Comment on acp-2022-259

The Southern Ocean radiative bias continues to impact climate and weather models, including the Australian Community Climate and Earth System Simulator (ACCESS). The radiative bias, characterised by too much shortwave radiation reaching the surface, is attributed to the incorrect simulation of cloud frequency and phase. In this work, we use k-means cloud clustering, combined with nudged simulations of the latest generation ACCESS atmosphere model, to evaluate cloud and radiation biases when cloud types are correctly and incorrectly simulated. We find that even if the ACCESS model correctly simulates the cloud type, biases of equivalent, or in some cases greater, magnitude then when they are incorrectly simulated remain in the cloud and radiation fields examined. Furthermore, we find that even when radiative biases appear small on average, cloud property biases, such as liquid or ice water paths or cloud fractions remain large. Our results suggest that simply getting the right cloud type (or the cloud macrophysics) is not enough to reduce the Southern Ocean radiative bias. Furthermore, in instances where the radiative bias is small, it may be so for the wrong reasons. Considerable effort is still required to improve cloud microphysics, with a particular focus on cloud phase.

The method of simultaneously retrieving ice water path and mass median diameter using microwave data at two frequencies is examined and implemented for tropical nonprecipitating clouds. To develop the retrieval algorithm, the authors first derived a bulk mass–size relation for ice particles in tropical clouds based on microphysical data collected during the Central Equatorial Pacific Experiment. This relation effectively allows ice particle density to decrease with particle size. In implementing the retrieval algorithm, 150- and 220-GHz Millimeter-Wave Imaging Radiometer data collected during the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment were used. Ice water path and mass median diameter are determined based on a lookup table generated by a radiative transfer model. The lookup table depends on cloud type, cloud liquid water path, and atmospheric temperature and humidity profiles. Only nonprecipitating clouds are studied in this paper. Error analyses were performed by a Monte Carlo procedure in which atmospheric profiles, ice cloud height, liquid water content, surface temperature, and instrument noise vary randomly within their uncertainty range through a Latin hypercube sampling scheme. The rms error in the retrievals is then assessed and presented in a two-dimensional diagram of ice water path and mass median diameter. It is shown that the simultaneous retrieval method using 150 and 220 GHz may be used for clouds with ice water path larger than 200 g m−2 and mass median diameter larger than 200 μm. To obtain meaningful retrievals for “thinner” clouds, higher microwave frequencies are needed. It is also shown that liquid water clouds that are at the same altitude as ice clouds interfere with the retrievals to a significant degree. To obtain reasonable ice water path and mass median size retrievals, it is necessary first to group clouds into several classes, then to apply separate algorithms to the different classes. The accuracy of the retrievals also depends on cloud type, with the best accuracy for cirrus and the worst for the midtop mixed-phase cloud among the clouds investigated in this study.

<p>The high-resolution DYAMOND simulations resolve much of the cloud relevant dynamics and cause a large improvement in the structure and diurnal cycle of clouds and precipitation. Nevertheless, from DYAMOND simulations we know that cloud properties can vary significantly even in high-resolution simulations. We focus on evaluating and if possible constraining ice cloud processes in the tropics, an area that should particularly benefit from the increased resolution because deep convection is resolved and controls the tropical upper tropospheric water budget. We analyse not only the horizontal distribution of IWP but also the cloud phase and cloud vertical structure as they are crucial to Earth’s radiation budget.</p><p>When comparing the high-resolution global simulations performed within the DYAMOND project among each other and with passive remote sensing data and ERA5 reanalysis we find that the horizontal distribution of ice water path (IWP) varies significantly. In order to understand better those differences, we analysed the connection between the simulated vertical velocity and the total IWP, and the water path of the individual hydrometeors. While the PDF of tropical vertical velocity simulated by the different models is quite similar, the total ice water path connected with those vertical velocities varies strongly. In most models, high vertical velocities are connected with significantly higher IWP than liquid water path (LWP) except in the ICON simulations which simulates similarly large increases in IWP and LWP. Most models simulate large increases in larger ice hydrometeors for large vertical velocities while FV3 simulates also large increases in ice water connected with deep convection. Differences in cloud phase e.g. when comparing NICAM and ICON simulations are connected with different vertical distributions of the condensate with NICAM IWC reaching higher atmospheric levels than the ICON IWC. We attempt to constrain the vertical distribution using active remote sensing data. </p>

