Lower Tropospheric Stability Research Articles

The Increasing Efficiency of the Poleward Energy Transport Into the Arctic in a Warming Climate

AbstractThis study quantifies the contribution to Arctic winter surface warming from changes in the tropospheric energy transport (Ftrop) and the efficiency with which Ftrop heats the surface in the RCP8.5 warming scenario of the Community Earth System Model Large Ensemble. A metric for this efficiency, Etrop, measures the fraction of anomalous Ftrop that is balanced by an anomalous net surface flux (NSF). Drivers of Etrop are identified in synoptic‐scale events during which Ftrop is the dominant driver of NSF. Etrop is sensitive to the vertical structure of Ftrop and pre‐existing Arctic lower‐tropospheric stability (LTS). In RCP8.5, winter‐mean Ftrop decreases from 95.1 to 85.4 W m−2, while Etrop increases by 5.7%, likely driven by decreased Arctic LTS, indicating an increased coupling between Ftrop and the surface energy budget. The net impact of decreasing Ftrop and increasing efficiency is a positive 0.7 W m−2 contribution to winter‐season surface heating.

Low‐Level Marine Tropical Clouds in Six CMIP6 Models Are Too Few, Too Bright but Also Too Compact and Too Homogeneous

AbstractSeveral studies have shown that most climate models underestimate cloud cover and overestimate cloud reflectivity, particularly for the tropical low‐level clouds. Here, we analyze the characteristics of low‐level tropical marine clouds simulated by six climate models, which provided COSP output within the CMIP6 project. CALIPSO lidar observations and PARASOL mono‐directional reflectance are used for model evaluation. It is found that the “too few, too bright” bias is still present for these models. The reflectance is particularly overestimated when cloud cover is low. Models do not simulate any optically thin clouds. They fail to reproduce the increasing cloud optical depth with increasing lower tropospheric stability as observed. These results suggest that most models do not sufficiently account for the effect of the small‐scale spatial heterogeneity in cloud properties or the variety of cloud types at the grid scale that is observed.

Stability-dependent increases in liquid water with droplet number in the Arctic

Abstract. The effects of aerosols on cloud microphysical properties are a large source of uncertainty when assessing anthropogenic climate change. The aerosol–cloud relationship is particularly unclear in high-latitude polar regions due to a limited number of observations. Cloud liquid water path (LWP) is an important control on cloud radiative properties, particularly in the Arctic, where clouds play a central role in the surface energy budget. Therefore, understanding how aerosols may alter cloud LWP is important, especially as aerosol sources such as industry and shipping move further north in a warming Arctic. Using satellite data, this work investigates the effects of aerosols on liquid Arctic clouds over open ocean by considering the relationship between cloud droplet number concentration (Nd) and LWP, an important component of the aerosol–LWP relationship. The LWP response to Nd varies significantly across the region, with increases in LWP with Nd observed at very high latitudes in multiple satellite datasets, with this positive signal observed most strongly during the summer months. This result is in contrast to the negative response typically seen in global satellite studies and previous work on Arctic clouds showing little LWP response to aerosols. The lower tropospheric stability (LTS) was found to be an important control on the spatial variations in LWP response, strongly influencing the sign and magnitude of the Nd–LWP relationship, with increases in LWP in high-stability environments. The influence of humidity varied depending on the stability, with little impact at low LTS but a strong influence at high LTS. The mean Nd state does not dominate the LWP response, despite the non-linearities in the relationship. As the Nd–LWP sensitivity changed from positive to negative when moving from high- to low-LTS environments, this work shows evidence of a temperature-dependent aerosol indirect effect. Additionally, the LWP–LTS relationship changes with Nd, generating an aerosol-dependent cloud feedback. As the LTS is projected to decrease and the boundary layer to become more polluted in a future Arctic, these results show that aerosol increases may produce lower cloud water paths. This shift to more unstable environments implies that LWP adjustments shift from enhancing the Twomey effect by 8 % to offsetting it by around 40 %, with this warming effect having potential consequences for sea ice extent.

