Cloud Fraction Research Articles

VIIRS Edition 1 Cloud Properties for CERES, Part 1: Algorithm Adjustments and Results

Cloud properties are essential for the Clouds and the Earth’s Radiant Energy System (CERES) Project, enabling accurate interpretation of measured broadband radiances, providing a means to understand global cloud-radiation interactions, and constituting an important climate record. Producing consistent cloud retrievals across multiple platforms is critical for generating a multidecadal cloud and radiation record. Techniques used by CERES for retrievals from measurements by the MODerate-Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua platforms are adapted for the application to radiances from the Visible Infrared Imaging Radiometer Suite (VIIRS) on the Suomi National Polar-orbiting Partnership to continue the CERES record beyond the MODIS era. The algorithm adjustments account for spectral and channel differences, use revised reflectance models, and set new thresholds for detecting thin cirrus clouds at night. Cloud amounts from VIIRS are less than their MODIS counterparts by 0.016 during the day and 0.026 at night, but trend consistently over the 2012–2020 period. The VIIRS mean liquid water cloud fraction differs by ~0.01 from the MODIS amount. The average cloud heights from VIIRS differ from the MODIS heights by less than 0.2 km, except the VIIRS daytime ice cloud heights, which are 0.4 km higher. The mean VIIRS nonpolar optical depths are 17% (1%) larger (smaller) than those from MODIS for liquid (ice) clouds. The VIIRS cloud hydrometeor sizes are generally smaller than their MODIS counterparts. Discrepancies between the MODIS and VIIRS properties stem from spectral and spatial resolution differences, new tests at night, calibration inconsistencies, and new reflectance models. Many of those differences will be addressed in future editions.

A geospatial risk analysis graphical user interface for identifying hazardous chemical emission sources.

Performing back trajectory and forward trajectory using the Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) is a reliable approach for assessing particle transport after release among mid-field atmospheric models. HYSPLIT has an externally facing online interface that allows non-expert users to run the model trajectories without requiring extensive training or programming. However, the existing HYSPLIT interface is limited if simulations have a large amount of meteorological data and timesteps that are not coincident. The objective of this study is to design and develop a more robust tool to rapidly evaluate hazard transport conditions and to perform risk analysis, while still maintaining an intuitive and user-friendly interface. HYSPLIT calculates forward and backward trajectories of particles based on wind speed, wind direction, and the corresponding location, timestamp, and Pasquill stability classes of the regions of the atmosphere in terms of the wind speed, the amount of solar radiation, and the fractional cloud cover. The computed particle transport trajectories, combined with the online Proton Transfer Reaction-Mass Spectrometry (PTR-MS) data (https://figshare.com/articles/dataset/ARL_Data_from_PROS_station_at_Hanford_site/19993964), can be used to identify and quantify the sources and affected area of the hazardous chemicals' emission using the potential source distribution function (PSDF). PSDF is an improved statistical function based on the well-known potential source contribution function (PSCF) in establishing the air pollutant source and receptor relationship. Performing this analysis requires a range of meteorological and pollutant concentration measurements to be statistically meaningful. The existing HYSPLIT graphical user interface (GUI) does not easily permit computations of trajectories of a dataset of meteorological data in high temporal frequency. To improve the performance of HYSPLIT computations from a large dataset and enhance risk analysis of the accidental release of material at risk, a geospatial risk analysis tool (GRAT-GUI) is created to allow large data sets to be processed instantaneously and to provide ease of visualization. The GRAT-GUI is a native desktop-based application and can be run in any Windows 10 system without any internet access requirements, thus providing a secure way to process large meteorological datasets even on a standalone computer. GRAT-GUI has features to import, integrate, and convert meteorological data with various formats for hazardous chemical emission source identification and risk analysis as a self-explanatory user interface. The tool is available at https://figshare.com/articles/software/GRAT/19426742.