Spaceborne lidar observations from the Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite are used to evaluate cloud amount and cloud phase in the Community Atmosphere Model version 5 (CAM5), the atmospheric component of a widely used state‐of‐the‐art global coupled climate model (Community Earth System Model). By embedding a lidar simulator within CAM5, the idiosyncrasies of spaceborne lidar cloud detection and phase assignment are replicated. As a result, this study makes scale‐aware and definition‐aware comparisons between model‐simulated and observed cloud amount and cloud phase. In the global mean, CAM5 has insufficient liquid cloud and excessive ice cloud when compared to CALIPSO observations. Over the ice‐covered Arctic Ocean, CAM5 has insufficient liquid cloud in all seasons. Having important implications for projections of future sea level rise, a liquid cloud deficit contributes to a cold bias of 2–3°C for summer daily maximum near‐surface air temperatures at Summit, Greenland. Over the midlatitude storm tracks, CAM5 has excessive ice cloud and insufficient liquid cloud. Storm track cloud phase biases in CAM5 maximize over the Southern Ocean, which also has larger‐than‐observed seasonal variations in cloud phase. Physical parameter modifications reduce the Southern Ocean cloud phase and shortwave radiation biases in CAM5 and illustrate the power of the CALIPSO observations as an observational constraint. The results also highlight the importance of using a regime‐based, as opposed to a geographic‐based, model evaluation approach. More generally, the results demonstrate the importance and value of simulator‐enabled comparisons of cloud phase in models used for future climate projection.

In early June 2016 a large rainband with an embedded subtropical cyclone, associated with a deep upper-level trough, brought extensive heavy rainfall along Australia’s east coast, from southern Queensland to Tasmania. In the lead-up to this event, sea-surface temperatures (SSTs) in the Coral and Tasman Seas were the warmest on record for the time of year. To investigate how the anomalously high SST, and its distribution, influenced the development of the cyclone, a high-resolution configuration of the Australian Community Climate and Earth System Simulator (ACCESS) over Australia, known as AUS2200, has been run under different SST scenarios. All simulations were run from 0000 UTC 3 June to 0000 UTC 8 June 2016, and use ERA5 data for the SST calculations.A more intense subtropical cyclone develops off the New South Wales (NSW) coast in two simulations run with observed SST — one with fixed initial SST (Control) and the other with daily evolving SST (Evolving) — compared with a simulation using 3 June climatological SST (Climatology). The cyclone also stalls longer near the NSW coast in the observed SST runs.Two additional simulations examine the role of the East Australian Current in the Tasman Sea. One smooths a prominent warm eddy (Smooth), and another replaces the Tasman Sea SST with climatological values (Tasclim). Both simulations retain the cyclone intensification seen in Control. A final simulation that replaces the Coral Sea SST with climatological values (Corclim) produces a weaker cyclone similar to Climatology.Taken together, the results indicate that the anomalously warm Coral Sea SSTs were more important for the cyclone intensification than those of the Tasman Sea even though the greatest intensification occurred over the Tasman Sea. The greater cyclone intensity and slower southward movement over the Tasman Sea resulted in stronger and more prolonged onshore winds along the southern NSW coast, increasing the potential for coastal damage.The greater intensity of the subtropical cyclone seen in Control, Evolving, Smooth, and Tasclim is associated with the formation of a warmer deep-tropospheric storm core than seen in Climatology and Corclim. This is linked to a greater reservoir of deep-tropospheric warm air that develops when using observed SST over the Coral Sea. These findings highlight the critical role of the Coral Sea’s warm SST as a driver of the cyclone’s development and intensification.

