Low Cloud Fraction Research Articles

Recent improvements and maximum covariance analysis of aerosol and cloud properties in the EC-Earth3-AerChem model

Abstract. Given the importance of aerosols and clouds and their interactions in the climate system, it is imperative that the global Earth system models accurately represent processes associated with them. This is an important prerequisite if we are to narrow the uncertainties in future climate projections. In practice, this means that continuous model evaluations and improvements grounded in observations are necessary. Numerous studies in the past few decades have shown both the usability and the limitations of utilizing satellite-based observations in understanding and evaluating aerosol–cloud interactions, particularly under varying meteorological and satellite sensor sensitivity paradigms. Furthermore, the vast range of spatio-temporal scales at which aerosol and cloud processes occur adds another dimension to the challenges faced when evaluating climate models. In this context, the aim of this study is two-fold. (1) We evaluate the most recent, significant changes in the representation of aerosol and cloud processes implemented in the EC-Earth3-AerChem model in the framework of the EU project FORCeS compared with its previous CMIP6 version (Coupled Model Intercomparison Project Phase 6; https://pcmdi.llnl.gov/CMIP6/, last access: 13 February 2019). We focus particularly on evaluating cloud physical properties and radiative effects, wherever possible, using a satellite simulator. We report on the overall improvements in the EC-Earth3-AerChem model. In particular, the strong warm bias chronically seen over the Southern Ocean is reduced significantly. (2) A statistical, maximum covariance analysis is carried out between aerosol optical depth (AOD) and cloud droplet (CD) effective radius based on the recent EC-Earth3-AerChem/FORCeS simulation to understand to what extent the Twomey effect can manifest itself in the larger spatio-temporal scales. We focus on the three oceanic low-level cloud regimes that are important due to their strong net cooling effect and where pollution outflow from the nearby continent is simultaneously pervasive. We report that the statistical covariability between AOD and CD effective radius is indeed dominantly visible even at the climate scale when the aerosol amount and composition are favourably preconditioned to allow for aerosol–cloud interactions. Despite this strong covariability, our analysis shows a strong cooling/warming in shortwave cloud radiative effects at the top of the atmosphere in our study regions associated with an increase/decrease in CD effective radius. This cooling/warming can be attributed to the increase/decrease in low cloud fraction, in line with previous observational studies.

Turbulent heat fluxes in the North Water Polynya and ice estimated based on ASRv2 data and their impact on cloud

The presence or absence of sea ice introduces a substantial perturbation to surface‒atmosphere energy exchanges. Comprehending the effect of varying sea ice cover on surface‒atmosphere interactions is an important consideration for understanding the Arctic climate system. The recurring North Water Polynya (NOW) serves as a natural laboratory for isolating cloud responses to a rapid, near-step perturbation in sea ice. In this study, we employed high-resolution Arctic System Reanalysis version 2 (ASRv2) data to estimate turbulent heat fluxes over the NOW and nearby sea ice (NSI) area between 2005/2006 and 2015/2016. The results indicate that the average turbulent heat fluxes in the polynya are about 87% and 86% higher than in the NSI area over the 10 years during the entire duration of the polynya and during polar night, respectively. Enhanced turbulent heat fluxes from the polynya tend to produce more low-level clouds. The relationship between the polynya and low cloud in winter was examined based on Cloud‒Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO). The low-cloud fraction (0–2 km) was about 7–34% larger over the polynya than the NSI area, and the ice water content below 200 m was about 250%–413% higher over the former than the latter. The correlation between cloud fraction and turbulent heat fluxes in the polynya peaks around the altitude of 200–300 m. These results suggest that the NOW affects the Arctic boundary layer cloudiness and structure in wintertime. Furthermore, higher horizontal resolution reanalysis data can advance our understanding of the cloud-polynya response.