Study on the Characteristics of Aerosol Radiative Forcing under Complex Pollution Conditions in Beijing

Aerosol radiative effects usually have a heating effect on the atmosphere and a cooling effect on the surface, and they are also important uncertainty factors that cause climate change. Based on the Moderate-Resolution Imaging Spectrometer (MODIS) and Aerosol Optical Properties Observation Network (AERONET), a study on the distribution characteristics of aerosol optical depth (AOD) in Beijing was developed, and a method to calculate the regional aerosol direct radiative forcing (ADRF) was improved. ADRF was calculated for Beijing by inputting aerosol optical parameters and surface parameters based on this method. The results show that the MODIS AOD and AERONET AOD both reached the correlation coefficient of 0.9 at 412 nm, 470 nm and 660 nm. Additionally, the correlation coefficient of ADRF as calculated by SBDART reached 0.8 through verification with AERONET ADRF. In addition, the ADRF of the atmosphere (ATM) under different degrees of pollution in Beijing was also calculated; the results indicate that the aerosol radiative effect becomes more obvious with higher pollution degrees. Finally, the interaction between the relevant factors (relative humidity, lower troposphere stability and wind speed) and the aerosol radiative effect was analyzed. Studies have found that the aerosol radiative effect influences the occurrence and continuation of pollution and provides a supporting basis for preventing the occurrence of pollution and predicting the climate.

Factors affecting precipitation formation and precipitation susceptibility of marine stratocumulus with variable above- and below-cloud aerosol concentrations over the Southeast Atlantic

Abstract. Aerosol–cloud–precipitation interactions (ACIs) provide the greatest source of uncertainties in predicting changes in Earth's energy budget due to poor representation of marine stratocumulus and the associated ACIs in climate models. Using in situ data from 329 cloud profiles across 24 research flights from the NASA ObseRvations of Aerosols above CLouds and their intEractionS (ORACLES) field campaign in September 2016, August 2017, and October 2018, it is shown that contact between above-cloud biomass burning aerosols and marine stratocumulus over the Southeast Atlantic Ocean was associated with precipitation suppression and a decrease in the precipitation susceptibility (So) to aerosols. The 173 “contact” profiles with aerosol concentration (Na) greater than 500 cm−3 within 100 m above cloud tops had a 50 % lower precipitation rate (Rp) and a 20 % lower So, on average, compared to 156 “separated” profiles with Na less than 500 cm−3 up to at least 100 m above cloud tops. Contact and separated profiles had statistically significant differences in droplet concentration (Nc) and effective radius (Re) (95 % confidence intervals from a two-sample t test are reported). Contact profiles had 84 to 90 cm−3 higher Nc and 1.4 to 1.6 µm lower Re compared to separated profiles. In clean boundary layers (below-cloud Na less than 350 cm−3), contact profiles had 25 to 31 cm−3 higher Nc and 0.2 to 0.5 µm lower Re. In polluted boundary layers (below-cloud Na exceeding 350 cm−3), contact profiles had 98 to 108 cm−3 higher Nc and 1.6 to 1.8 µm lower Re. On the other hand, contact and separated profiles had statistically insignificant differences between the average liquid water path, cloud thickness, and meteorological parameters like surface temperature, lower tropospheric stability, and estimated inversion strength. These results suggest the changes in cloud microphysical properties were driven by ACIs rather than meteorological effects, and adjustments to existing relationships between Rp and Nc in model parameterizations should be considered to account for the role of ACIs.

On the relationship between convective precipitation and aerosol pollution in North China Plain during autumn and winter

Aerosols can modulate the convective cloud-precipitation system in complex ways, which was rarely investigated in North China during the heavily polluted autumn and winter. In this study, the relationships between aerosol pollution and convective precipitation in the North China Plain (112 to 116°E, 36 to 42°N) during autumn and winter were elucidated by combining the data of Global Precipitation Measurement Dual-Frequency Precipitation Radar (GPM-DPR) and the Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2). A positive correlation was found between the aerosol optical depth (AOD) and convective rain rate (RR). Comparative analyses between polluted and clean conditions were conducted to understand this AOD-RR relationship. Higher droplet concentration with smaller size were noted under the polluted condition, associated with higher latent heat released, implying that the increased aerosols may favor the development of the convective cloud-precipitation system through the “aerosol invigoration effect”. Besides, the impacts of ambient meteorological conditions on the AOD-RR relationship were also analyzed. It was found that correlations between AOD and RR were always positive in the studied region, irrespective of precipitable water vapor, lower tropospheric stability, and wind shear. A stronger AOD-RR correlation can be found when the lower tropospheric stability or wind shear becomes weaker. Our work provided evidence on the “aerosol invigoration effect” during the heavily polluted months in North China, which may improve the understanding of the complex interactions between aerosol and precipitation.

