Cloud Microphysics Research Articles

Day–Night Transport-induced Chemistry and Clouds on WASP-39b: Gas-phase Composition

JWST has recently detected the first robust photochemical product on an exoplanet: sulfur dioxide (SO2) on WASP-39b. The data from the NIRISS instrument also reveal signs of partial coverage of clouds. Most of the previous studies have focused on interpreting spectral data with 1D models. To explore how the chemical species and cloud particles are altered by global circulation, we applied a 2D photochemical model and a 2D microphysical cloud model separately to postprocess the thermal and dynamical structures simulated by a 3D general circulation model of WASP-39b. We found that SO2 produced by photochemistry on the dayside can be transported to the nightside owing to the efficient replenishment of horizontal transport. The morning–evening limb differences in methane (CH4) abundances predicted by the 1D models disappeared after horizontal transport is included. Similarly, the inclusion of horizontal transport also reduced the limb differences in SO2. Our modeling results suggest that the fast zonal wind results in minimal or negligible limb asymmetry in composition. Based on the synthetic spectra generated by our 2D atmosphere simulations, we propose that observing SO2 absorption in the emission spectra of WASP-39b at different phases may offer opportunities to probe the horizontal quenching process of photochemical products. We will focus on the gas-phase chemistry in this paper and leave the results regarding clouds in the subsequent paper as part of the series.

The Effects of Aerosol on Small‐Scale Cloud‐Environment Mixing: Implications for Simulating and Observing Inhomogeneous Mixing

AbstractEntrainment‐mixing modulates the number and size of cloud droplets, and thus affects the optical properties of clouds and their role in the climate system. Using a statistical turbulence model coupled with Lagrangian cloud microphysics, we analyze the role of aerosol in the entrainment‐mixing process, which, for instance, prevent the full evaporation of cloud droplets, leaving behind haze particles. To test a commonly applied indicator for inhomogeneous mixing, a set of different mixing scenarios is simulated. We conclude that if a hard separation radius between cloud droplets and haze particles is chosen, the typical classification into homogeneous and inhomogeneous mixing can be wrong because larger haze particles might be misidentified as cloud droplets, making the mixing appear more homogeneous. Furthermore, we show that the growth of cloud droplets on the expense of other hydrometeors due to differences in aerosol loading and particle curvature (Ostwald ripening) can produce cloud microphysical signatures indistinguishable from inhomogeneous mixing. Finally, we investigate how the consideration of haze particles can mitigate the previously reported negative impacts of inhomogeneous mixing on the cloud albedo. These findings should be considered when interpreting observations and simulations of small‐scale entrainment‐mixing.

Maximum Supersaturation in the Marine Boundary Layer Clouds Over the North Atlantic

AbstractThe maximum supersaturation (Sx) in clouds is a key parameter affecting the cloud's microphysical and radiative properties. We investigate the Sx of the marine boundary layer clouds by combining airborne and surface observations in the Eastern North Atlantic. The cloud droplet number concentration (Nc) in the least diluted cloud cores agrees well with the number concentration of particles larger than the Hoppel Minimum (HM) (N>HM) below clouds, indicating that the HM represents the average size threshold above which particles are activated to form cloud droplets. The Sx values derived from surface observations vary from 0.10% to 0.50% from June 2017 to June 2018, with a clear seasonal variation exhibiting higher values during winter. Most of the Sx variance (∼60%) can be explained by the cloud condensation nuclei (CCN) concentration and updraft velocity (w), with the CCN concentration playing a more important role than w in explaining the variation of Sx. The influence of CCN concentration on Sx leads to a buffered response of Nc to aerosol perturbations. The response of Nc to low aerosol concentration during winter is further buffered by the high w. The global Community Earth System Model (CESM) simulated Sx values in the Azores have a positive bias compared to measured Sx, likely due to overestimated w and underestimated CCN concentration. The CESM simulated Sx exhibits higher values further north over the North Atlantic Ocean, which is attributed to stronger w. The suppression of Sx by aerosol is also evident in regions with high CCN concentrations.