Recent global climate models with sufficient resolution and physics offer a promising approach for simulating real-world tropical cyclone (TC) statistics and their changing relationship with climate. In the first part of this study, we examine the performance of a high-resolution (~40-km horizontal grid) global climate model, the atmospheric component of the Australian Community Climate and Earth System Simulator (ACCESS) based on the Met Office Unified Model (UM8.5) Global Atmosphere (GA6.0). The atmospheric model is forced with observed sea surface temperature, and 20 years of integrations (1990–2009) are analyzed for evaluating the simulated TC statistics compared with observations. The model reproduces the observed climatology, geographical distribution, and interhemispheric asymmetry of global TC formation rates reasonably well. The annual cycle of regional TC formation rates over most basins is also well captured. However, there are some regional biases in the geographical distribution of TC formation rates. To identify the sources of these biases, a suite of model-simulated large-scale climate conditions that critically modulate TC formation rates are further evaluated, including the assessment of a multivariate genesis potential index. Results indicate that the model TC genesis biases correspond well to the inherent biases in the simulated large-scale climatic states, although the relative effects on TC genesis of some variables differs between basins. This highlights the model’s mean-state dependency in simulating accurate TC formation rates.

Abstract. Over the last decade many climate models have evolved into Earth system models (ESMs), which are able to simulate both physical and biogeochemical processes through the inclusion of additional components such as the carbon cycle. The Australian Community Climate and Earth System Simulator (ACCESS) has been recently extended to include land and ocean carbon cycle components in its ACCESS-ESM1 version. A detailed description of ACCESS-ESM1 components including results from pre-industrial simulations is provided in Part 1. Here, we focus on the evaluation of ACCESS-ESM1 over the historical period (1850–2005) in terms of its capability to reproduce climate and carbon-related variables. Comparisons are performed with observations, if available, but also with other ESMs to highlight common weaknesses. We find that climate variables controlling the exchange of carbon are well reproduced. However, the aerosol forcing in ACCESS-ESM1 is somewhat larger than in other models, which leads to an overly strong cooling response in the land from about 1960 onwards. The land carbon cycle is evaluated for two scenarios: running with a prescribed leaf area index (LAI) and running with a prognostic LAI. We overestimate the seasonal mean (1.7 vs. 1.4) and peak amplitude (2.0 vs. 1.8) of the prognostic LAI at the global scale, which is common amongst CMIP5 ESMs. However, the prognostic LAI is our preferred choice, because it allows for the vegetation feedback through the coupling between LAI and the leaf carbon pool. Our globally integrated land–atmosphere flux over the historical period is 98 PgC for prescribed LAI and 137 PgC for prognostic LAI, which is in line with estimates of land use emissions (ACCESS-ESM1 does not include land use change). The integrated ocean–atmosphere flux is 83 PgC, which is in agreement with a recent estimate of 82 PgC from the Global Carbon Project for the period 1959–2005. The seasonal cycle of simulated atmospheric CO2 is close to the observed seasonal cycle (up to 1 ppm difference for the station at Mace Head and up to 2 ppm for the station at Mauna Loa), but shows a larger amplitude (up to 6 ppm) in the high northern latitudes. Overall, ACCESS-ESM1 performs well over the historical period, making it a useful tool to explore the change in land and oceanic carbon uptake in the future.

Abstract. Marine stratocumuli are the most dominant cloud type by area coverage in the Southern Ocean (SO). They can be divided into different self-organized cellular morphological regimes known as open and closed mesoscale-cellular convective (MCC) clouds. Open and closed cells are the two most frequent types of organizational regimes in the SO. Using the liDAR-raDAR (DARDAR) version 2 retrievals, we quantify 59 % of all MCC clouds in this region as mixed-phase clouds (MPCs) during a 4-year time period from 2007 to 2010. The net radiative effect of SO MCC clouds is governed by changes in cloud albedo. Both cloud morphology and phase have previously been shown to impact cloud albedo individually, but their interactions and their combined impact on cloud albedo remain unclear. Here, we investigate the relationships between cloud phase, organizational patterns, and their differences regarding their cloud radiative properties in the SO. The mixed-phase fraction, which is defined as the number of MPCs divided by the sum of MPC and supercooled liquid cloud (SLC) pixels, of all MCC clouds at a given cloud-top temperature (CTT) varies considerably between austral summer and winter. We further find that seasonal changes in cloud phase at a given CTT across all latitudes are largely independent of cloud morphology and are thus seemingly constrained by other external factors. Overall, our results show a stronger dependence of cloud phase on cloud-top height (CTH) than CTT for clouds below 2.5 km in altitude. Preconditioning through ice-phase processes in MPCs has been observed to accelerate individual closed-to-open cell transitions in extratropical stratocumuli. The hypothesis of preconditioning has been further substantiated in large-eddy simulations of open and closed MPCs. In this study, we do not find preconditioning to primarily impact climatological cloud morphology statistics in the SO. Meanwhile, in-cloud albedo analysis reveals stronger changes in open and closed cell albedo in SLCs than in MPCs. In particular, few optically thick (cloud optical thickness >10) open cell stratocumuli are characterized as ice-free SLCs. These differences in in-cloud albedo are found to alter the cloud radiative effect in the SO by 21 to 39 W m−2 depending on season and cloud phase.