Diurnal climatology of correlations between the planetary boundary layer height and surface meteorological factors over the contiguous United States

AbstractThe correlations between the planetary boundary layer height (PBLH) and surface meteorological factors, including the surface wind speed (RWS), temperature (RTS), specific humidity (RSH), pressure (RPS), and lower tropospheric stability (RLTS), are investigated using hourly profiles from the Aircraft Meteorological Data Reports at 54 major airports over the contiguous United States (CONUS) and surface observations from weather stations. At the diurnal cycle, the RWS and RTS are positive and the RPS and RLTS are negative across the CONUS, while the RSH is negative over most areas but tends to be positive in the inland humid region. At the annual cycle, the correlations show significant diurnal variations that cannot be well captured by routine twice‐daily radiosonde data. The RWS is significantly positive at night but less significant during the daytime over most regions. The RTS and RSH are positive and the RPS and RLTS are negative at the daytime, which are of the opposite sign at the nighttime, with exceptions in some coastal areas. The diurnal variations of the correlations at the annual cycle also exhibit significant geographic variability, with the diurnal variation generally stronger in central eastern humid areas, weaker in some coastal areas, and moderate in relatively arid or mountain areas. This study highlights that the correlations between the PBLH and meteorological variables depend on the thermal stratification and are affected by the local hydrological and synoptic factors.

Multi‐Source Data Based Investigation of Aerosol‐Cloud Interaction Over the North China Plain and North of the Yangtze Plain

AbstractAlthough great progress has been made in the study of aerosol‐cloud interactions (ACIs), representation of ACI is still the largest uncertainty in current weather and climate models. In this study, the ACI over the North China Plain and north of the Yangtze Plain is investigated using multi‐source data including satellite, ground‐based, reanalysis, and fusion data. The effects of aerosol characteristics (PM2.5, PM10, and PM2.5/PM10 ratio), atmospheric conditions including liquid water path (LWP) and lower tropospheric stability (LTS), and drizzle on ACI are analyzed. Results suggest that both aerosol characteristics and atmospheric conditions can affect cloud effective radius (), but drizzle in clouds plays a decisive role on ACI. In the case of fixed LTS and LWP, the average cloud droplet increases first and then fluctuates for all clouds examined with the increase of PM2.5 concentration. The PM2.5 concentration corresponding to the turning point of increases with the increasing LWP due to the increased chance of collision and coalescence. In contrast, the average cloud droplet and PM2.5 concentration show a negative correlation for clouds without drizzle, which is mainly caused by competition of water vapor. The quantitative ACI results show that the values of the aerosol first indirect effect are negative for most cases when considering all clouds examined, but positive when only considering clouds without drizzle.

Characteristics of Summer Hourly Extreme Precipitation Events and Its Local Environmental Influencing Factors in Beijing under Urbanization Background

Studies on urban extreme precipitation and its influencing factors are significant for prevention and reduction of meteorological disasters; however, few studies focus on hourly extreme precipitation (HEP) events due to the limitation of observation. By using the summer hourly precipitation data in Beijing from 1980 to 2020, the spatial distribution and temporal variation of HEP as well as its local environmental influencing factors are investigated. It is found that both summer precipitation amount and frequency of HEP are affected by topography, with high values in windward slope area. The summer precipitation amount of HEP is 160–200 mm, accounting for 42–47% of the annual summer precipitation amount, while the frequency proportion of HEP is only 5.5–6.0%. Although the summer precipitation amount and frequency in Beijing both decrease in the past 41 years, those for HEP present an opposite trend mainly due to the increasing HEP since 2003 and this is a phenomenon worthy of attention. A similar bimodal pattern in diurnal variation is found for the summer precipitation amount and frequency of HEP, with two peaks in 19–22 LT and 01–05 LT, respectively, indicating that HEPs are more concentrated in the evening and early morning especially in urban area. Moreover, the urbanization process of Beijing is consistent with the change trend of HEP, implying that the stronger the urban heat island intensity (UHI), the higher the probability of HEP. Furthermore, the convergence lines of terrain are also conducive to local heavy rainfall, and lower tropospheric stability (LTS) and convective available potential energy (CAPE) as well as aerosols may also affect HEP in Beijing.

