Cloud Radiative Effects Research Articles

Nocturnal surface radiation cooling modulated by cloud cover change reinforces PM2.5 accumulation: Observational study of heavy air pollution in the Sichuan Basin, Southwest China

Surface radiation is crucial to atmospheric boundary layer development and air pollution formation. Several studies have revealed that surface radiation plays a vital role in developing the daytime convective boundary layer that controls the explosive growth of PM2.5 concentration; however, less attention has been paid to the effects of changing nighttime surface radiation on the near-surface temperature inversion layer and PM2.5 accumulation. In this study, we used long-term observations of meteorological and environmental data and atmospheric boundary layer measurements during a severe PM2.5 pollution event to investigate the effect of changes in nocturnal surface radiation on the increase in PM2.5 concentrations. The results showed that surface radiation cooling was enhanced (weakened) by decreased (increased) cloud cover fraction by changing longwave radiation at night; this strengthened (weakened) near-surface temperature inversion intensity and promoted (prevented) the accumulated increase in PM2.5. This observational study using 5-year data further confirmed the cloud radiative effect on the nighttime accumulation of PM2.5 with a significant negative correlation between nighttime averages of surface PM2.5 concentrations and cloud cover fractions. This reveals an important mechanism for the impact of surface radiation cooling modulated by cloud cover change on the nighttime accumulated increase in PM2.5. This finding extends our understanding of air pollutant accumulation at night with potential implications for atmospheric environment change.

Uncertainty Quantification and Bayesian Inference of Cloud Parameterization in the NCAR Single Column Community Atmosphere Model (SCAM6)

Uncertainty quantification (UQ) in weather and climate models is required to assess the sensitivity of their outputs to various parameterization schemes and thereby improve their consistency with observations. Herein, we present an efficient UQ and Bayesian inference for the cloud parameters of the NCAR Single Column Atmosphere Model (SCAM6) using surrogate models based on a polynomial chaos expansion. The use of a surrogate model enables to efficiently propagate uncertainties in parameters into uncertainties in model outputs. We investigated eight uncertain parameters: the auto-conversion size threshold for ice to snow (dcs), the fall speed parameter for stratiform cloud ice (ai), the fall speed parameter for stratiform snow (as), the fall speed parameter for cloud water (ac), the collection efficiency of aggregation ice (eii), the efficiency factor of the Bergeron effect (berg_eff), the threshold maximum relative humidity for ice clouds (rhmaxi), and the threshold minimum relative humidity for ice clouds (rhmini). We built two surrogate models using two non-intrusive methods: spectral projection (SP) and basis pursuit denoising (BPDN). Our results suggest that BPDN performs better than SP as it enables to filter out internal noise during the process of fitting the surrogate model. Five out of the eight parameters (namely dcs, ai, rhmaxi, rhmini, and eii) account for most of the variance in predicted climate variables (e.g., total precipitation, cloud distribution, shortwave and longwave cloud radiative effect, ice, and liquid water path). A first-order sensitivity analysis reveals that dcs contributes ~40–80% of the total variance of the climate variables, ai around 15–30%, and rhmaxi, rhmini, and eii around 5–15%. The second- and higher-order effects contribute ~7 and 20%, respectively. The sensitivity of the model to these parameters was further explored using response curves. A Markov chain Monte Carlo (MCMC) sampling algorithm was also implemented for the Bayesian inference of dcs, ai, as, rhmini, and berg_eff using cloud distribution data collected at the Southern Great Plains (USA). The inferred parameters suggest improvements in the global Climate Earth System Model (CESM2) simulations of the tropics and sub-tropics.