Improving Low‐Cloud Fraction Prediction Through Machine Learning

AbstractIn this study, we evaluated the performance of machine learning (ML) models (XGBoost) in predicting low‐cloud fraction (LCF), compared to two generations of the community atmospheric model (CAM5 and CAM6) and ERA5 reanalysis data, each having a different cloud scheme. ML models show a substantial enhancement in predicting LCF regarding root mean squared errors and correlation coefficients. The good performance is consistent across the full spectrums of atmospheric stability and large‐scale vertical velocity. Employing an explainable ML approach, we revealed the importance of including the amount of available moisture in ML models for representing spatiotemporal variations in LCF in the midlatitudes. Also, ML models demonstrated marked improvement in capturing the LCF variations during the stratocumulus‐to‐cumulus transition (SCT). This study suggests ML models' great potential to address the longstanding issues of “too few” low clouds and “too rapid” SCT in global climate models.

Drivers of the Extreme Early Spring Glacier Melt of 2022 on the Central Tibetan Plateau

AbstractExtreme glacier melt has important implications for climate change studies and glacier‐related hazards. Few attempts have been made to study the characteristics and mechanisms of extreme melt on the Tibetan Plateau (TP) and surroundings, one of the largest concentrations of glaciers beyond the polar regions. To address this gap, we investigated the magnitude and possible drivers of anomalous early spring glacier melt in 2022 on the central TP using multi‐source observations (October 2020–July 2022) of Kuoqionggangri and Sangqu glaciers and an energy and mass balance model. Our results show that anomalous melt of both glaciers occurred in early spring (18 March–10 April 2022), when glaciers are traditionally expected to be frozen. There were 89 cumulative hours with air temperatures above 0°C, with a positive cumulative air temperature of 121.80°C hour at 5,700 m on Kuoqionggangri Glacier. The glacier‐wide cumulative melts on Kuoqionggangri and Sangqu glaciers from 18 March to 10 April 2022 were 22 ± 14.2 and 48 ± 37.5 mm w.e., respectively. Such anomalous glacier melt was driven by high incoming shortwave radiation and sensible heat flux, which were influenced by low cloud fraction and precipitation, and high air temperature during early spring. The weakening and northward‐shift of the westerlies, coupled with descending air motions over the central TP, reduced cloud fraction and hindered the transport of cold, moist air to the central TP. These changes occurred both in the central TP and the Himalaya, indicating the influence of macroscale atmospheric circulation patterns on this extreme glacier melt.

Polar Low Circulation Enhances Greenland's West Coast Cloud Surface Warming

AbstractMass loss of the Greenland Ice Sheet (GrIS) plays a major role in the global sea level rise. The west coast of the GrIS has contributed 1,000 Gt of the 4,488 Gt GrIS mass loss between 2002 and 2021, making it a hotspot for GrIS mass loss. Surface melting is driven by changes in the radiative budget at the surface, which are modulated by clouds. Previous works have shown the impact of North Atlantic transport for influencing cloudiness over the GrIS. Here we used space‐based lidar cloud profile observations to show that a polar low circulation promotes the presence of low clouds over the GrIS west coast that warm radiatively the GrIS surface during the melt season. Polar low circulation transports moisture and low clouds from the sea to the west of Greenland up over the GrIS west coast through the melt season. The concomitance of the increasing presence of low cloud in fall over the Baffin Sea due to seasonal sea‐ice retreat and a maximum occurrence of Polar low circulation in September results in a maximum of low cloud fraction (∼14% at 2.5 km above sea level) over the GrIS west coast in September. These low clouds warm radiatively the GrIS west coast surface up to 80 W/m2 locally. This warming contributes to an average increase of 10 W/m2 of cloud surface warming in September compared to July on the GrIS west coast. Overall, this study suggests that regional atmospheric processes independent from North Atlantic transport may also influence the GrIS melt.

Microphysical Parameterization Scheme with Satellite Data Verification and Observation Data for Analysis of Heavy Rain in Yogyakarta City

The numerical weather prediction model Weather Research and Forecasting - Advanced Research WRF (WRF-ARW) was used to simulate the atmospheric conditions during heavy rainfall in the Yogyakarta area on February 3, 2022. Several parameterization schemes were compared with observational data to obtain the best choice of microphysical parameterization scheme in describing the atmospheric conditions at the time of the event. The microphysical parameterization schemes used are: Kessler, Purdue Lin, and WRF Single-Moment. Class (WSM3). The verification results show that the Kessler microphysical parameterization scheme has the best performance in representing heavy rain events with a fairly high low cloud fraction data accuracy value ranging from 0.3 - 0.4 and the highest rainfall modeling value is 8.3 mm. It can be concluded that the Kessler scheme is sufficient to model the occurrence of heavy rain in the city of Yogyakarta.

