Cloud Microphysical Properties Research Articles

Single particle characteristics and ice nucleation potential of particles collected during Asian dust storms in 2021

Dust storms have great impacts on air quality and climate. Dust can influence cloud microphysical properties and determine their radiative forcing and precipitation. Asian dust storms (ADS) are important sources of global aerosol. However, the physiochemical characteristics of dust from ADS at a single particle level are less understood, and the exact particles that can serve as ice nucleating particles (INPs) remain unclear. Here, we present the physicochemical properties and ice nucleation ability of dust particles collected in Beijing during two major ADS in March 2021. The particles from two ADS were classified into Illite, Kaolinite, Feldspar, Quartz, Chlorite, Mixed-dust, and Non-dust particles, which contributed 28.6 % ± 3.3 %, 20.0 % ± 3.9 %, 12.3 % ± 2.3 %, 11.1 % ± 2.8 %, 9.8 % ± 0.8 %, 13.7 % ± 1.8 %, and 4.4 % ± 1.7 % in number, respectively. On average, the ADS particles formed ice crystals via deposition ice nucleation from relative humidity with respect to ice (RHice) of 112 % ± 1 % at 250 K to 154 % ± 15 % RHice at 205 K. Part of the samples also formed ice via immersion freezing between 230 K and 250 K. Among the 149 identified INPs, Clay-like particles (Chlorite, Illite, and Kaolinite) contributed 71.1 % ± 6.2 % in number and followed by Mixed-dust-like particles (16.9 % ± 8.7 %) and Feldspar-like particles (10.4 % ± 6.3 %). Enrichment factor for each particle type is calculated as the ratio of its number fractions in INPs and the aerosol population. It ranges from 0.6 ± 0.7 to 1.3 ± 2.2. The contribution of each particle type to INP was correlated with its fraction in the population. These results imply that each particle type can serve as INP. Clay-like particles are the dominant INPs during the ADS. We conducted ice nucleation kinetic analysis and provided parameterizations of heterogeneous ice nucleation rate coefficient and contact angle for ADS. These parameterizations can be used in the modeling study to evaluate the impact of ADS in atmospheric ice crystal formation in clouds.

Bayesian cloud-top phase determination for Meteosat Second Generation

Abstract. A comprehensive understanding of the cloud thermodynamic phase is crucial for assessing the cloud radiative effect and is a prerequisite for remote sensing retrievals of microphysical cloud properties. While previous algorithms mainly detected ice and liquid phases, there is now a growing awareness for the need to further distinguish between warm liquid, supercooled and mixed-phase clouds. To address this need, we introduce a novel method named ProPS (PRObabilistic cloud top Phase retrieval for SEVIRI), which enables cloud detection and the determination of cloud-top phase using SEVIRI (Spinning Enhanced Visible and Infrared Imager), the geostationary passive imager aboard Meteosat Second Generation. ProPS discriminates between clear sky, optically thin ice (TI) cloud, optically thick ice (IC) cloud, mixed-phase (MP) cloud, supercooled liquid (SC) cloud and warm liquid (LQ) cloud. Our method uses a Bayesian approach based on the cloud mask and cloud phase from the lidar–radar cloud product DARDAR (liDAR/raDAR). The validation of ProPS using 6 months of independent DARDAR data shows promising results: the daytime algorithm successfully detects 93 % of clouds and 86 % of clear-sky pixels. In addition, for phase determination, ProPS accurately classifies 91 % of IC, 78 % of TI, 52 % of MP, 58 % of SC and 86 % of LQ clouds, providing a significant improvement in accurate cloud-top phase discrimination compared to traditional retrieval methods.