The present study investigates the effect of increasing sea surface temperatures (SSTs) on tropical cyclone (TC) frequency using the high-resolution Australian Community Climate and Earth-System Simulator (ACCESS) model. We examine environmental conditions leading to changes in TC frequency in aqua-planet global climate model simulations with globally uniform sea surface temperatures (SSTs). Two different TC tracking schemes are used. The Commonwealth Scientific and Industrial Research Organization (CSIRO) scheme (a resolution-dependent scheme) detects TCs that resemble observed storms, while the Okubo–Weiss zeta parameter (OWZP) tracking scheme (a resolution-independent scheme) detects the locations within “marsupial pouches” that are favorable for TC formation. Both schemes indicate a decrease in the global mean TC frequency with increased saturation deficit and static stability of the atmosphere. The OWZP scheme shows a poleward shift in the genesis locations with rising temperatures, due to lower vertical wind shear. We also observe an overall decrease in the formation of tropical depressions (TDs) with increased temperatures, both for those that develop into TCs and non-developing cases. The environmental variations at the time of TD genesis between the developing and the non-developing tropical depressions identify the Okubo–Weiss (OW) parameter and omega (vertical mass flux) as significant influencing variables. Initial vortices with lower vorticity or with weaker upward mass flux do not develop into TCs due to environments with higher saturation deficit and stronger static stability of the atmosphere. The latitudinal variations in the large-scale environmental conditions account for the latitudinal differences in the TC frequency in the OWZP scheme.

The relationship between precipitation and cloud properties in Southwest China are investigated by using the CLARA‐A2 cloud parameters data and TRMM‐3B43 precipitation data from 1998 to 2015. Ice water path (IWP) and cloud top height (CTH) are significantly and positively correlated with precipitation in all regions, indicating that ice‐phase processes and cloud development processes are the critical processes influencing precipitation. Precipitation is also directly associated with cloud fractional coverage (CFC) due to the significant positive correlation between CFC and precipitation in all regions except the Sichuan Basin (SCB). A positive correlation between liquid water path (LWP) and precipitation is found in the Eastern Tibetan Plateau (ETP) and Yunnan‐Kweichow Plateau (YKP), but not in the Western Tibetan Plateau (WTP) and SCB. Notably, the response of precipitation to LWP is not as good as that to IWP in SCB. Precipitation is significantly negatively correlated with ice effective radius (IREF) in WTP and ETP and positively correlated with liquid effective radius (LREF) in ETP, YKP and SCB. IREF and LREF are closely related to cloud microphysical processes. Specifically, small IREF could accelerate the Bergeron process and thus increase precipitation, while large LREF is closely related to the cloud droplets coalescence process. Results indicate that the difference in precipitation between the cold and warm seasons is related to convective available potential energy (CAPE) and low troposphere relative humidity (RH). High CAPE and RH favour the precipitation occurrence in Southwest China. The influence of CAPE and RH on precipitation is more significant in the ETP than that in the WTP, owing to the orographic lifting and moisture transport from the Indian Ocean. Thermodynamic and humidity conditions have a greater impact on precipitation by influencing LREF, LWP and IWP in YKP. In SCB, precipitation shows a strong dependence on CAPE, IWP and LREF, but not on RH.