Cloud characteristics over the Yunnan–Guizhou plateau as observed by MODIS and Himawari‐8

AbstractCloud descriptions and parameterizations are major sources of uncertainty in weather and climate modelling studies. In this study, we investigated the cloud properties over the Yunnan–Guizhou Plateau (YGP) by using the Moderate Resolution Imaging Spectroradiometer (MODIS) and Himawari‐8 (H8_Japan and H8_Zhuge) cloud datasets. Corresponding to their distinct terrain features, the cloud climate patterns on the western and eastern sides of the YGP are different. Our results show that the spatial patterns of the cloud parameters in all three datasets are very similar over the YGP, especially the cloud cover and cloud effective radius. The high cloud frequency region is located to the east of Yunnan–Guizhou quasi‐stationary front in cold season, and the largest gradient is along front. On frontal days, the regional differences in the cloud properties over the YGP are much more obvious, with the cloud cover across the front increasing from ~20%–35% on its western side to more than 95% on its eastern side. Furthermore, higher thin clouds with larger cloud effective radius typically exist on the western side of the front, while lower thick clouds with smaller particles appear on its eastern side. This study enhances our understanding how cloud characteristics impact by the frontal system and provide a valuable insight for the design and improvement of cloud microphysics parameters in weather forecast models over the YGP region.

A new experimental set-up for aerosol stability investigations in microgravity conditions

The temporal and spatial evolution of dispersed media is a fundamental problem in a wide range of physicochemical systems, such as emulsions, suspensions and aerosols. These systems are multiphasic and involve compounds of different densities. They are therefore subject to the influence of gravity which determines the sedimentation rate of their dispersed phase. This effect can be dominant and prevent a detailed study of the phenomena occurring between the constituents themselves, such as the coalescence of drops in emulsions, the evaporation of droplets or the flocculation in suspensions. In this context, the Centre National d’Etudes Spatiales (CNES) has recently supported the development of a new instrument to produce populations of droplets, a few micrometers in radius, under controlled conditions with the objective of allowing a detailed study of their properties in microgravity conditions. The principle of this instrument is to generate, by a fast compression/expansion of air, populations of water droplets and to track their evolution by optical scanning tomography in transmission mode within a volume of approximately 2 mm 3 . Parabolic flight experiments have shown the possibility to generate and accurately follow the evolution of populations of several hundred droplets for more than 20 s. The first experimental results show that it is possible to study their evaporation kinetics or their motion when imposing von Karman swirling flows. This work is part of the AEROSOL project of DECLIC-EVO supported by CNES and aims to help the understanding of cloud microphysics which remains a critical open problem in the context of global warming.

Sensitivity of cirrus and contrail radiative effect on cloud microphysical and environmental parameters

Abstract. Natural cirrus clouds and contrails cover about 30 % of the Earth's mid-latitudes and up to 70 % of the tropics. Due to their widespread occurrence, cirrus clouds have a considerable impact on the Earth energy budget, which, on average, leads to a warming net radiative effect (solar + thermal infrared). However, whether the instantaneous radiative effect (RE), which in some cases corresponds to a radiative forcing, of natural cirrus or contrails is positive or negative depends on their microphysical, macrophysical, and optical properties, as well as the radiative properties of the environment. This is further complicated by the fact that the actual ice crystal shape is often unknown, and thus, ice clouds remain one of the components that are least understood in the Earth's radiative budget. The present study aims to investigate the dependency of the effect on cirrus RE on eight parameters, namely solar zenith angle, ice water content, ice crystal effective radius, cirrus temperature, surface albedo, surface temperature, cloud optical thickness of an underlying liquid water cloud, and three ice crystal shapes. In total, 283 500 plane-parallel radiative transfer simulations have been performed, not including three-dimensional scattering effects. Parameter ranges are selected that are typically associated with natural cirrus and contrails. In addition, the effect of variations in the relative humidity profile and the ice cloud geometric thickness have been investigated for a sub-set of the simulations. The multi-dimensionality and complexity of the eight-dimensional parameter space makes it impractical to discuss all potential configurations in detail. Therefore, specific cases are selected and discussed. For a given parameter combination, the largest impact on solar, thermal-infrared (TIR), and net RE is related to the ice crystal effective radius. The second most important parameter is ice water content, which equally impacts the solar and terrestrial RE. The solar RE of cirrus is also determined by solar zenith angle, surface albedo, liquid cloud optical thickness, and ice crystal shape (in descending priority). RE in the TIR spectrum is dominated by surface temperature, ice cloud temperature, liquid water cloud optical thickness, and ice crystal shape. Net RE is controlled by surface albedo, solar zenith angle, and surface temperature in decreasing importance. The relative importance of the studied parameters differs, depending on the ambient conditions. Furthermore, and during nighttime the net RE is equal to the TIR RE. The data set generated in this work is publicly available. It can be used as a lookup table to extract the RE of cirrus clouds, contrails, and contrail cirrus instead of full radiative transfer calculations.

Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package, version 2: assessing aerosols, clouds, and aerosol–cloud interactions via field campaign and long-term observations

Abstract. Poor representations of aerosols, clouds, and aerosol–cloud interactions (ACIs) in Earth system models (ESMs) have long been the largest uncertainties in predicting global climate change. Huge efforts have been made to improve the representation of these processes in ESMs, and the key to these efforts is the evaluation of ESM simulations with observations. Most well-established ESM diagnostics packages focus on the climatological features; however, they lack process-level understanding and representations of aerosols, clouds, and ACIs. In this study, we developed the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package to facilitate the routine evaluation of aerosols, clouds, and ACIs simulated the Energy Exascale Earth System Model (E3SM) from the US Department of Energy (DOE). This paper documents its version 2 functionality (ESMAC Diags v2), which has substantial updates compared with version 1 (Tang et al., 2022a). The simulated aerosol and cloud properties have been extensively compared with in situ and remote-sensing measurements from aircraft, ship, surface, and satellite platforms in ESMAC Diags v2. It currently includes six field campaigns and two permanent sites covering four geographical regions: the eastern North Atlantic, the central US, the northeastern Pacific, and the Southern Ocean. These regions produce frequent liquid- or mixed-phase clouds, with extensive measurements available from the DOE Atmospheric Radiation Measurement user facility and other agencies. ESMAC Diags v2 generates various types of single-variable and multivariable diagnostics, including percentiles, histograms, joint histograms, and heatmaps, to evaluate the model representation of aerosols, clouds, and ACIs. Select examples highlighting the capabilities of ESMAC Diags are shown using E3SM version 2 (E3SMv2). In general, E3SMv2 can reasonably reproduce many observed aerosol and cloud properties, with biases in some variables such as aerosol particle and cloud droplet sizes and number concentrations. The coupling of aerosol and cloud number concentrations may be too strong in E3SMv2, possibly indicating a bias in processes that control aerosol activation. Furthermore, the liquid water path response to a perturbed cloud droplet number concentration behaves differently in E3SMv2 and observations, which warrants further study to improve the cloud microphysics parameterizations in E3SMv2.

Opinion: A critical evaluation of the evidence for aerosol invigoration of deep convection

Abstract. Deep convective updraft invigoration via indirect effects of increased aerosol number concentration on cloud microphysics is frequently cited as a driver of correlations between aerosol and deep convection properties. Here, we critically evaluate the theoretical, modeling, and observational evidence for warm- and cold-phase invigoration pathways. Though warm-phase invigoration is plausible and theoretically supported via lowering of the supersaturation with increased cloud droplet concentration in polluted conditions, the significance of this effect depends on substantial supersaturation changes in real-world convective clouds that have not been observed. Much of the theoretical support for cold-phase invigoration depends on unrealistic assumptions of instantaneous freezing and unloading of condensate in growing, isolated updrafts. When applying more realistic assumptions, impacts on buoyancy from enhanced latent heating via fusion in polluted conditions are largely canceled by greater condensate loading. Many foundational observational studies supporting invigoration have several fundamental methodological flaws that render their findings incorrect or highly questionable. Thus, much of the evidence for invigoration has come from numerical modeling, but different models and setups have produced a vast range of results. Furthermore, modeled aerosol impacts on deep convection are rarely tested for robustness, and microphysical biases relative to observations persist, rendering many results unreliable for application to the real world. Without clear theoretical, modeling, or observational support, and given that enervation rather than invigoration may occur for some deep convective regimes and environments, it is entirely possible that the overall impact of cold-phase invigoration is negligible. Substantial mesoscale variability of dominant thermodynamic controls on convective updraft strength coupled with substantial updraft and aerosol variability in any given event are poorly quantified by observations and present further challenges to isolating aerosol effects. Observational isolation and quantification of convective invigoration by aerosols is also complicated by limitations of available cloud condensation nuclei and updraft speed proxies, aerosol correlations with meteorological conditions, and cloud impacts on aerosols. Furthermore, many cloud processes, such as entrainment and condensate fallout, modulate updraft strength and aerosol–cloud interactions, varying with cloud life cycle and organization, but these processes remain poorly characterized. Considering these challenges, recommendations for future observational and modeling research related to aerosol invigoration of deep convection are provided.