A Climatology of Midlatitude Maritime Cloud Fraction and Radiative Effect Derived from the ARM ENA Ground-Based Observations

Abstract More than four years of ground-based measurements taken at the ARM Eastern North Atlantic (ENA) site between July 2015 and September 2019 have been collected and processed in this study. Monthly and hourly means of clear-sky, all-sky, total cloud fraction (CFT), and single-layered low (CFL) and high (CFH) clouds, the impacts of all scene types on the surface radiation budget (SRB), and their cloud radiative effects (CREs) have been examined. The annual averages of CFT, CFL, and CFH are 0.785, 0.342, and 0.123, respectively. The annual averages of the SW (LW) CREs for all sky, total, low, and high clouds are −56.7 (37.7), −76.6 (48.5), −73.7 (51.4), and −26.8 (13.9) W m−2, respectively, resulting in the NET CREs of −19.0, −28.0, −22.2, and −12.9 W m−2. Comparing the cloud properties and CREs at both ARM ENA and Southern Great Plains (SGP) sites, we found that the clear-sky downwelling SW and LW fluxes at the two sites are similar to each other due to their similar atmospheric background. Compared to SGP, the lower all-sky SW and higher LW fluxes at ENA are caused by its higher CFT and all-sky precipitable water vapor (PWV). With different low cloud microphysical properties and cloud condensation nuclei at the two sites, much higher cloud optical depth at SGP plays an important role in determining its lower SW flux, while Tb and PWV are important for downwelling LW flux at the surface. A sensitivity study has shown that the all-sky SW CREs at SGP are more sensitive to CFT (−1.07 W m−2 %−1) than at ENA (−0.689 W m−2 %−1), with the same conclusion for all-sky LW CREs (0.735 W m−2 %−1 at SGP vs 0.318 W m−2 %−1 at ENA). The results over the two sites shed new light on the impacts of clouds on the midlatitude surface radiation budgets, over both ocean and land.

Influence of physicochemical properties of depressor additives on their performance in diesel fuels

The work investigates the influence of the physicochemical properties of depressor additives on their performance in diesel fuels of various chemical and fractional compositions. Heavy, summer and marine diesel fuels were used. The following physicochemical properties of fuels were determined: cloud point, freezing point, density, viscosity, fraction composition and hydrocarbon content that formed a complex with carbamide. The content and molar mass distribution of individual n-alkanes in diesel fuels were determined. The following foreign depressant-dispersing additives were used: Dodiflow with codes 4971, 5416, 5817 and 7118, Keroflux with codes 3501, 5696a and Ofi-8863. Their active agents were isolated from the commercial additives by dialysis using semi-permeable rubber membranes. The dropping point of the active agents, their intrinsic viscosity in kerosene and the refractive index at 100 °C were identified. The content of vinyl acetate components and the degree of branching of aliphatic radicals of depressor additives were determined using infrared spectroscopy of the active agents. The relationship between the physicochemical properties of depressor-dispersing additives and their performance in diesel fuels was established. Additives characterised by a relatively high melting point, an average intrinsic viscosity and low branching of aliphatic compounds in the polymer structure exhibit the best performance in fuels. The consumption of additives to achieve the maximum depression of freezing point decreases with the transition from summer to marine fuel and further to heavy diesel fuel. A complex tкп / СВА value, comprising the ratio of the dropping points tкп and the content of vinyl acetate components in the additives, was proposed as a means of predicting the efficiency of depressant additives СВА. In the range of tкп / СВА values of 3.02–4.00 the additives have universal depressant properties. A correlation was established between the refractive index nD100 of additives and the complex value tкп / СВА (R2 = 0.975).

An Assessment of the Influences of Clouds on the Solar Photovoltaic Potential over China

Clouds are important modulators of the solar radiation reaching the earth’s surface. However, the impacts of cloud properties other than cloud cover are seldom mentioned. By combining the satellite-retrieved cloud properties, the latest radiative transfer model, and an advanced PVLIB-python software for solar photovoltaic (PV) estimation, the impacts of different types of clouds on the maximum available solar PV potential (measured with the plane-of-array-irradiance, POAI) are quantified. The impacts of ice and liquid water clouds are found to be the highest on Tibetan Plateau over western China in spring, and central and southern China in winter, respectively. The reduction of POAI by liquid water clouds is almost twice of that by ice clouds except for spring. It is found that the POAI can be reduced by 27–34% by all clouds (ice + liquid water clouds) in different seasons. The sensitivities of the solar PV potential to the changes in cloud properties including the cloud fraction, cloud top pressure, cloud effective radius, and cloud water path are also analyzed. Three kinds of settings of PV panel tilting, namely fixed tilt, one-axis tracking, and two-axis tracking, are considered. It is found that the cloud properties are essential to estimate the solar PV potentials, especially for the cloud fraction. The attenuation of solar radiation by clouds are growingly larger as the solar plane tilting settings get more complicated. The outlook of solar PV potential is quite variable as the changes in cloud properties are highly uncertain in the future climate scenarios.