An Investigation on Potential Dispersal of Airborne Pollen Over China and Their Impact on Climate as Ice Nuclei Using RegCM‐Pollen

AbstractPollen can serve as an effective ice‐nuclei (IN), altering cloud microphysical and radiative properties, thus precipitation and cloud life cycles. Here, a nationwide pollen emission inventory with a horizontal resolution of 5 km was established based on a parameterization scheme of mass balance of pollen grain fluxes surrounding the plant crowns, and using satellite observational data sets (including leaf area index and fractional vegetation cover) as well as pollen emission rates. The potential emission is then implemented in RegCM‐pollen model which treated pollen as aerosol tracers. Besides, pollen‐IN parameterization schemes were incorporated in RegCM‐pollen to simulate the interactions between pollen and ice clouds. Investigations show that the mean annual pollen emission in China is 2.65 × 107 grains m−2 yr−1, mainly distributed in the south and northeast of China. The IN magnitude is mainly determined by a combination of temperature and pollen concentration. Notably, an increasing number concentration of pollen grains produces opposite effects in Southern China (SC) and Northern China (NC). The weakened upward motion and vertical transport of water vapor in NC made ice clouds hardly form, resulting in cloud forcing (CF) of +0.86 W/m2. In contrast, it generates a CF of −0.84 W/m2 in SC mainly owing to expanded cloud cover. The changes in shortwave radiative forcing is more significant compared to longwave radiative forcing in the two regions. At the surface, the net radiative forcing in NC is +0.74 W/m2, while it is a −0.51 W/m2 in SC. Among them, downward shortwave radiative forcing is approximately twice that of upward longwave radiative forcing in SC and 1.4 times in NC. Surface temperature shows rising over NC, ranging from 0.05 to 0.25 K. In SC, it is primarily decreasing by −0.12 to −0.03 K. The pollen‐IN effect also causes a decline of precipitation in NC (−0.17 mm/day) and a rise in SC (0.09 mm/day). Our results suggest that the pollen effect on ice clouds is complex, yet significant in understanding its impact on radiation and climate of the atmosphere.

Long‐Term Trends in Aerosols, Low Clouds, and Large‐Scale Meteorology Over the Western North Atlantic From 2003 to 2020

AbstractA continuous decrease in aerosols over the Western North Atlantic Ocean (WNAO) on a decadal timescale provides a long‐term benchmark to evaluate how various natural and anthropogenic processes affect the manifestation of aerosol‐cloud interactions in this region. Furthermore, the WNAO serves as a natural laboratory with diverse aerosol sources, marine boundary layer clouds more variable than those in marine stratocumulus deck regions, and unique flow regimes established by the Gulf Stream and the semi‐permanent Bermuda High. We investigate how satellite‐retrieved macrophysical and microphysical properties of low clouds and the surface shortwave irradiance changed from 2003 to 2020, in tandem with this aerosol decrease. The decadal changes in large‐scale meteorology related to the North Atlantic Oscillation (NAO) are also examined. We find a reduction in low‐cloud optical thickness, accompanied by fewer and larger cloud droplets, yet observe no significant changes in low‐cloud fraction and liquid water path. Despite the reduction in low‐cloud optical thickness together with aerosol decrease, a corresponding increase in the trends of surface shortwave irradiance, also known as surface brightening, is lacking. This absence of brightening is potentially related to concomitant changes found in large‐scale meteorology associated with NAO—Bermuda High strengthening, sea surface warming, and atmospheric moistening— as well as an increase in high‐level cloud fraction that can counteract the surface brightening. Ultimately, our findings suggest that spatial patterns of decadal meteorological variability introduce complexities in the surface cloud radiative effect over the WNAO, thereby complicating the isolation and examination of aerosol‐cloud interactions.

