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The susceptibility of cloud droplet number concentration Nd$\\left({N}_{\\mathrm{d}}\\right)$to aerosols (β)$(\\beta )$remains challenging to constrain in satellite observations. This difficulty arises from limitations in representing cloud condensation nuclei, which depend on aerosol size and composition. To address this, we combine aerosol‐type‐specific retrievals of dry extinction coefficient and number concentration from Cloud–Aerosol LiDAR and Infrared Pathfinder Satellite Observation with co‐located Nd${N}_{\\mathrm{d}}$from CloudSat and Moderate Resolution Imaging Spectroradiometer. We find that β$\\beta $associated with mineral dust is consistently near zero across all aerosol‐Nd${N}_{\\mathrm{d}}$combinations. Furthermore, β$\\beta $decreases nonlinearly as the dust fraction increases, with a pronounced reduction occurring only when dust exceeds approximately 70%. Accordingly, excluding dust from the analysis increases the globally aggregated β$\\beta $from 0.24–0.26 to 0.30–0.37. These findings highlight the importance of considering aerosol composition when constraining aerosol–cloud interactions and their associated radiative forcing in satellite observations.

Ground‐based observations show that persistent liquid‐containing Arctic clouds occur frequently and have a dominant influence on Arctic surface radiative fluxes. Yet, without a hemispheric multi‐year perspective, the climate relevance of these intriguing Arctic cloud observations was previously unknown. In this study, Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) observations are used to document cloud phase over the Arctic basin (60–82°N) during a five‐year period (2006–2011). Over Arctic ocean‐covered areas, low‐level liquid‐containing clouds are prevalent in all seasons, especially in Fall. These new CALIPSO observations provide a unique and climate‐relevant constraint on Arctic cloud processes. Evaluation of one climate model using a lidar simulator suggests a lack of liquid‐containing Arctic clouds contributes to a lack of “radiatively opaque” states. The surface radiation biases found in this one model are found in multiple models, highlighting the need for improved modeling of Arctic cloud phase. Key Points New CALIPSO‐GOCCP observations show ubiquitous liquid‐containing Arctic clouds Insufficient liquid‐containing Arctic cloud leads to radiation biases in models Reproducing observed cloud phase is an important target for model improvement

The Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite provides robust and global direct measurements of the cloud vertical structure. The GCM‐Oriented CALIPSO Cloud Product is used to evaluate the simulated clouds in five climate models using a lidar simulator. The total cloud cover is underestimated in all models (51% to 62% vs. 64% in observations) except in the Arctic. Continental cloud covers (at low, mid, high altitudes) are highly variable depending on the model. In the tropics, the top of deep convective clouds varies between 14 and 18 km in the models versus 16 km in the observations, and all models underestimate the low cloud amount (16% to 25%) compared to observations (29%). In the Arctic, the modeled low cloud amounts (37% to 57%) are slightly biased compared to observations (44%), and the models do not reproduce the observed seasonal variation. Key Points To evaluate the cloud vertical structure of models using CALIPSO satellite Five GCMs underestimate the total cloud cover at all latitudes except in Arctic Discrepancies are more pronounced in tropics and poles, and over continents

The complex and diverse cloud vertical distribution (CVD) largely impacts radiative and precipitation properties of clouds. Using 10‐year active satellite observations, we classified CVD over the Tibetan Plateau into 12 categories and found that overlapping clouds have less frequency but stronger radiative effect, heating rate and larger precipitation (partly reflecting the seeding effect) compared with single‐layer non‐strong convective clouds. Under a warming climate due to uniform sea surface temperature increase of 4K (quadrupling CO2 increase), extremely high (>10 km) ice clouds will increase, particularly those below the tropopause will increase slightly (largely), accompanied by clear (weak) increases in stratospheric clouds. Simultaneously, a moderate to rapid decrease will occur in clouds below 10 km. Such CVD changes could further exacerbate tropopause warming. The probability of cloud overlap is also likely to increase in warmer climates, thus possibly further causing non‐convective cloud systems with stronger intra‐atmospheric heating, larger precipitation intensity and proportion. Plain Language Summary The diverse vertical morphologies of clouds (cloud vertical distribution, CVD) cause great challenges in accurately simulating radiative and precipitation properties, influencing regional radiation budget. As a robust signature of climate change, CVD significantly impacts cloud feedback and will change dramatically with warming. Therefore, knowledge about the CVD and its potential change are essential, especially on the Tibetan Plateau (TP, with high climate sensitivity). Using 10‐year active satellite observations, we classified clouds into 12 classes and found multi‐layer (overlapping) clouds are less frequent but with stronger radiative effect, atmospheric heating and larger precipitation intensity (proportion) than single‐layer clouds excluding convective clouds. Under a warming climate due to uniform sea surface temperature increase of 4K (quadrupling CO2 increase), clouds (especially ice‐cloud) above 10 km will increase, and those below the tropopause increase slightly (largely) accompanied by clear (weak) increases in the stratospheric clouds. Simultaneously, clouds below 10 km will experience a moderate to rapid decrease. Such CVD changes could exacerbate tropopause warming. In addition, the probability of cloud overlap in warmer climates is also likely to increase due to stronger convective available potential energy, possibly resulting in stronger atmospheric heating and larger precipitation intensity and proportion for non‐convective cloud systems. Key Points Multi‐layer clouds are less frequent on the Tibetan Plateau but with stronger radiation effect and precipitation intensity than single‐layer clouds Increase/decrease in clouds above/below tropopause might be tied to a possible convective available potential energy (CAPE)‐induced switch from general to intense convection The enhanced CAPE‐induced deep convection may increase the likelihood of cloud overlap, further enhancing intra‐atmospheric heating