Using EUREC4A/ATOMIC field campaign data to improve trade wind regimes in the Community Atmosphere Model

Abstract. Improving the prediction of clouds in shallow-cumulus regimes via turbulence parameterization in the planetary boundary layer (PBL) will likely increase the global skill of global climate models (GCMs) because this cloud regime is common over tropical oceans where low-cloud fraction has a large impact on Earth's radiative budget. This study attempts to improve the prediction of PBL structure in tropical trade wind regimes in the Community Atmosphere Model (CAM) by updating its formulation of momentum flux in CLUBB (Cloud Layers Unified by Binormals), which currently does not by default allow for upgradient momentum fluxes. Hindcast CAM output from custom CLUBB configurations which permit countergradient momentum fluxes are compared to in situ observations from weather balloons collected during the ElUcidating the RolE of Cloud–Circulation Coupling in ClimAte and Atlantic Tradewind Ocean–Atmosphere Mesoscale Interaction Campaign (EUREC4A/ATOMIC) field campaign in the tropical Atlantic in early 2020. Comparing a version with CAM–CLUBB with a prognostic treatment of momentum fluxes results in vertical profiles that better match large-eddy simulation results. Countergradient fluxes are frequently simulated between 950 and 850 hPa over the EUREC4A/ATOMIC period in CAM–CLUBB. Further modification to the planetary boundary layer (PBL) parameterization by implementing a more generalized calculation of the turbulent length scale reduces model bias and root mean squared error (RMSE) relative to sounding data when coupled with the prognostic momentum configuration. Benefits are also seen in the diurnal cycle, although more systematic model errors persist. A cursory budget analysis suggests the buoyant production of momentum fluxes, both above and below the jet maximum, significantly contributes to the frequency and depth of countergradient vertical momentum fluxes in the study region. This paper provides evidence that higher-order turbulence parameterizations may offer pathways for improving the simulation of trade wind regimes in global models, particularly when evaluated in a process study framework.

Evaluation of Stratocumulus Evolution Under Contrasting Temperature Advections in CESM2 Through a Lagrangian Framework

AbstractThis study leveraged a Lagrangian framework to examine the evolution of stratocumulus clouds under cold and warm advections (CADV and WADV) in the Community Earth System Model 2 (CESM2) against observations. We found that CESM2 simulates a too rapid decline in low‐cloud fraction (LCF) and cloud liquid water path (CLWP) under CADV conditions, while it better aligns closely with observed LCF under WADV conditions but overestimates the increase in CLWP. Employing an explainable machine learning approach, we found that too rapid decreases in LCF and CLWP under CADV conditions are related to overestimated drying effects induced by sea surface temperature, whereas the substantial increase in CLWP under WADV conditions is associated with the overestimated moistening effects due to free‐tropospheric moisture and surface winds. Our findings suggest that overestimated drying effects of sea surface temperature on cloud properties might be one of crucial causes for the high equilibrium climate sensitivity in CESM2.

Impact of wildfire smoke on ozone concentrations using a Generalized Additive model in Salt Lake City, Utah, USA, 2006–2022