The Response of Cloud-Precipitation Recycling in China to Global Warming

Cloud water is an important geophysical quantity that connects the hydrological and radiation characteristics of climate systems and plays an essential role in the global circulation of the atmosphere, water, and energy. However, compared to the contribution of water vapor to precipitation, the understanding of cloud-precipitation transformation and its climate feedback mechanism remains limited. Based on precipitation and temperature datasets of the National Meteorological Observatory and MODIS (Moderate Resolution Imaging Spectroradiometer) satellite remote sensing products, the evolution characteristics of cloud water resources in China over the last twenty years of the 21st century were evaluated. Significant decreasing trends of −3.3 and −4.89 g/m2 decade−1 were found for both the liquid and ice water path. In humid areas with high precipitation, the cloud water path decreased fast. In semiarid areas with an annual precipitation ranging from 500–800 mm, the decreasing trend of the cloud water path was the lowest. The cloud-water period was calculated to represent the relative changes in clouds and precipitation. The national average cloud-water period in China is approximately 12.4 h, with obvious seasonal changes. Over the last 20 years, the cloud water path in dry regions decreased more slowly than that in wet regions, and the cloud-precipitation efficiency significantly increased, which narrowed the climate difference between the dry and wet regions. Finally, the mechanism of the cloud-water period evolution in the different regions were examined from the perspectives of the dynamic and thermal contributions, respectively. Due to the overall low upward moisture flux (UMF) in the dry region, the response of the cloud-water period to the lower tropospheric stability (LTS) mainly first increased and then decreased, which was the opposite in the wet region. The increase in cloud-precipitation efficiency in the dry region of Northwest China is accompanied by a continuous decrease in LTS. The different configurations of regional UMF and LTS play a crucial role in the evolution of cloud-precipitation, which can be used as a diagnostic basis to predict changes in the precipitation intensity to a certain extent.

Contrasting Observed Atmospheric Responses to Tropical Sea Surface Temperature Warming Patterns

AbstractEquilibrium climate sensitivity (ECS) is a theoretical concept which describes the change in global mean surface temperature that results from a sustained doubling of atmospheric CO2. Current ECS estimates range from ∼1.8 to 5.6 K, reflecting uncertainties in climate feedbacks. The sensitivity of the lower (1,000–700 hPa) and upper (500–200 hPa) troposphere to changes in spatial patterns of tropical sea surface temperature (SST) have been proposed by recent model studies as key feedbacks controlling climate sensitivity. We examine empirical evidence for these proposed mechanisms using 14 years of satellite data. We examine the response of temperature and humidity profiles, clouds, and top‐of‐the‐atmosphere radiation to relative warming in tropical ocean regions when there is either strong convection or subsidence. We find warmer SSTs in regions of strong subsidence are coincident with a decrease in lower tropospheric stability (−0.9 ± 0.4 KK−1) and low cloud cover (∼−6% K−1). This leads to a warming associated with the weakening in the shortwave cooling effect of clouds (4.2 ± 1.9 Wm−2K−1), broadly consistent with model calculations. In contrast, warmer SSTs in regions of strong convection are coincident with an increase in upper tropospheric humidity (3.2 ± 1.5% K−1). In this scenario, the dominant effect is the enhancement of the warming longwave cloud radiative effect (3.8 ± 3.0 Wm−2K−1) from an increase in high cloud cover (∼7% K−1), though changes in the net (longwave and shortwave) effect are not statistically significant (p < 0.003). Our observational evidence supports the existence of mechanisms linking contrasting atmospheric responses to patterns in SST, mechanisms which have been linked to climate sensitivity.

How Does the Relationship between Ambient Deep-Tropospheric Vertical Wind Shear and Tropical Cyclone Tornadoes Change between Coastal and Inland Environments?