Moisture Variation with Cloud Effects during a BSISO over the Eastern Maritime Continent in a Cloud-Permitting-Scale Simulation

AbstractDespite the great importance of interactions between moisture, clouds, radiation, and convection in the Madden–Julian oscillation, their role in the boreal summer intraseasonal oscillation (BSISO) has not been well established. This study investigates the moisture variation of a BSISO during its rapid redevelopment over the eastern Maritime Continent through a cloud-permitting-scale numerical simulation. It is found that moisture variation depends closely on the evolution of clouds and precipitation. Total moisture budget analysis reveals that the deepening and strengthening (lessening) of humidity before (after) the BSISO deep convection are attributed largely to zonal advection. In addition, the column moistening/drying is mostly in phase with the humidity and is related to the maintenance of BSISO. An objective cloud-type classification method and a weak temperature gradient approximation are used to further understand the column moistening/drying. Results indicate that elevated stratiform clouds play a significant role in moistening the lower troposphere through cloud water evaporation. Decreases in deep convection condensation and reevaporation of deep stratiform precipitation induce moistening during the development and after the decay of BSISO deep convection, respectively. Meanwhile, anomalous longwave radiative heating appears first in the lower troposphere during the developing stage of BSISO, further strengthens via the increase of deep stratiform clouds, and eventually deepens with elevated stratiform clouds. Accordingly, anomalous moistening largely in phase with the humidity of BSISO toward its suppressed stage is induced via compensated ascent. Owing to the anomalous decrease in the ratio of vertical moisture and potential temperature gradients, the cloud–radiation effect is further enhanced in the convective phase of BSISO.

Influence of Upper-Troposphere Stratification and Cloud-Radiation Interaction on Convective Overshoots in the Tropical Tropopause Layer

AbstractIt is still debated whether radiative heating observed in the tropical tropopause layer (TTL) is balanced primarily by cooling from convective overshoots, as in an entrainment layer, or by adiabatic cooling from large-scale eddy-driven upwelling. In this study, three-dimensional cloud-resolving model simulations of radiative-convective equilibrium were carried out with three different cloud microphysics schemes and 1-km horizontal resolution. We demonstrate that overshooting cooling in the TTL can be strongly modulated by upper-troposphere stratification. Two of the schemes produce a hard-landing scenario in which convective overshoots reach the TTL with frequent large vertical velocity leading to strong overshooting cooling (~ −0.2 K day-1). The third scheme produces a soft-landing scenario in which convective overshoots rarely reach the TTL with large vertical velocity and produce little overshooting cooling (~ −0.03 K day-1). The difference between the two scenarios is attributed to changes in the upper-troposphere stratification related to different atmospheric cloud radiative effects (ACRE). The microphysics scheme that produces the soft-landing scenario has much stronger ACRE in the upper troposphere leading to a ~3K warmer and more stable layer which acts as a buffer zone to slow down the convective updrafts. The stratification mechanism suggests the possibility for the ozone variation or eddy-driven upwelling in the TTL to modulate convective overshoots. We further test the sensitivity of overshooting cooling to changes in model resolution by increasing the horizontal resolution to 100 m. The corresponding change of overshooting cooling is much smaller compared with the difference between the hard-landing and soft-landing scenarios.

Convective Cloud Regimes From a Classification of Object‐Based CloudSat Observations Over Asian‐Australian Monsoon Areas

AbstractThe present study objectively classified the convective cloud objects detected by the space‐borne CloudSat radar over the Asian‐Australian monsoon region using the hierarchical agglomerative clustering algorithm. Based on key properties representing the morphological features and convective intensity of the systems, five distinct convective cloud regimes were derived. The unique Coastal‐Intense (CI) regime exhibits the most expansive horizontal scales (>1,000 km), high convective strength, the strongest cloud radiative effects, the highest probability of extreme rainfall, and a significant coupling with the sharp onset of the Asian summer monsoon circulation. Second, the Coastal regime illustrates smaller but also highly organized coastal convections, with the strongest convective strength. Less than 10% of the systems in the CI and Coastal regimes overlap with the tropical cyclones. The rest three regimes mark the less organized convection at various life cycle stages mainly over the land areas, with small seasonal variation in their occurrence.

