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Measurements with a 763 nm channel, located within the oxygen A-band and equipped on the Second-generation Global Imager (SGLI) on board the Japan Aerospace Exploration Agency (JAXA) Global Change Observation Mission – Climate (GCOM-C) satellite, have the potential to retrieve cloud-base height (CBH) and cloud geometric thickness (CGT) through passive remote sensing. This study implemented an algorithm to retrieve the CBH using the SGLI 763 nm channel in combination with several other SGLI channels in the visible, shortwave infrared, and thermal infrared regions. In addition to CBH, the algorithm can simultaneously retrieve other key cloud properties, including cloud optical thickness (COT), cloud effective radius, ice COT fraction as the cloud thermodynamic phase, cloud-top height (CTH), and CGT. Moreover, the algorithm can be seamlessly applied to global clouds comprised of liquid, ice, and mixed phases. The SGLI-retrieved CBH exhibited quantitative consistency with CBH data obtained from the ground-based ceilometer network, shipborne ceilometer, satellite-borne radar, and lidar observations, as evidenced by sufficiently high correlations and small biases. These results provide practical evidence that the retrieval of CBH is indeed possible using the SGLI 763 nm channel. Moreover, the results lend credence to the future use of SGLI CBH data, including the estimation of the surface downward longwave radiative flux from clouds. Nevertheless, issues remain that must be addressed to enhance the value of SGLI-derived cloud retrieval products. These include the bias of SGLI CTH related to cirrus clouds and the bias of SGLI CBH caused by multi-layer clouds. [ABSTRACT FROM AUTHOR]

Several publications have reported that total column ozone (TCO) may oscillate with an amplitude of up to 10 DU (Dobson units) during a solar eclipse, whereas other researchers have not seen evidence that an eclipse leads to variations in TCO beyond the typical natural variability. Here, we try to resolve these contradictions by measuring short-term variations (of seconds to minutes) in TCO using "global" (Sun and sky) and direct-Sun observations in the ultraviolet (UV) range with filter radiometers (GUVis-3511 and Microtops II®). Measurements were performed during three solar eclipses: the "Great American Eclipse" of 2024, which was observed in Mazatlán, Mexico, on 8 April 2024; a partial solar eclipse that took place in the United States on 14 October 2023 and was observed at Fort Collins, Colorado (40.57° N, 105.10° W); and a total solar eclipse that occurred in Antarctica on 4 December 2021 and was observed at Union Glacier (79.76° S, 82.84° W). The upper limits of the amplitude of oscillations in TCO observed at Mazatlán, Fort Collins, and Antarctica were 0.4 %, 0.3 %, and 0.03 %, respectively. The variability at all sites was within that observed during times not affected by an eclipse. The slightly larger variability at Mazatlán is due to cirrus clouds occurring throughout the day of the eclipse and the difficulty of separating changes in the ozone layer from cloud effects. These results support the conclusion that a solar eclipse does not lead to variations in TCO of more than ± 1.2 DU and that these variations are likely much lower, drawing into question reports of much larger oscillations. In addition to calculating TCO, we also present changes in the spectral irradiance and aerosol optical depth during eclipses and compare radiation levels observed during totality. The new results augment our understanding of the effect of a solar eclipse on the Earth's upper atmosphere. [ABSTRACT FROM AUTHOR]

To suppress the influence of aerosols scattering on the double-edge detection technique and achieve high-accuracy measurement of the wind field throughout the troposphere to the lower stratosphere, an ultraviolet 355 nm Rayleigh–Brillouin Doppler lidar technology based on a dual-pass dual Fabry–Perot interferometer (FPI) is proposed. The wind speed detection principle of this technology is analyzed, and the formulas for radial wind speed measurement error caused by random noise and wind speed measurement bias caused by Mie scattering signal contamination are derived. Based on the detection principle, the structure of the lidar system is designed. Combining the wind speed measurement error and measurement bias on both sides, the parameters of the dual-pass dual-FPI are optimized. The free spectral range (FSR) of the dual-pass dual-FPI is selected as 12 GHz, the bandwidth as 1.8 GHz, and the peak-to-peak spacing as 6 GHz. Further, the detection performance of this new type of Rayleigh–Brillouin Doppler lidar with the designed system parameters is simulated and analyzed. The simulation results show that at an altitude of 0–20 km, within the radial wind speed dynamic range of ±50 m/s, the radial wind speed measurement bias caused by aerosol scattering signal is less than 0.17 m/s in the cloudless region; within the radial wind speed dynamic range of ±30 m/s, the bias is less than 0.44 m/s and 0.91 m/s in the simulated cumulus cloud at 4 km where aerosol backscatter ratio Rβ = 3.8 and cirrus cloud at 9 km where Rβ = 2.9, respectively; using a laser with a pulse energy of 350 mJ and a repetition frequency of 50 Hz, a 450 mm aperture telescope, setting the detection zenith angle of 30°, vertical resolution of 26 m@0–10 km, 78 m@10–20 km, and 260 m@20–30 km, and a time resolution of 1 min, with the daytime sky background brightness taking 0.3 WSr−1m−2nm−1@355 nm, the radial wind speed measurement errors of the system during the day and night are below 2.9 m/s and 1.6 m/s, respectively, up to 30 km altitude, below 0.28 m/s at 10 km altitude, and below 0.91 m/s at 20 km altitude all day. [ABSTRACT FROM AUTHOR]

We investigate the formation mechanism of a tropopause cirrus cloud layer observed during the Balloon measurement campaigns of the Asian Tropopause Aerosol Layer (BATAL) over Hyderabad (17.47° N, 78.58° E), India, on 23 August 2017. Simultaneous measurements from a backscatter sonde and an optical particle counter on board a balloon flight revealed the presence of a subvisible cirrus cloud layer (optical thickness ∼ 0.025) at the cold-point tropopause (temperature ∼ - 86.4 °C, altitude ∼ 17.9 km). Ice crystals in this layer are smaller than 50 µm with a layer mean ice crystal number concentration of about 46.79 L-1. Simultaneous backscatter and extinction coefficient measurements allowed us to estimate the range-resolved extinction to backscatter coefficient ratio (lidar ratio) inside this layer with a layer mean value of about 32.18 ± 6.73 sr, which is in good agreement with earlier reported values at similar cirrus cloud temperatures. The formation mechanism responsible for this tropopause cirrus is investigated using a combination of three-dimensional back trajectories, satellite observations, and ERA5 reanalysis data. Satellite observations revealed that the overshooting convection associated with a category 3 typhoon, Hato, which hit Macau and Hong Kong on 23 August 2017, injected ice into the lower stratosphere. This caused a hydration patch that followed the Asian summer monsoon anticyclone to subsequently move towards Hyderabad. The presence of tropopause cirrus cloud layers in the cold temperature anomalies and updrafts along the back trajectories suggested the role of typhoon-induced waves in their formation. This case study highlights the role of typhoons in influencing the formation of tropopause cirrus clouds through stratospheric hydration and waves. [ABSTRACT FROM AUTHOR]

Warm conveyor belts (WCBs) are coherent ascending airstreams in extratropical cyclones. They are a major source of moisture for the extratropical upper troposphere and lower stratosphere (UTLS), where moisture acts as a potent greenhouse gas and WCB-associated cirrus clouds contribute to cloud radiative forcing. However, the processes controlling WCB moisture transport and cloud properties are poorly characterised. Furthermore, recent studies have revealed (embedded) convection as a ubiquitous feature of WCBs, highlighting the importance of understanding their updraught and microphysical structure. We present a Lagrangian investigation of WCB moisture transport for a case from the WISE (Wave-driven ISentropic Exchange) campaign based on a convection-permitting simulation. Lagrangian non-dimensional metrics of the moisture budget suggest that the ascent timescale (τ600) strongly controls the end-of-ascent total moisture content, which is largest for slowly ascending trajectories (τ600≥20h , 30 % of all WCB trajectories). This is due to relatively warm end-of-ascent temperatures and the strong temperature control on transported water vapour. Deviations from equilibrium water vapour condensate partitioning are largest for slow trajectories due to faster glaciation and lower ice crystal numbers. A local moisture transport minimum at intermediate τ600 results from a shift towards a riming-dominated precipitation formation pathway and decreasing outflow temperatures with decreasing τ600. The fastest trajectories (τ600≤5h , 5 % of all WCB trajectories) transport the largest condensate mass to the UTLS due to less efficient condensate loss and produce the longest-lived outflow cirrus clouds. Models that parameterise convection may under-represent these processes, potentially impacting weather forecasts and climate predictions. [ABSTRACT FROM AUTHOR]