The algorithm to produce the Clouds and the Earth’s Radiant Energy System (CERES) Edition 4.0 (Ed4) Energy Balanced and Filled (EBAF)-surface data product is explained. The algorithm forces computed top-of-atmosphere (TOA) irradiances to match with Ed4 EBAF-TOA irradiances by adjusting surface, cloud, and atmospheric properties. Surface irradiances are subsequently adjusted using radiative kernels. The adjustment process is composed of two parts: bias correction and Lagrange multiplier. The bias in temperature and specific humidity between 200 and 500 hPa used for the irradiance computation is corrected based on observations by Atmospheric Infrared Sounder (AIRS). Similarly, the bias in the cloud fraction is corrected based on observations by Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and CloudSat. Remaining errors in surface, cloud, and atmospheric properties are corrected in the Lagrange multiplier process. Ed4 global annual mean (January 2005 through December 2014) surface net shortwave (SW) and longwave (LW) irradiances increase by 1.3 W m−2 and decrease by 0.2 W m−2, respectively, compared to EBAF Edition 2.8 (Ed2.8) counterparts (the previous version), resulting in an increase in net SW + LW surface irradiance of 1.1 W m−2. The uncertainty in surface irradiances over ocean, land, and polar regions at various spatial scales are estimated. The uncertainties in all-sky global annual mean upward and downward shortwave irradiance are 3 and 4 W m−2, respectively, and the uncertainties in upward and downward longwave irradiance are 3 and 6 W m−2, respectively. With an assumption of all errors being independent, the uncertainty in the global annual mean surface LW + SW net irradiance is 8 W m−2.

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) version 4.10 (V4) level 2 aerosol data products, released in November 2016, include substantial improvements to the aerosol subtyping and lidar ratio selection algorithms. These improvements are described along with resulting changes in aerosol optical depth (AOD). The most fundamental change in the V4 level 2 aerosol products is a new algorithm to identify aerosol subtypes in the stratosphere. Four aerosol subtypes are introduced for stratospheric aerosols: polar stratospheric aerosol (PSA), volcanic ash, sulfate/other, and smoke. The tropospheric aerosol subtyping algorithm was also improved by adding the following enhancements: (1) all aerosol subtypes are now allowed over polar regions, whereas the version 3 (V3) algorithm allowed only clean continental and polluted continental aerosols; (2) a new “dusty marine” aerosol subtype is introduced, representing mixtures of dust and marine aerosols near the ocean surface; and (3) the “polluted continental” and “smoke” subtypes have been renamed “polluted continental/smoke” and “elevated smoke”, respectively. V4 also revises the lidar ratios for clean marine, dust, clean continental, and elevated smoke subtypes. As a consequence of the V4 updates, the mean 532 nm AOD retrieved by CALIOP has increased by 0.044 (0.036) or 52 % (40 %) for nighttime (daytime). Lidar ratio revisions are the most influential factor for AOD changes from V3 to V4, especially for cloud-free skies. Preliminary validation studies show that the AOD discrepancies between CALIOP and AERONET–MODIS (ocean) are reduced in V4 compared to V3.

We present an improved algorithm based on the POlarization LIdar PHOtometer Networking (POLIPHON) method to retrieve cloud condensation nuclei (CCN) concentration profiles from spaceborne lidar observations. Our previous paper, which was the first study to demonstrate the feasibility of using measurements from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) to retrieve CCN is revisited. Our results focus on the Evaluation of CALIPSO’s Aerosol Classification scheme over Eastern Mediterranean (ACEMED) research campaign that took place over Thessaloniki, Greece, in September 2011. We compare our results with our earlier retrievals, discussing the critical changes that have been made and the importance of using the proper conversions factors. We also demonstrate the use of conversion factors acquired based on CALIPSO aerosol typing for CCN retrievals. The analysis highlights the strong influence of smoke on CCN concentrations and shows that the assumed aging state of the smoke can significantly alter the retrieval outcome.