ABSTRACTAerosol-cloud interaction is the subject of considerable scientific research, due to the importance of clouds in controlling climate. In the present study, three years (2011–2013) satellite observations are used to investigate the aerosol indirect effect (AIE) over Dehradun. The low values of Angstrom exponent (α) during March–July are attributed to the loading of dust-like coarse particles in the atmosphere, whereas the analysis of aerosol type and Spectral Radiation Transport Model for Aerosol species (SPRINTARS) simulated aerosol species variation supports the fact. Moderate Resolution Imaging Spectroradiometer (MODIS) derived AOD data are associated to the cloud product to examine the dust impact on properties of liquid cloud and ice cloud. The positive values of aerosol cloud interaction effect (ACI) for ice cloud during pre-monsoon (March–May) and monsoon (June–August) seasons reveal the significant impact of dust on ice clouds over Dehradun, which is maximum during May (~0.24 ± 0.05). The present study shows that ice cloud effective radius (ICER) decrease with AOD during dust period. The increase in ice water path (IWP) and ice cloud optical depth (ICOD) reveals the impact of dust on heterogeneous ice generation in low level clouds. However, there is no relation between dust and liquid water cloud during dust period. It is difficult to provide definite conclusions that the dust and cloud changes are driven by the same meteorological conditions. Cloud and the Earth’s Radiant Energy System (CERES) derived flux data are used to examine the associated changes in TOA cloud radiative forcing. The diminution in effective size of ice crystal due to aerosol first indirect effect traps more longwave radiation and reflects more solar radiation. Both first and second indirect effects enhance cloud cooling, whereas the dust induced cloud warming is mainly the result of the semi-direct effect.

The Moderate Resolution Imaging Spectroradiometer (MODIS) Airborne Simulator (MAS) and MODIS/Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Airborne Simulator (MASTER) were used to obtain measurements of the bidirectional reflectance and brightness temperature of clouds at 50 discrete wavelengths between 0.47 and 14.2 μm (12.9 μm for MASTER). These observations were obtained from the NASA ER‐2 aircraft as part of the Tropical Composition, Cloud and Climate Coupling (TC4) experiment conducted over Central America and surrounding Pacific and Atlantic Oceans between 17 July and 8 August 2007. Multispectral images in eleven distinct bands were used to derive a confidence in clear sky (or alternatively the probability of cloud) over land and ocean ecosystems. Based on the results of individual tests run as part of the cloud mask, an algorithm was developed to estimate the phase of the clouds (liquid water, ice, or undetermined phase). The cloud optical thickness and effective radius were derived for both liquid water and ice clouds that were detected during each flight, using a nearly identical algorithm to that implemented operationally to process MODIS cloud data from the Aqua and Terra satellites (Collection 5). This analysis shows that the cloud mask developed for operational use on MODIS, and tested using MAS and MASTER data in TC4, is quite capable of distinguishing both liquid water and ice clouds during daytime conditions over both land and ocean. The cloud optical thickness and effective radius retrievals use five distinct bands of the MAS (or MASTER), and these results were compared with nearly simultaneous retrievals of marine liquid water clouds from MODIS on the Terra spacecraft. Finally, this MODIS‐based algorithm was adapted to Multiangle Imaging SpectroRadiometer (MISR) data to infer the cloud optical thickness of liquid water clouds from MISR. Results of this analysis are compared and contrasted.

