Understanding the Extratropical Liquid Water Path Feedback in Mixed-Phase Clouds with an Idealized Global Climate Model

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.

Quality Assessment of Acquired GEDI Waveforms: Case Study over France, Tunisia and French Guiana

The Global Ecosystem Dynamics Investigation (GEDI) full-waveform (FW) LiDAR instrument on board the International Space Station (ISS) has acquired in its first 18 months of operation more than 25 billion shots globally, presenting a unique opportunity for the analysis of LiDAR data across multiple domains (e.g., forestry, hydrology). Nonetheless, not all acquired GEDI shots provide exploitable waveforms due to instrumental (e.g., transmitted energy, viewing angle) and atmospheric conditions (e.g., clouds, aerosols). In this study, we analyzed the quality of all available GEDI acquisitions over France, Tunisia, and French Guiana, in order to determine the extent of the impact of instrumental and climatic factors on the viability of these acquisitions. Results showed that with favorable acquisition conditions (i.e., cloud-free acquisitions), the factor with the highest impact on the viability of GEDI data is the acquisition time, as acquisitions around noon were the least viable due to higher solar noise. In addition to acquisition time, the viewing angle, the transmitted energy, and the aerosol optical depth all affected, to a lesser extent, the viability of GEDI data. Nonetheless, the percentage of exploitable cloud-free GEDI acquisitions ranged from 75 to 91% of all total acquisitions, depending on the acquisition site. The analysis of the quality of GEDI shots acquired in the presence of clouds showed that clouds have a greater impact on their exploitability, with sometimes as much as 69% of acquired data being unusable. For cloudy acquisitions, the two factors that mostly affect the LiDAR signal are the cloud optical depth (or cloud opacity) and cloud water content. Overall, nonviable GEDI data represent less than 50% of total acquisitions across the different instrumental, climatic, and environmental conditions.

Subgrid-scale Horizontal and Vertical Variations of Cloud Water in Stratocumulus Clouds: A case study based on LES and comparisons with in-situ observations

Stratocumulus clouds in the marine boundary layer cover a large fraction of ocean surface and play an important role in the radiative energy balance of the Earth system. Simulating these clouds in Earth system models (ESMs) has proven to be extremely challenging, in part because cloud microphysical processes such as the autoconversion of cloud water into precipitation occur at the scales much smaller than typical ESM grid sizes. An accurate autoconversion parameterization needs to account for not only the local microphysical process (e.g., the dependence on cloud water content qc and cloud droplet number concentration Nc), but also the sub-grid scale variability of the cloud properties the determine the process rate. Accounting for subgrid-scale variability is often achieved by the introduction of a so-called enhancement factor E. Previous studies of E for autoconversion focused more on its dependence on cloud regime and ESM grid size, but largely overlooked the vertical dependence of E within the cloud. In this study, we use a large-eddy simulation (LES) model, initialized and constrained with in situ and surface-based measurements from a recent airborne field campaign, to characterize the vertical dependence of the horizontal variation of qc in stratocumulus clouds and the implications for E. Similar to our recent observational study (Zhang et al., 2021), we found that the inverse relative variance of qc, an index of horizontal homogeneity, generally increases from cloud base upward through the lower 2/3 of the cloud, and then decreases in the uppermost 1/3 of the cloud. As a result, E decreases from cloud base upward, and then increases towards the cloud top. We apply a decomposition analysis to the LES cloud water field to understand the relative roles of the mean and variances of qc in determining the vertical dependence of E. Our analysis reveals that the vertical dependence of the horizontal qc variability and enhancement factor E is a combined result of condensation growth throughout the lower portion of the cloud and entrainment mixing at cloud top. The findings from this study indicate that a vertically dependent E should be used in ESM autoconversion parameterizations.

Evaluation of simulated cloud liquid water in low clouds over the Beaufort Sea in the Arctic System Reanalysis using ARISE airborne in situ observations