ABSTRACT We investigated the impact of wildfires on maximum daily 8-hr average ozone concentrations (MDA8 O3) at four sites in Salt Lake City (SLC), Utah for May to September for 2006–2022. Smoke days, which were identified by a combination of overhead satellite smoke detection and surface PM2.5 data and accounted for approximately 9% of the total number of days, exhibited O3 levels 6.8 to 8.9 ppb higher than no-smoke days and were predominantly characterized by high daily maximum temperatures and low relative humidity. A Generalized Additive Model (GAM) was developed to quantify the impact of wildfire contributions to O3. The GAM, which provides smooth functions that make the interpretation of relationships more intuitive, employed 17 predictors and demonstrated reliable performance in various evaluation metrics. The mean of the residuals for all sites was approximately zero for the training and cross-validation data and 5.1 ppb for smoke days. We developed three approaches to estimate the contribution of smoke to O3 from the model residuals. These generate a minimum and maximum contribution for each smoke day. The average of the minimum and maximum wildfire contributions to O3 for the SLC sites was 5.1 and 8.5 ppb, respectively. Between 2006 and 2022, an increasing trend in the wildfire contributions to O3 was observed in SLC. Moreover, trends of the fourth-highest MDA8 O3 before and after removing the wildfire contributions to O3 at the SLC Hawthorne site in 2006–2022 were quite different. Whereas the unadjusted data do not meet the current O3 standard, after removing the contributions from wildfires the SLC region is close to achieving levels that are consistent with meeting the O3 standard. We also found that the wildfire contribution during smoke days was particularly high under conditions of high temperature, high PM2.5 concentration, and low cloud fraction. Implications: In this study, we quantified the impact of wildfires on maximum daily 8-hr average ozone concentrations (MDA8 O3) in Salt Lake City, Utah, using a Generalized Additive Model (GAM). The GAM results demonstrate the importance of wildfires as contributors to O3 air pollution. Our results suggest that states could use the GAM approach to assist in quantifying the wildfire contribution to MDA8 O3 under the U.S. EPA exceptional events rule. These findings also highlight the need for strategies to manage wildfires and their subsequent impacts on air quality in an era of climate warming.

Origins of Uncertainty in the Response of the Summer North Pacific Subtropical High to CO2 Forcing

AbstractThe variability of the summer North Pacific Subtropical High (NPSH) has substantial socioeconomic impacts. However, state‐of‐the‐art climate models significantly disagree on the response of the NPSH to anthropogenic warming. Inter‐model spread in NPSH projections originates from models' inconsistency in simulating tropical precipitation changes. This inconsistency in precipitation changes is partly due to inter‐model spread in tropical sea surface temperature (SST) changes, but it can also occur independently of uncertainty in SST changes. Here, we show that both types of precipitation uncertainty influence the NPSH via the Matsuno‐Gill wave response, but their relative impact varies by region. Through the modulation of low cloud fraction, inter‐model spread of the NPSH can have a further impact on extra‐tropical land surface temperature. The teleconnection between tropical precipitation and the NPSH is examined through a series of numerical experiments.

Summary of atmospheric characteristics of days with inland penetrating sea breezes from 2015 to 2021

AbstractSea breezes penetrate inland more than 100 km. Using 7 years of meteorological observations, we have identified 470 cases of deep inland (>100 km) penetrating sea breezes at the Savannah River Site between March and October (27% of days) of 2015–2021. We compared measurements of temperature, dewpoint temperature, incoming solar radiation, cloud fraction, and lightning on days of sea breeze initiation, the day after the sea breeze passage, and all other nonsea breeze (NSB) days for these 8 months over the 7 years. Days of sea breeze initiation were found to have lower cloud fraction, higher temperature, and greater incoming solar radiation compared with NSB days. Variations occurred by time of year as days after the sea breeze passage were found to have higher dewpoint temperature than NSB days in the spring. Lightning density measurements indicated that residual sea breeze conditions could drive earlier initiation of deep convection on days following the sea breeze than normal non sea breeze days. This data set provides a 7‐year record of sea breezes which can be leveraged for future studies.

Subseasonal Variation Characteristics of Low-Cloud Fraction in Southeastern and Northwestern North Pacific

The subseasonal variability of the low-cloud fraction (LCF) over the southeastern North Pacific (SENP) and northwestern North Pacific (NWNP) was studied using satellite observations and the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis. It is found that subseasonal variability of the LCF was closely related to variations in the estimated inversion strength (EIS), sea surface wind speed (SSW), sensible heat flux (SHF), sea surface temperature (SST), surface temperature advection (Tadv), relative humidity (RH), surface level pressure (SLP) and surface air temperature (SAT). An increase in the LCF over the SENP is associated with the development of an anomalous anticyclonic circulation, which is located on the west coast of America. The cold advection, together with the subsidence warming associated with the anticyclonic circulation, strengthens the temperature inversion, favoring the development of the LCF. In the NWNP, the maximum LCF anomaly was also correlated with the stable boundary layer. The southerly wind blows airflow over the Kuroshio Extension from the subtropics, which brings warm and moist air. When air flows to the colder sea surface, it is cooled and condensed by the intensified heat exchange. A lead-lag composite analysis indicates that the mechanisms are different between the SENP and the NWNP, possibly due to the different types of low-level clouds over these two regions. In the SENP, the trade cumulus dominates under a strong capping inversion over the subtropics, whereas fog and stratus often occur under a shallow capping inversion in the NWNP. The effects of atmospheric circulation are also discussed.

