Journal of Geophysical Research: Atmospheres最新文献

Cloud radiative effects (CREs) and cloud-type mean CREs depend upon how clear-sky fluxes are computed over a large area: those of the immediate environment of clouds or the regional mean clear-sky fluxes. Five convectively active regions in the Tropics, two over land (Africa and Amazon) and three over ocean (eastern and western Pacific and Atlantic), are selected to understand the influence of immediate environment of clouds on CREs. Fluxes derived from 19 years of high-resolution CERES satellite data, categorized by cloud type, are utilized. The cloud types are classified based on the joint cloud top pressure and cloud optical depth distribution. For the entire tropical region, differences in cloud-type mean CRE with regional mean and immediate environment clear skies range from −7.8 to 10.7 Wm⁻² for shortwave (SW), 2.9 to 15.8 Wm⁻² for longwave (LW), and 6.1 to 17.9 Wm⁻² for net, respectively. The oceanic and Amazonia regions have negative (positive) SW (LW) CRE differences, typically 2–6 Wm⁻² in SW but 7–10 Wm⁻² in LW, whereas Africa has positive SW and LW CRE differences (typically 20–30 Wm⁻², up to 40–50 Wm⁻²). The influence of immediate environment reduces the regionally averaged, that is, cloud-type mean CREs weighted by cloud fractions, SW cloud cooling, and LW cloud warming in four of the five regions except for Africa. For Africa, it increases the SW cloud cooling and greatly reduces the LW cloud warming, resulting in net cloud cooling as in other regions instead of warming. The implications of these findings for observational and modeling studies are discussed.

Cloud condensation and hydrometeor evaporation fractionate stable isotopes of water, enriching liquid with heavy isotopes; whereupon updrafts, downdrafts, and rain vertically redistribute water and its isotopes in the lower troposphere. These vertical water fluxes through the marine boundary layer affect low cloud climate feedback and, combined with isotope fractionation, are hypothesized to explain the depletion of tropical precipitation at higher precipitation rates known as the “amount effect.” Here, an efficient and numerically stable quasi-analytical model simulates the evaporation of raindrops and enrichment of their isotope composition. It is applied to a drop size distribution and subcloud environment representative of Atlantic trade cumulus clouds. Idealized physics experiments artificially zero out selected processes to discern the separate effects on the isotope ratio of raindrops, of exchange with the environment, evaporation, and kinetic molecular diffusion. A parameterization of size-dependent molecular and eddy diffusion is formulated that enriches raindrops much more strongly (+5‰ for deuterated water [HDO] and +3.5‰ for $��H_2^{18}�$O) than equilibrium evaporation as they become smaller than 1 mm. The effect on evaporated vapor is also assessed. Rain evaporation enriches subcloud vapor by +12‰ per mm rain (for HDO), explaining observations of enriched vapor in cold pools sourced by evaporatively cooled downdrafts. Drops smaller than 0.5 mm evaporate completely before falling 700 m in typical subtropical marine boundary layer conditions. The early and complete evaporation of these smaller drops in the rain size distribution enriches the vapor produced by rain evaporation.

The Gobi Desert is a prominent dust source in Asia, where the dust storm is severe and features great interannual and seasonal variability. Previous studies have found land surface variation plausibly plays an important role in the occurrence and intensity of dust storms. However, the quantitative estimation and numerical description in current models are still limited. Here, a comprehensive study utilizing multiple observations and modeling methods to assess the influence of vegetation and snow on dust was conducted. We found that Gobi deserts exhibit substantial monthly and interannual variability in dust storms, which shows a close connection with vegetation and snow. To quantitatively understand the impact of vegetation and snow cover on dust emissions and also to better characterize such effects in numerical models, we introduced a high-resolution dynamic dust source function that incorporates the effects of vegetation and snow on erodibility. The new parameterization noticeably improved dust-related simulations, including aerosol optical thickness and PM₁₀ concentrations, and provided insights into the distinct effects of vegetation and snow on dust emissions. This study sheds light on the effects of vegetation and snow on dust storms over the Gobi Desert, highlighting the importance of dynamic representation of time-varying surface properties in dust simulation.

During the summer season, deep convection over the central United States has a significant impact on the dynamics and composition of the upper troposphere and lower stratosphere (UTLS). These storms transport tropospheric air containing trace gases, ice particles, and aerosols into the UTLS, which can affect chemical and radiative processes over a large region. Because overshooting storms necessarily have strong updrafts, there is a marked correlation between overshooting and the occurrence of severe weather at the surface. Heat released by these storms also helps to drive the North American Monsoon Anticyclone (NAMA) in the UTLS, which partially confines air injected into the stratosphere by overshooting storms. In support of the Dynamics and Chemistry of the Summer Stratosphere (DCOTSS) project, this study is a climatological analysis of the environmental factors that affect the occurrence of deep and overshooting storms. Using hourly analyses of overshooting storms based on GridRad radar data and ERA5 reanalyzes, we focus on the roles of convective available potential energy (CAPE), convective inhibition (CIN), jet location, and other relevant dynamical and thermodynamic variables. The results show that northward intrusion of airmasses containing moist high CAPE air from the Gulf of Mexico into the central plains plays a major role in producing the conditions necessary for overshooting storms with other factors playing secondary roles.