Observation of Blue Corona Discharges and Cloud Microphysics in the Top of Thunderstorm Cells in Cyclone Fani

AbstractBlue corona discharges are often observed at the top of thunderclouds. They are bursts of streamers, but the cloud conditions that enable them are not well known. Here we present observations by the Atmosphere‐Space Interactions Monitor (ASIM) of 92 discharges during its ∼1 min pass over tropical cyclone Fani in the Bay of Bengal from 20:10:55 to 20:12:05 UTC on 30 April 2019. The discharges were observed in convective cells forming in the rainbands of the cyclone where Convective Available Potential Energy reached ∼6,000 J kg−1. The Cloud‐Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite passed over one of the cells ∼12 min after ASIM from 20:23:58 to 20:24:14 UTC. It measured the cloud microphysics related to the discharges and indicated they occurred in a convection region with the cloud top overshooting for over 20 min. The updraft lifted ice particles to lower stratospheric altitudes and formed the gullwing‐shaped cirrus. The discharges are found at an average altitude of ∼16 km where the cloud environment contained ∼2 × 107 m−3 ice particles with ∼50 µm radius, resulting in a photon mean free path of ∼3 m. Around 20% of the blue corona discharges coincide with Narrow Bipolar Events indentified from the Earth Networks Total Lightning Network. Our observations suggest that the overshooting cloud top formed by deep convection and a surge in lightning activity facilitated conditions for the blue corona discharges. This work provides the first‐ever estimate of important microphysical parameters related to blue corona discharges based on data measurements, establishing a reference for future empirical and theoretical studies.

Overcoming computational challenges to realize meter- to submeter-scale resolution in cloud simulations using the super-droplet method

Abstract. A particle-based cloud model was developed for meter- to submeter-scale-resolution simulations of warm clouds. Simplified cloud microphysics schemes have already made meter-scale-resolution simulations feasible; however, such schemes are based on empirical assumptions, and hence they contain huge uncertainties. The super-droplet method (SDM) is a promising candidate for cloud microphysical process modeling and is a particle-based approach, making fewer assumptions for the droplet size distributions. However, meter-scale-resolution simulations using the SDM are not feasible even on existing high-end supercomputers because of high computational cost. In the present study, we overcame challenges to realize such simulations. The contributions of our work are as follows: (1) the uniform sampling method is not suitable when dealing with a large number of super-droplets (SDs). Hence, we developed a new initialization method for sampling SDs from a real droplet population. These SDs can be used for simulating spatial resolutions between meter and submeter scales. (2) We optimized the SDM algorithm to achieve high performance by reducing data movement and simplifying loop bodies using the concept of effective resolution. The optimized algorithms can be applied to a Fujitsu A64FX processor, and most of them are also effective on other many-core CPUs and possibly graphics processing units (GPUs). Warm-bubble experiments revealed that the throughput of particle calculations per second for the improved algorithms is 61.3 times faster than those for the original SDM. In the case of shallow cumulous, the simulation time when using the new SDM with 32–64 SDs per cell is shorter than that of a bin method with 32 bins and comparable to that of a two-moment bulk method. (3) Using the supercomputer Fugaku, we demonstrated that a numerical experiment with 2 m resolution and 128 SDs per cell covering 13 8242×3072 m3 domain is possible. The number of grid points and SDs are 104 and 442 times, respectively, those of the highest-resolution simulation performed so far. Our numerical model exhibited 98 % weak scaling for 36 864 nodes, accounting for 23 % of the total system. The simulation achieves 7.97 PFLOPS, 7.04 % of the peak ratio for overall performance, and a simulation time for SDM of 2.86×1013 particle ⋅ steps per second. Several challenges, such as incorporating mixed-phase processes, inclusion of terrain, and long-time integrations, remain, and our study will also contribute to solving them. The developed model enables us to study turbulence and microphysics processes over a wide range of scales using combinations of direct numerical simulation (DNS), laboratory experiments, and field studies. We believe that our approach advances the scientific understanding of clouds and contributes to reducing the uncertainties of weather simulation and climate projection.