Arctic low clouds and the water they contain influence the evolution of the Arctic system through their effects on radiative fluxes, boundary layer mixing, stability, turbulence, humidity, and precipitation. Atmospheric models struggle to accurately simulate the occurrence and properties of Arctic low clouds, stemming from errors in both the simulated atmospheric state and the dependence of cloud properties on the atmospheric state. Knowledge of the contributions from these two factors to the model errors allows for the isolation of the process contributions to the model–observation differences. We analyze the differences between the Arctic System Reanalysis version 2 (ASR) and data taken during the September 2014 Arctic Radiation–IceBridge Sea and Ice Experiment (ARISE) airborne campaign conducted over the Beaufort Sea. The results show that ASR produces less total and liquid cloud water than observed along the flight track and is unable to simulate observed large in-cloud water content. Contributing to this bias, ASR is warmer by nearly 1.5 K and drier by 0.06 g kg−1 (relative humidity 4.3 % lower) than observed. Moreover, ASR produces cloud water over a much narrower range of thermodynamic conditions than shown in ARISE observations. Analyzing the ARISE–ASR differences by thermodynamic conditions, our results indicate that the differences are primarily attributed to disagreements in the cloud–thermodynamic relationships and secondarily (but importantly) to differences in the occurrence frequency of thermodynamic regimes. The ratio of the factors is about 2/3 to 1/3. Substantial sampling uncertainties are found within low-likelihood atmospheric regimes; sampling noise cannot be ruled out as a cause of observation–model differences, despite large differences. Thus, an important lesson from this analysis is that when comparing in situ airborne data and model output, one should not restrict the comparison to flight-track-only model output.

Vertical structure of cloud radiative heating in the tropics: confronting the EC-Earth v3.3.1/3P model with satellite observations

Understanding the coupling of clouds to large-scale circulation is one of the grand challenges for the global climate research community. In this context, realistically modelling the vertical structure of cloud radiative heating (CRH) and/or cooling in Earth system models is a key premise to understand this coupling. Here, we evaluate CRH in two versions of the European Community Earth System Model (EC-Earth) using retrievals derived from the combined radar and lidar data from the CloudSat and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellites. One model version is also used with two different horizontal resolutions. Our study evaluates large-scale intraseasonal variability in the vertical structure of CRH and cloud properties and investigates the changes in CRH during different phases of the El Niño–Southern Oscillation (ENSO), a process that dominates the interannual climate variability in the tropics. EC-Earth generally captures both the intraseasonal and meridional pattern of variability in CRH over the convectively active and stratocumulus regions and the CRH during the positive and negative phases of ENSO. However, two key differences between model simulations and satellite retrievals emerge. First, the magnitude of CRH, in the upper troposphere, over the convectively active zones is up to twice as large in the models compared to the satellite data. Further dissection of net CRH into its shortwave and longwave components reveals noticeable differences in their vertical structure. The shortwave component of the radiative heating is overestimated by all model versions in the lowermost troposphere and underestimated in the middle troposphere. These over- and underestimates of shortwave heating are partly compensated by an overestimate of longwave cooling in the lowermost troposphere and heating in the middle troposphere. The biases in CRH can be traced back to disagreement in cloud amount and cloud water content. There is no noticeable improvement of CRH by increasing the horizontal resolution in the model alone. Our findings highlight the importance of evaluating models with satellite observations that resolve the vertical structure of clouds and cloud properties.

Investigating Wintertime Cloud Microphysical Properties and Their Relationship to Air Mass Advection at Ny-Ålesund, Svalbard Using the Synergy of a Cloud Radar–Ceilometer–Microwave Radiometer

This study investigates the relationship of cloud properties and radiative effects with air mass origin during the winter (November–February, 2016–2020) at Ny-Ålesund, Svalbard, through a combination of cloud radar, ceilometer, and microwave radiometer measurements. The liquid cloud fraction (CF) was less than 2%, whereas the ice CF predominantly exceeded 10% below 6 km. The liquid water content (LWC) of mixed-phase clouds (LWCmix), which predominantly exist in the boundary layer (CFmix: 10–30%), was approximately four times higher than that of liquid clouds (LWCliq). Warm air mass advection () cases were closely linked with strong southerly/southwesterly winds, whereas northerly winds brought cold and dry air masses () to the study area. Elevated values of LWC and ice water content (IWC) during cases can be explained by the presence of mixed-phase clouds in the boundary layer and ice clouds in the middle troposphere. Consistently, the re of ice particles in cases was approximately 5–10 μm larger than that in cases at all altitudes. A high CF and cloud water content in cases contributed to a 33% (69 W m−2) increase in downward longwave (LW) fluxes compared to cloud-free conditions.