AbstractThis work investigates how the relationship between tropical cyclone (TC) tornadoes and ambient (i.e., synoptic-scale) deep-tropospheric (i.e., 850–200-hPa) vertical wind shear (VWS) varies between coastal and inland environments. Observed U.S. TC tornado track data are used to study tornado frequency and location, while dropsonde and radiosonde data are used to analyze convective-scale environments. To study the variability in the TC tornado–VWS relationship, these data are categorized by both 1) their distance from the coast and 2) reanalysis-derived VWS magnitude. The analysis shows that TCs produce coastal tornadoes regardless of VWS magnitude primarily in their downshear sector, with tornadoes most frequently occurring in strongly sheared cases. Inland tornadoes, including the most damaging cases, primarily occur in strongly sheared TCs within the outer radii of the downshear-right quadrant. Consistent with these patterns, dropsondes and coastal radiosondes show that the downshear-right quadrant of strongly sheared TCs has the most favorable combination of enhanced lower-tropospheric near-surface speed shear and veering, and reduced lower-tropospheric thermodynamic stability for tornadic supercells. Despite the weaker intensity farther inland, these kinematic conditions are even more favorable in inland environments within the downshear-right quadrant of strongly sheared TCs, due to the strengthened veering of the ambient winds and the lack of changes in the TC outer tangential wind field strength. The constructive superposition of the ambient and TC winds may be particularly important to inland tornado occurrence. Together, these results will allow forecasters to anticipate how the frequency and location of tornadoes and, more broadly, convection may change as TCs move inland.

Strong Aerosol Effects on Cloud Amount Based on Long‐Term Satellite Observations Over the East Coast of the United States

AbstractHere, we use 16‐year satellite and reanalysis data in combination with a multivariate regression model to investigate how aerosols affect cloud fraction (CF) over the East Coast of the United States. Cloud droplet number concentrations (Nd), cloud geometrical thickness, lower tropospheric stability, and relative humidity at 950 hPa (RH950) are identified as major cloud controlling parameters that explain 97% of the variability in CF. Nd is shown to play an important role in regulating the dependence of CF on RH950. The observed annual‐mean CF shows no significant trend due to the cancellation from the opposite trends in Nd and RH950. The multivariate regression model revealed that the decline in Nd alone would lead to about a 20% relative decline in CF. Our results indicate the significant aerosol effects on CF and suggest the need to account for pollution‐induced cloud changes in quantifying cloud feedback based on long‐term observations.

Effective Radiative Forcing in a GCM With Fixed Surface Temperatures

AbstractEffective radiative forcing (ERF) is evaluated in the ACCESS1.0 General Circulation Model (GCM) with fixed land and sea‐surface‐temperatures (SST) as well as sea‐ice. The 4xCO2 ERF is 8.0 W m−2. In contrast, a typical ERF experiment with only fixed SST and sea‐ice gives rise to an ERF of only 7.0 W m−2. This difference arises due to the influence of land warming in the commonly used fixed‐SST ERF experimental design, which results in: (i) increased emission of longwave radiation to space from the land surface (−0.45 W m−2) and troposphere (−0.90 W m−2), (ii) reduced land snow‐cover and albedo (+0.17 W m−2), (iii) increased water‐vapor (+0.49 W m−2), and (iv) a cloud adjustment (−0.26 W m−2) due to reduced stability and cloudiness over land (positive ERF) counteracted by increased lower tropospheric stability and marine cloudiness over oceans (negative ERF). The sum of these radiative adjustments to land warming is to reduce the 4xCO2 ERF in fixed‐SST experiments by ∼1.0 W m−2. CO2 stomatal effects are quantified and found to contribute just over half of the land warming effect and adjustments in the fixed‐SST ERF experimental design in this model. The basic physical mechanisms in response to land warming are confirmed in a solar ERF experiment. We test various methods that have been proposed to account for land warming in fixed‐SST ERFs against our GCM results and discuss their strengths and weaknesses.

Direct and semi-direct radiative forcing of biomass-burning aerosols over the southeast Atlantic (SEA) and its sensitivity to absorbing properties: a regional climate modeling study

Abstract. Simulations are performed for the period 2000–2015 by two different regional climate models, ALADIN and RegCM, to quantify the direct and semi-direct radiative effects of biomass-burning aerosols (BBAs) in the southeast Atlantic (SEA) region. Different simulations have been performed using strongly absorbing BBAs in accordance with recent in situ observations over the SEA. For the July–August–September (JAS) season, the single scattering albedo (SSA) and total aerosol optical depth (AOD) simulated by the ALADIN and RegCM models are consistent with the MACv2 climatology and MERRA-2 and CAMS-RA reanalyses near the biomass-burning emission sources. However, the above-cloud AOD is slightly underestimated compared to satellite (MODIS and POLDER) data during the transport over the SEA. The direct radiative effect exerted at the continental and oceanic surfaces by BBAs is significant in both models and the radiative effects at the top of the atmosphere indicate a remarkable regional contrast over SEA (in all-sky conditions), with a cooling (warming) north (south) of 10 ∘S, which is in agreement with the recent MACv2 climatology. In addition, the two models indicate that BBAs are responsible for an important shortwave radiative heating of ∼0.5–1 K per day over SEA during JAS with maxima between 2 and 4 km a.m.s.l. (above mean sea level). At these altitudes, BBAs increase air temperature by ∼0.2–0.5 K, with the highest values being co-located with low stratocumulus clouds. Vertical changes in air temperature limit the subsidence of air mass over SEA, creating a cyclonic anomaly. The opposite effect is simulated over the continent due to the increase in lower troposphere stability. The BBA semi-direct effect on the lower troposphere circulation is found to be consistent between the two models. Changes in the cloud fraction are moderate in response to the presence of smoke, and the models differ over the Gulf of Guinea. Finally, the results indicate an important sensitivity of the direct and semi-direct effects to the absorbing properties of BBAs. Over the stratocumulus (Sc) region, DRE varies from +0.94 W m−2 (scattering BBAs) to +3.93 W m−2 (most absorbing BBAs).