Characteristics of Atmospheric Ice Nucleation during Spring: A Case Study on Huangshan

Atmospheric ice nucleation particles (INPs) play a crucial role in influencing cloud formation and microphysical properties, which in turn impact precipitation and Earth’s radiation budget. However, the influence of anthropogenic activities on the properties and concentrations of INPs remains an area of significant uncertainty. This study investigated the physical and chemical characteristics of atmospheric ice nucleation particles in Huangshan, China during the May Day labor holiday period (spanning 8 days, from April 27th to May 5th). INP concentrations were measured at temperatures from −17 °C to −26 °C and relative humidities (RHw) from 95% to 101%. Average INP concentrations reached 13.7 L−1 at −26 °C and 101% RH, 137 times higher than at −17 °C and 95% RH. INP concentrations showed exponential increases with decreasing temperature and exponential increases with increasing RH. Concentration fluctuations were observed over time, with a peak of ~30 L−1 (t = −26 °C, RHw = 101%) around the start and end of the holiday period. Aerosol number concentrations were monitored simultaneously. The peak in aerosols larger than 0.5 μm aligned with the peak in INP concentrations, suggesting a link between aerosol levels and INPs. Chemical composition analysis using SEM–EDX revealed the distinct elemental makeup of INPs based on the activation temperature. INPs active at warmer temperatures contained N, Na, and Cl, indicating possible biomass and sea salt origins, while those active at colder temperatures contained crustal elements like Al and Ca.

Interactions between trade wind clouds and local forcings over the Great Barrier Reef: a case study using convection-permitting simulations

Abstract. Trade wind clouds are ubiquitous across the subtropical oceans, including the Great Barrier Reef (GBR), playing an important role in modulating the regional energy budget. These shallow clouds, however, are by their nature sensitive to perturbations in both their thermodynamic environment and microphysical background. In this study, we employ the Weather Research and Forecasting (WRF) model with a convection-permitting configuration at 1 km resolution to examine the sensitivity of the trade wind clouds to different local forcings over the GBR. A range of local forcings including coastal topography, sea surface temperature (SST), and local aerosol loading is examined. This study shows a strong response of cloud fraction and accumulated precipitation to orographic forcing both over the mountains and upwind over the GBR. Orographic lifting, low-level convergence, and lower troposphere stability are found to be crucial in explaining the cloud and precipitation features over the coastal mountains downwind of the GBR. However, clouds over the upwind ocean are more strongly constrained by the trade wind inversion, whose properties are, in part, regulated by the coastal topography. On the scales considered in this study, the warm-cloud fraction and the ensuant precipitation over the GBR show only a small response to the local SST forcing, with this response being tied to the surface flux and lower troposphere stability. Cloud microphysical properties, including cloud droplet number concentration, liquid water path, and precipitation, are sensitive to the changes in atmospheric aerosol population over the GBR. While cloud fraction shows little responses, a slight deepening of the simulated clouds is evident over the upwind region in correspondence to the increased aerosol number concentration. A downwind effect of aerosol loading on simulated cloud and precipitation properties is further noted.

A new spectrally-invariant approach to the remote sensing of inhomogeneous clouds

Current operational satellite retrievals of cloud optical and microphysical properties go back to the Nakajima-King technique developed at the end of the 1980 s. This technique is based on library calculations for plane-parallel homogeneous clouds. It often works well for overcast skies but leads to substantial errors for inhomogeneous and broken cloud fields where the plane-parallel-geometry assumption is no longer valid. The basic concept of a new technique was first introduced in nuclear physics to quantify the critical conditions of reactors. Based on the eigenvalues of the radiative transfer equation, their approach provides a powerful means to parameterize the structure of 3D media. This parameterization was later successfully applied to relate surface reflectance spectra to 3D canopy structure and is known as the spectrally-invariant approximation. The proposed approach adapts this technique to the remote sensing of cloud properties such as droplet single scattering albedo and the average number of scatterings (which are the fundamental parameters in radiative transfer theory), with an emphasis on quantifying the associated errors and uncertainties. This retrieval is free from the plane-parallel homogeneous cloud assumption.