Sensitivity of radiative flux simulations to ice cloud parameterization over the equatorial western Pacific Ocean region

AbstractPrevious studies suggest explanations of the observed cancellation of shortwave (SW) and longwave (LW) cloud radiative effects (CREs) at the top of the atmosphere (TOA) over tropical oceans where deep convection prevails, such as interactions among cloud microphysics, radiation, and dynamics. However, simulations based on general circulation models (GCMs) show disagreement in terms of the net (SW + LW) CREs over tropical deep convective ocean regions. One of the GCM uncertainty sources is the parameterization of ice cloud bulk optical properties. In this study, a combination of active and passive satellite daytime cloud retrievals is used to study the sensitivity of radiation flux calculations to ice cloud parameterization over the equatorial western Pacific Ocean region. Three ice cloud schemes are tested. The first is a widely used scheme that assumes hexagonal column ice particles. The second scheme treats ice particles as aggregates of surface-roughened hexagonal columns. The third scheme best matches the cloud ice mass-dimension relation in the cloud microphysics scheme by assuming a mixture of two ice particle habits. The results show that the hexagonal-column-based scheme has the weakest SW CRE but strongest LW CRE among the three. In addition, cloud optical thickness and effective radius are used to cluster cold-top single-layer ice clouds into three types, which resemble thin cirrus, detrained anvil clouds, and deep convective cores, respectively. In agreement with previous studies, cloud SW heating overwhelms LW cooling in the upper portion of anvil-like clouds.

SimCloud version 1.0: a simple diagnostic cloud scheme for idealized climate models

Abstract. A simple diagnostic cloud scheme (SimCloud) for general circulation models (GCMs), which has a modest level of complexity and is transparent in describing its dependence on tunable parameters, is proposed in this study. The large-scale clouds, which form the core of the scheme, are diagnosed from relative humidity. In addition, the marine low stratus clouds, typically found off the west coast of continents over subtropical oceans, are determined largely as a function of inversion strength. A “freeze-dry” adjustment based on a simple function of specific humidity is also available to reduce an excessive cloud bias in polar regions. Other cloud properties, such as the effective radius of cloud droplet and cloud liquid water content, are specified as simple functions of temperature. All of these features are user-configurable. The cloud scheme is implemented in Isca, a modeling framework designed to enable the construction of GCMs at varying levels of complexity, but could readily be adapted to other GCMs. Simulations using the scheme with realistic continents generally capture the observed structure of cloud fraction and cloud radiative effect (CRE), as well as its seasonal variation. Specifically, the explicit low-cloud scheme improves the simulation of shortwave CREs over the eastern subtropical oceans by increasing the cloud fraction and cloud water path. The freeze-dry adjustment alleviates the longwave CRE biases in polar regions, especially in winter. However, the longwave CRE in tropical regions and shortwave CRE over the extratropics are both still too strong compared to observations. Nevertheless, this simple cloud scheme provides a suitable basis for examining the impacts of clouds on climate in idealized modeling frameworks.

Evolution of the Tropical Response to Periodic Extratropical Thermal Forcing

AbstractThis study examines the temporal evolution of the extratropically forced tropical response in an idealized aquaplanet model under equinox condition. We apply a surface thermal forcing in the northern extratropics that oscillates periodically in time. It is shown that tropical precipitation is unaltered by sufficiently high-frequency extratropical forcing. This sensitivity to the extratropical forcing periodicity arises from the critical time required for sea surface temperature (SST) adjustment. Low-frequency extratropical forcing grants sufficient time for atmospheric transient eddies to diffuse moist static energy to perturb the mid-latitude SSTs outside the forcing region, as demonstrated by a one-dimensional energy balance model with a fixed diffusivity. As the transient eddies weaken in the subtropics, a further equatorward advection is accomplished by the Hadley circulation. The essential role of Hadley cell advection in connecting the subtropical signal to the equatorial region is supported by an idealized thermodynamical-advective model. Associated with the SST changes in the tropics is a meridional shift of the Intertropical Convergence Zone. Since the time needed for SST adjustment increases with increasing mixed layer depth, the critical forcing period at which the extratropical forcing can affect the tropics scales linearly with the mixed layer depth. Our results highlight the important role of decadal-and-longer extratropical climate variability in shaping the tropical climate system. We also raise the possibility that the transient behavior of a tropical response forced by extratropical variability may be strongly dependent on cloud radiative effects.