Temperature and water vapor are known to fluctuate on multiple scales. In this study 27 years of airborne measurements of temperature and relative humidity from In‐service Aircraft for a Global Observing System (IAGOS) are used to parameterize the distribution of water vapor in the upper troposphere and lower stratosphere. The parameterization is designed to simulate water vapor fluctuations within gridboxes of atmospheric general circulation models (AGCMs) with typical size of a few tens to a few hundred kilometers. The distributions currently used in such models are often not supported by observations at high altitude. More sophisticated distributions are key to represent ice supersaturation, a physical phenomenon that plays a major role in the formation of natural cirrus and contrail cirrus. Here the observed distributions are fitted with a beta law whose parameters are adjusted from the gridbox mean variables. More specifically the standard deviation and skewness of the distributions are expressed as empirical functions of the average temperature and specific humidity, two typical prognostic variables of AGCMs. Thus, the distribution of water vapor is fully parameterized for a use in these models. The new parameterization reproduces the observed distributions with a determination coefficient always greater than 0.917 and with a mean value of 0.997. The parameterization is robust to a selection of various geographical subsets of data and to gridbox sizes varying between 25 and 300 km. Plain Language Summary: Temperature and water vapor fluctuate in the atmosphere on different scales, from micrometers to thousands of kilometers. In this study we use airborne measurements of temperature and water vapor to study the spatial variability of humidity in the upper troposphere and lower stratosphere. The observations are used to build a simple modeling of water vapor distribution on scales from tens of kilometers to hundreds of kilometers, which is designed to be used in atmospheric general circulation models (AGCMs), the atmospheric components of Earth system models. This new modeling of water vapor fluctuations aims to increase the physical representation of cirrus clouds and aviation‐induced cloudiness in AGCMs. The observed water vapor distributions are modeled with a beta distribution, whose parameters are completely determined as empirical functions of two major variables of AGCMs, the average temperature in a gridbox, and the average water vapor in a gridbox. Overall, the modeled distributions fit those observed very well. Key Points: The fine‐scale distribution of water vapor in the upper troposphere is fully parameterized for use in atmospheric general circulation modelsThe parameterization is empirical and based on 257 million airborne observations made between 1995 and 2021This parameterization aims to improve the quality of the simulation of ice supersaturation, and the formation of cirrus and contrail clouds [ABSTRACT FROM AUTHOR]

Cirrus clouds are of great importance to the global climate, with their net radiative forcing strongly dependent on the microphysical properties that are related to the ice‐nucleating regime. However, the influence of long‐range transport of dust on primary ice formation in cirrus clouds is limitedly understood, specifically over the clean remote ocean regions. Here, two case studies show that transpacific Asian dust can impact the ice formation of cirrus clouds over the central Pacific based on Cloud‐Aerosol Lidar with Orthogonal Polarization and Cloud Profiling Radar (CPR, CloudSat) observations. One case shows a well‐developed horizontally extended cirrus embedded in a pure dust layer, with an average dust‐related ice‐nucleating particle concentration (INPC) of 7 L−1 and 96 L−1 for an ice saturation ratio Si of 1.15 and 1.25, respectively; ice crystal number concentration (ICNC) with diameters >25 and 100 μm (denoted as nice,25 μm and nice,100 μm) are 64 L−1 and 7 L−1, respectively. Another case shows that cirrus clouds with a much smaller horizontal extent appeared in the vicinity of polluted dust, with an average INPC of 42–310 L−1 for the typical higher Si of 1.25–1.35 by considering a tenfold reduction of the ice nucleation efficiency of ice crystals; nice,25 μm and nice,100 μm are 168 L−1 and 20 L−1, respectively. The estimated INPC and ICNC values suggest the dominance of ice formation by dust‐induced heterogeneous nucleation, proving that the long‐range transport of dust toward the upper troposphere and the potential influence on cirrus formation over the central Pacific should be well considered in atmospheric models. Plain Language Summary: Cirrus clouds are vital to the global radiative balance. Their net radiation effect is very uncertain, depending on the microphysical properties that are mainly determined by the ice nucleation mechanism, that is, heterogeneous and homogeneous ice nucleation. In this work, two dust‐cirrus interaction cases are studied with the combinational observations of space‐borne lidar and radar. Over the remote central Pacific, where is generally very clean, we show that the long‐range transported Asian dust can significantly influence the ice nucleation at cirrus height by acting as efficient ice‐nucleating particles (INPs). The estimated number concentrations of INPs and ice crystals reveal that dust‐induced heterogeneous nucleation is dominant in ice formation, which should thus be better considered in atmospheric and climate models. Key Points: Cloud‐Aerosol Lidar with Orthogonal Polarization (CALIOP)‐CloudSat observations corroborate that dust in the outflow regime of Asia can influence cirrus formation over the central PacificCALIOP observations indicate the strongest dust occurrence in the upper troposphere over the Pacific during the spring seasonDust transport toward the upper troposphere and the potential impact on cirrus formation should be well considered in atmospheric models [ABSTRACT FROM AUTHOR]

This study aims to achieve the classification of the cirrus clouds over the Observatory of Haute-Provence (OHP) in France. Rayleigh–Mie–Raman lidar measurements, in conjunction with the ERA5 dataset, are analyzed to provide geometrical morphology and optical cirrus properties over the site. The method of cirrus cloud climatology presented here is based on a threefold classification scheme based on the cirrus geometrical and optical properties and their formation history. Principal component analysis (PCA) and subsequent clustering provide four morphological cirrus classes, three optical groups, and two origin-related categories. Cirrus clouds occur approximately 37% of the time, with most being single-layered (66.7%). The mean cloud optical depth (COD) is 0.39 ± 0.46, and the mean heights range around 10.8 ± 1.35 km. Thicker tropospheric cirrus are observed under higher temperature and humidity conditions than cirrus observed in the vicinity of the tropopause level. Monthly cirrus occurrences fluctuate irregularly, whereas seasonal patterns peak in spring. Concerning the mechanism of the formation, it is found that the majority of cirrus clouds are of in situ origin. The liquid-origin cirrus category consists nearly entirely of thick cirrus. Overall results suggest that in situ origin thin cirrus, located in the upper tropospheric and tropopause regions, have the most noteworthy occurrence over the site. [ABSTRACT FROM AUTHOR]

Cirrus clouds have an extensive global coverage and their high altitude means they play a critical role in the atmospheric radiation balance. Hexagonal ice plates and columns are two of the most abundant species present in cirrus and yet there remains a poor understanding of how surface roughness affects the scattering of light from these particles. To advance current understanding, the scattering properties of hexagonal ice plates with varying surface roughness properties are simulated using the discrete dipole approximation and the parent beam tracer physical–optics method. The ice plates are chosen to have a volume-equivalent size parameter of 2 π r / λ = 60 , where r is the radius of the volume-equivalent sphere, and a refractive index n = 1.31 + 0 i at a wavelength λ = 0.532 µm. The surface roughness is varied in terms of a characteristic length scale and an amplitude. The particles are rotated into 96 orientations to obtain the quasi-orientation averaged scattering Mueller matrix and integrated single-scattering parameters. The study finds that the scattering is largely invariant with respect to the roughness length scale, meaning it can be characterised solely by the roughness amplitude. Increasing the amplitude is found to lead to a decrease in the asymmetry parameter. It is also shown that roughness with an amplitude much smaller than the wavelength has almost no effect on the scattering when compared with a pristine smooth plate. The parent beam tracer method shows good agreement with the discrete dipole approximation when the characteristic length scale of the roughness is several times larger than the wavelength, with a computation time reduced by a factor of approximately 500. [ABSTRACT FROM AUTHOR]

The change in clouds during the day is critical to the Earth's energy balance and climatic evolution. However, there have been relatively few studies on cloud variations at daily timescales, owing to limitations of ground‐ and satellite‐observations, especially for cirrus clouds. In this study, we examined the daytime cirrus variation (DCV) at the global scales and its associated effects on radiation budgets based on the International Satellite Cloud Climatology Project H data set. The changes in continental cirrus cover are more significant than that over the ocean, reaching a maximum of 17.3% in the afternoon. Over the tropical deep convection regions, cirrus cloud cover and optical depth exhibit large amplitudes during the daytime, closely linked to average properties of cirrus clouds. Using a process‐based radiative transfer model, we calculated the variations in daytime cirrus cloud radiative forcing (CRF). After noon, cirrus clouds over both land and ocean generate the strongest shortwave (SW) cooling and longwave (LW) warming effects at the top of the atmosphere (TOA). At the global scale, daytime cirrus clouds cause an average net CRF of 3.6 W/m2 at the TOA. If the DCV is neglected in the model, the SW cooling and LW warming effects are overestimated by 2.5 and 1.8 W/m2 at the TOA, leading to a net radiation bias of 0.7 W/m2. The findings provide key information for targeting specific aspects of the cirrus parameterization scheme in climate models. Plain Language Summary: Cirrus clouds comprise large amounts of ice crystals, and frequently appear over tropical and mid‐latitude storm track areas. They play a crucial role in Earth's energy balance through interactions with shortwave and thermal radiation. These processes are closely related to the diurnal changes in cirrus clouds. However, accurately representing the daily changes in cirrus clouds in climate models remains challenging due to observational limitations, which affects the simulation of cloud radiation processes. We investigated the daytime cirrus variation (DCV) and its impacts on radiation budgets using the International Satellite Cloud Climatology Project‐H data set, combined with a radiative transfer model, and found that DCV contributes considerably to the radiation budget. This work may help improve the cirrus parameterization scheme in climate models. Key Points: The changes in daytime cirrus clouds and their impacts on the Earth's energy budget were investigated using the International Satellite Cloud Climatology Project‐H observationsThe changes in daytime cirrus clouds exhibit an obvious difference between land and oceanThe changes in daytime cirrus clouds have a considerable contribution to radiation calculation [ABSTRACT FROM AUTHOR]