Stratospheric Modulation of the MJO through Cirrus Cloud Feedbacks

Abstract Recent observations have indicated significant modulation of the Madden–Julian oscillation (MJO) by the phase of the stratospheric quasi-biennial oscillation (QBO) during boreal winter. Composites of the MJO show that upper-tropospheric ice cloud fraction and water vapor anomalies are generally collocated, and that an eastward tilt with height in cloud fraction exists. Through radiative transfer calculations, it is shown that ice clouds have a stronger tropospheric radiative forcing than do water vapor anomalies, highlighting the importance of incorporating upper-tropospheric–lower-stratospheric processes into simple models of the MJO. The coupled troposphere–stratosphere linear model previously developed by the authors is extended by including a mean wind in the stratosphere and a prognostic equation for cirrus clouds, which are forced dynamically and allowed to modulate tropospheric radiative cooling, similar to the effect of tropospheric water vapor in previous formulations. Under these modifications, the model still produces a slow, eastward-propagating mode that resembles the MJO. The sign of zonal mean wind in the stratosphere is shown to control both the upward wave propagation and tropospheric vertical structure of the mode. Under varying stratospheric wind and interactive cirrus cloud radiation, the MJO-like mode has weaker growth rates under stratospheric westerlies than easterlies, consistent with the observed MJO–QBO relationship. These results are directly attributable to an enhanced barotropic mode under QBO easterlies. It is also shown that differential zonal advection of cirrus clouds leads to weaker growth rates under stratospheric westerlies than easterlies. Implications and limitations of the linear theory are discussed. Significance Statement Recent observations have shown that the strength of the Madden–Julian oscillation (MJO), a global-scale envelope of wind and rain that slowly moves eastward in the tropics and dominates global-weather variations on time scales of around a month, is strongly influenced by the direction of the winds in the lower stratosphere, the layer of the atmosphere that lies above where weather occurs. So far, modeling studies have been unable to reproduce this connection in global climate models. The purpose of this study is to investigate the mechanisms through which the stratosphere can modulate the MJO, by using simple theoretical models. In particular, we point to the role that ice clouds high in the atmosphere play in influencing the MJO.

Low-Level Cloud Budgets across Sea Ice Edges

Abstract Interpreting behaviors of low-level clouds (LLCs) in a climate model is often not straightforward. This is particularly so over polar oceans where frozen and unfrozen surfaces coexist, with horizontal winds streaming across them, shaping LLCs. To add clarity to this interpretation issue, we conduct budget analyses of LLCs using a global atmosphere model with a fully prognostic cloud scheme. After substantiating the model’s skill in reproducing observed LLCs, we use the modeled budgets of cloud fraction and water content to elucidate physics governing changes of LLCs across sea ice edges. Contrasting LLC regimes between open water and sea ice are found. LLCs over sea ice are primarily maintained by large-scale condensation: intermittent intrusions of maritime humid air and surface radiative cooling jointly sustain high relative humidity near the surface, forming extensive but tenuous stratus. This contrasts with the LLCs over open water where the convection and boundary layer condensation sustain the LLCs on top of deeper boundary layers. Such contrasting LLC regimes are influenced by the direction of horizontal advection. During on-ice flow, large-scale condensation dominates the regions, both open water and sea ice regions, forming clouds throughout the lowest several kilometers of the troposphere. During off-ice flow, as cold air masses travel over the open water, the cloud layer lifts and becomes denser, driven by increased surface fluxes that generate LLCs through boundary layer condensation and convective detrainment. These results hold in all seasons except summer when the atmosphere–surface decoupling substantially reduces the footprints of surface type changes.

Absorbing Aerosol Optical Depth From OMI/TROPOMI Based on the GBRT Algorithm and AERONET Data in Asia

Quantifying the concentration of absorbing aerosol is essential for pollution tracking and calculation of atmospheric radiative forcing. To quickly obtain absorbing aerosol optical depth (AAOD) with high-resolution and high-accuracy, the gradient boosted regression trees (GBRT) method based on the joint data from Ozone Monitoring Instrument (OMI), Moderate Resolution Imaging Spectro-Radiometer (MODIS), and AErosol RObotic NETwork (AERONET) is used for TROPOspheric Monitoring Instrument (TROPOMI). Compared with the ground-based data, the correlation coefficient of the results is greater than 0.6 and the difference is generally within ±0.04. Compared with OMI data, the underestimation has been greatly improved. By further restricting the impact factors, three valid conclusions can be drawn: 1) the model with more spatial difference information achieves better results than the model with more temporal difference information; 2) the training dataset with a high cloud fraction (0.1–0.4) can partly improve the performance of GBRT results; and 3) when aerosol optical depth (AOD) is less than 0.3, the perform of retrieved AAODs is still good by comparing with ground-based measurements. The novel finding is expected to contribute to regional and even urban anthropogenic pollution research.