Top‐of‐Atmosphere Radiation Budget and Cloud Radiative Effects Over the Tibetan Plateau and Adjacent Monsoon Regions From CMIP6 Simulations

AbstractThis study investigates the top‐of‐atmosphere (TOA) radiation budget (RT) and cloud radiative effects (CREs) over the Tibetan Plateau (TP) and adjacent Asian monsoon regions including Eastern China (EC) and South Asia (SA) using the Coupled Model Intercomparison Project 6 (CMIP6) simulations. Considerable simulation biases occur but specific causes differ in these regions. Most models underestimate the intensity of annual mean RT and cloud radiative cooling effect over the TP, and the RT during the cold‐warm transition period is hard to capture. The biases in surface temperature and cloud fractions substantially contribute to cloud‐radiation biases over the western and eastern TP, respectively. Over EC, the intensity of RT and cloud radiative cooling effect is seriously underestimated especially in the springtime when the model spread is large, and their biases are closely related to less low‐middle cloud fractions and weaker ascending motion. Over SA, simulation biases mainly arise from longwave radiative components associated with less high cloud fraction and weaker convection, with the large model spread in the summertime. The annual cycles of RT and CREs over EC and SA can be well reproduced by most models, while the summertime peak of the net CRE over the TP occurs later than the observation. The RT and its simulation bias strongly depend on the cloud radiative cooling effect over EC and SA. Our results demonstrate that contemporary climate models still have obvious difficulties in representing various complex cloud‐radiation processes in Asian monsoon regions.

Midlatitude Cloud Radiative Effect Sensitivity to Cloud Controlling Factors in Observations and Models: Relationship with Southern Hemisphere Jet Shifts and Climate Sensitivity

AbstractAn effective method to understand cloud processes and to assess the fidelity with which they are represented in climate models is the cloud controlling factor framework, in which cloud properties are linked with variations in large-scale dynamical and thermodynamical variables. This study examines how midlatitude cloud radiative effects (CRE) over oceans co-vary with four cloud controlling factors: mid-tropospheric vertical velocity, estimated inversion strength (EIS), near-surface temperature advection, and sea surface temperature (SST), and assesses their representation in CMIP6 models with respect to observations and CMIP5 models.CMIP5 and CMIP6 models overestimate the sensitivity of midlatitude CRE to perturbations in vertical velocity, and underestimate the sensitivity of midlatitude shortwave CRE to perturbations in EIS and temperature advection. The largest improvement in CMIP6 models is a reduced sensitivity of CRE to vertical velocity perturbations. As in CMIP5 models, many CMIP6 models simulate a shortwave cloud radiative warming effect associated with a poleward shift in the Southern Hemisphere (SH) midlatitude jet stream, an effect not present in observations. This bias arises because most models’ shortwave CRE are too sensitive to vertical velocity perturbations and not sensitive enough to EIS perturbations, and because most models overestimate the SST anomalies associated with SH jet shifts. The presence of this bias directly impacts the transient surface temperature response to increasing greenhouse gases over the Southern Ocean, but not the global-mean surface temperature. Instead, the models’ climate sensitivity is correlated with their shortwave CRE sensitivity to surface temperature advection perturbations near 40°S, with models with more realistic values of temperature advection sensitivity generally having higher climate sensitivity.

Quantifying and attributing time step sensitivities in present-day climate simulations conducted with EAMv1

