Microphysics Scheme Research Articles

Impact of host climate model on contrail cirrus effective radiative forcing estimates

Abstract. Estimates of aviation effective radiative forcing (ERF) indicate that contrail cirrus is currently its largest contributor, although with a substantial associated uncertainty of ∼ 70 %. Here, we implement the contrail parameterisation developed for the Community Atmosphere Model (CAM) in the UK Met Office Unified Model (UM), allowing us to compare, for the first time, the impact of key features of the host climate model on contrail cirrus ERF. We find that differences in background humidity between the models result in the UM-simulated contrail fractions being 2 to 3 times larger than in CAM. Additionally, the models show contrasting responses in overall global cloud fraction, with contrails increasing the total cloud fraction in the UM and decreasing it in CAM. Differences in the complexity of the cloud microphysics schemes lead to significant differences in simulated changes to cloud ice water content due to aviation. After compensating for the unrealistically low contrail optical depth in the UM, we estimate the 2018 contrail cirrus ERF to be 40.8 mW m−2 in the UM, compared to 60.1 mW m−2 in CAM. These values highlight the substantial uncertainty in contrail cirrus ERF due to differences in microphysics and radiation schemes between the two models. We also find a factor-of-8 uncertainty in contrail cirrus ERF due to existing uncertainty in contrail cirrus optical depth. Future research should focus on better representing microphysical and radiative contrail characteristics in climate models and on improved observational constraints.

Evaluating the Performance of Land Surface Models and Microphysics Schemes on Simulation of an Extreme Rainfall Event in Tanzania Using the Weather Research and Forecasting Model

Evaluating the Performance of Land Surface Models and Microphysics Schemes on Simulation of an Extreme Rainfall Event in Tanzania Using the Weather Research and Forecasting Model

Characteristics of extreme rainfall from warm clouds associated with a mesoscale convective system: sensitivity of different microphysical and cumulus parameterization schemes

Characteristics of extreme rainfall from warm clouds associated with a mesoscale convective system: sensitivity of different microphysical and cumulus parameterization schemes

Structural Difference on the Response of Microphysical and Precipitation Processes to Aerosol Perturbation in a Quasi‐Stationary Southwest Vortex System

AbstractUsing the WRF coupled with Thompson aerosol‐aware microphysics scheme, a quasi‐stationary southwest vortex (SWV) precipitation process occurring in the Sichuan Basin is simulated. Based on three experiments with low aerosol concentration background (“Low”), medium aerosol concentration background (“Medium”), and high aerosol concentration background (“High”), the effects of hydrophilic aerosol serving as Cloud Condensation Nuclei (CCN) on microphysical and precipitation processes are investigated. Results indicate the impact of hydrophilic aerosol on clouds and precipitation structure exhibits structural difference. Aerosol increases from “Low” to “Medium”, precipitation in middle circle of SWV decreases, precipitation in outer circle of SWV increases. Because the outer circle of SWV with strong convection competes with the middle circle of SWV for liquid droplets, leading to a reduction in ice‐phase particles in middle circle of SWV. In contrast, more ice‐phase particles are formed in outer circle of SWV. The increased ice‐phase particles melt into raindrops, leading to an increase in precipitation. Aerosol increases from “Medium” to “High”, precipitation in middle circle of SWV increases, precipitation in outer circle of SWV decreases. The size of liquid droplets formed in outer circle of SWV further becomes smaller. This is not conducive to the formation of ice‐phase particles, leading to weaker convection, which makes it becomes less competitive. A large number of small cloud droplets in middle circle of SWV are transported above the freezing layer and participate in the formation of ice‐phase particles. The released latent heat promotes convective development, resulting in more precipitation.

Numerical simulation of aerosol concentration effects on cloud droplet size spectrum evolutions of warm stratiform clouds in Jiangxi, China