Impacts of the antartic ozone hole influence events over southern Brazil in October 2015.

The impact of the Antarctic Ozone Hole Influence over Southern Brazil in October 2015 was analyzed using daily mean data of the Total Column Ozone (TCO), Ultraviolet Index (UVI) and Radiative Cloud Fraction (RCF) from the Ozone Monitoring Instrument satellite instrument. Vertical profiles and fields of ozone content and Potential Vorticity available from the European Centre for Medium-Range Weather Forecast reanalysis, air masses backward trajectories from the HYbrid Single-Particle Lagrangian Integrated Trajectory model and channel 3 water vapor images from the Geostationary Operational Environmental Satellite GOES-13 were also analyzed. The five identified events showed an -7.4±2.3% average TCO reduction, leading to an +16.6±54.6% UVI increase even with a predominance of partly cloudy days. Other impacts were observed in the ozone profiles, where the most significant anomalies occurred from 650 K reaching 1.2 ppmv at the 850 K level. In the ozone fields at 700 K, the presence of a polar origin tongue was observed causing negatives anomalies between -0.2 and 0.4 ppmv in a transient system format forced with eastward-traveling Rossby waves passing through the Southern of Brazil and Uruguay.

Comparing ground-based and satellite retrievals of cloud fraction over the Amazon

Comparing ground-based and satellite retrievals of cloud fraction over the Amazon

Impacts of shifting phenology on boundary layer dynamics in North America in the CESM

Plant phenology modulates water and energy exchanges between the biosphere and the atmosphere and therefore influences planetary boundary layer (PBL) dynamics. Here we conduct a modeling experiment using the Community Earth System Model version 2, where plant phenology is prescribed based on satellite climatology in the control experiment. We then shift the timing of vegetation green-up and senescence in North America by one month earlier and later and investigate how shifting phenology could influence land-atmosphere interactions. Altering plant phenology modifies boundary layer fluxes through both direct influences on evapotranspiration and absorbed solar radiation and indirect effects through changes in low cloud fraction. The prescribed shift in phenology has significant but different influences on PBL dynamics and land-atmosphere coupling in the spring and fall in the Great Plains and Eastern United States. In the spring, earlier plant phenology significantly decreases PBL height in the Great Plains by more than 100 m. In the autumn, the Great Plains experience a significant increase in PBL height of over 100 m in the early fall while Eastern US exhibits a significant increase in the late fall when prescribed senescence is shifted earlier. As shifts in plant phenology alone can cause significant changes in PBL conditions at the seasonal timescale in the Great Plains and Eastern US, our experiments can help infer the potential location and magnitude of phenology-induced changes and provide useful information for observation-based analysis and model evaluation.

Cloud parameter retrieval for Environmental trace gases Monitoring Instrument (EMI) using the O2-O2 absorption band

This study proposes an improved cloud parameter retrieval algorithm for the existing cloud parameter algorithm of the Environmental trace gases Monitoring Instrument (EMI) using the collision complex of the oxygen (O2-O2) absorption feature. The main improvements are the evaluation of the impact of temperature on the O2-O2 slant column densities (SCDs), and the well-corrected EMI measured reflectance. The cloud parameters will help improve the accuracy of EMI trace gas retrievals. The O2-O2 SCDs were fitted based on EMI-observed radiances and solar irradiance, and the impact of temperature on the O2-O2 SCD was evaluated. A simulated reflectance look-up table (LUT), as well as the O2-O2 SCD LUT, were established through the SCIATRAN radiative transfer model. Reflectance and O2-O2 SCD LUTs are functions of effective cloud fraction (ECF) and cloud pressure (CP), which can be inverted to ECF and CP LUTs. On this basis, the EMI ECF and CP were obtained using the EMI observation geometric information, EMI measured reflectance, and O2-O2 SCD to interpolate the ECF and CP LUTs. To evaluate the results, we performed an inter-comparison between the EMI cloud parameters, TROPOspheric Monitoring Instrument (TROPOMI) cloud products, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) CP, and ground-based lidar cloud altitude. Of them, the one-day global ECF and CP of EMI and TROPOMI exhibited good agreement; the correlation coefficients were 0.925 and 0.866, respectively. Additionally, EMI was closer to the CALIOP results when the cloud pressure was >600 hPa. The comparison with the ground-based lidar cloud altitude also yielded good agreement during the continuous observation period from September 21 to November 10, 2019. The results prove that the improved EMI cloud retrieval algorithm could provide effective cloud products for EMI trace gas inversion.