Measurements with a 763 nm channel, located within the oxygen A-band and equipped on the Second-generation Global Imager (SGLI) onboard the JAXA's Global Change Observation Mission – Climate (GCOM-C) satellite, have the potential to retrieve cloud base height (CBH) and cloud geometric thickness (CGT) through passive remote sensing. This study implemented an algorithm to retrieve the CBH using the SGLI 763 nm channel in combination with several other SGLI channels in the visible, shortwave infrared, and thermal infrared regions. In addition to CBH, the algorithm can simultaneously retrieve other key cloud properties, including cloud optical thickness (COT), cloud effective radius, ice COT fraction as the cloud thermodynamic phase, cloud top height (CTH), and CGT. Moreover, the algorithm can be seamlessly applied to global clouds comprised of liquid, ice, and mixed phases. The SGLI-retrieved CBH exhibited quantitative consistency with CBH data obtained from the ground-based ceilometer network, ship-borne ceilometer, satellite-borne radar and lidar observations, as evidenced by sufficiently high correlations and small biases. These results provide practical evidence that the retrieval of CBH is indeed possible using the SGLI 763 nm channel. Moreover, the results lend credence to the future use of SGLI CBH data, including the estimation of the surface downward longwave radiative flux from clouds. Nevertheless, issues remain that must be addressed to enhance the value of SGLI-derived cloud retrieval products. These include the systematic bias of SGLI CTH related to cirrus clouds and the bias of SGLI CBH caused by multi-layer clouds. [ABSTRACT FROM AUTHOR]

Globally, emissions from aviation affect Earth's climate via complex processes. Contrail cirrus and carbon dioxide emissions are the largest factors contributing to aviation's radiative forcing on climate. Contrail cirrus, like natural cirrus clouds, impacts Earth's climate. Even with the extensive ongoing research, the relative importance of the climate effects of contrails compared to other aviation effects on climate still has major uncertainties requiring further research. Contrail cirrus encompasses linear contrails and the associated cirrus clouds; these are characterized by ice particle properties, e.g., size, concentration, mixing, extinction, ice water content, optical depth, geometrical depth, and cloud coverage. The climate impact of contrails may intensify due to projected increases in air traffic. The radiative forcing from global contrail cirrus has the potential to triple and could reach as much as 160 mWm-2 by 2050. This projection is based on anticipated growth in air traffic and a potential shift to higher altitudes. The future climate impact of contrail cirrus is influenced by factors like the magnitude and geographical spread in air traffic, advancements in fuel efficiency, the effects of the use of alternative fuels, and the effects of the changing climate on the background atmosphere. This study reviews the microphysical processes affecting contrail formation and the aging of contrails and contrail cirrus. Furthermore, the study explores global observational datasets for contrails, current analyses, and future projections and will aid in evaluating the effectiveness and tradeoffs associated with various mitigation strategies. The research highlights gaps in knowledge and uncertainties while outlining research priorities for the future. [ABSTRACT FROM AUTHOR]

Global warming is amplified in the Arctic. However, numerical models struggle to represent key processes that determine Arctic weather and climate. To collect data that help to constrain the models, the HALO–(AC) 3 aircraft campaign was conducted over the Norwegian and Greenland seas, the Fram Strait, and the central Arctic Ocean in March and April 2022. The campaign focused on one specific challenge posed by the models, namely the reasonable representation of transformations of air masses during their meridional transport into and out of the Arctic via northward moist- and warm-air intrusions (WAIs) and southward marine cold-air outbreaks (CAOs). Observations were made over areas of open ocean, the marginal sea ice zone, and the central Arctic sea ice. Two low-flying and one long-range, high-altitude research aircraft were flown in colocated formation whenever possible. To follow the air mass transformations, a quasi-Lagrangian flight strategy using trajectory calculations was realized, enabling us to sample the same moving-air parcels twice along their trajectories. Seven distinct WAI and 12 CAO cases were probed. From the quasi-Lagrangian measurements, we have quantified the diabatic heating/cooling and moistening/drying of the transported air masses. During CAOs, maximum values of 3 K h -1 warming and 0.3 g kg -1 h -1 moistening were obtained below 1 km altitude. From the observations of WAIs, diabatic cooling rates of up to 0.4 K h -1 and a moisture loss of up to 0.1 g kg -1 h -1 from the ground to about 5.5 km altitude were derived. Furthermore, the development of cloud macrophysical (cloud-top height and horizontal cloud cover) and microphysical (liquid water path, precipitation, and ice index) properties along the southward pathways of the air masses were documented during CAOs, and the moisture budget during a specific WAI event was estimated. In addition, we discuss the statistical frequency of occurrence of the different thermodynamic phases of Arctic low-level clouds, the interaction of Arctic cirrus clouds with sea ice and water vapor, and the characteristics of microphysical and chemical properties of Arctic aerosol particles. Finally, we provide a proof of concept to measure mesoscale divergence and subsidence in the Arctic using data from dropsondes released during the flights. [ABSTRACT FROM AUTHOR]

Data from the Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS) instruments onboard the Landsat 8 and Landsat 9 satellite platforms are subject to contamination by cloud cover, with cirrus contributions being the most difficult to detect and mask. To help address this issue, a cirrus detection channel (Band 9) centered within the 1.375-μm water vapor absorption region was implemented on OLI, with a spatial resolution of 30 m. However, this band has not yet been fully utilized in the Collection 2 Landsat 8/9 Level 2 surface temperature data products that are publicly released by U.S. Geological Survey (USGS). The temperature products are generated with a single-channel algorithm. During the surface temperature retrievals, the effects of absorption of infrared radiation originating from the warmer earth's surfaces by ice clouds, typically located in the upper portion of the troposphere and re-emitting at much lower temperatures (approximately 220 K), are not taken into consideration. Through an analysis of sample Level 1 TOA and Level 2 surface data products, we have found that thin cirrus cloud features present in the Level 1 1.375-μm band images are directly propagated down to the Level 2 surface data products. The surface temperature errors resulting from thin cirrus contamination can be 10 K or larger. Previously, we reported an empirical and effective technique for removing thin cirrus scattering effects in OLI images, making use of the correlations between the 1.375-μm band image and images of any other OLI bands located in the 0.4–2.5 μm solar spectral region. In this article, we describe a variation of this technique that can be applied to the thermal bands, using the correlations between the Level 1 1.375-μm band image and the 11-μm BT image for the effective removal of thin cirrus absorption effects. Our results from three data sets acquired over spatially uniform water surfaces and over non-uniform land/water boundary areas suggest that if the cirrus-removed TOA 11-μm band BT images are used for the retrieval of the Level 2 surface temperature (ST) data products, the errors resulting from thin cirrus contaminations in the products can be reduced to about 1 K for spatially diffused cirrus scenes. [ABSTRACT FROM AUTHOR]

Abstract: We present 123 cloud-resolving simulations to study how temperatures of anvil clouds and radiative tropopause (RT) change with surface warming. Our simulation results show that the RT warms at approximately the same rate as anvil clouds. This relationship persists across a variety of modeling choices, including surface temperature, greenhouse gas concentration, and the representation of radiative transfer. We further show that the shifting ozone profile associated with climate warming may give rise to a fixed RT temperature as well as a fixed anvil temperature. This result points to the importance of faithful treatment of ozone in simulating clouds and climate change; the robust anvil–RT relationship may also provide alternative ways to understand what controls anvil temperature.

