The arid region of Northwest China and Mongolia (NCM) receives most of the precipitation in the summer. The need for a better understanding of the synoptic-scale mechanism responsible for precipitation formation is accentuated by the recent wetting trend and its implications for future hydroclimate change. By conducting a hierarchical clustering analysis on an observationally-based daily precipitation dataset, we show that there are three distinct precipitation patterns over NCM, one of which is associated with strong precipitation over the western part of the region and another over the eastern part. The corresponding large-scale circulation anomalies indicate that these strong precipitation events are triggered by the upper-tropospheric disturbances in the form of transient Rossby wave packets. Furthermore, the wetting trend is linked to more frequent strong precipitation events over the eastern NCM, suggesting that it may have been induced remotely by atmospheric circulation perturbations.

We evaluate cloud simulations using satellite simulators against multiple observational datasets. These simulators have been run within the Geophysical Fluid Dynamics Laboratory’s Atmosphere Model version 4.0 (AM4.0), as well as an alternative configuration where a two-moment Morrison-Gettelman bulk cloud microphysics with prognostic precipitation (MG2) is applied, denoted as AM4-MG2. The modelled cloud spatial distributions, vertical profiles, phase partitioning, cloud-to-precipitation transitions, and radiative effects from AM4.0 and AM4-MG2 compare reasonably well with satellite observations. Model biases include the underestimate of total and low-level clouds, especially optically thin/intermediate clouds, but the overestimate of optically thick clouds, indicating “too few, too bright’ biases. These biases compensate each other and result in reasonable estimates of cloud radiative effects. The underestimate of low-level clouds is associated with too frequent and too early drizzle/precipitation formation. The precipitation bias is improved in AM4-MG2, where the autoconversion scheme initiates the precipitation more realistically.

Global kilometer-scale models are the future of Earth system models as they can explicitly simulate organized convective storms and their associated extreme weather. Here, we comprehensively examined tropical mesoscale convective system (MCS) characteristics in the DYAMOND (DYnamics of the atmospheric general circulation modeled on non-hydrostatic domains) models for both summer and winter phases by applying eight different feature trackers to the simulations and satellite observations. Although different trackers produce substantial differences (a factor of 2-3) in observed MCS frequency and their contribution to total precipitation, model-observation differences in MCS statistics are more consistent among the trackers. DYAMOND models are generally skillful in simulating tropical mean MCS frequency, with multi-model mean biases of 2.9% over land and -0.5% over ocean. However, most models underestimate the MCS precipitation amount (23%) and their contribution to total precipitation (17%) relative to observations. These biases show large inter-model variability, but are generally smaller over land (13%) than over ocean (21%) on average. MCS diurnal cycle and cloud shield characteristics are better simulated than precipitation. Most models overestimate MCS precipitation intensity and underestimate stratiform rain contribution (up to a factor of 2), particularly over land. Models also predict a wide range of precipitable water in the tropics compared to reanalysis and satellite observations, and many models simulate a greater sensitivity of MCS precipitation intensity to precipitable water. The MCS metrics developed in this work provide process-oriented diagnostics for future model development efforts.

The initiation of springtime mesoscale convective systems (MCSs) over the U.S. Great Plains is strongly supported by synoptically forced uplift. In this study, we first quantify these uplift mechanisms by numerically solving the quasi-geostrophic omega equation in Q-vector form. To provide a process-based assessment, Q vectors are decomposed into shearwise and transverse components, representing changes in the direction and magnitude of the potential temperature gradient along the geostrophic motion. The composite analysis reproduces the upper- and lower-tropospheric synoptic conditions favorable for MCS initiation, which have been well documented in the literature. We reveal that shearwise ascent, induced by a baroclinically organized trough–ridge couplet, is the leading contributor to total dynamical ascent. The contribution of an upper-level jet, which induces upward motion in its right entrance region through geostrophic frontogenesis by confluent motion, is minor as indicated by weaker transverse ascent. Likewise, the lower-tropospheric transverse ascent, induced by warm frontogenesis at the exit of the Great Plains low-level jet, plays a secondary role compared to shearwise ascent. Furthermore, MCSs initiated under stronger shearwise ascent tend to grow into larger, more precipitating storms, while no significant sensitivity to initial transverse ascent is observed throughout the MCS lifecycle. This study underscores the critical role of baroclinic wave amplification not only in the genesis but also in the subsequent evolution of MCSs, offering operational insights for their prediction.

Precipitation changes under global warming are widely studied. However, the direct radiative effect of CO2 on precipitation changes, independent from CO2-induced SST changes, has received less attention. Mechanistic understanding of the CO2 direct effect is therefore important and necessary. Utilizing multiple global atmospheric models, we identify robust summer precipitation changes across North America in response to the direct CO2 forcing. We find that spatial distribution of CO2 forcing at land surface is primarily shaped by climatological distribution of water vapor and clouds. This, coupled with changes in convection and moisture supply resulting from CO2-induced circulation changes, largely determines North America hydroclimate changes. In central North America, increasing CO2 decreases summertime precipitation by warming the surface and inducing dry advection into the region to reduce moisture supply. Meanwhile, for the southwest and the east, CO2-induced northward shift of subtropical highs generates wet advections to mitigate the drying effect from surface warming.

Changes in precipitation extremes remain a key uncertainty as the climate warms. Improved understanding of their evolution is crucial for effective water management. A number of studies have demonstrated various scaling relationships between precipitation extremes and several different environmental variables. In this chapter, we review recent important advances in two of these relationships primarily based on observations: The scaling of precipitation extremes with surface temperature (both air temperature and dew point temperature) and convective available potential energy (CAPE). Two up-to-date global daily datasets are also used to provide a further check on the generality of earlier findings. Known scaling relationships are used to quantify the impacts of these two factors on precipitation extremes. Results show that both of them play important roles, but their impacts vary over different regions on various time scales, highlighting the challenges of constructing global relationships to explain the changing nature of precipitation extremes.