Calibration and Validation of Global Horizontal Irradiance Clear Sky Models against McClear Clear Sky Model in Morocco

This study calibrated and compared the capabilities of hourly global horizontal irradiance (GHI) clear sky models for six Moroccan locations, using the McClear clear sky model as a reference. Complex clear sky models, namely Bird, Simplified Solis, Ineichen and Perez, and simple clear sky models, namely Adnot–Bourges–Campana–Gicquel (ABCG), Berger–Duffie, and Haurwitz were tested. The SOLCAST satellite-based dataset estimates were validated against the McClear clear sky model. pvlib python was used to configure the models, and ERA5 hourly fractional cloud cover was used to identify clear-sky days. The study period was from 2014 to 2021, and the study sites were in different climatic regions in Morocco. Bar graphs, tables, and quantitative statistical metrics, namely relative mean bias error (rMBE), relative root mean square error (rRMSE), relative mean absolute error (rMAE), and the coefficient of determination (R2), were used to quantify the skill of the clear sky model at different sites. The overall rMBE was negative in 5/6 sites, indicating consistent overestimation of GHI, and positive in Tantan (14.4%), indicating frequent underestimation of GHI. The overall rRMSE varied from 6 to 22%, suggesting strong agreement between clear sky models and the McClear clear sky model. The overall correlation was greater than 0.96, indicating a very strong relationship. Overall, the Bird clear sky model proved to be the most feasible. Complex clear sky models outperformed simple clear sky models. The SOLCAST satellite-based dataset and ERA5 cloud fraction information could well be used with quantifiable certainty as an accurate clear sky model in the study region and in other areas where complex clear sky models’ inputs are not available.

Revisiting cloud overlap with a merged dataset of liquid and ice cloud extinction from CloudSat and CALIPSO

We update the parameterization capturing the variation of parameters that describe how cloud occurrence (layer cloud fraction) and layer cloud optical depth (COD) distributions overlap vertically. Our updated analysis is motivated by the availability of a new dataset constructed by combining two products describing the two-dimensional extinction properties of liquid and ice phase clouds (and their mixtures) according to active cloud observations by the CloudSat and CALIPSO satellites. As before, cloud occurrence overlap is modeled with the decorrelation length of an inverse exponential function describing the decay with separation distance of the relative likelihood that two cloudy layers are overlapped maximally versus randomly. Similarly, cloud optical depth distribution vertical overlap is described again with a decorrelation length that describes the assumed inverse exponential decay with separation distance of the rank correlation between cloud optical depth distribution members in two cloudy layers. We derive the climatological zonal variability of these two decorrelation lengths using 4 years of observations for scenes of ∼100 km scale length, a typical grid size of numerical models used for climate simulations. As previously, we find a strong latitudinal dependence reflecting systematic differences in dominant cloud types with latitude, but substantially different magnitudes of decorrelation length compared to the previous work. The previously used parameterization form is therefore updated with new parameters to describe the latitudinal dependence of decorrelation lengths and its seasonal shift. Similar zonal patterns of decorrelation length are found when the analysis is broken down by different cloud classes. When the revised parameterization is implemented in a cloud subcolumn generator, simulated column cloud properties compare to observations quite well, and so do their associated cloud radiative effects, but improvements over the earlier version of the parameterization are marginal.