Variability of ice microphysical properties like crystal size and density in cirrus clouds is important for climate through its impact on radiative forcing, but challenging to represent in models. For the first time, recent laboratory experiments of particle growth (tied to crystal morphology via deposition density) are combined with a state‐of‐the‐art Lagrangian particle‐based microphysics model in large‐eddy simulations to examine sources of microphysical variability in cirrus. Simulated particle size distributions compare well against balloon‐borne observations. Overall, microphysical variability is dominated by variability in the particles' thermodynamic histories. However, diversity in crystal morphology notably increases spatial variability of mean particle size and density, especially at mid‐levels in the cloud. Little correlation between instantaneous crystal properties and supersaturation occurs even though the modeled particle morphology is directly tied to supersaturation based on laboratory measurements. Thus, the individual thermodynamic paths of each particle, not the instantaneous conditions, control the evolution of particle properties. Plain Language Summary: Thin, high‐altitude ice clouds—cirrus—are critical to climate through their interactions with incoming solar radiation and outgoing longwave radiation. With a zoomed‐in view, observations show that cirrus comprise ice crystals of diverse sizes and shapes. These crystal properties determine the bulk properties of the clouds, like their ice water content. What controls this diversity of crystal properties? To address this question, we performed numerical simulations using a state‐of‐the‐art model that tracks the growth of individual particles, informed by laboratory crystal growth experiments, in a realistic turbulent cloud flow. We show that variability in the local environmental conditions (e.g., relative humidity) that particles experience in a turbulent environment is a primary driver of crystal diversity in cirrus. Diversity is also driven by different shapes of newly formed crystals, leading to different growth characteristics. This diversity drives spatial variability of properties like mean crystal density across the cloud layer. Climate models that represent cirrus using simple relationships based on observations that are essentially snapshots of average crystal properties cannot capture this variability. Overall, our analysis indicates that the history of environmental conditions along particle trajectories, not just instantaneous conditions, are required to understand crystal growth and variability in cirrus. Key Points: Variability in the thermodynamic histories of ice crystals are a primary driver of particle variability in cirrusDiversity in crystal morphology also drives spatial variability of mean particle size and density, particularly at mid‐levels in the cloudThermodynamic histories along particle trajectories, not just local conditions, are required to understand crystal growth in cirrus [ABSTRACT FROM AUTHOR]

Many types of halos (including arcs) appear in the sky. Each type of halo corresponds to the shape and orientation of ice crystals in clouds, and reflects the state of the atmosphere; therefore observing them from the ground greatly helps in understanding the state of the atmosphere. However, halos are easily obscured by the contrast of the cloud itself, making it difficult to observe them. This difficulty can be overcome by enhancing halos in images, for which various techniques have been developed. This study describes the construction of a sky-color model for halos and a new effective algorithm to reveal halos in images. [ABSTRACT FROM AUTHOR]

The paper deals with numerical simulations related to radiation transfer in ice clouds. A mathematical model of crystal particles of irregular shape and an algorithm for modeling such particles based on constructing a convex hull of a set of random points are considered. Two approaches to simulating radiation transfer in optically anisotropic clouds are studied. One approach uses pre-calculated scattering phase functions for crystals of various shapes and orientations. In the other approach, no knowledge of phase functions is required; the radiation scattering angle is simulated directly at interaction of a photon with faces of crystal. This approach enables simple adjustment of the input parameters of the problem to changing microphysical characteristics of the environment, including the shape, orientation, and transparency of particles and roughness of their boundaries, and does not require time-consuming pre-calculations. The impact of flutter on the radiation transfer by the cloud layer and angular distributions of the reflected and transmitted radiation are studied. [ABSTRACT FROM AUTHOR]

Stratospheric aerosol injection (SAI) aims to reflect solar radiation by increasing the stratospheric aerosol burden. To understand how the background circulation influences stratospheric transport of injected particles, we use a Lagrangian trajectory model (lacking numerical diffusion) to quantify particles' number, flux, lifetime, and tropospheric sinks from a SAI injection strategy under present-day conditions. While particles are being injected, stratospheric particle number increases until reaching a steady-state. During the steady-state, the time series of particle number shows a dominant period of ~2 years (rather than a 1-year cycle), suggesting modulation by the quasi-biannual oscillation. More than half of particles, injected in the tropical lower stratosphere (15° S to 15° N, 65 hPa), undergo quasi-horizontal transport to the midlatitude. We find a zonal asymmetry of particles' tropospheric sinks that are co-located with tropopause folding beneath the midlatitude jet stream, which can help predict tropospheric impacts of SAI (e.g., cirrus cloud thinning). [ABSTRACT FROM AUTHOR]

Cirrus clouds often contain numerous hollow ice crystals, which are distinct in scattering properties from solid ice crystals, and will be challenging to microphysical retrieval and radiative forcing assessment. Currently, hollow ice crystals have not been observed by remote sensing methods, and the estimation of their hollowness is a complex task. To address this issue, the Mixed Modal Hollow Columns (MMHC) model for hollow ice crystals is introduced, and its backscattering properties are computed using the physical optics approximation method. Through comparison with spaceborne lidar observations, we identify a specific type of cirrus associated with the MMHC model for the first time. The visible optical depth of this cirrus is less than or equal to 0.1, and the temperature is between −60 and −40°C. The MMHC characteristic cirrus clouds are prevalent in middle and high latitudes but less comm+on in low latitudes. They exhibit distinct patterns in terms of sea and land distribution as well as seasonal variation. Plain Language Summary: Cirrus clouds typically form at altitudes exceeding 6 km and consist of non‐spherical ice crystals, each with unique optical properties affecting the earth's radiation balance through scattering and absorption. Notably, these crystals include hollow formations, which are distinct in scattering properties from their solid counterparts. The coexistence of hollow and solid ice crystals presents challenges in accurately inverting ice crystal morphology in remote sensing and evaluating radiation properties in climate models. To address these complexities, we propose a MMHC model. Through analysis of spaceborne lidar observational data, we identify characteristic cirrus clouds associated with such type of ice crystals and study the global distribution and seasonal distribution of this kind of cirrus clouds. Key Points: A Mixed Modal Hollow Columns model is formulated to characterize the presence of hollow ice crystals in cirrus cloudsFor the first time, hollow characteristic cirrus clouds are observed using spaceborne lidarHollow characteristic cirrus clouds exhibit distinct global and seasonal distribution variations [ABSTRACT FROM AUTHOR]

Tropical tropopause layer (TTL) clouds have a significant impact on the Earth's radiative budget and regulate the amount of water vapor entering the stratosphere. Estimating the total coverage of tropical cirrus clouds is challenging, since the range of their optical depth spans several orders of magnitude, from thick opaque cirrus detrained from convection to sub-visible clouds just below the stratosphere. During the Strateole-2 observation campaign, three microlidars were flown on board stratospheric superpressure balloons from October 2021 to late January 2022, slowly drifting only a few kilometers above the TTL. These measurements have unprecedented sensitivity to thin cirrus and provide a fine-scale description of cloudy structures both in time and in space. Case studies of collocated observations with the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) show very good agreement between the instruments and highlight the Balloon-borne Cirrus and convective overshOOt Lidar's (BeCOOL) higher detection sensitivity. Indeed, the microlidar is able to detect optically very thin clouds (optical depth τ<2×10-3) that are undetected by CALIOP. Statistics on cloud occurrence show that TTL cirrus appear in about 50 % of the microlidar profiles and have a mean geometrical depth of 1 km. Ultrathin TTL cirrus (τ<2×10-3) have a significant coverage (23 % of the profiles), and their mean geometrical depth is 0.5 km. [ABSTRACT FROM AUTHOR]

Warm-air intrusions (WAIs) are responsible for the transportation of warm and moist air masses from the mid-latitudes into the high Arctic (> 70° N). In this work, we study cirrus clouds that form during WAI events (WAI cirrus) and during undisturbed Arctic conditions (AC cirrus) and investigate possible differences between the two cloud types based on their macrophysical and optical properties with a focus on relative humidity over ice (RHi). We use airborne measurements from the combined high-spectral-resolution and differential-absorption lidar, WALES, performed during the HALO-(AC) 3 campaign. We classify each research flight and the measured clouds as either AC or WAI, based on the ambient conditions, and study the macrophysical, geometrical and optical characteristics for each cirrus group. As our main parameter we choose the relative humidity over ice (RHi), which we calculate RHi by combining the lidar water vapor measurements with model temperatures. Ice formation occurs at certain RHi values depending on the dominant nucleation process taking place. RHi can thus be used as an indication of the nucleation process and the structure of cirrus clouds. We find that during WAI events the Arctic is warmer and moister and WAI cirrus clouds are both geometrically and optically thicker compared to AC cirrus. WAI cirrus clouds and the layer directly surrounding them are more frequently supersaturated, also at high supersaturations over the threshold for homogeneous ice nucleation (HOM). AC cirrus clouds have a supersaturation-dominated cloud top and a subsaturated cloud base. WAI cirrus clouds also have high supersaturations at cloud top but also at cloud base. [ABSTRACT FROM AUTHOR]