Abstract. This study assesses the relative importance of time integration error in present-day climate simulations conducted with the atmosphere component of the Energy Exascale Earth System Model version 1 (EAMv1) at 1∘ horizontal resolution. We show that a factor-of-6 reduction of time step size in all major parts of the model leads to significant changes in the long-term mean climate. Examples of changes in 10-year mean zonal averages include the following: up to 0.5 K of warming in the lower troposphere and cooling in the tropical and subtropical upper troposphere, 1 %–10 % decreases in relative humidity throughout the troposphere, and 10 %–20 % decreases in cloud fraction in the upper troposphere and decreases exceeding 20 % in the subtropical lower troposphere. In terms of the 10-year mean geographical distribution, systematic decreases of 20 %–50 % are seen in total cloud cover and cloud radiative effects in the subtropics. These changes imply that the reduction of temporal truncation errors leads to a notable although unsurprising degradation of agreement between the simulated and observed present-day climate; to regain optimal climate fidelity in the absence of those truncation errors, the model would require retuning. A coarse-grained attribution of the time step sensitivities is carried out by shortening time steps used in various components of EAM or by revising the numerical coupling between some processes. Our analysis leads to the finding that the marked decreases in the subtropical low-cloud fraction and total cloud radiative effect are caused not by the step size used for the collectively subcycled turbulence, shallow convection, and stratiform cloud macrophysics and microphysics parameterizations but rather by the step sizes used outside those subcycles. Further analysis suggests that the coupling frequency between the subcycles and the rest of EAM significantly affects the subtropical marine stratocumulus decks, while deep convection has significant impacts on trade cumulus. The step size of the cloud macrophysics and microphysics subcycle itself appears to have a primary impact on cloud fraction in the upper troposphere and also in the midlatitude near-surface layers. Impacts of step sizes used by the dynamical core and the radiation parameterization appear to be relatively small. These results provide useful clues for future studies aiming at understanding and addressing the root causes of sensitivities to time step sizes and process coupling frequencies in EAM. While this study focuses on EAMv1 and the conclusions are likely model-specific, the presented experimentation strategy has general value for weather and climate model development, as the methodology can help researchers identify and understand sources of time integration error in sophisticated multi-component models.

The effect of low-level thin arctic clouds on shortwave irradiance: evaluation of estimates from spaceborne passive imagery with aircraft observations

Abstract. Cloud optical properties such as optical thickness along with surface albedo are important inputs for deriving the shortwave radiative effects of clouds from spaceborne remote sensing. Owing to insufficient knowledge about the snow or ice surface in the Arctic, cloud detection and the retrieval products derived from passive remote sensing, such as from the Moderate Resolution Imaging Spectroradiometer (MODIS), are difficult to obtain with adequate accuracy – especially for low-level thin clouds, which are ubiquitous in the Arctic. This study aims at evaluating the spectral and broadband irradiance calculated from MODIS-derived cloud properties in the Arctic using aircraft measurements collected during the Arctic Radiation-IceBridge Sea and Ice Experiment (ARISE), specifically using the upwelling and downwelling shortwave spectral and broadband irradiance measured by the Solar Spectral Flux Radiometer (SSFR) and the BroadBand Radiometer system (BBR). This starts with the derivation of surface albedo from SSFR and BBR, accounting for the heterogeneous surface in the marginal ice zone (MIZ) with aircraft camera imagery, followed by subsequent intercomparisons of irradiance measurements and radiative transfer calculations in the presence of thin clouds. It ends with an attribution of any biases we found to causes, based on the spectral dependence and the variations in the measured and calculated irradiance along the flight track. The spectral surface albedo derived from the airborne radiometers is consistent with prior ground-based and airborne measurements and adequately represents the surface variability for the study region and time period. Somewhat surprisingly, the primary error in MODIS-derived irradiance fields for this study stems from undetected clouds, rather than from the retrieved cloud properties. In our case study, about 27 % of clouds remained undetected, which is attributable to clouds with an optical thickness of less than 0.5. We conclude that passive imagery has the potential to accurately predict shortwave irradiances in the region if the detection of thin clouds is improved. Of at least equal importance, however, is the need for an operational imagery-based surface albedo product for the polar regions that adequately captures its temporal, spatial, and spectral variability to estimate cloud radiative effects from spaceborne remote sensing.

Challenging and Improving the Simulation of Mid‐Level Mixed‐Phase Clouds Over the High‐Latitude Southern Ocean