Interpreting and Stabilizing Machine-Learning Parametrizations of Convection

AbstractNeural networks are a promising technique for parameterizing subgrid-scale physics (e.g., moist atmospheric convection) in coarse-resolution climate models, but their lack of interpretability and reliability prevents widespread adoption. For instance, it is not fully understood why neural network parameterizations often cause dramatic instability when coupled to atmospheric fluid dynamics. This paper introduces tools for interpreting their behavior that are customized to the parameterization task. First, we assess the nonlinear sensitivity of a neural network to lower-tropospheric stability and the midtropospheric moisture, two widely studied controls of moist convection. Second, we couple the linearized response functions of these neural networks to simplified gravity wave dynamics, and analytically diagnose the corresponding phase speeds, growth rates, wavelengths, and spatial structures. To demonstrate their versatility, these techniques are tested on two sets of neural networks, one trained with a superparameterized version of the Community Atmosphere Model (SPCAM) and the second with a near-global cloud-resolving model (GCRM). Even though the SPCAM simulation has a warmer climate than the cloud-resolving model, both neural networks predict stronger heating/drying in moist and unstable environments, which is consistent with observations. Moreover, the spectral analysis can predict that instability occurs when GCMs are coupled to networks that support gravity waves that are unstable and have phase speeds larger than 5 m s−1. In contrast, standing unstable modes do not cause catastrophic instability. Using these tools, differences between the SPCAM-trained versus GCRM-trained neural networks are analyzed, and strategies to incrementally improve both of their coupled online performance unveiled.

The Climatology of Lower Tropospheric Temperature Inversions in China from Radiosonde Measurements: Roles of Black Carbon, Local Meteorology, and Large-Scale Subsidence

AbstractThe variability of the lower tropospheric temperature inversion (TI) across China remains poorly understood. Using seven years’ worth of high-resolution radiosonde measurements at 120 sites, we compile the climatology of lower tropospheric TI in terms of frequency, intensity, and depth during the period from 2011 to 2017. The TI generally exhibits strong seasonal and geographic dependencies. Particularly, the TI frequency is found to be high in winter and low in summer, likely due to the strong aerosol radiative effect in winter. The frequency of the surface-based inversion (SBI) exhibits a “west low, east high” pattern at 0800 Beijing time (BJT), which then switches to “west high, east low” at 2000 BJT. Both the summertime SBI and elevated inversion (EI) reach a peak at 0800 BJT and a trough at 1400 BJT. Interestingly, the maximum wintertime EI frequency occurs over Southeast China (SEC) rather than over the North China Plain (NCP), likely attributable to the combination of the heating effect of black carbon (BC) originating from the NCP, along with the strong subsidence and trade inversion in SEC. Correlation analyses between local meteorology and TI indicate that larger lower tropospheric stability (LTS) favors more frequent and stronger TIs, whereas the stronger EI under smaller LTS conditions (unstable atmosphere) is more associated with subsidence rather than BC. Overall, the spatial pattern of the lower tropospheric TI and its variability in China are mainly controlled by three factors: local meteorology, large-scale subsidence, and BC-induced heating. These findings help shed some light on the magnitude, spatial distribution, and underlying mechanisms of the lower tropospheric TI variation in China.