Abstract. Changes in aerosol amount and size distribution significantly impact cloud droplet size distribution, as aerosols act as cloud condensation nuclei (CCNs) and influence the relative dispersion (ε) of cloud droplet spectra. Relative dispersion plays a key role in parameterizing cloud processes in general circulation models (GCMs) and microphysical schemes, affecting precipitation estimates and climate predictions. However, the effects of varying aerosol modes on cloud microphysics remain debated, depending on thermodynamic conditions and cloud type. This study simulates a warm stratiform cloud in Jiangxi, China, using the Weather Research and Forecasting (WRF) Spectra–Bin Microphysics scheme (SBM-FAST) from 18:00 on 24 December 2014 to 06:00 on 25 December 2014 (UTC). Satellite and aircraft observations were used to validate the simulation, showing good agreement in cloud structure. Sensitivity experiments were conducted by increasing nucleation, accumulation, and coarse-mode aerosols 5-fold and by reducing the total aerosol concentration to 1/5 of the control. Results show that higher aerosol concentrations enhance cloud formation and broaden droplet spectra, while lower concentrations suppress cloud development. Accumulation-mode aerosols increase small-droplet concentrations, while nucleation- and coarse-mode aerosols favor larger droplets. The correlation between ε and volume-weighted radius (Rv) shifts from positive to negative as Rv increases. This transition is driven by cloud droplet collision–coalescence, condensation, and activation. Increased accumulation-mode aerosol concentrations shift the ε–Rv correlation from negative to positive in the Rv range of 4.5–8 µm, while reduced aerosol concentrations strengthen the negative correlation. Regardless of different coalescence intensities, ε converges with the increase in number concentration of cloud droplets (Nc).

The Impact of Cumulus Clouds and CCN Regeneration on Aerosol Vertical Distribution and Size

Abstract This study employs a high-resolution (10m) System for Atmospheric Modeling (SAM) coupled with the Spectral Bin Microphysical (SBM) scheme to thoroughly investigate the processes governing the evolution of aerosol properties within and outside a shallow cumulus cloud. The model encompasses the complete life cycle of cloud droplets, starting from their formation through their evolution until their complete evaporation or sedimentation to the ground. Additionally, the model tracks the aerosols’ evolution both within droplets and in the air. Aerosols are transported within the droplets, grow by droplet coalescence, and are released into the atmosphere after droplet evaporation (regeneration process). The aerosol concentration increases by droplet evaporation and decreases along with falling drops. So, the effects of clouds on the surrounding aerosols depend on the microphysical and dynamic processes, which in turn depend on the amount of background aerosols; here, we compare clean and polluted conditions. It is shown that the regeneration process is highly important and that shallow trade cumulus clouds significantly impact the vertical profile of aerosol concentration in the lower troposphere, as well as their size distribution, and can serve as a source of large cloud condensation nuclei. Furthermore, it is shown that both precipitating and non-precipitating boundary layer clouds contribute to a substantial increase in aerosol concentration within the inversion layer due to intense evaporation.

Fragmentation in Collisions of Snow with Graupel/Hail: New Formulation from Field Observations

Abstract Secondary ice production (SIP) has been attributed to the generation of most ice particles observed in precipitating clouds with cloud tops warmer than −36°C, from various aircraft- and ground-based field observations across the globe. One of the known SIP mechanisms is fragmentation during collisions among ice particles. It has been studied with our theoretical formulation, which has been applied in microphysical schemes of atmospheric models in a few studies. These have predicted an extensive impact on cloud glaciation and radiative properties. However, there has been a lack of experimental field studies, especially involving naturally falling snowflakes, to better understand this particular mechanism of SIP. This study reports the first field measurements with modern technology for fragmentation during collisions between naturally falling snowflakes and graupel/hail particles. This was observed with an innovatively designed portable chamber that was deployed outdoors in northern Sweden. Applying the observations from this field-based study, we optimized the existing formulation for predicting numbers of fragments from collisions of snow with graupel/hail. The observations show the average numbers of fragments per collision for dendritic (3–12 mm) and nondendritic (1–3 mm) snow were about 12 and 1, respectively. This represents a boost of predicted fragment numbers relative to our original formulation published in 2017. The updated formulation for breakup in ice–ice collisions can be implemented in the microphysical schemes of atmospheric models.