AbstractClimate models exhibit major radiative biases over the Southern Ocean owing to a poor representation of mixed‐phase clouds. This study uses the remote‐sensing dataset from the Measurements of Aerosols, Radiation and Clouds over the Southern Ocean (MARCUS) campaign to assess the ability of the Weather Research and Forecasting (WRF) model to reproduce frontal clouds off Antarctica. It focuses on the modeling of thin mid‐level supercooled liquid water layers which precipitate ice. The standard version of WRF produces almost fully glaciated clouds and cannot reproduce cloud top turbulence. Our work demonstrates the importance of adapting the ice nucleation parameterization to the pristine austral atmosphere to reproduce the supercooled liquid layers. Once simulated, droplets significantly impact the cloud radiative effect by increasing downwelling longwave fluxes and decreasing downwelling shortwave fluxes at the surface. The net radiative effect is a warming of snow and ice covered surfaces and a cooling of the ocean. Despite improvements in our simulations, the local turbulent circulation related to cloud‐top radiative cooling is not properly reproduced, advocating for the need to develop a parameterization for top‐down convection to capture the turbulence‐microphysics interplay at cloud top.

The Dependence of Ship‐Polluted Marine Cloud Properties and Radiative Forcing on Background Drop Concentrations

AbstractMarine low clouds of the busy shipping lane in the southeast Atlantic during the springs of 2003–2015 were analyzed to study the dependence of their properties and radiative forcing on the background cloud drop concentrations (Nd‐bg). The overall average cloud radiative effect within the shipping lane was larger by only −1 Wm−2 compared to the adjacent clouds. However, this near‐zero averaged effect was composed of large negative cloud radiative forcing (CRF) for the cleanest (13%) of the cases with Nd‐bg < 50 cm−3, which was almost neutralized by a positive CRF for the 40% of the cases with Nd‐bg > 70 cm−3. A possible explanation for this positive forcing is the cloud burning effect of the black carbon from ship emissions. The negative forcing was composed of 45% for the cloud fraction (Cf) effect and 55% for the albedo effects, which included a small contribution of the liquid water path (LWP) effect. Positive Cf susceptibility to Nd‐core was at maximum for the lowest Nd‐bg and disappeared near 60 cm−3. The albedo susceptibility to Nd‐core reached its theoretical limit of 1/3 for constant LWP when Nd‐bg <40 cm−3, and diminishes to 0.2 when Nd‐bg = 60 cm−3. These susceptibilities represent cause and effect relationships because the differences of aerosols caused by the ship emissions vary at a much smaller scale than meteorology. Globally, under similar environmental conditions, nearly half of the area has Nd < 50 cm−3, thus possessing the indicated large susceptibility of negative radiative forcing to anthropogenic aerosols.

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.

Characterization of cloud microphysical properties in different cloud types over East Asia based on CloudSat/CALIPSO satellite products

By using four-year CloudSat/CALIPSO satellite data, the authors investigated cloud microphysical properties in three representative regions over East Asia, where models commonly suffer from great biases in simulations of cloud radiative effects. This study aims to provide an observational basis of cloud microphysical properties for the modeling community, against which the model simulations can be validated. The analyzed cloud microphysical properties include mass, number concentration, and effective radius for both liquid and ice phases. For liquid clouds, both cloud mass and number concentration gradually decrease with height, leading to the effective radius being nearly uniformly spread in the range of 8–14 µm. For ice clouds, the cloud mass and effective radius decrease with height, whereas the number concentration is nearly uniform in the vertical. The cloud microphysical properties show remarkable differences among different cloud types. Cloud mass and number concentration are larger in cumuliform clouds, whereas smaller in cirrus clouds. By comparing cloud properties among the Tibetan Plateau, East China, and the western North Pacific, results show the values are overall smaller for liquid clouds but larger for ice clouds over the Tibetan Plateau.摘要利用CloudSat/CALIPSO卫星资料, 本文揭示了东亚三个代表性区域的云微物理属性, 为评估和改进模式云微物理过程提供重要的观测基础. 研究的云微物理量包括云水/冰质量, 数浓度和有效半径. 研究表明: 暖云中云水质量和数浓度随高度增加而减小, 有效半径处于8-14 µm 范围. 对于冰云, 云冰质量和有效半径随高度增加而减小, 而数浓度在垂直方向上变化不大. 此外, 云微物理属性在不同云型之间存在显著差异: 积云的云水质量和数浓度最大, 而卷云的云水质量和数浓度最小. 从三个区域的对比结果来看, 相比于华东和西北太平洋地区, 青藏高原地区暖云的云水质量和数浓度较小, 而冰云的则较大.