YunMa: Enabling Spectral Retrievals of Exoplanetary Clouds

In this paper, we present YunMa, an exoplanet cloud simulation and retrieval package, which enables the study of cloud microphysics and radiative properties in exoplanetary atmospheres. YunMa simulates the vertical distribution and sizes of cloud particles and their corresponding scattering signature in transit spectra. We validated YunMa against results from the literature. When coupled to the TauREx 3 platform, an open Bayesian framework for spectral retrievals, YunMa enables the retrieval of the cloud properties and parameters from transit spectra of exoplanets. The sedimentation efficiency (f sed), which controls the cloud microphysics, is set as a free parameter in retrievals. We assess the retrieval performances of YunMa through 28 instances of a K2-18 b-like atmosphere with different fractions of H2/He and N2, and assuming water clouds. Our results show a substantial improvement in retrieval performances when using YunMa instead of a simple opaque cloud model and highlight the need to include cloud radiative transfer and microphysics to interpret the next-generation data for exoplanet atmospheres. This work also inspires instrumental development for future flagships by demonstrating retrieval performances with different data quality.

Cold Fog Amongst Complex Terrain

Abstract Cold fog forms via various thermodynamic, dynamic, and microphysical processes when the air temperature is less than 0°C. It occurs frequently during the cold season in the western United States yet is challenging to detect using standard observations and is very difficult to predict. The Cold Fog Amongst Complex Terrain (CFACT) project was conceived to investigate the life cycle of cold fog in mountain valleys. The overarching goals of the CFACT project are to 1) investigate the life cycle of cold-fog events over complex terrain with the latest observation technology, 2) improve microphysical parameterizations and visibility algorithms used in numerical weather prediction (NWP) models, and 3) develop data assimilation and analysis methods for current and next-generation (e.g., subkilometer scale) NWP models. The CFACT field campaign took place in Heber Valley, Utah, during January and February 2022, with support from NSF’s Lower Atmospheric Observing Facilities (managed by NCAR’s Earth Observing Laboratory), the University of Utah, and Ontario Technical University. A network of ground-based and aerial in situ instruments and remote sensing platforms were used to obtain comprehensive measurements of thermodynamic profiles, cloud microphysics, aerosol properties, and environmental dynamics. Nine intensive observation periods (IOPs) explored various mountainous weather and cold-fog conditions. Field observations, NWP forecasts, and large-eddy simulations provided unprecedented data sources to help understand the mechanisms associated with cold-fog weather and to identify and mitigate numerical model deficiencies in simulating winter weather over mountainous terrain. This article summarizes the CFACT field campaign, its observations, and challenges during the field campaign, including real-time fog prediction issues and future analysis.

NUMAC: Description of the Nested Unified Model With Aerosols and Chemistry, and Evaluation With KORUS‐AQ Data

AbstractWe describe and evaluate a system for regional modeling of atmospheric composition with the Met Office Unified Model (UM), suitable for climate, weather forecasting and air quality applications. In this system, named NUMAC (“Nested UM with Aerosols and Chemistry”), a global model provides boundary conditions for regional models nested within it, using the Met Office's Regional Nesting Suite for multi‐scale simulations. The regional models, which can run at convection‐permitting or cloud‐resolving scales, use the same code as the global model. The system includes double‐moment prognostic aerosol microphysics with interactive chemistry of sulfur species, ozone, NOx, and CO as in the UK Earth System Model. Double‐moment prognostic cloud microphysics is optional. To test NUMAC, we compare simulations to surface and aircraft measurements from NASA's Korea‐United States Air Quality campaign over South Korea. The performance of the regional model, which we run at 5 km resolution, is similar to the well‐evaluated global model when the regional and global models use the same emissions. Most species such as ozone, NOx, OH, or PM2.5 are simulated within a factor of 2 of observations most of the time, though they are biased low compared to monitors in polluted areas (observed surface dry PM2.5 averages 28 μgm−3 but we simulate 17 μgm−3). Meteorology and clouds are represented satisfactorily. With higher‐resolution emissions, many of the low model biases are reduced, but a tuning was required to keep NO concentrations realistic, indicating shortcomings in the chemistry scheme. We demonstrate the potential of NUMAC for studies of aerosol‐cloud interactions.