"The Art and Science of the Atmosphere" is an article written by Alan Sealls, a retired Chief Meteorologist and author. Sealls discusses his passion for both photography and meteorology, explaining how the two disciplines complement each other. He provides tips for capturing weather phenomena, such as using the direction and altitude of the sun and the type of clouds to forecast photo opportunities. Sealls also showcases several of his own photographs, including images of crepuscular rays, a circumzenith arc, a dust storm, a fogbow, grid waves, a gust front panorama, ice storm icicles, a cumulonimbus cloud, lightning strike, and a red sky at night. [Extracted from the article]

Cirrus (Ci) clouds have an important influence on Earth's radiation budget, and they remain one of the most significant uncertainties in predicting Earth's climate. In this study, we use ground-based radiometers along with a sky imager to monitor clouds and retrieve cloud properties (cloud fraction (CF), cloud optical depth (COD) and effective radii (Re)) over a rain shadow region in south peninsular India during September and October months, 2011. Lower part of Ci clouds are identified using the thresholds pertaining to COD and cloud base height (CBH). The optical and radiative properties of Ci clouds showed large variability on temporal and diurnal scales. The CF, COD and Re varied from 7 to 100%, 0.76 to 9.99, and 2.76 to 37.92 μm, respectively. The CBH and Cloud Base Temperature (CBT) are found to vary from 7.24 to 8.99 km and − 31.99 to − 13.75 °C. The Shortwave Cloud Radiative forcing (SWCRF) exerted by the lower part of Ci clouds over the region is observed to vary from − 435 to 148.87 W m−2 on a temporal scale with an average value of − 23.06 W m−2. The relationship between SWCRF and COD revealed radiative cooling effect with increase in COD with a dependency rate of − 18.53 W m−2/τ. SWCRF is found to be more sensitive to COD as compared to other cloud characteristics (CF, CBH and CBT). The case studies depict that the observed lower part of Ci clouds are advected from the ocean indicating the influence of large scale systems. Lower part of Ci optical and radiative properties showed wide variability depending up on the source of formation and evolution. This study also suggests that the high temporal variability of optical and radiative properties of Ci clouds needs to be well considered in climate models to reduce the uncertainty of cirrus radiative effects. [ABSTRACT FROM AUTHOR]

The ice phase impacts many cloud properties as well as cloud lifetime. Ice particles that sediment into a lower cloud from an upper cloud (external seeder–feeder process) or into the mixed-phase region of a deep cloud from cirrus levels (internal seeder–feeder process) can influence the ice phase of the lower cloud, amplify cloud glaciation and enhance surface precipitation. Recently, numerical weather prediction modeling studies have aimed at representing the ice crystal number concentration in mixed-phase clouds more accurately by including secondary ice formation processes. The increase in the ice crystal number concentration can impact the number of ice particles that sediment into the lower cloud and alter its composition and precipitation formation. In the Swiss Alps, the orography permits the formation of orographic clouds, making it ideal for studying the occurrence of multi-layered clouds and the seeder–feeder process. We present results from a case study on 18 May 2016, showing the occurrence frequency of multi-layered clouds and the seeder–feeder process. About half of all observed clouds were categorized as multi-layered, and the external seeder–feeder process occurred in 10 % of these clouds. Between cloud layers, ≈60 % of the ice particle mass was lost due to sublimation or melting. The external seeder–feeder process was found to be more important than the internal seeder–feeder process with regard to the impact on precipitation. In the case where the external seeder–feeder process was inhibited, the average surface precipitation and riming rate over the domain were both reduced by 8.5 % and 3.9 %, respectively. When ice–graupel collisions were allowed, further large reductions were seen in the liquid water fraction and riming rate. Inhibiting the internal seeder–feeder process enhanced the liquid water fraction by 6 % compared to a reduction of 5.8 % in the cloud condensate, therefore pointing towards the de-amplification in cloud glaciation and a reduction in surface precipitation. Adding to the observational evidence of frequent seeder–feeder situations, at least over Switzerland, our study highlights the extensive influence of sedimenting ice particles on the properties of feeder clouds as well as on precipitation formation. [ABSTRACT FROM AUTHOR]

Organic‐lean and organic‐rich size‐selected soot particles were exposed to a varying O3 concentration, progressively decreasing the soot‐water contact angle (θ) to study its impact on ice nucleation (IN). The IN ability of fresh and O3‐aged soot between 218 and 233 K was observed while monitoring the particle mass and size distributions. The properties of fresh and O3‐aged bulk organic‐lean soot samples with a low and high O3‐adsorption were characterized for soot‐water θ, chemical composition, functional groups, soot‐water interaction ability and porosity. By retaining the soot porosity between aged and unaged samples, we demonstrate that a decrease in θ after O3‐aging enhances organic‐lean soot IN via pore condensation and freezing. Fresh organic‐rich soot exhibits suppressed homogeneous freezing, but after O3‐aging it freezes within uncertainty of the homogeneous freezing threshold of solution drops, because of increased hydrophilicity. Plain Language Summary: This study investigates the ice formation ability of soot exposed to O3 in the temperature range <−40°C relevant to the cirrus cloud regime for the role of surface wettability in the ice formation ability of organic‐lean and ‐rich soot. O3‐aged organic‐lean soot is more effective at forming ice crystals than unaged soot, due to an increase in soot‐water interaction ability promoting capillary condensation of water into porous structures that subsequently freeze. As the chemical functional group abundance of the organic‐lean soot does not change after O3‐exposure, the increased soot‐water interaction ability for the soot is attributed to O3‐H2O binding rather than surface oxidation. However, both water sorption isotherms and pore size distribution derived from N2 sorption measurements confirm the O3‐adsorption does not change the porosity of organic‐lean soot. This highlights the sole importance of hydrophilicity in pore water condensation prior to soot ice nucleation. O3‐aged organic‐rich soot shows poor ice formation ability because of unavailability of porous structures to condense capillary water. This study implies that organic‐lean soot will have an enhanced ice formation ability in the upper troposphere if exposed to O3 concentrations similar to that simulated in this study. Key Points: Higher O3‐concentration leads to a larger decease in water contact angle for organic‐lean soot without changing the soot porosityThe decrease in soot‐water contact angle from O3‐aging produces an ice nucleation enhancement for organic‐lean soot via PCF at T < 233 KO3‐aged organic‐rich soot freezes homogeneously at bulk droplet conditions despite increased hydrophilicity due to unavailable pores [ABSTRACT FROM AUTHOR]

This study presented an analysis of the geometric and optical properties of cirrus clouds with data produced by Compact Cloud-Aerosol Lidar (ComCAL) over Koror, Palau (7.3°N, 134.5°E), in the Tropical Western Pacific region. The lidar measurement dataset covers April 2018 to May 2019 and includes data collected during March, July and August 2022. The results show that cirrus clouds occur approximately 47.9% of the lidar sampling time, predominantly between altitudes of 15 and 18 km. Seasonal variations in cirrus top height closely align with those of the cold point tropopause. Most cirrus clouds exhibit low cloud optical depth (COD < 0.1), with an annual mean depolarization ratio of 31 ± 19%. Convective-forming cirrus clouds during the summer monsoon season exhibit a larger size by notably lower values in terms of color ratio. Extremely thin cirrus clouds (COD < 0.005) constituting 1.6% of total cirrus occurrences are frequently observed at 1–2 km above the cold point, particularly during winter and summer, suggesting significant stratosphere–troposphere exchange. The coldest and highest tropopause over Palau is persistent during winter, and related to the pathway of tropospheric air entering the stratosphere through the cold trap. In summer, the extremely thin cirrus above the cold point is likely correlated with equatorial Kelvin waves induced by western Pacific monsoon convection. [ABSTRACT FROM AUTHOR]

Tropical-tropopause-layer cirrus clouds and their radiative effects represent a major uncertainty in the evaluation of Earth's energy budget. High-altitude aircraft offer an opportunity to provide observations at cirrus cloud altitudes, most commonly using in situ measurements of ice particle optical properties and composition. In particular, remote sensing of scattering properties and near-IR ice water absorption in the limb can provide unique insights into thin and sub-visible cirrus clouds. Here we present novel spectroscopic observations of path-averaged ice water absorptions on board NASA's Global Hawk aircraft during the Airborne Tropical TRopopause Experiment (ATTREX), which took place in 2011, 2013, and 2014. The University of California Los Angeles and University of Heidelberg mini-differential optical absorption spectroscopy (mini-DOAS) instrument provided multi-angle limb-scanning observations of scattered solar radiation in the near-IR (900–1726 nm), allowing the identification of ice and liquid water, O 2 , CO 2 , and H 2 O. The VLIDORT-QS radiative transfer (RT) code was specifically developed for this study and used to simulate high-altitude limb observations for varied cloud scenarios. We performed a comprehensive sensitivity study, developing a fundamental understanding of airborne near-IR limb observations of cirrus clouds. We identified two general distinct cases: a linear regime for optically thin clouds, where the ice absorption is proportional to ice water content (IWC), and a regime for optically thick cirrus clouds, where ice absorption is in saturation and independent of IWC. Results also demonstrate how molecular oxygen absorption can be used to infer information on optical properties of ice particles in the second regime only, with minimal information for thin cirrus clouds. We also explored the feasibility of retrieving IWC from mini-DOAS path-averaged ice water absorption (SIWP) measurements. This innovative interpolation-based approach requires a small number of RT calculations per observation to determine the sensitivity of SIWP to IWC. Spectral retrievals were applied for a particularly interesting case during Science Flight 2 over Guam in February 2014, during which the aircraft flew in circles in the same general area for an extended period of time. Retrieved IWC results are consistent with independent in situ measurements from other instruments on board. The measurements of ice particle scattering and absorption at different azimuths relative to the sun and at different altitudes represent a unique opportunity to test our approach and to infer properties of the ice particles, together with information on cirrus cloud radiative transfer. [ABSTRACT FROM AUTHOR]