Variations in aerosols and aerosols–cloud interactions in Bangkok using MODIS satellite data during high PM2.5 concentrations

The relationships between particulate matter with aerodynamic diameters less than 2.5 µm (PM2.5), aerosol optical depth (AOD), and cloud parameters were investigated during high PM2.5 concentrations from 1 January 2016 to 31 December 2021 in Bangkok using satelliteremote sensingdatafrom Moderate Resolution Imaging Spectroradiometer (MODIS). Cloud parameters included: Cloud effective radius (CER), Cloud fraction (CF), Cloud optical depth (COD), Cloud liquid water (CLW), Cloud top pressure (CTP), and Cloud top temperature (CTT). The analysis showed a strong negative correlation between PM2.5 and CF. There was a negative correlation between CF and AOD. In addition, PM2.5 showed a negative relationship with CER. In contrast, PM2.5 showed a positive correlation with CTP and CTT. A negative correlation was detected between COD and PM2.5. During high PM2.5 concentrations, cloud parameters are significantly influenced by PM2.5 concentrations in the atmosphere. The three-month of CER, CF, CLW, COD, CTP, and CTT ranges from 16.34 μm to 37.05 μm, 0.22 to 0.86, 15.67 g/m2 to 169.80 g/m2, 1.14 to 19.06, 261.67 hPa to 991.67 hPa, and −66.26C to –22.17C, respectively. Consequently, Altostratus clouds most appear during high PM2.5 concentrations in Bangkok. The findings may help better understand Bangkok's cloud properties and atmospheric aerosols, providing more information for rainmaking during high PM2.5 concentrations.

Interaction between cloud–radiation, atmospheric dynamics and thermodynamics based on observational data from GoAmazon 2014/15 and a cloud-resolving model

Abstract. Observational meteorological data from the field experiment GoAmazon 2014/15 and data from numerical simulations with the cloud-resolving model (CRM) called the System for Atmospheric Modeling (SAM) are used to study the interaction between the cloudiness–radiation as well as the atmospheric dynamics and thermodynamics variables for a site located in the central Amazon region (−3.2∘ S, −60.6∘ W) during the wet and dry periods. The main aims are to (a) analyze the temporal series of the integrated cloud fraction, precipitation rate and downward shortwave flux as well as (b) to determine the relationship between the integrated cloud fraction, radiative fluxes and large-scale variable anomalies as a function of the previous day's average. The temporal series of the integrated cloud fraction, precipitation rate and downward shortwave flux from SAM simulations showed physical consistency with the observations from GoAmazon 2014/15. Shallow and deep convection clouds show to have a meaningful impact on radiation fluxes in the Amazon region during wet and dry periods. Anomalies of large-scale variables (relative to the previous day's average) are physically associated with cloud formation, evolution and dissipation. SAM consistently simulated these results, where the cloud fraction vertical profile shows a pattern very close to the observed data (cloud type). Additionally, the integrated cloud fraction and large-scale variable anomalies, as a function of the previous day's average, have a good correlation. These results suggest that the memory of the large-scale dynamics from the previous day can be used to estimate the cloud fraction as well as the water content, which is a variable of the cloud itself. In general, the SAM satisfactorily simulated the interaction between cloud–radiation as well as dynamic and thermodynamic variables of the atmosphere during the periods of this study, being able to obtain atmospheric variables that are impossible to obtain in an observational way.

Analysis of Daytime Cloud Fraction Spatiotemporal Variation over the Arctic from 2000 to 2019 from Multiple Satellite Products

Abstract Insufficient understanding of complex Arctic cloud properties introduced large errors in estimating radiant energy balance parameters at the regional and global scales. Comprehensive and reliable cloud information is necessary for improving the accuracy of flux inversion. This study evaluated daytime cloud fraction (CF) uncertainties from 16 available satellite products and estimated the spatiotemporal distributions of Arctic daytime CF during 2000–19. Our results show that the differences among multiple products had significant temporal and spatial heterogeneities. Temporally, the maximum and minimum interproduct discrepancies occurred in April and the summer months, respectively. Spatially, the largest uncertainties were seen over Greenland. Substantial inconsistency also occurred on the central and Pacific sides of the Arctic Ocean. The active satellite product tended to capture more clouds in these two regions. We found that the inconsistencies caused by sensor differences were smaller than those caused by algorithm differences; that is, for MODIS based CF products, the inconsistencies caused by different sensors and different algorithms are ±2% and ±5%, while for AVHRR-based products, these inconsistencies are ±6% and ±15%, respectively. The annual average daytime CF in sunlit months was 70.9% ± 2.93% and increased over the Arctic during study periods. These upward trends might cool the Arctic by approximately 0.05–0.5 W m−2 decade−1. In terms of the spatiotemporal distributions, the CF over the ocean is higher than that over the land, and the former increased significantly while the latter decreased; the CF trends of most products are positive in June and July but are opposite in other months. From this study, the findings based on multiple products would be more robust than that based on a single or few datasets. Significance Statement This study aimed to comprehensively understand and obtain more robust general characteristics of the temporal and spatial distributions of Arctic daytime cloud fraction by comparing and analyzing the consistencies and discrepancies of multisource satellite products. It is important because the cloud fraction is a nonnegligible modulator of Earth’s energy budget and climate change. Although the Arctic is the most climate-sensitive region, existing studies lack a comprehensive assessment of the cloud fraction over the entire Arctic. We analyzed 16 different cloud products and found that although the inconsistencies were inevitable, most products showed similar spatiotemporal distribution and trend distribution of daytime CF. This study provided a new idea for Arctic CF research under the existing conditions.