Volcanic Aerosol Impacts on Hawai‘i Island Rainfall

In recent decades, a significant rainfall decline over the Island of Hawai‘i has been noted, with many hypothesizing that the drying is associated with the volcanic aerosols emitted from the Kīlauea Volcano. While it is clear that volcanic emissions can create hazardous air quality for Hawaiian communities, the impacts on rainfall are less clear. Here we investigate the impact of volcanic aerosol emissions on Hawai‘i Island rainfall. Based on observed daily rainfall and SO2 emissions, it is found that days with high SO2 emissions have on average 8 mm day−1 less rainfall downstream of the Kīlauea Volcano. Sensitivity studies with varying volcanic aerosol emission sources from the Kīlauea vent locations have also been conducted by the Weather Research and Forecasting (WRF) Model in order to examine the detailed physical processes. Consistent with SO2 air quality observations, it is found that the diurnal change in aerosol number concentration is strongly dependent on the diurnal variation of local circulations. The added aerosols are lofted into the orographic convection where they modify the microphysical properties of the warm clouds by increasing the cloud droplet number concentration, decreasing the cloud droplet size, increasing cloud water content and enhancing cloud evaporation. The volcanic aerosols also delay precipitation production and modify the spatial distribution of rainfall on the downstream mountainside. The modification of precipitation on an island has far reaching consequences. For this reason, we work to quantify the sensitivity of the orographic precipitation to volcanic aerosols and move beyond hypothesized relationships towork toward understanding the underlying problem.

Effects of improved interpolation in the wet-scavenging scheme of FLEXPART

<p>The Lagrangian dispersion model FLEXPART v10.4 uses cloud water content, temperature, and precipitation rates to calculate wet scavenging. Currently, only precipitation fields are interpolated spatially to the particle positions. A simple nearest-neighbour approach is used for cloud parameters and temperature. This is made worse by the fact that precipitation fields from the European Centre for Medium Range Weather Forecasts (ECMWF) are temporal integrals whereas all the other parameters refer to a specific time. The pre-processor flex_extract disaggregates the precipitation fields to construct point values that can preserve the integral quantity when interpolated in FLEXPART. However, this method does not preserve precipitation in each time interval, leading to smoothing, or even shifting precipitation into dry periods.</p><p>We have implemented interpolation of all fields relevant for wet scavenging in FLEXPART v10.4 as well as the option to use our improved precipitation disaggregation scheme (https://doi.org/10.5194/gmd-11-2503-2018). It introduces two additional subgrid points within one original time interval. This secures consistency, continuity and mass conservation of precipitation within each time interval.</p><p>These updates lead to a massive improvement of the wet deposition fields in a specific test case where we applied a high-resolution outgrid that makes the effects of interpolation issues more visible. Originally, a kind of checkerboard pattern was visible, as well as a banded structure due to the finite time interval between meteorological input fields. Both features are mostly eliminated now. Additionally, the influence of varying the temporal and spatial resolution of the ECMWF input fields was investigated, and the benefit of using the ECMWF cloud water content instead of parametrised values. We also look at the impact of the new version on other, previously used test cases, for example, a lifetime analysis of aerosol particles as well as transport of mineral dust and black carbon.</p>

Airborne in-situ observations of Arctic clouds in spring and summer above sea ice and the open ocean

<p>Two airborne campaigns (AFLUX and MOSAiC-ACA) were conducted in spring 2019 and late summer 2020 to investigate low- and midlevel clouds and related atmospheric parameters in the central Arctic. The measurements aim at better understanding the role of Arctic clouds and their interactions with the surface - open ocean or sea ice - in light of amplified climate change in the Arctic.<br>During the campaigns the Basler BT-67 research aircraft Polar 5 based in Svalbard (78.24 N, 15.49 E) equipped with a comprehensive in-situ cloud payload performed in total 24 flights over the Arctic ocean and in the Fram Strait. A combination of size spectrometers (CDP and CAS) and 2-dimensional imaging probes (CIP and PIP) covering the size range of Arctic cloud hydrometeors from 0.5µm to 6.2mm measured the total particle number concentration, the particle size distribution and the median volume diameter. Liquid water content and ice water content were measured with the Nevzorov bulk probe. The cloud water content (liquid and ice water content) from the Nevzorov probe is compared to the cloud water content derived from particle size measurements using consistent mass-dimension relationships.<br>Here we give an overview of the microphysical cloud properties measured in spring and late summer in high northern latitudes at altitudes up to 4 km. We derive the temperature and altitude dependence of liquid, mixed phase and ice cloud properties and investigate their seasonal variability. Differences in cloud properties above the sea ice and the open ocean are examined, supporting the hypothesis of an enhanced median volume diameter over open ocean compared to clouds formed over the sea ice. The comprehensive data set on microphysical cloud properties enhances our understanding of cloud formation and mixed phase cloud processes over the Arctic ocean, it can be used to validate remote sensing retrievals and models and helps to assess the role of clouds for stronger impact of climate change in the Arctic. </p>