The Anthropogenic Carbon Dioxide Monitoring (CO2M) mission is a constellation of satellites currently planned to be launched in 2026. CO2M is planned to be a core component of a Monitoring and Verification Support (MVS) service capacity under development as part of the Copernicus Atmosphere Monitoring Service (CAMS). The CO2M radiance measurements will be used to retrieve column-averaged dry-air mole fractions of atmospheric carbon dioxide (XCO2), methane (XCH4) and total columns of nitrogen dioxide (NO2). Using appropriate inverse modelling, the atmospheric greenhouse gas (GHG) observations will be used to derive United Nations Framework Convention on Climate Change (UNFCCC) COP 21 Paris Agreement relevant information on GHG sources and sinks. This challenging application requires highly accurate XCO2 and XCH4 retrievals. Three different retrieval algorithms to derive XCO2 and XCH4 are currently under development for the operational processing system at EUMETSAT. One of these algorithms uses the heritage of the FOCAL (Fast atmOspheric traCe gAs retrievaL) method, which has already successfully been applied to measurements from other satellites. Here, we show recent results generated using the CO2M version of FOCAL, called FOCAL-CO2M. To assess the quality of the FOCAL-CO2M retrievals, a large set of representative simulated radiance spectra has been generated using the radiative transfer model SCIATRAN. These simulations consider the planned viewing geometry of the CO2 instrument and corresponding geophysical scene data (including different types of aerosols and varying surface properties), which were taken from model data for the year 2015. We consider instrument noise and systematic errors caused by the retrieval method but have not considered additional error sources due to, for example, instrumental issues, spectroscopy or meteorology. On the other hand, we have also not taken advantage in this study of CO2M's MAP (multi-angle polarimeter) instrument, which will provide additional information on aerosols and cirrus clouds. By application of the FOCAL retrieval to these simulated data, confidence is gained that the FOCAL method is able to fulfil the challenging requirements for systematic errors for the CO2M mission (spatio-temporal bias ≤ 0.5 ppm for XCO2 and ≤ 5 ppb for XCH4). [ABSTRACT FROM AUTHOR]

Surface solar irradiance varies on scales as small as seconds or metres. This variability is driven mostly by wavelength‐dependent scattering by clouds, and to a lesser extent by aerosols and water vapour. The highly variable nature of solar irradiance is not resolved by most atmospheric models, yet it affects, most notably, the land–atmosphere coupling and the quality of solar energy forecasting. Characterising variability, understanding the mechanisms, and developing models capable of resolving it accurately requires spatially and spectrally resolved observational datasets of solar irradiance at high resolution, which are rare. In 2021, we deployed a network of low‐cost radiometers in the Field Experiment on submesoscale spatio‐temporal variability in Lindenberg (FESSTVaL, Germany) and Land surface Interactions with the Atmosphere over the Iberian Semi‐arid Environment (LIAISE, Spain) field campaigns to gather data on cloud‐driven surface patterns of irradiance, including spectral effects, with the aim of addressing this gap in observations and understanding. We find in case studies of cumulus, altocumulus, and cirrus clouds that these clouds generate large spatiotemporal variability in irradiance, but through different mechanisms and at different spatial scales, ranging from 50 m to 30 km. Spectral irradiance in the visible range varies at similar scales, with significant blue enrichment in cloud shadows, most strongly for cumulus, and red enrichment in irradiance peaks, particularly in the case of semitransparent clouds or near cumulus cloud edges. Under clear‐sky conditions, solar irradiance varies significantly in water‐vapour absorption bands at the minute scale, due to variability in atmospheric moisture in the boundary layer. With this study, we show that observing detailed spatiotemporal irradiance patterns is possible using a relatively small, low‐cost sensor network, and that such network observations can provide insight and validation for the development of models capable of resolving irradiance variability. [ABSTRACT FROM AUTHOR]

Contrails created by aircraft are a very hot topic today because they contribute to the warming of the atmosphere. Air traffic density is very high, and current forecasts predict a further significant increase. Increased air traffic volume is associated with an increased occurrence of contrails and induced cirrus clouds. The scientific level of contrails and their impact on the Earth's climate is surprisingly low. The scientific studies published so far are mainly based on global models, in situ measurements, and satellite observations of contrails. The research is based on observations of contrails in flight paths in the vicinity of Děčín and Prague, and the collection of flight and meteorological data. It focused on the influence of the meteorological situation on the formation of persistent contrails. The collected data on contrails and meteorological variables were statistically processed using machine learning methods for classification models. Several models were developed to predict and simulate the properties of contrails as a function of given air traffic and meteorological conditions. The Random Forests model produced the best results. Dependencies between meteorological conditions, formation, and contrail lifetime were found. The aim of the study was to identify the possibility of using available meteorological data to predict persistent contrails. [ABSTRACT FROM AUTHOR]

Aviation is a rapidly growing source of climate forcing, and the non-CO2 effective radiative forcing of aviation is approximately twice that of aviation CO2. However, considerable uncertainty remains regarding aviation's non-CO2 effects because the radiative forcing of aviation aerosol-cloud interactions, especially with cirrus clouds, is poorly known. Here, we use a large eddy simulation model to quantify the impact of ice crystal number concentration (ICNC) perturbations on the water budget and microphysics of pre-existing cirrus clouds. These perturbations aim to represent the second half of the chain of effects linking aircraft aerosol emissions to changes in ICNC and ice water path. We examine two types of cirrus: warm conveyor belt outflow and gravity wave cirrus, which represent different updraft regimes and formation mechanisms. In both cases, the primary effect of an idealised increase in ICNC is to extend cloud lifetime, with the increase proportional to the magnitude of the ICNC perturbation applied. The effect is more pronounced in the gravity wave cirrus case than in the warm conveyor belt outflow cirrus case because the latter has lower initial ICNC and ice water contents. Quantitatively, the sensitivity of ice water path (IWP) to changes in ICNC, expressed as ∆ln(IWP)/∆ln(ICNC), is 0.06 for gravity wave cirrus and 0.35 for warm conveyor belt outflow cirrus when calculated 45 minutes after imposing the ICNC perturbation. These results suggest that aviation has the potential to increase the lifetime and radiative effects of pre-existing cirrus clouds. [ABSTRACT FROM AUTHOR]

We present a machine learning based emulator of a microphysics scheme for condensation and precipitation processes (Zhao‐Carr) used operationally in a global atmospheric forecast model (FV3GFS). Our tailored emulator architecture achieves high skill (≥94%) in predicting condensate and precipitation amounts and maintains low global‐average bias (≤4%) for 1 year of continuous simulation when replacing the Fortran scheme. The stability and success of this emulator stems from key design decisions. By separating the emulation of condensation and precipitation processes, we can better enforce physical priors such as mass conservation and locality of condensation, and the vertical dependence of precipitation falling downward, using specific network architectures. An activity classifier for condensation imitates the discrete‐continuous nature of the Fortran microphysics outputs (i.e., tendencies are identically zero where the scheme is inactive, and condensate is zero where clouds are fully evaporated). A temperature‐scaled conditional loss function ensures accurate condensate adjustments for a high dynamic range of cloud types (e.g., cold, low‐condensate cirrus clouds or warm, condensate‐rich clouds). Despite excellent overall performance, the emulator exhibits some deficiencies in the uppermost model levels, leading to biases in the stratosphere. The emulator also has short episodic skill dropouts in isolated grid columns and is computationally slower than the original Fortran scheme. Nonetheless, our challenges and strategies should be applicable to the emulation of other microphysical schemes. More broadly, our work demonstrates that with suitable physically motivated architectural choices, ML techniques can accurately emulate complex human‐designed parameterizations of fast physical processes central to weather and climate models. Plain Language Summary: In this study, we create computer code that uses machine learning to mimic a weather model's algorithm for handling how clouds form and rain falls. When used in the weather model to replace this algorithm, our machine learning code is highly accurate in simulations for a whole year. We achieve this by making smart code design choices. We split the code into two parts: one for cloud formation and one for rain and snow. This allows us to better build important aspects of these processes into the machine learning approach. For instance, clouds form where it is moist and evaporate when it gets dry, and rain and snow fall downward. Our code learns cloud behavior based on temperature to ensure it works both for cold, thin clouds high up in the sky and warm, thick clouds closer to the ground. Our work shows a path for suitably designed machine learning code to eventually replace important parts of weather and climate models, but also that this path still requires careful human design respecting known physical principles. Key Points: We build an emulator to replace the Zhao‐Carr Fortran microphysics scheme in FV3GFSThe integrated emulator sustains high skill throughout a 1‐year simulationTailoring the ML architecture to the structure of the underlying scheme greatly improves the online behavior of the emulator [ABSTRACT FROM AUTHOR]