The Dual Nature of Entrainment-Mixing Signatures Revealed through Large-Eddy Simulations of a Convection-Cloud Chamber

Abstract Entrainment of subsaturated air into a cloud can influence its optical and microphysical properties in various ways, depending on the droplet evaporation and turbulent mixing time scales. Previous experiments in the Pi convection-cloud chamber have revealed that, given a fixed entrained air property, the mixing of entrained subsaturated air results in complete evaporation of some cloud droplets, with the rest remaining unchanged. This is a signature of inhomogeneous mixing. While comparing the results of entrainment with varying air properties, the mixing signature appears as if the subsaturated air is well mixed with the cloud to evenly reduce the droplets’ size. In other words, taken together, the experiments appear to have the signature of homogeneous mixing. To explore these results in a greater depth, we conduct large-eddy simulations combined with a bin microphysics scheme. Our results reproduce the similar signatures of inhomogeneous and homogeneous mixing, implying that LES can resolve the inhomogeneous mixing when the grid spacing is smaller than the entrained air parcel. Additionally, we observe that increasing the aerosol injection rate enhances the signature of inhomogeneous mixing, while coarser grid spacing diminishes it. Finally, the change in wall fluxes in response to various entrained air properties confirms that the homogeneous signature seen in the analysis of an ensemble of simulations is the result of various equilibrium states. This further strengthens the suggestion that the homogeneous mixing signature found in aircraft observations near the cloud top may result from combining entrainment events of different intensities, possibly caused by various-sized eddies. Significance Statement Large-eddy simulation and size-resolved microphysics can resolve time scales for turbulent mixing and evaporation and, therefore, are well suited for reproducing, extending, and interpreting the entrainment experiment in the Pi convection-cloud chamber. Our simulation results confirm (i) the inhomogeneous mixing signature for an individual entrainment event and (ii) the appearance of homogeneous mixing in an ensemble of entrainment episodes. Furthermore, we demonstrate that the inhomogeneous mixing signature is more pronounced in a polluted cloud, but coarser grid spacing in simulations may compromise the accuracy of this signature. Last, the homogeneous mixing signature results from various equilibrium states established for different entrainment intensities and adjusted wall fluxes, which are challenging to measure experimentally but can be easily analyzed in the simulations.

Effects of the Species Number of Hydrometeors on the Rapid Intensification of Super Typhoon Mujigae (2015)

Super Typhoon Mujigae (2015) was simulated using the WRF-ARW model version 4.1 with the WSM3, WSM5, WSM6, and WSM7 microphysics schemes, which include 3, 5, 6, and 7 hydrometeor classes, respectively. This study investigated the species number of hydrometeors (SNHs) from simple to complex on the rapid intensification (RI) of a tropical cyclone (TC). SNHs significantly affected the distribution of hydrometeors, microphysical conversion processes (MCPs), latent heat budget, and the interaction between thermal and dynamic processes, thereby influencing the RI. Different SNHs resulted in varied MCPs and a latent heat budget. The WSM3 and WSM5 schemes share the same top three dominating MCPs: condensation of cloud water (COND), accretion of cloud water by rain (RACW), and evaporation of rain (REVP). COND, accretion of cloud water by graupel (GACR), and RACW contributed to the WSM6 scheme. The WSM7 scheme included hail, with contributions from the instantaneous melting of snow, graupel, and COND, respectively. The dominating latent cooling processes were identical, while in different orders, which were evaporation of rain (REVP), sublimation of snow (SSUB), and evaporation of cloud water (CEVP) in the WSM3 and WSM5 schemes; while CEVP, REVP, and SSUB were in the WSM6 and WSM7. The interaction between thermal and dynamic processes was ultimately responsible for the RI. The WSM6 scheme presented an excellent latent heating rate, warm-core structure, and secondary circulation, which enhanced convection and absolute angular momentum transportation, and further indicating RI. The results highlighted the importance of an adequate complexity microphysics scheme to better reproduce the RI.

A Numerical Study on Cloud Structure of Typical Summer Precipitation Process over Liupan Mountain Area

Using Weather Research and Forecasting model (WRF), four microphysical schemes (Lin, Goddard, WSM6 and Thompson) were applied for precipitation simulations over southern Ningxia on July 21st, 2024. The simulated results are used to analyze the impact of different microphysical schemes on summertime precipitation processes. The sensitivity experiments show the precipitation process simulated by WSM6 and Thompson schemes are closer to observed precipitation than Lin and Goddard schemes in Southern Ningxia mountainous areas. The evolution characteristics of the dynamic field, water vapor field, and microphysical structures of cloud structures are analyzed. In vertical direction, the cloud system in mountainous areas generally displays a structure of "catalysis-supply". The structure of water condensation in each layer of cloud is different, leading to differences in the contribution of various microphysical processes to precipitation. The super-cooled cloud water is the main source for rain water production. When cloud system grows upward, the abundant cloud water layer simultaneously enhances the microphysical processes within clouds. On the windward slope (eastern part) of the mountain, deep warm cloud layer will contribute to the development of warm cloud precipitation process, which leads to enhanced precipitation under the combined action of cold and warm clouds.