Secondary Ice Production in Simulated Deep Convective Clouds: A Sensitivity Study

Abstract Multiple mechanisms have been proposed to explain secondary ice production (SIP), and SIP has been recognized to play a vital role in forming cloud ice crystals. However, most weather and climate models do not consider SIP in their cloud microphysical schemes. In this study, in addition to the default rime splintering (RS) process, two SIP processes, namely, shattering/fragmentation during freezing of supercooled rain/drizzle drops (DS) and breakup upon ice–ice collisions (BR), were implemented into a two-moment cloud microphysics scheme. Besides, two different parameterization schemes for BR were introduced. A series of sensitivity experiments were performed to investigate how SIP impacts cloud microphysics and cloud phase distributions in warm-based deep convective clouds developed in the central part of Europe. Simulation results revealed that cloud microphysical properties were significantly influenced by the SIP processes. Ice crystal number concentrations (ICNCs) increased up to more than 20 times and surface precipitation was reduced by up to 20% with the consideration of SIP processes. Interestingly, BR was found to dominate SIP, and the BR process rate was larger than the RS and DS process rates by four and three orders of magnitude, respectively. Liquid pixel number fractions inside clouds and at the cloud top decreased when implementing all three SIP processes, but the decrease depended on the BR scheme. Peak values of ice enhancement factors (IEFs) in the simulated deep convective clouds were 102–104 and located at −24°C with the consideration of all three SIP processes, while the temperature dependency of IEF was sensitive to the BR scheme. However, if only RS or RS and DS processes were included, the IEFs were comparable, with peak values of about 6, located at −7°C. Moreover, switching off the cascade effect led to a remarkable reduction in ICNCs and ice crystal mass mixing ratios. Significance Statement The cloud phase is found to have a significant impact on cloud evolution, radiative properties, and precipitation formation. However, the simulation of the cloud phase is a big challenge for cloud research because multiple processes are not well described or missing in numerical models. In this study, we implemented two secondary ice production (SIP) processes, namely, shattering/fragmentation during the freezing of supercooled rain/drizzle drops and breakup upon ice–ice collisions, which are missing in most numerical models. Sensitivity experiments were conducted to investigate how SIP impacts cloud microphysics and cloud phase in deep convective clouds. We found that SIP significantly impacts in-cloud and cloud-top phase distribution. We also identified that the collisional breakup of ice particles is the dominant SIP process in the simulated deep convective clouds.

Bulk cloud microphysical properties as seen from numerical simulation and remote sensing products: case study of a hailstorm event over the La Plata Basin

Hailstorms develop over the La Plata Basin, in south-eastern South America, more often during later winter and early austral spring, between September and October. These systems have significant socioeconomic impacts over the region. Thus, a better understanding of how atmospheric drivers modulate the formation of hailstorms is important to improve the forecast of such phenomena. In this study, we selected a hailstorm event observed over the eastern La Plata Basin during 14–15 July 2016 to evaluate the performance of the Brazilian developments on the Regional Atmospheric Modelling System (BRAMS) model. The ability of the model in simulating cloud microphysical properties was evaluated by comparing simulations driven by different global forcings against in situ and remote sensing observations. The model results showed good skill in capturing the basic characteristics of the thunderstorm, particularly in terms of the spatial distribution of hydrometeors. The simulated spatial distribution of hail covers locations where hail fall was reported. The BRAMS simulations suggest that, despite relatively low values of the convective available potential energy (CAPE) (700–1000 J kg−1), environments with strong 0–8-km bulk shear (60–70 kt, ~30.9–36.0 m s–1) can promote the formation of ice clouds and hail fall over the eastern La Plata Basin. To be more conclusive, however, further research is needed to understand how different combinations of CAPE and shear affect hail formation over the region.

Efficient single-scattering lookup table for lidar and polarimeter phytoplankton studies.