Mineral dust, the most abundant atmospheric aerosol by mass, interacts with radiation directly and alters cloud properties indirectly. Many operational numerical weather prediction models account for aerosol direct effects by using climatological mean concentrations and neglect indirect effects. This simplification may lead to shortcomings in model forecasts during outbreaks of Saharan dust towards Europe, when climatological mean dust concentrations deviate strongly from actual concentrations. This study investigates errors in model analyses and short‐range forecasts during such events. We investigate a pronounced dust event in March 2021 using the pre‐operational ICOsahedral Nonhydrostatic weather and climate model with Aerosols and Reactive Trace gases (ICON‐ART) with prognostic calculation of dust and the operational European Centre for Medium‐Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) model, which deploys a dust climatology. We compare model analysis and forecast with measurements from satellite and in situ instruments. We find that inclusion of prognostic aerosol and direct radiative effects from dust improves forecasts of surface radiation during clear‐sky conditions. However, dust‐induced cirrus clouds are strongly underestimated, highlighting the importance of representing indirect effects adequately. These findings are corroborated by systematic quantification of forecast errors against satellite measurements. For this we construct an event catalogue with 49 dust days over Central Europe between January 2018 and March 2022. We classify model cells by simulated and observed cloudiness and simulated dustiness in the total atmospheric column. We find significant overestimations of brightness temperature for cases with dust compared with cases without dust. For surface shortwave radiation, we find median overestimations of 6.2% during cloudy conditions with dust optical depth greater than 0.1, however these are not significant compared with cloudy conditions without dust. Our findings show that the pre‐operational ICON‐ART and the operational IFS model still do not reproduce cloudiness adequately during events with Saharan dust over Central Europe. Missing implementations of prognostic dust, particularly of indirect effects on cloud formation, lead to significant underestimations of cloudiness and potentially overestimations of surface radiation. [ABSTRACT FROM AUTHOR]

Ice-nucleating particles catalyze ice formation in clouds, affecting climate through radiative forcing from aerosol–cloud interactions. Aviation directly emits particles into the upper troposphere where ice formation conditions are favorable. Previous studies have used proxies of aviation soot to estimate their ice nucleation activity; however, investigations with commercial aircraft soot from modern in-use aircraft engines have not been quantified. In this work, we sample aviation soot particles at ground level from different commercial aircraft engines to test their ice nucleation ability at temperatures ≤228 K as a function of engine thrust and soot particle size. Additionally, soot particles were catalytically stripped to reveal the impact of mixing state on their ice nucleation ability. Particle physical and chemical properties were further characterized and related to the ice nucleation properties. The results show that aviation soot nucleates ice at or above relative humidity conditions required for homogeneous freezing of solution droplets (RH hom). We attribute this to a mesopore paucity inhibiting pore condensation and the sulfur content which suppresses freezing. Only large soot aggregates (400 nm) emitted under 30 %–100 % thrust conditions for a subset of engines (2 out of 10) nucleate ice via pore condensation and freezing. For those specific engines, the presence of hydrophilic chemical groups facilitates the nucleation. Aviation soot emitted at thrust ≥ 100 % (sea level thrust) nucleates ice at or above RH hom. Overall, our results suggest that aviation soot will not contribute to natural cirrus formation and can be used in models to update impacts of soot–cirrus clouds. [ABSTRACT FROM AUTHOR]

In this study, a method for assimilating FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances (CER) is investigated, and the impact of this method on water vapor analysis and rainstorm forecasting is examined through observing system simulation experiments and actual case experiments. The high proportion of inverted humidity profiles in the cirrus‐effected pixels is the main reason for the negative effect of assimilation in the mid‐to‐lower troposphere. To address this, relevant constraint conditions are incorporated into the cost function. The statistical results reveal that the addition of a CER assimilation improves the analysis increment of water vapor, with pattern correlation coefficients of 0.33, 0.35, and 0.20 at 200, 300, and 400 hPa, respectively, which are greater than those of a clear‐sky radiance assimilation (0.28, 0.33, and 0.17, respectively). Moreover, the inclusion of a CER assimilation greatly improves data utilization, and has a neutral to positive effect on precipitation forecasting. Plain Language Summary: Infrared all‐sky radiance assimilation is an attractive but challenging problem in satellite data assimilation. Is there an alternative approach to achieve the assimilation of infrared radiance for a certain type of cloud? It is found that cirrus clouds, which are loose ice clouds composed of ice crystals, can partially transmit infrared radiance and are large in number. Considering these advantages, a new direct assimilation method for FY4A advanced geostationary radiance imager (AGRI) cirrus‐effected radiances is proposed in this paper. The method addresses the uncertainty in the assimilation of cirrus‐effected radiances by adding weak constraints of inverse humidity. This research highlights the substantial increase in AGRI data usage when incorporating cirrus‐effected radiance data, as well as the neutral‐to‐positive impact on water vapor analysis and precipitation forecasting. This study also suggests that future endeavors could combine infrared channels with lower‐level microwave channels, which may have a more significant contribution to infrared radiance assimilation. Key Points: A high percentage of inverse humidity exists in the atmospheric profile corresponding to cirrus cloud fields of view over landThe assimilation of cirrus cloud pixels greatly improves the utilization rateAssimilating advanced geostationary radiance imager cirrus‐effected radiances has a neutral to positive effect on water vapor analysis and precipitation forecasting [ABSTRACT FROM AUTHOR]

Remote sensing satellite monitoring involving the use of shortwave infrared (SWIR) solar backscatter radiation to measure atmospheric CH4 column concentrations provides wide−ranging and accurate data for quantitatively determining atmospheric CH4 emissions and is highly important for human studies of atmospheric composition and environmental protection. The ESA−launched Sentinel−2 satellite equipped with a tropospheric monitoring instrument (TROPOMI) can provide the concentration of CH4 columns in every piece of the global atmosphere every day. However, these data may be affected by surface albedo, SWIR, aerosols, cirrus cloud scattering, and other factors. The greenhouse gas observing satellite (GOSAT) launched by Japan has fairly accurate data that are minimally affected by the aforementioned factors; however, its data density is much less than that of the TROPOMI. In this study, we propose a CH4 model that combines the TROPOMI and GOSAT data. We construct the model by analyzing the data from the TROPOMI and GOSAT at the same location at the same time. Then, we apply the proposed model to a certain location at a certain time with TROPOMI data but without GOSAT data to obtain a large range of high−precision CH4 data. The most developed urban agglomeration in the Yangtze River Delta in China was selected for model construction and the correlations between the TROPOMI and GOSAT data and their spatial and temporal trends were analyzed. First, we analyzed the CH4 concentrations in the same area measured by both models. The results revealed a high degree of temporal and spatial correlation in the YRD region. The correlation coefficient reached 0.71 in the metropolitan area of the YRD. At the small−city scale, the correlation is much more significant, with the correlation reaching 0.80, 0.79, and 0.71 for Nanjing, Shanghai, and Ningbo, respectively. The most accurate model was screened through comparative construction to calibrate the TROPOMI data and high−precision and high−coverage CH4 concentration information was obtained for the study area. Five models (linear model, quadratic term model, cubic term model, lognormal model, and logistic model) were used to select the best−fitting model. The magnitudes of the differences in the CH4 concentrations calculated by each model were compared. The final results showed that the linear model, as the prediction model, had the highest accuracy, with a coefficient of determination (R22) of 0.542. To avoid the specificity of the constructed model, we used the same method in several simulations to validate. The coefficient of determination of the model constructed with different stochastic data was greater than 0.5. Subsequently, we used Nanjing as the study area and applied the same method to construct the model. The coefficient of determination of the model (R22) was approximately 0.601. The model constructed in this research can be used not only for data conversion between the same products from different sensors to obtain high−precision data products but also for calibrating newly developed satellite data products that utilize mature data products. [ABSTRACT FROM AUTHOR]