A Numerical Simulation of Convective Systems in Southeast China: A Comparison of Microphysical Schemes and Sensitivity Experiments on Raindrop Break and Evaporation

This study employed version 4.2.2 of the Weather Research and Forecasting (WRF) model for this simulation and applied two microphysics schemes, the Thompson scheme (THOM) and Milbrandt–Yau scheme (MY)—which are widely used in convective simulations—to simulate a mesoscale severe convective precipitation event that occurred in southeastern China on 8 May 2017. The simulations were then compared with dual-polarization radar observations using a radar simulator. It was found that THOM produced vertical structures of radar reflectivity (ZH) closer to radar observations and accumulated precipitation more consistent with ground-based observations. However, both schemes overestimated specific differential phase (KDP) and differential reflectivity (ZDR) below the 0 °C level. Further analysis indicated that THOM produced more rain with larger raindrop sizes below the 0 °C level. Due to the close connection between raindrop breakup, evaporation rate, and raindrop size, sensitivity experiments on the breakup threshold (Db) and the evaporation efficiency (EE) of the THOM scheme were carried out. It was found that adjusting Db significantly changed the simulated raindrop size distribution and had a certain impact on the strength of cold pool; whereas modifying EE not only significantly changed the intensity and scope of the cold pool, but also had great effect on the raindrop size distribution. At the same time, comparison with dual-polarization radar observations indicated that reducing the Db can improve the model’s simulation of polarimetric radar variables such as ZDR. This paper specifically analyzes a severe convective precipitation event in the Guangdong region under weak synoptic conditions and a humid climate. It demonstrates the feasibility of a method based on polarimetric radar data that modifies Db of THOM to achieve better consistency between simulations and observations in southeast China. Since the microphysical processes of different Mesoscale Convective Systems (MCSs) vary, the generalizability of this study needs to be validated through more cases and regions in the future.

The Direct Assimilation of Radar Reflectivity Data with a Two-Moment Microphysics Scheme for a Landfalling Typhoon in an OSSE Framework

Despite the well-known importance of radar data assimilation, there are limited studies on landfalling typhoons in terms of directly assimilating radar reflectivity data, especially using a reflectivity operator based on double-moment microphysics. In this study, radar reflectivity data assimilation experiments are conducted with an ensemble Kalman filter (EnKF), using simulated observations in an Observing System Simulation Experiment (OSSE) framework for the landfalling typhoon In-Fa. With an OSSE, it is convenient to analyze the impact of assimilation of radar reflectivity on analysis and forecast for various state variables, especially for hydrometeors. Our results show that the direct assimilation of radar reflectivity with EnKF does not introduce non-physical hydrometeors and is able to adjust well, not only to hydrometers, but also to some large-scale variables which are not directly related to reflectivity, especially in terms of temperature and vertical velocity. Though the most notable reduction in the Root Mean Square Errors (RMSEs) is observed through mixing the ratio of rainwater and snow, the analysis of other variables is also significantly improved with the accumulation of assimilation cycles. The correlation analysis reveals the strongest correlation between radar reflectivity data and hydrometeor-related variables as well as the correlation with certain large-scale variables, indicating that these cross-variables are updated well through the reliable multivariate ensemble covariance in the EnKF. As a result, an obvious improvement in typhoon intensity and precipitation forecast is obtained in the data assimilation experiment. The impact of assimilation on radar reflectivity can last for up to 15–16 h.