Multi-Layer Cloud Motion Vector Forecasting for Solar Energy Applications

Real-time forecasting of solar radiation posses several benefits and has huge potential for industrial applications. However, the intermittent nature of solar radiation makes it difficult to forecast accurately. Cloud cover is one of the major influencing factors of solar radiation. Thus, forecasting cloud motion effectively can help to improve the accuracy of short-term solar radiation forecasts. In this study, a novel Multi-Layer Cloud Motion Vector (referred as 3D-CMV) forecasting technique was introduced, which combined with the fast radiative transfer model (FRTM) produces forecasts up to 3 h ahead at 15 min intervals over 5km × 5km grids across Europe and North Africa. The cloud microphysics obtained from the Support to Nowcasting and Very Short Range Forecasting (SAFNWC) of the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) was used as input to the forecasting system. The results obtained improvements in forecasts as compared to the conventional cloud motion vector techniques, across all seasons and sky conditions. Comparisons against ground-based measurements from the Baseline Surface Radiation Network (BSRN) revealed an overall maximum percentage difference of less than 12%, bias under -20 Wm−2 and a root mean square error (RMSE) under 80 Wm−2. Performance evaluations of Multi-Layer Cloud Motion Vector has been performed against several state-of-the-art techniques and presented in this study. Short-term solar energy forecasting has an established market and rising demand. Accurate forecasts from Multi-Layer CMV hence pose a high potential for real world applications.

Influence of Atmospheric Non-Uniform Saturation on Extreme Hourly Precipitation Cloud Microphysical Processes in a Heavy Rainfall Case in Zhengzhou

Heavy rainfall not only affects urban infrastructure, it also impacts environmental changes, and which then influence the sustainability of development and ecology. Therefore, researching and forecasting heavy rainfall to prevent disaster-related damages is essential. A high-resolution numerical simulation was carried out for a heavy rainfall case in Zhengzhou, Henan Province, China, from 19–20 July 2021. The analysis of weather conditions revealed that the main cause of heavy rainfall in Zhengzhou was the supersaturation and condensation of water vapor, resulting from the invasion of dry and cold air from the upper and middle atmospheric layers. This weather condition is ideally suited for applying generalized potential temperature that is informed by the non-uniform saturation theory. Based on this, the new scheme revised the cloud microphysical scheme of the cloud water condensation parameterization process by substituting generalized potential temperature. The characteristics of the mesoscale environment and water condensates were comparatively analyzed between the original and the new scheme. Then, the quantitative mass budget and latent heat budget related to microphysical conversions were comparatively calculated over Zhengzhou. Furthermore, the possible two-scheme mechanisms through which the cloud microphysics processes affected the rainfall were investigated and discussed. It was found that: (1) The new scheme, which takes into account generalized potential temperature, produced precipitation fields more in line with observations and simulated stronger hourly precipitation compared to the original scheme. (2) The conversions of snow were the main source of microphysical processes that produced precipitation and released latent heat due to the dry and cold air invasion. (3) Given that the condensation of water vapor was hypothesized to occur at 70% relative humidity (RH) or above, rather than the original 100% RH, the new scheme simulated more supercooled water and ice-phase particles than the original scheme. This enhancement, in turn, intensified convective development owing to positive feedback within the cloud microphysics processes and cloud environment, ultimately leading to the simulation of more intense hourly precipitation.

On the Resolution Sensitivity of Equatorial Precipitation in a GFDL Global Atmospheric Model

AbstractWe performed a series of aquaplanet simulations at the horizontal resolution from 50 to 6 km with identical parameterization settings using the Geophysical Fluid Dynamics Laboratory's Atmosphere Model version 4 implemented with the two‐moment Morrison‐Gettelman cloud microphysics with prognostic precipitation (GFDL AM4‐MG2). At the finer resolution, the global mean resolved‐scale precipitation increases and that from cumulus parameterization decreases. The model also simulates less/thinner clouds over the low latitudes and more/thicker clouds over the high latitudes as the resolution increases. The precipitation over the deep tropics is investigated in detail. We find little resolution sensitivity in the daily mean precipitation extremes. Changes of the equatorial resolved precipitation with resolution cannot be fully explained by the resolution dependence in the vertical velocity amplitude. We report a robust sensitivity in the convective organization over the deep tropics to the model resolution. In simulations of finer resolution, the localized convection is suppressed, and the organized convective system associated with large‐scale circulations becomes more prominent.