Transition of Low Clouds in the East China Sea and Kuroshio Region in Winter: A Regional Atmospheric Model Study

AbstractBias in simulating the stratocumulus‐to‐cumulus transition remains a main source of uncertainties in climate projection and can significantly affect the energy budget in climate models. To gain insights into the transition, this study investigates the cloud transition forced by the sea surface temperature (SST) front and synoptic disturbances in the East China Sea and Kuroshio region in winter based on both observations and regional atmospheric model simulations. The Kuroshio SST front greatly accelerates cloud transition by enhancing surface latent heat flux, marine atmospheric boundary layer (MABL) dynamical adjustment, and cloud top entrainment. With the sharp SST increase from the cold flank to the Kuroshio SST warm tongue (KWT), surface wind convergence (SWC) over the KWT induced by the SST front and synoptic disturbances enhances the coupling between the cloud layer and subcloud layer. An underlying positive feedback between the SWC and latent heating in the cloud layer can enhance abrupt change in cloud properties and maintain cloud band over the KWT against the decoupling through the so‐called “Deepening‐Warming” mechanism induced by latent heating. From the KWT downwind southward, the surface layer turbulent mixing weakens, while latent heating in the cloud layer and cloud top longwave radiative cooling enhance buoyancy and vertical mixing in the cloud layer. This difference in vertical mixing between the cloud layer and subcloud layer facilitates the MABL decoupling and impedes upward moisture transport. Meanwhile, decreasing lower tropospheric stability is conducive to the entrainment of drier and warmer air from above into the cloud layer, strengthening cloud evaporation.

Assessment of climate models in relation to the low‐level clouds over the southern Indian Ocean

AbstractAgainst the backdrop of limited fidelity of climate models in capturing low‐level cloud variability, the representation of the southern Indian Ocean (SIO) marine boundary layer (MBL) clouds and their transition from low to deep cloud have been investigated in this study. A historical run of 26 models, that featured in the Coupled Model Intercomparison Project Phase 5 (CMIP5), and the National Centers for Environmental Prediction (NCEP)'s Climate Forecast System version 2.0 (CFSv2) models have been analysed along with different observational and reanalysis products. Observations clearly show the prominent occurrence of MBL low‐level clouds over the SIO in a 30–10°S latitudinal and 80–100°E longitudinal belt. Furthermore, there is a gradual transition from low to deep cloud towards the north of the Equator. The results reveal that the CMIP5 models were hardly able to capture the MBL low‐level clouds due to inaccurate temperature inversion and lower‐tropospheric stability (LTS) simulations. As compared to observations, the CMIP5 models show limited fidelity in capturing the transition from low to deep cloud at the north of the Equator. In this study, evaluation of one version of the CFS in which the convective parameterization is changed to the revised simplified Arakawa–Schubert (RSAS) scheme is carried out. In another CFS version (CFSR) with a more physically based cloud scheme (WRF Single‐Moment 6‐Class microphysics scheme; WSM6), comparisons are made with the default CFSv2 (CTRL) and RSAS. Only very few models, such as the MPI‐ESM‐LR, MRI, HadGEM, and NorESM models from among the 26 CMIP5 suites, and CFSCR from among the CFS suites, showed some fidelity in capturing the low‐level clouds over the SIO. This highlights that significant improvement is needed in climate models to improve the representation of the MBL over the SIO.

Climatology of Planetary Boundary Layer Height-Controlling Meteorological Parameters Over the Korean Peninsula

Planetary boundary layer (PBL) height plays a significant role in climate modeling, weather forecasting, air quality prediction, and pollution transport processes. This study examined the climatology of PBL-associated meteorological parameters over the Korean peninsula and surrounding sea using data from the ERA5 dataset produced by the European Centre for Medium-range Weather Forecasts (ECMWF). The data covered the period from 2008 to 2017. The bulk Richardson number methodology was used to determine the PBL height (PBLH). The PBLH obtained from the ERA5 data agreed well with that derived from sounding and Global Positioning System Radio Occultation datasets. Significant diurnal and seasonal variability in PBLH was observed. The PBLH increases from morning to late afternoon, decreases in the evening, and is lowest at night. It is high in the summer, lower in spring and autumn, and lowest in winter. The variability of the PBLH with respect to temperature, relative humidity, surface pressure, wind speed, lower tropospheric stability, soil moisture, and surface fluxes was also examined. The growth of the PBLH was high in the spring and in southern regions due to the low soil moisture content of the surface. A high PBLH pattern is evident in high-elevation regions. Increasing trends of the surface temperature and accordingly PBLH were observed from 2008 to 2017.