Compared to other regions, little is known about clouds in Antarctica. This arises in part from the challenging deployment of instrumentation in this remote and harsh environment and from the limitations of traditional satellite passive remote sensing over the polar regions. Yet clouds have a critical influence on the ice sheet's radiation budget and its surface mass balance. The extremely low temperatures, absolute humidity levels, and aerosol concentrations found in Antarctica create unique conditions for cloud formation that greatly differ from those encountered in other regions, including the Arctic. During the first decade of the 21st century, new results from field studies, the advent of cloud observations from spaceborne active sensors, and improvements in cloud parameterizations in numerical models have contributed to significant advances in our understanding of Antarctic clouds. This review covers four main topics: (1) observational methods and instruments, (2) the seasonal and interannual variability of cloud amounts, (3) the microphysical properties of clouds and aerosols, and (4) cloud representation in global and regional numerical models. Aside from a synthesis of the existing literature, novel insights are also presented. A new climatology of clouds over Antarctica and the Southern Ocean is derived from combined measurements of the CloudSat and Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites. This climatology is used to assess the forecast cloud amounts in 20th century global climate model simulations. While cloud monitoring over Antarctica from space has proved essential to the recent advances, the review concludes by emphasizing the need for additional in situ measurements. Key Points CloudSat‐CALIPSO data provide new insight into Antarctic cloud climatology This data set is used to assess clouds in IPCC global climate models Direct observations of Antarctic clouds are still limited and urgently needed

Cloud detection is critical for satellite remote sensing algorithms and downstream applications. This study evaluates the official cloud mask (CLM) product of the Advanced Geostationary Radiation Imager (AGRI) on the Fengyun-4A (FY-4A) satellite using two years of data from the Cloud Aerosol Lidar with Orthogonal Polarization (CALIOP) over China. The evaluation reveals moderate performance, with an accuracy (ACC) of 79% for daytime and 80% for nighttime. However, the FY-4A CLM struggles with high false-positive rates (FPRs of 35% during the day and 23% at night), often misclassifying clear skies as clouds. To address this issue, a random forest (RF)-based cloud detection algorithm is developed, using collocated CALIOP observations as reference labels for model development and validation. The models are divided into daytime and nighttime categories based on the solar zenith angle. Feature engineering demonstrates that adding temporal information, spatial texture information, and dynamic surface features reduces FPR values significantly. The ACC of the daytime (nighttime) model improved by up to 13.6% (10.2%). The proposed RF models achieve exceptional cloud detection, with ACC and true-positive rates (TPR) exceeding 90% with an FPR below 10% for both day and night, outperforming the FY-4A CLM. Compared to MODIS and FY-4A CLM, the RF-based models demonstrate superior accuracy in identifying clouds under challenging conditions such as dust, snow, and high pollution. This study offers a promising alternative to enhance cloud detection for the FY-4A imager.

The spatiotemporal and especially the vertical distributions of dust aerosols play crucial roles in the climatic effect of dust aerosol. In the present study, the spatial-temporal distribution of dust aerosols over East Asia was investigated using Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) retrievals (01/2007–12/2011) from the perspective of the frequency of dust occurrence (FDO), dust top layer height (TH) and profile of aerosol subtypes. The results showed that a typical dust belt was generated from the dust source regions (the Taklimakan and Gobi Deserts), in the latitude range of 25°N~45°N and reaching eastern China, Japan and Korea and, eventually, the Pacific Ocean. High dust frequencies were found over the dust source regions, with a seasonal sequence from high to low as follows: spring, summer, autumn and winter. Vertically, FDOs peaked at about 2 km over the dust source regions. In contrast, FDOs decreased with altitude over the downwind regions. On the dust belt from dust source regions to downwind regions, the dust top height (TH) was getting higher and higher. The dust TH varied in the range of 1.9–3.1 km above surface elevation (a.s.e.), with high values over the dust source regions and low values in the downwind areas, and a seasonally descending sequence of summer, spring, autumn and winter in accord with the seasonal variation of the boundary layer height. The annual AOD (Aerosol Optical Depth) was generally characterized by two high and two low AOD centers over East Asia. The percent contribution of the Dust Aerosol Optical Depth to the total AOD showed a seasonal variation from high to low as follows: spring, winter, autumn and summer. The vertical profile of the extinction coefficient revealed the predominance of pure dust particles in the dust source regions and a mixture of dust particles and pollutants in the downwind regions. The dust extinction coefficients over the Taklimakan Desert had a seasonal pattern from high to low as follows: spring, winter, summer and autumn. The results of the present study offered an understanding of the horizontal and vertical structures of dust aerosols over East Asia and can be used to evaluate the performance aerosol transport models.