Muted extratropical low cloud seasonal cycle is closely linked to underestimated climate sensitivity in models

A large spread in model estimates of the equilibrium climate sensitivity (ECS), defined as the global mean near-surface air-temperature increase following a doubling of atmospheric CO2 concentration, leaves us greatly disadvantaged in guiding policy-making for climate change adaptation and mitigation. In this study, we show that the projected ECS in the latest generation of climate models is highly related to seasonal variations of extratropical low-cloud fraction (LCF) in historical simulations. Marked reduction of extratropical LCF from winter to summer is found in models with ECS > 4.75 K, in accordance with the significant reduction of extratropical LCF under a warming climate in these models. In contrast, a pronounced seasonal cycle of extratropical LCF, as supported by satellite observations, is largely absent in models with ECS < 3.3 K. The distinct seasonality in extratropical LCF in climate models is ascribed to their different prevailing cloud regimes governing the extratropical LCF variability.

Corrections for Geostationary Cloud Liquid Water Path Using Microwave Imagery

Abstract Geostationary observations provide measurements of the cloud liquid water path (LWP), permitting continuous observation of cloud evolution throughout the daylit portion of the diurnal cycle. Relative to LWP derived from microwave imagery, these observations have biases related to scattering geometry, which systematically varies throughout the day. Therefore, we have developed a set of bias corrections using microwave LWP for the Geostationary Operational Environmental Satellite-16 and -17 (GOES-16 and GOES-17) observations of LWP derived from retrieved cloud-optical properties. The bias corrections are defined based on scattering geometry (solar zenith, sensor zenith, and relative azimuth) and low cloud fraction. We demonstrate that over the low-cloud regions of the northeast and southeast Pacific, these bias corrections drastically improve the characteristics of the retrieved LWP, including its regional distribution, diurnal variation, and evolution along short-time-scale Lagrangian trajectories. Significance Statement Large uncertainty exists in cloud liquid water path derived from geostationary observations, which is caused by changes in the scattering geometry of sunlight throughout the day. This complicates the usefulness of geostationary satellites to analyze the time evolution of clouds using geostationary data. Therefore, microwave imagery observations of liquid water path, which do not depend on scattering geometry, are used to create a set of corrections for geostationary data that can be used in future studies to analyze the time evolution of clouds from space.

Quantifying Parametric Uncertainty Effects on Tropical Cloud Fraction in an AGCM

AbstractThe underestimation of cloud fraction, especially the low stratus cloud (LSC) fraction over the eastern oceans, remains a problem in most atmospheric global climate models. This study investigated potential improvements through perturbing nine moist physical parameters, using uniform sampling and Latin hypercube sampling methods, and quantified the parametric uncertainty and effects of non‐linear interaction between parameters on the tropical cloud fraction in the Grid‐Point Atmospheric Model of the Institute of Atmospheric Physics/State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, version 2. Results showed that the uncertainty ranges of the tropical total cloud fraction and LSC associated with multiple‐parameter perturbation were larger than those from any single‐parameter perturbation. The total cloud fraction was significantly improved with multiple‐parameter perturbation and the LSC also increased notably when using parameter values optimized for the total cloud fraction because of the indirect parametric effect on lower‐tropospheric stability. Non‐linear effects between parameters on simulating LSC were much stronger than those on simulating the total cloud fraction. Furthermore, the non‐linear interaction reduced large values of total cloud fraction but had a strong incremental effect on large values of LSC over the southeast Pacific. The findings demonstrate the feasibility of improving the simulation of LSC over the eastern oceans by tuning moist parameters, and provide further insight into the non‐linear effects between parameters on the simulation of cloud fraction.