Coupled atmosphere and ocean remote sensing retrievals of aerosol, cloud, and oceanic phytoplankton microphysical properties, such as those carried out by the NASA Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, involve single-scattering calculations that are time consuming. Lookup tables (LUTs) exist to speed up these calculations for aerosol and water droplets in the atmosphere. In our new Lorenz-Mie lookup table, we tabulate single scattering by an ensemble of coated isotropic spheres representing oceanic phytoplankton at wavelengths from 0.355 µm. The lookup table covers phytoplankton particles with radii in the range of 0.15-100 µm at an increase of up to 104 in computational speed compared to single-scattering calculations. The allowed complex refractive indices range from 1.05 to 1.24 for the shell's real part, from 10-7 to 0.3 for the shell's imaginary part, from 0 to 0.001 for the core's imaginary part, and equal to 1.02 for the core's real part. We show that we precisely compute inherent optical properties for the phytoplankton size distributions ranging up to 5 µm for the effective radius and up to 0.6 for the effective variance. We test wavelengths from 0.355 to 1.065 µm and find that all the inherent optical properties of interest agree with the single-scattering calculations to within 1% for 99.9% of cases. We also provide an example of using the lookup table to reproduce the phytoplankton optical datasets listed in the PANGAEA database for synthetic hyperspectral algorithm development. The table together with C++, Fortran, MATLAB, and Python codes to apply different complex refractive indices and phytoplankton size distributions is freely available online.

Aerosol influence on cloud macrophysical and microphysical properties over the Tibetan Plateau and its adjacent regions.

This study uses aerosol optical depth (AOD) and cloud properties data to investigate the influence of aerosol on the cloud properties over the Tibetan Plateau and its adjacent regions. The study regions are divided as the western part of the Tibetan Plateau (WTP), the Indo-Gangetic Plain (IGP), and the Sichuan Basin (SCB). All three regions show significant cloud effects under low aerosol loading conditions. In WTP, under low aerosol loading conditions, the effective radius of liquid cloud particles (LREF) decreases with the increase of aerosol loading, while the effective radius of ice cloud particles (IREF) and cloud top height (CTH) increase during the cold season. Increased aerosol loading might inhibit the development of warm rain processes, transporting more cloud droplets above the freezing level and promoting ice cloud development. During the warm season, under low aerosol loading conditions, both the cloud microphysical (LREF and IREF) and macrophysical (cloud top height and cloud fraction) properties increase with the increase of aerosol loading, likely due to higher dust aerosol concentration in this region. In IGP, both LREF and IREF increase with the increase in aerosol loading during the cold season. In SCB, LREF increases with the increase in aerosol loading, while IREF decreases, possibly due to the higher hygroscopic aerosol concentration in the SCB during the cold season. Meteorological conditions also modulate the aerosol-cloud interaction. Under different convective available potential energy (CAPE) and relative humidity (RH) conditions, the influence of aerosol on clouds varies in the three regions. Under low CAPE and RH conditions, the relationship between LREF and aerosol in both the cold and warm seasons is opposite in the WTP: LREF decreases with the increase of aerosol in the cold season, while it increases in the warm season. This discrepancy may be attributed to a difference in the moisture condition between the cold and warm seasons in this region. In general, the influence of aerosols on cloud properties in TP and its adjacent regions is characterized by significant nonlinearity and spatial variability, which is likely related to the differences in aerosol types and meteorological conditions between different regions.

The preliminary measurements of water cloud microphysical properties using multiple scattering Raman lidar

Clouds play an important role in the energy balance and water cycle for the Earth-Atmosphere system, and the accurate measurement of their macro-and microphysical properties is important for understanding atmospheric physical processes, studying aerosol-cloud interactions and improving numerical model parameterization schemes. In this paper, a multiple scattering Raman lidar system is developed, which greatly simplifies the structure of the optical system and solves the complexity of the optical system in detecting the cloud characteristic parameters by adopting the dual field-of-view (FOV) technique. Based on the Quasi-Small-Angle (QSA) approximation model, the forward single or multiple scattering signals of cloud droplet particles at the bottom of the cloud layer at the dual-FOV channel and the vibrational Raman backscattering signals of nitrogen molecules are simultaneously detected. Using the correlation between the width of the forward scattering peak and the particle size of the cloud droplets, an iterative algorithm for the Raman signal is proposed for retrieving cloud parameters such as the extinction coefficient, the effective radius, and the liquid water content (LWC). To verify the feasibility of the system and retrieval algorithms, some preliminary measurements were carried out and the resulting liquid water content was compared and verified by combined observations with a co-located microwave radiometer. The experimental results show that the average deviation of the liquid water content is 0.004 g/m3, and the relative error is 20%. The system has an ability to invert cloud microphysical properties, which provides an effective method for further study of aerosol-cloud interactions.