Severe convection, responsible for hazards such as tornadoes, flash floods, and hail, is usually preceded by abundant convective available potential energy (CAPE). In this work, we use a Lagrangian approach to study the buildup of anomalously large values of CAPE from 2012 to 2013 in various regions. Nearly all extreme values of CAPE arise from surface fluxes underneath a layer of convective inhibition (the CIN layer) over several diurnal cycles, but the origin of the CIN layer and the diurnal cycle of surface fluxes differ around the world. In some regions, such as North America and Europe, the air above the boundary layer must be much warmer than usual to form this CIN layer, whereas in other regions, especially the Middle East and central Africa, a CIN layer is common. Additionally, high CAPE occurrences that are over land (those in the Americas, Europe, Africa, and Southeast Asia) tend to lose their CIN layers before the time of maximum CAPE due to large diurnal cycles of sensible heating, whereas those that occur over coastal waters (in the Middle East, Northern Australia, South Asia, and the Mediterranean) usually retain substantial convective inhibition. Uniquely, CAPE in Southeast Australia often builds up due to cooling aloft rather than to boundary layer warming. These results show that one hoping to understand or predict CAPE patterns must understand a variety of mechanisms acting in different regions.

In this study, a record-breaking surface gust wind event of over 45 m s⁻¹, which occurred in the coastal region of East China during the early evening hours of 30 April 2021, is examined. The dynamical characteristics of this event is explored by using a high-resolution mesonet comprised of eight radar wind profilers (RWPs), surface observations, radar and satellite data. Observational analyses show the development of several cloud clusters ahead of the axis of a midlevel trough with pronounced baroclinicity, and the subsequent organization into a comma-shaped squall system with a leading convective line over land and a trailing stratiform region moved offshore. The latter is embedded by a mesovortex with intense northerly rear inflows descending to the surface, accounting for the generation of the gusty winds. Results indicate the different roles of multi-scale processes in accelerating the surface winds to extreme intensity. Specifically, the large-scale baroclinic trough provides intense background rear inflows that are enhanced by the formation of the mesovortex, while moist downdrafts in the rear inflows account for the downward transport of horizontal momentum, leading to the generation of intense cold outflows and gusty winds close to the leading convective line. Despite the lack of sufficient observations for quantitative analysis, this study provides a qualitative analysis that offers valuable insights into the dynamics of extreme gusty winds. Moreover, the above results underscore the value of RWP mesonet observations in enhancing our understanding of extreme wind events and in improving the nowcasting and prediction efforts in the future.

Globally, increasing occurrences of forest fires are major threats to the ecosystem. The rich forests in the Himalayas also suffer from high incidents of forest fires in the pre-monsoon summer months, March to June. Research studies are limited in identifying the meteorological factors governing the spatiotemporal distribution of forest fires. Using three satellite-based data sets of monthly burned area (BA) for March to June, we found higher BA in the Eastern Himalayas (EH) compared to the Central (CH) and Western Himalayas (WH). Using statistical methods, we found Vapor Pressure Deficit (VPD) to be the most dominating variable controlling BA in the Himalayas. Precipitation, soil moisture and temperature, with their relative variability, control VPD that governs the interannual and intraseasonal variations of BA. Our results imply that a good forecast of VPD will facilitate alert generation for the Himalayan forest fires.

The uncertainty of climate projection is significantly related to warm cloud feedback, which involves a complex interplay of various mechanisms. However, it is hard to unentangle temperature's impact on a single cloud with experiments, since the cloud dynamics always covary with environmental thermodynamical conditions. In this study, we investigate a simulated single shallow cumulus cloud's response to temperature using two perturbation methods, namely “uniform” and “buoyancy-fixed”, the latter of which keeps the buoyancy profile unchanged in temperature perturbation. High-resolution large eddy simulations show that uniform warming significantly increases cloud buoyancy, reducing cloud adiabaticity. If buoyancy is fixed, warming only reduces cloud area, leaving adiabatic fraction almost unchanged. Such a response can be explained by the Clausius-Clapeyron effect with an idealized 1D diffusion model, showing that warming increases the cloud-environment absolute humidity difference more than the increase in cloud liquid water content, resulting in a faster loss in both cloud coverage and total liquid water solely by lateral mixing. The responses of cloud coverage and total liquid water counteract, making adiabatic fraction insensitive to temperature change. Our work shows that the cloud adiabatic fraction's response to temperature is sensitive to the perturbed structure of the boundary layer, and the cloud coverage reduction by diffusion acts as a positive cloud feedback mechanism in addition to the adjustment processes of the boundary layer.