New Observational Constraints on Warm Rain Processes and Their Climate Implications

AbstractLow stratiform clouds have profound impacts on the hydrological cycle and the Earth’s radiation budget. However, realistic simulation of low clouds in climate models presents a major challenge. Here we employ the newly retrieved cloud and drizzle microphysical properties to improve the autoconversion and accretion parameterizations in a microphysical scheme. We find that the new autoconversion (accretion) rate contributes 14% lower (greater) to total drizzle water content than the original scheme near the cloud top. Compared to satellite results, the simulated cloud liquid water path (LWP) and shortwave cloud radiative effect using the original scheme in a climate model agree well on global average but with large regional differences. Simulations using the updated scheme show a 7.3% decrease in the light rain frequency, and a 10% increase in LWP. The updated microphysics scheme alleviates the long‐lasting problem in most climate models, that is “too frequent and too light precipitation.”

Eulerian and Lagrangian views of warm and moist air intrusions into summer Arctic

In this study, warm and moist air intrusions (WaMAI) over the sea sectors of Kara, Laptev, East Siberian and Beaufort from 1979 to 2018 are identified in ERA5 reanalysis and their air-mass transformation is analysed using interpolation in ERA5 and satellite products along trajectories. The analysis shows that WaMAIs, driven by blocking high-pressure systems over the respective ocean sectors, induce surface warming (11–18 W m−2) and sea ice melt from positive anomalies of net longwave radiation (5–8 W m−2) and turbulent flux (8–13 W m−2) to the surface, although the anomaly of net shortwave radiation (−9 ~ +1 W m−2) is negative. From a Lagrangian perspective, the surface energy-budget anomaly decreases linearly, while total column cloud liquid water (TCLW) increases linearly with the downstream distance from the sea-ice edge. However, the cloud radiative effects of both longwave and shortwave radiation reach an equilibrium as TCLW increases in a much lower rate beyond 7 degrees north of the sea ice edge. The boundary-layer energy-budget pattern can be categorized into two classes: radiation-dominated and turbulence-dominated, comprised of 26% and 62% WaMAIs respectively. Statistically, turbulence-dominated cases occur with 3 times stronger large-scale subsidence, and also feature a larger anomaly in net shortwave radiation. In radiation-dominated WaMAIs, stratocumulus develops more strongly and hence exerts larger longwave and shortwave forcing to the surface. In both categories, a well-mixed boundary layer deepens by 500 m along the trajectories, from the continuous turbulent mixing.

Investigating the impact of cloud-radiative feedbacks on tropical precipitation extremes

Although societally important, extreme precipitation is difficult to represent in climate models. This study shows one robust aspect of extreme precipitation across models: extreme precipitation over tropical oceans is strengthened through a positive feedback with cloud-radiative effects. This connection is shown for a multi-model ensemble with experiments that make clouds transparent to longwave radiation. In all cases, tropical extreme precipitation reduces without cloud-radiative effects. Qualitatively similar results are presented for one model using the cloud-locking method to remove cloud feedbacks. The reduced extreme precipitation without cloud-radiative feedbacks does not arise from changes in the mean climate. Rather, evidence is presented that cloud-radiative feedbacks enhance organization of convection and most extreme precipitation over tropical oceans occurs within organized systems. This result suggests that climate models must correctly predict cloud structure and properties, as well as capture the essence of organized convection in order to accurately represent extreme rainfall.

A Novel Computer-Aided Cloud Type Classification Method Based on Convolutional Neural Network with Squeeze-And- Excitation

Clouds have a huge impact on the energy balance, climate and weather of the earth. Cloud types have different cloud radiation effects, which is an important indicator of cloud radiation effects. Therefore, determining the type of cloud is of great significance in meteorology. In this paper, the Convolutional neural network with Squeeze & Excitation Networks (SENet) are mainly used to solve this probelm. CNN can automatically learn the filters that need to be manually set before, and can learn complex edge, spatial and texture information in the image which are difficult for traditional methods to learn and extract. Moerover, a website and a deep learning framework are established to showcase the results of this article and to further develop our models and methods through open source methods.