Clothing Textiles as Carriers of Biological Ice Nucleation Active Particles.

Microplastics have littered the globe, with synthetic fibers being the largest source of atmospheric microplastics. Many atmospheric particles can act as ice nucleators, thereby affecting the microphysical and radiative properties of clouds and, hence, the radiative balance of the Earth. The present study focused on the ice-nucleating ability of fibers from clothing textiles (CTs), which are commonly shed from the normal wear of apparel items. Results from immersion ice nucleation experiments showed that CTs were effective ice nucleators active from -6 to -12 °C, similar to common biological ice nucleators. However, subsequent lysozyme and hydrogen peroxide digestion stripped the ice nucleation properties of CTs, indicating that ice nucleation was biological in origin. Microscopy confirmed the presence of biofilms (i.e., microbial cells attached to a surface and enclosed in an extracellular polysaccharide matrix) on CTs. If present in sufficient quantities in the atmosphere, biological particles (biofilms) attached to fibrous materials could contribute significantly to atmospheric ice nucleation.

Impacts of ice-nucleating particles on cirrus clouds and radiation derived from global model simulations with MADE3 in EMAC

Abstract. Atmospheric aerosols can act as ice-nucleating particles (INPs) and influence the formation and the microphysical properties of cirrus clouds, resulting in distinct climate effects. We employ a global aerosol–climate model, including a two-moment cloud microphysical scheme and a parameterization for aerosol-induced ice formation in cirrus clouds, to quantify the climate impact of INPs on cirrus clouds (simulated period 2001–2010). The model considers mineral dust, soot, crystalline ammonium sulfate, and glassy organics as INPs in the cirrus regime. Several sensitivity experiments are performed to analyse various aspects of the simulated INP–cirrus effect regarding (i) the ice-nucleating potential of the INPs, (ii) the inclusion of ammonium sulfate and organic particles as INPs in the model, and (iii) the model representations of vertical updraughts. The resulting global radiative forcing of the total INP–cirrus effect, considering all different INP types, assuming a smaller and a larger ice-nucleating potential of INPs, to explore the range of possible forcings due to uncertainties in the freezing properties of INPs, is simulated as −28 and −55 mW m−2, respectively. While the simulated impact of glassy organic INPs is mostly small and not statistically significant, ammonium sulfate INPs contribute a considerable radiative forcing, which is nearly as large as the combined effect of mineral dust and soot INPs. Additionally, the anthropogenic INP–cirrus effect is analysed considering the difference between present-day (2014) and pre-industrial conditions (1750) and amounts to −29 mW m−2, assuming a larger ice-nucleating potential of INPs. In a further sensitivity experiment we analyse the effect of highly efficient INPs proposed for cirrus cloud seeding as a means to reduce global warming by climate engineering. However, the results indicate that this approach risks an overseeding of cirrus clouds and often results in positive radiative forcings of up to 86 mW m−2 depending on number concentration of seeded INPs. Idealized experiments with prescribed vertical velocities highlight the crucial role of the model dynamics for the simulated INP–cirrus effects. For example, resulting forcings increase about 1 order of magnitude (−42 to −340 mW m−2) when increasing the prescribed vertical velocity (from 1 to 50 cm s−1). The large discrepancy in the magnitude of the simulated INP–cirrus effect between different model studies emphasizes the need for future detailed analyses and efforts to reduce this uncertainty and constrain the resulting climate impact of INPs.