An Updated CLUBB PDF Closure Scheme to Improve Low Cloud Simulation in CAM6

AbstractCloud Layers Unified By Binormals (CLUBB) adopts the joint probability density function (PDF) to close higher‐order turbulence and diagnose the cloud fraction. CLUBB assumes the equal PDF width of vertical velocity () as the default closure scheme, called Analytic Double Gaussian 1 (ADG1). In this study, a new unequal width PDF closure scheme is adopted in CLUBB, in which the PDF width of is assumed to be associated with skewness and kurtosis of vertical velocity. Offline calculation shows that the updated closure scheme improves the tail in the joint PDF and produces the saturation area from the joint PDF of the total water and liquid water potential temperature closer to that derived from large‐eddy simulations than ADG1. The new PDF scheme implemented in Community Atmosphere Model Version 6 is shown to increase low cloud fraction by 20%–30% in most stratocumulus‐to‐cumulus transition regions. The updated closure scheme is found to improve the low cloud simulation by simulating more symmetric turbulence in stratocumulus and stronger turbulent transport in shallow cumulus. Furthermore, the updated closure scheme enhances the cloud fraction near the cloud base by interacting with the microphysical scheme. Our work indicates the importance of continuous improvement in the PDF closures for higher‐order turbulence schemes.

Markovian Statistical Model of Cloud Optical Thickness. Part I: Theory and Examples

Abstract We present a generalization of the binary-value Markovian model previously used for statistical characterization of cloud masks to a continuous-value model describing 1D fields of cloud optical thickness (COT). This model has simple functional expressions and is specified by four parameters: the cloud fraction, the autocorrelation (scale) length, and the two parameters of the normalized probability density function of (nonzero) COT values (this PDF is assumed to have gamma-distribution form). Cloud masks derived from this model by separation between the values above and below some threshold in COT appear to have the same statistical properties as in binary-value model described in our previous publications. We demonstrate the ability of our model to generate examples of various cloud-field types by using it to statistically imitate actual cloud observations made by the Research Scanning Polarimeter (RSP) during two field experiments.

Smoke‐Driven Changes in Photosynthetically Active Radiation During the U.S. Agricultural Growing Season

AbstractWildfire smoke is frequently present over the U.S. during the agricultural growing season and will likely increase with climate change. Studies of smoke impacts have largely focused on air quality and human health; however, understanding smoke's impact on photosynthetically active radiation (PAR) is essential for predicting how smoke affects plant growth. We compare surface shortwave irradiance and diffuse fraction (DF) on smoke‐impacted and smoke‐free days from 2006 to 2020 using data from multifilter rotating shadowband radiometers at 10 U.S. Department of Agriculture UV‐B Monitoring and Research Program stations and smoke plume locations from operational satellite products. On average, 20% of growing season days are smoke‐impacted, but smoke prevalence increases over time (r = 0.60, p < 0.05). Smoke presence peaks in the mid to late growing season (i.e., July, August), particularly over the northern Rocky Mountains, Great Plains, and Midwest. We find an increase in the distribution of PAR DF on smoke‐impacted days, with larger increases at lower cloud fractions. On clear‐sky days, daily average PAR DF increases by 10 percentage points when smoke is present. Spectral analysis of clear‐sky days shows smoke increases DF (average: +45%) and decreases total irradiance (average: −6%) across all six wavelengths measured from 368 to 870 nm. Optical depth measurements from ground and satellite observations both indicate that spectral DF increases and total spectral irradiance decreases with increasing smoke plume optical depth. Our analysis provides a foundation for understanding smoke's impact on PAR, which carries implications for agricultural crop productivity under a changing climate.