Abstract. The ice phase in clouds is essential for precipitation formation over continents. The underlying processes for ice growth are still poorly understood, leading to large uncertainties in precipitation forecasts and climate simulations. One crucial aspect is the Wegener–Bergeron–Findeisen (WBF) process, which describes the growth of ice crystals at the expense of cloud droplets, leading to a partial or full glaciation of the cloud. In the CLOUDLAB project, we employ glaciogenic cloud seeding to initiate the ice phase in supercooled low-level clouds in Switzerland using uncrewed aerial vehicles with the goal of investigating the WBF process. An extensive setup of ground-based remote-sensing and balloon-borne in situ instrumentation allows us to observe the formation and subsequent growth of ice crystals in great detail. In this study, we compare the seeding signals observed in the field to those simulated using a numerical weather model in large-eddy mode (ICON-LEM). We first demonstrate the capability of the model to accurately simulate and reproduce the seeding experiments across different environmental conditions. Second, we investigate the WBF process in the model by comparing the simulated cloud droplet and ice crystal number concentration changes to in situ measurements. In the field experiments, simultaneous reductions in cloud droplet number concentrations with increased ice crystal number concentrations were observed, with periods showing a full depletion of cloud droplets. The model can reproduce the observed ice crystal number concentrations most of the time; however, it cannot reproduce the observed fast reductions in cloud droplet number concentrations. Our detailed analysis shows that the WBF process appears to be less efficient in the model than in the field. In the model, exaggerated ice crystal number concentrations are required to produce comparable changes in cloud droplet number concentrations, highlighting the inefficiency of the WBF process in the numerical weather model ICON.

A negative shortwave cloud feedback associated with higher extratropical liquid water content in mixed-phase clouds is a common feature of global warming simulations, and multiple mechanisms have been hypothesized. A set of process-level experiments performed with an idealized global climate model (a dynamical core with passive water and cloud tracers and full Rotstayn–Klein single-moment microphysics) show that the common picture of the liquid water path (LWP) feedback in mixed-phase clouds being controlled by the amount of ice susceptible to phase change is not robust. Dynamic condensate processes—rather than static phase partitioning—directly change with warming, with varied impacts on liquid and ice amounts. Here, three principal mechanisms are responsible for the LWP response, namely higher adiabatic cloud water content, weaker liquid-to-ice conversion through the Bergeron–Findeisen process, and faster melting of ice and snow to rain. Only melting is accompanied by a substantial loss of ice, while the adiabatic cloud water content increase gives rise to a net increase in ice water path (IWP) such that total cloud water also increases without an accompanying decrease in precipitation efficiency. Perturbed parameter experiments with a wide range of climatological LWP and IWP demonstrate a strong dependence of the LWP feedback on the climatological LWP and independence from the climatological IWP and supercooled liquid fraction. This idealized setup allows for a clean isolation of mechanisms and paints a more nuanced picture of the extratropical mixed-phase cloud water feedback than simple phase change.

Three cloud-phase determination algorithms from passive satellite imagers are explored to assess their suitability for climate monitoring purposes in midlatitude coastal climate zones. The algorithms are the Moderate Resolution Imaging Spectroradiometer (MODIS)-like thermal infrared cloud-phase method, the Satellite Application Facility on Climate Monitoring (CM-SAF) method, and an International Satellite Cloud Climatology Project (ISCCP)-like method. Using one year (May 2004–April 2005) of data from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) on the first Meteosat Second Generation satellite (Meteosat-8), retrievals of the methods are compared with collocated and synchronized ground-based cloud-phase retrievals obtained from cloud radar and lidar observations at Cabauw, Netherlands. Three aspects of the satellite retrievals are evaluated: 1) instantaneous cloud-phase retrievals, 2) monthly-averaged water and ice cloud occurrence frequency, and 3) diurnal cycle of cloud phase for May–August 2004. For the instantaneous cases, all methods have a very small bias for thick water and ice cloud retrievals (∼5%). The ISCCP-like method has a larger bias for pure water clouds (∼10%), which is likely due to the 260-K threshold leading to misdetection of water clouds existing at lower temperatures. For the monthly-averaged water and ice cloud occurrence, the CM-SAF method is best capable of reproducing the annual cycle, mainly for the water cloud occurrence frequency, for which an almost constant positive bias of ∼8% was found. The ISCCP- and MODIS-like methods have more problems in detecting the annual cycle, especially during the winter months. The difference in annual cycle detection among the three methods is most probably related to the use of visible/near-infrared reflectances that enable a more direct observation of cloud phase. The diurnal cycle in cloud phase is reproduced well by all methods. The MODIS-like method reproduces the diurnal cycle best, with correlations of 0.89 and 0.86 for water and ice cloud occurrence frequency, respectively.