Rainfall Area Identification Algorithm Based on Himawari-8 Satellite Data and Analysis of its Spatiotemporal Characteristics

Real-time monitoring of rainfall areas based on satellite remote sensing is of vital importance for extreme rainfall research and disaster prediction. In this study, a new rainfall area identification algorithm was developed for the new generation of geostationary satellites with high spatial and temporal resolution and rich bands. As the main drivers of the rainfall process, the macro and micro physical properties of clouds play an important role in the formation and development of rainfall. We considered differences in the absorption capacity of the water vapor absorption channels in the infrared band and introduced a sensitivity difference of rainfall area in water vapor channels to construct a sensitive detection of the water vapor region. The results of this algorithm were evaluated using Global Precipitation Measurement (GPM) satellite products and CloudSat measurements in various scenarios, with hit rates of 70.03% and 81.39% and false alarm rates of 2.05% and 21.34%, respectively. Spatiotemporal analysis revealed that the types of upper clouds in the rainfall areas mainly consisted of deep convection, cirrostratus, and nimbostratus clouds. Our study provides supporting data for weather research and disaster prediction, as well as an efficient and reliable method for capturing temporal and spatial features.

Tethered balloon-borne observations of thermal-infrared irradiance and cooling rate profiles in the Arctic atmospheric boundary layer

Abstract. Clouds play an important role in controlling the radiative energy budget of the Arctic atmospheric boundary layer. To quantify the impact of clouds on the radiative heating or cooling of the lower atmosphere and of the surface, vertical profile observations of thermal-infrared irradiances were collected using a radiation measurement system carried by a tethered balloon. We present 70 profiles of thermal-infrared radiative quantities measured in summer 2020 during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition and in autumn 2021 and spring 2022 in Ny-Ålesund, Svalbard. Measurements are classified into four groups: cloudless, low-level liquid-bearing cloud, elevated liquid-bearing cloud, and elevated ice cloud. Cloudless cases display an average radiative cooling rate of about −2 K d−1 throughout the atmospheric boundary layer. Instead, low-level liquid-bearing clouds are characterized by a radiative cooling up to −80 K d−1 within a shallow layer at cloud top, while no temperature tendencies are identified underneath the cloud layer. Radiative transfer simulations are performed to quantify the sensitivity of radiative cooling rates to cloud microphysical properties. In particular, cloud top cooling is strongly driven by the liquid water path, especially in optically thin clouds, while for optically thick clouds the cloud droplet number concentration has an increased influence. Additional radiative transfer simulations are used to demonstrate the enhanced radiative importance of the liquid relative to ice clouds. To analyze the temporal evolution of thermal-infrared radiation profiles during the transitions from a cloudy to a cloudless atmosphere, a respective case study is investigated.

A Method for Retrieving Cloud Microphysical Properties Using Combined Measurement of Millimeter-Wave Radar and Lidar

Clouds are an important component of weather systems and are difficult to effectively characterize using current climate models and estimation of radiative forcing. Due to the limitations in observational capabilities, it remains difficult to obtain high-spatiotemporal-resolution, continuous, and accurate observations of clouds. To overcome this issue, we propose a novel and practical combined retrieval method using millimeter-wave radar and lidar, which enables the microphysical properties of thin liquid water clouds, such as cloud droplet effective radius, number concentration, and liquid water content, to be retrieved. This method was utilized to analyze the clouds observed at the Shanghai World Expo Park and was validated through synchronous observations with a microwave radiometer. Furthermore, the most suitable extinction backscatter ratio was determined through sensitivity analysis. This study provides vertical distributions of cloud microphysical properties with a time resolution of 1 min and a spatial resolution of 30 m, demonstrating the scientific potential of this combined retrieval method.

