earliest occurrence in the Pacific Northwest and northern California regions. When examining the response as a function of changes in the global mean temperature (ΔGMT), a linear relationship is revealed at the 95% confidence level. Generally, 1 °C increase of GMT leads to 11% and 17% more lands experiencing changes in summer and winter runoff PDFs, respectively. Such changes in land fraction scale with ΔGMT at the country scale independent of emission scenarios, but the same relationship does not necessarily hold at sub-basin scales, due to the larger role of atmospheric circulation changes and their uncertainties on regional precipitation. Further analyses show that the emergence of significant changes in sub-basin runoff PDFs is indicative of the emergence of new hydrology regimes and it is dominated by the changes in variability rather than shift in the mean, regardless of the emission scenarios.

This study examines future changes of cold air outbreaks (CAOs) using a multi-model ensemble of global climate simulations from the Coupled Model Intercomparison Project Phase 5 and high resolution regional climate simulations. Overall, climate models agree on a dip in CAO duration across North America, but the percentage change is consistently smaller from western Canada to the upper mid-western US with historically more frequent CAO. By decomposing the changes of the probability density function of daily surface temperature into changes due to mean warming and changes in standard deviation (std) and skewness/higher order moments, the contributions of each factor to CAO changes are quantified. Results show that CAO changes can be explained largely by the mean warming, but the decrease in temperature std contributes to about 20% reduction of CAO from Alaska to northeastern US and eastern Canada possibly due to the Arctic amplification and weakening of storm track. A thermodynamical modulation of the skewness called the ‘0 °C mode’ effect is found to operate prominently along the 0 °C isotherm hemispherically and reduce CAO in western and northeastern US with winter snow cover by up to 10%. This effect also produces a manifold increase in CAO events over the Arctic sea ice. An increased frequency in atmospheric blocking also contributes to increases in CAO duration over Alaska and the Arctic region. Regional simulations revealed more contributions of existing snowpack to CAO in the near future over the Rocky Mountain, southwestern US, and Great Lakes areas through surface albedo effects. Overall, the multi-model projections emphasize that cold extremes do not completely disappear in a warming climate. Concomitant with the relatively smaller reduction in CAO events in northwestern US, the top five most extreme CAO events may still occur, and wind chill will continue to have societal impacts in that region.

Sea surface temperature (SST) is not the only oceanic parameter that can play a key role in the interannual variability of Northeast Pacific hurricane activity. Using several observational data sets and the statistical technique of multiple linear regression analysis, we show that, along with SST, the thermocline depth (TD) plays an important role in hurricane activity at interannual timescales in this basin. Based on the parameter that dominates, the ocean basin can be divided into two sub-regions. In the Southern sub-region, which includes the hurricane main development area, interannual variability of the upper-ocean heat content (OHC) is primarily controlled by TD variations. Consequently, the interannual variability in the hurricane power dissipation index (PDI), which is a measure of the intensity of hurricane activity, is driven by that of the TD. On the other hand, in the Northern sub-region, SST exerts the major control over the OHC variability and, in turn, the PDI. Our study suggests that both SST and TD have a significant influence on the Northeast Pacific hurricane activity at interannual timescales and that their respective roles are more clearly delineated when sub-regions along an approximate north–south demarcation are considered rather than the basin as a whole.