An observation-based method to assess tropical stratocumulus and shallow cumulus clouds and feedbacks in CMIP6 and CMIP5 models

In the Earth system models (ESMs) participating in the Coupled Models Intercomparison Project phase 6 (CMIP6), the tropical low-cloud feedback is 50% more positive than its predecessors (CMIP5) and continues to dominate the spread in simulated climate sensitivity. In the context of recent studies reporting larger feedbacks for stratocumulus (Sc) than shallow cumulus (Cu) clouds, it appears crucial to faithfully represent the geographical extent of each cloud type to simulate realistic low-cloud feedbacks. Here we use a novel observation-based method to distinguish Sc and Cu clouds together with satellite data from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) and Clouds and the Earth’s Radiant Energy System (CERES) to evaluate Sc and Cu cloud fractions, cloud radiative effects and cloud feedbacks in the two latest generations of CMIP ESMs. Overall, the CMIP6 models perform better than the CMIP5 models in most aspects considered here, indicating progress. Yet the ensemble mean continues to underestimate the marine tropical low-cloud fraction, mostly attributable to Sc. Decomposition of the bias reveals that the Sc-regime cloud fraction is better represented in CMIP6, although Sc regimes occur too infrequently—even less frequently than in CMIP5. Building on our Sc and Cu discrimination method, we demonstrate that CMIP6 models also simulate more realistic low-cloud feedbacks than CMIP5 models, especially the Sc component. Finally, our results suggest that part of the CMIP6 low-cloud feedback increase can be traced back to greater cloud fraction in Sc-dominated regions.

Reduction in the Arctic Surface Warm Bias in the NCAR CAM6 by Reducing Excessive Low-Level Clouds in the Arctic

High-latitude low clouds in the Northern winter have been known to be closely related to the Arctic surface air temperature by controlling downward longwave radiation, but Earth system models often fail to accurately simulate this relationship. In this study, we conducted a series of model experiments to examine the role of winter high-latitude low-level clouds in determining the Arctic surface temperature. Our findings show that low-level clouds play a significant role in regulating the Arctic surface temperature. We used the NCAR CAM6 model and compared the results of an unforced simulation run with those of an experiment using an empirical low-level cloud scheme to alleviate the typical overestimation of the low cloud fraction of state-of-the-art general circulation models at high latitudes. The unforced simulation exhibited excessive downward longwave radiation in the Arctic, resulting in a significant warm bias compared to reanalysis data. On the other hand, the experiment using a modified scheme more closely resembled the reanalysis data in terms of low-level cloud simulation. Overall, our study underscores the importance of accurately representing low-level clouds in high-latitude regions to reduce surface temperature bias in the model.

Rainfall and Convection in ERA5 and MERRA-2 over the Northern Equatorial Western Pacific during PISTON

Abstract This study evaluates rainfall, cloudiness, and related fields in the European Centre for Medium-Range Weather Forecasts fifth-generation climate reanalysis (ERA5) and the National Aeronautics and Space Administration’s Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), gridded global reanalysis products against observations from the Office of Naval Research’s Propagation of Intraseasonal Tropical Oscillations (PISTON) field campaign. We focus on the first PISTON cruise, which took place from August to October 2018 in the northern equatorial western Pacific Ocean. We find biases in the mean surface heat and radiative fluxes consistent with observed biases in high and low cloud fraction and convective activity in the reanalyses. Biases in the high, middle, and low cloud fraction are also consistent with the biases in the thermodynamic profiles, with positive biases in upper-level humidity associated with excessive high cloud in both products, whereas negative biases in humidity above the boundary layer are associated with too few low and middle clouds and increased static stability. ERA5 exhibits a profile that is more top-heavy than that of MERRA-2 during periods dominated by MCSs and stronger upward motion during rainy periods, consistent with higher total rainfall in this product during PISTON. The coarser grid size in MERRA-2 relative to ERA5 and the fact that MERRA-2 did not assimilate PISTON data likely both contribute to the overall larger biases seen in MERRA-2. The observed biases in the reanalyses during PISTON have also been seen in comparisons of these products with satellite data, suggesting that the results of this study are more broadly applicable.

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.

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.