Disentangling Satellite Precipitation Estimate Errors of Heavy Rainfall at the Daily and Sub-Daily Scales in the Western Mediterranean

In the last decade, substantial improvements have been achieved in quantitative satellite precipitation estimates, which are essential for a wide range of applications. In this study, we evaluated the performance of Integrated Multi-satellitE Retrievals for GPM (IMERG V06B) at the sub-daily and daily scales. Ten years of half-hourly precipitation records aggregated at different sub-daily periods were evaluated over a region in the Western Mediterranean. The analysis at the half-hourly scale examined the contribution of passive microwave (PMW) and infrared (IR) sources in IMERG estimates, as well as the relationship between various microphysical cloud properties using Cloud Microphysics (CMIC–NWC SAF) data. The results show the following: (1) a marked tendency to underestimate precipitation compared to rain gauges which increases with rainfall intensity and temporal resolution, (2) a weaker negative bias for retrievals with PMW data, (3) an increased bias when filling PMW gaps by including IR information, and (4) an improved performance in the presence of precipitating ice clouds compared to warm and mixed-phase clouds. This work contributes to the understanding of the factors affecting satellite estimates of extreme precipitation. Their relationship with the microphysical characteristics of clouds generates added value for further downstream applications and users’ decision making.

Wind-driven emissions of coarse-mode particles in an urban environment

Abstract. Quantifying surface–atmosphere exchange rates of particles is important for understanding the role of suspended particulate matter in radiative transfer, clouds, precipitation, and climate change. Emissions of coarse-mode particles with a diameter greater than 0.5 µm provide giant cloud condensation nuclei and ice nuclei. These emissions are critical for understanding the evolution of cloud microphysical properties yet remain poorly understood. Here we introduce a new method that uses lidar retrievals of the elastic backscatter and Doppler velocity to obtain surface number emissions of particles with a diameter greater than 0.53 µm. The technique is applied to study particle number fluxes over a 2-month period from 1 June to 10 August 2022 during the TRACER campaign at an urban site near Houston, TX, USA. We found that all the observed fluxes were positive (upwards), indicating particle emission from the surface. The fluxes followed a diurnal pattern and peaked near noon local time. Flux intensity varied through the 2 months with multi-day periods of strong fluxes and multi-day periods of weak fluxes. Emission particle number fluxes peaked near ∼ 100 cm−2 s−1. The daily averaged emission fluxes correlated with friction velocity and were anticorrelated with surface relative humidity. The emission flux can be parameterized as F= 3000 u*4, where u* is the friction velocity in m s−1 and the emission flux F is in cm−2 s−1. The u* dependence is consistent with emission from wind-driven erosion. Estimated values for the mass flux are in the lower range of literature values from non-urban sites. These results demonstrate that urban environments may play an important role in supplying coarse-mode particles to the boundary layer. We anticipate that quantification of these emissions will help constrain aerosol–cloud interaction models that use prognostic aerosol schemes.

Machine Learning Approach to Investigating the Relative Importance of Meteorological and Aerosol-Related Parameters in Determining Cloud Microphysical Properties

Aerosol effects on cloud properties are notoriously difficult to disentangle from variations driven by meteorological factors. Here, a machine learning model is trained on reanalysis data and satellite retrievals to predict cloud microphysical properties, as a way to illustrate the relative importance of meteorology and aerosol, respectively, on cloud properties. It is found that cloud droplet effective radius can be predicted with some skill from only meteorological information, including estimated air mass origin and cloud top height. For ten geographical regions the mean coefficient of determination is 0.41 and normalised root-mean square error 24%. The machine learning model thereby performs better than a reference linear regression model, and a model predicting the climatological mean. A gradient boosting regression performs on par with a neural network regression model. Adding aerosol information as input to the model improves its skill somewhat, but the difference is small and the direction of the influence of changing aerosol burden on cloud droplet effective radius is not consistent across regions, and thereby also not always consistent with what is expected from cloud brightening.