Large amounts of tropical precipitation have been observed as significantly concentrated over the western coast of Sumatra Island. In the present study, we used a cloud-resolving model to perform 14-day numerical simulations and reproduce the distinctive precipitation distributions over western Sumatra Island and adjacent areas. The control experiment, in which the warmer sea surface temperature (SST) near the coast was incorporated and the terminal velocity and effective radius of ice clouds were parameterized to be temperature dependent, adequately reproduced the precipitation concentration as well as the diurnal cycles of precipitation. We then used the column-integrated frozen moist static energy budget equation, which is virtually equivalent to the column-integrated moisture budget equation under the weak temperature gradient assumption, to formulate sensitivity experiments focusing on the effects of coastal SST and upper-level ice clouds. Analysis of the time-averaged fields revealed that the column-integrated moisture and precipitation in the coast were significantly reduced when a cooler coastal SST or larger ice cloud particle size was assumed. Based on the comparison of the sensitivity experiments and in situ observations, we speculate that ice clouds, which are exported from inland convection that is strictly regulated by solar radiation, promote the accumulation of moisture in the coastal region by mitigating radiative cooling. Together with the moisture and heat supplied by the warm ocean surface, they contribute to the large amounts of precipitation here. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Water vapor and cirrus clouds in the tropical tropopause layer (TTL) are important for the climate and are largely controlled by temperature in the TTL. On interannual timescales, both stratospheric and tropospheric modes of the large‐scale variability could affect temperatures in the TTL. Here multiple linear regression (MLR) is used to investigate explained variance in the cold point tropopause temperature (CPT), cold point tropopause height (CPZ), 83 hPa water vapor (WV83), 83 hPa ozone (O383), and total cirrus cloud fraction with cloud base (TTLCCF) and top (ALLCF) above 14.5 km, all averaged over 15°S‐15°N. Predictors of the MLR are a set of stratospheric and tropospheric large‐scale modes of variability. The MLR explains significant variance in CPT (76%), CPZ (78%), WV83 (65%), O383 (62%), TTLCCF (52%), and ALLCF (36%). The interannual variability of CPT and WV83 is dominated by stratospheric processes associated with the Quasi‐Biennial Oscillation (QBO) and Brewer‐Dobson Circulation (BDC), whereas the variability of CPZ, O383, TTLCCF and ALLCF is also controlled by 500 hPa temperature (T500). Residual variability in CPT and CPZ not captured by the MLR are further significantly correlated to stratospheric temperature. It is shown that the portion of the BDC's shallow branch missed by the eddy heat flux based BDC index contributes significant amounts of the explained variances. Plain Language Summary: Between the tropical upper troposphere and lower stratosphere, water can exist as either vapor or ice. The amount of water that enters the stratosphere depends on the portion of vapor that is frozen out by the coldest temperature that air experiences in this region, which on interannual timescales could be modulated by both large‐scale stratospheric and tropospheric modes of variability. Here we show that 76%, 65%, and 52% of the interannual variance in cold point temperature, water vapor at 83 hPa, and ice cloud fraction in this region can be explained using a multiple linear regression (MLR), where the predictors are the modes of the large‐scale variability. Stratospheric processes are much more important in controlling the interannual variance of cold point temperature and water vapor at 83 hPa, but notably, the height of the cold point is controlled by both stratospheric and tropospheric processes. Residual variability of the cold point temperature not captured by the MLR is still connected to temperature variability in the stratosphere. Key Points: The interannual variability in the cold point tropopause temperature averaged over 15°S‐15°N is driven by stratospheric processesThis cold point tropopause temperature residual after regressing out large‐scale modes is still correlated with stratospheric temperatureThe portion of the BDC's shallow branch, which is independent of our eddy heat flux BDC index, is an important source of TTL variability [ABSTRACT FROM AUTHOR]

Organized deep convective activity has been routinely monitored by satellite precipitation radar from the Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Mission (GPM). Organized deep convective activity is found to increase not only with sea surface temperature (SST) above 27°C, but also with low-level wind shear. Precipitation shows a similar increasing relationship with both SST and low-level wind shear, except for the highest low-level wind shear. These observations suggest that the threshold for organized deep convection and precipitation in the tropics should consider not only SST, but also vertical wind shear. The longwave cloud radiative feedback, measured as the tropospheric longwave cloud radiative heating per amount of precipitation, is found to generally increase with stronger organized deep convective activity as SST and low-level wind shear increase. Organized deep convective activity, the longwave cloud radiative feedback, and cirrus ice cloud cover per amount of precipitation also appear to be controlled more strongly by SST than by the deviation of SST from its tropical mean. This study hints at the importance of non-thermodynamic factors such as vertical wind shear for impacting tropical convective structure, cloud properties, and associated radiative energy budget of the tropics. Significance Statement: This study uses tropical satellite observations to demonstrate that vertical wind shear affects the relationship between sea surface temperature and tropical organized deep convection and precipitation. Shear also affects associated cloud properties and how clouds affect the flow of radiation in the atmosphere. Although how vertical wind shear affects convective organization has long been studied in the mesoscale community, the study attempts to apply mesoscale theory to explain the large-scale mean organization of tropical deep convection, cloud properties, and radiative feedbacks. The study also provides a quantitative observational baseline of how vertical wind shear modifies cloud radiative effects and convective organization, which can be compared to numerical simulations. [ABSTRACT FROM AUTHOR]

In this paper a statistical study of cirrus geometrical and optical properties based on 4 years of continuous ground-based lidar measurements with the Barcelona (Spain) Micro Pulse Lidar (MPL) is analysed. First, a review of the literature on the two-way transmittance method is presented. This method is a well-known lidar inversion method used to retrieve the optical properties of an aerosol–cloud layer between two molecular (i.e. aerosol and cloud-free) regions below and above, without the need to make any a priori assumptions about their optical and/or microphysical properties. Second, a simple mathematical expression of the two-way transmittance method is proposed for both ground-based and spaceborne lidar systems. This approach of the method allows the retrieval of the cloud optical depth, the cloud column lidar ratio and the vertical profile of the cloud backscatter coefficient. The method is illustrated for a cirrus cloud using measurements from the ground-based MPL and from the spaceborne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Third, the database is then filtered with a cirrus identification criterion based on (and compared to) the literature using only lidar and radiosonde data. During the period from November 2018 to September 2022, 367 high-altitude cirrus clouds were identified at 00:00 and 12:00 UTC, of which 203 were successfully inverted with the two-way transmittance method. The statistical results of these 203 high-altitude cirrus clouds show that the cloud thickness is 1.8 ± 1.1 km, the mid-cloud temperature is - 51 ± 8 ∘ C and the linear cloud depolarization ratio is 0.32 ± 0.13. The application of the transmittance method yields an average cloud optical depth (COD) of 0.36 ± 0.45 and a mean effective column lidar ratio of 30 ± 19 sr. Statistical results of the errors associated with the two-way transmittance method retrievals are also provided. The highest occurrence of cirrus is observed in spring and the majority of cirrus clouds (48 %) are visible (0.03 < COD < 0.3), followed by opaque (COD > 0.3) with a percentage of 38 %. Together with results from other sites, possible latitudinal dependencies have been analysed together with correlations between cirrus cloud properties. For example, we noted that in Barcelona the COD correlates positively with the cloud base temperature, effective column lidar ratio and linear cloud depolarization ratio and negatively with the cloud base height. [ABSTRACT FROM AUTHOR]

Observations and measurements show that crystals remain relatively compact at low ice supersaturations, but become increasingly hollowed and complex as the ice supersaturation rises. Prior measurements at temperatures >−25°C indicate that the transition from compact, solid ice to morphologically complex crystals occurs when the excess vapor density exceeds a threshold value of about 0.05 g m−3. A comparable threshold is not available at low temperatures. A temperature-dependent criterion for the excess vapor density threshold (Δρthr) that defines morphological transformations to complex ice is derived from laboratory measurements of vapor grown ice at temperatures below −40°C. This criterion depends on the difference between the equilibrium vapor density of liquid ( ρ e l ) and ice (ρei) multiplied by a measurement-determined constant, Δ ρ thr ≃ 0.27 (ρ e l − ρ e i ) . The new criterion is consistent with prior laboratory measurements, theoretical estimates, and it reproduces the classical result of about 0.05 g m−3 above −25°C. Since Δρthr defines the excess vapor density above which crystals transition to a morphologically complex (lower density) growth mode, we can estimate the critical supersaturation (scrit) for step nucleation during vapor growth. The derived values of scrit are consistent with previous measurements at temperatures above −20°C. No direct measurements of scrit are available for temperatures below −40°C; however, our derived values suggest some measurement-based estimates may be too high while estimates from molecular dynamics simulations may be too low. [ABSTRACT FROM AUTHOR]