The Benefits and Challenges of Downscaling a Global Reanalysis With Doubly‐Periodic Large‐Eddy Simulations

AbstractGlobal reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the “Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics,” or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions.

Rainy Days in the Arctic

Abstract The Arctic is warming faster than anywhere on Earth, and with these warming temperatures, there is likely to be more precipitation falling as rain. This precipitation phase change will have profound impacts on the hydrologic cycle, energy balance, and snow and sea ice mass budgets. Here, we examine the number of rainfall days in the Arctic from three reanalyses, ERA-Interim, ERA5, and MERRA-2, over 1980–2016. We show that the number of rainfall days has increased over this period, predominantly in the autumn and in the North Atlantic and peripheral seas, and the length of the rain season has increased in all reanalyses. This is positively correlated to the number of days with above freezing air temperatures and a lengthening of the warm season. ERA-Interim produces significantly more rainfall days than other reanalyses and CloudSat observations, as well as significantly more rainfall when temperatures are below freezing. Investigation into the cloud microphysics schemes revealed that the scheme employed by ERA-Interim allowed for mixed-phase clouds to form rain at temperatures below freezing following a temperature-dependent phase partitioning function between 250 and 273 K. This simple diagnostic treatment erroneously overestimates rain at temperatures below 273 K and produces unrealistic rainfall compared to ERA5 and MERRA-2. This work highlights the importance of having accurate physics and improving microphysical schemes in models for simulating precipitation in the Arctic and the caution that is warranted for interpreting reanalysis trends.

Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China

Cloud Microphysical Processes and Atmospheric Water Budget during the 20 July 2021 Extreme Precipitation Event in Zhengzhou, China

Air quality simulation with WRF-Chem over southeastern Brazil, part I: Model description and evaluation using ground-based and satellite data

A comprehensive Weather Research and Forecasting with Chemistry (WRF-Chem) model evaluation is conducted using ground-based and total column observational data from air quality stations and satellite retrievals. Fine particles (PM2.5; ≤ 2.5 μm in aerodynamic diameter), nitrogen oxides (NOx, NO + NO2), carbon monoxide (CO), tropospheric ozone (O3) concentrations and AOD values over southeastern Brazil were analyzed to assess the model's capability in reproducing atmospheric observation. The model simulations were performed over simple one domain at grid resolution of 10 km over southeastern Brazil. This spatial resolution was chosen due to a previous evaluation between five MODIS AOD products with AERONET estimates, resulting in Dark Target at 10 km of spatial resolution the best product to represent the AOD values over our study domain. Model input emissions comprise vehicular emissions derived from a bottom-up emission model, as well as on-line calculations of biogenic and fire emission rates. Given that the atmospheric state affects air pollution dispersion, a model evaluation on the meteorological conditions was carried out to better evaluate the model performance in reproducing the pollutant concentrations. Good agreement between model simulations and observations for air temperature and relative humidity at 2 m height was found, with correlation coefficients higher than 0.85 in most periods. Expected benchmarks for wind speed and direction at 10 m height were also found in this analysis, though with larger uncertainties. Underestimation occurred for daily accumulated precipitation due to the limitations of the cloud microphysics scheme or cumulus parameterization. Model simulations of PM2.5, NOx, CO and O3 agreed well with ground-based observations in terms of temporal variations and trends, with model-observation discrepancies due to uncertainties in the emission inventories. O3 was the better simulated pollutant in terms of temporal variability, with the characteristic large and small amplitudes observed over urban and rural areas being well represented by the model. High O3 concentrations were observed at the Botucatu station, due to transport of pollutants generated in the Metropolitan Area of São Paulo, and were also represented by the model, indicating the need of more active air quality monitoring stations over inland regions in southeastern Brazil. Moderate and high correlation coefficients (ranging 0.46–0.81) were found for tropospheric NO2 VCD and CO column, and AOD at 550 nm due to uncertainties in the emission inventories and aerosol model simplifications. Both the model and satellite captured higher values in similar regions over our study domain. This work represents a first effort, in southeastern Brazil, that combines numerical modeling, remote sensing and ground-based stations to analyze and understand the impact exerted by the emissions of urban pollution over surrounding areas. A more in-depth analysis of the impact of emissions transport to inland regions from urban areas in southeastern Brazil will be discussed in the second part of this work.