Optimal Configuration of Physical Process Parameterization Scheme Combination for Simulating Meteorological Variables in Weather Research and Forecasting Model: Based on Orthogonal Experimental Design and Comprehensive Evaluation Method

The weather research and forecasting (WRF) model is frequently used to investigate the meteorological field around nuclear installations. The configuration of physical process parameterization schemes in the WRF model has a significant impact on the accuracy of the simulation results. Consequently, carrying out a pre-experiment to quickly obtain the optimal combination of parameterization schemes is essential before conducting meteorological parameter research. To obtain the optimal combination of physical process parameterization schemes from the planetary boundary layer (PBL), land surface (LSF), microphysical (MP), long-wave (LW), and short-wave (SW) radiation processes of the WRF model for simulating the near-surface meteorological variables near a nuclear power plant in Sanshan Town, Fuqing City, Fujian Province, China on 4 June 2019 were observed. Orthogonal experimental design (OED), a comprehensive evaluation method based on the CRiteria Import Through Intercriteria Correlation (CRITIC) weight analysis, and comprehensive balance method were employed for the first time to conduct the research. The sensitivity of meteorological variables to physical processes was first discussed. The findings revealed that the PBL scheme configuration had a profound impact on simulating wind fields. Furthermore, the LSF scheme configuration had a significant influence on simulating near-surface temperature and relative humidity, which was much greater than that of other physical processes. In addition, the choice of the radiation scheme had a significant impact on how the temperature was distributed close to the ground and how the wind field was simulated. Furthermore, the configuration of the MP scheme was found to exert a certain influence on the simulation of relative humidity; however, it demonstrated a weak influence on other meteorological variables. Secondly, The MYNN3 scheme for PBL process, the NoahMP scheme for LSF process, the WSM5 scheme for MP process, the RRTMG scheme for LW process, and the Dudhia scheme for SW process are found to be the comprehensive optimal physical process parameterization scheme combination for simulating meteorological variables in the research area selected in this study. As evident from the findings, the use of the OED method to obtain the combinations of the optimal physical process parameterization scheme could successfully reproduce the wind field, temperature, and relative humidity in the current study. Thus, this method appears to be highly reliable and effective for use in the WRF models to explore the optimal combinations of the physical process parameterization scheme, which could provide theoretical support to quickly analyzing accurate meteorological field data for longer periods and contribute to deeply investigating the migration and diffusion behavior of airborne pollutants in the atmosphere.

The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators

Abstract. Supercooled liquid clouds are common at higher latitudes (especially over the Southern Ocean) and are critical for constraining climate projections. We take advantage of the Macquarie Island Cloud and Radiation Experiment (MICRE) to perform an analysis of observed and simulated cloud processes over the Southern Ocean in a region and season dominated by supercooled liquid clouds. Using a single-column version of the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), we compare two different cloud microphysical schemes to ground-based observations of cloud, precipitation, and radiation over a 2.5-month period (1 January–17 March 2017). Both schemes are able to reproduce aspects of the cloud and radiation observations during MICRE to within the uncertainty of the data when the thermodynamic profile is prescribed with relaxation. There are differences in water mass and representation of reflectivity between the schemes. A sensitivity study of the cloud microphysics schemes, one a bulk one-moment scheme and the other a two-moment scheme with prediction of mass and number, indicates that several key processes create differences between the schemes. Surface radiative fluxes and total water path are highly sensitive to the formation and fall speed of precipitation. The prediction of hydrometeor number with the two-moment scheme yields a better comparison with observed reflectivity and radiative fluxes, despite predicting higher liquid water contents than observed. With the two-moment scheme, we are also able to test the sensitivity of the results to the input of liquid cloud condensation nuclei (CCN) and ice nuclei (IN). The cloud properties and resulting radiative effects are found to be sensitive to the CCN and IN concentrations. More CCN and IN increase liquid and ice water paths, respectively. Thus, both the dynamic environment and aerosols, integrated through the cloud microphysics, are important for properly representing Southern Ocean cloud radiative effects.

Investigating secondary ice production in a deep convective cloud with a 3D bin microphysics model: Part I - Sensitivity study of microphysical processes representations

Secondary ice production (SIP) is a crucial phenomenon for explaining the formation of ice crystal clouds, especially when addressing the discrepancies between observed ice crystal number concentrations and ice nucleating particles (INPs). In this study, we investigate parameterizations of three SIP processes (Hallett-Mossop, fragmentation of freezing drops, and fragmentation due to ice–ice collision) by simulating a deep convective cloud observed during the HAIC/HIWC campaign with the 3D bin microphysics scheme DESCAM (DEtailed SCAvening and Microphysics model). The simulated mean cloud properties, including particle size distributions and ice crystal number concentration are compared with in situ probe observations obtained during the campaign. Simulation excluding SIP shows a large underestimation of small ice crystals (< 1 mm diameter) for temperatures warmer than ‐30∘C. In our results, incorporating Hallett-Mossop and fragmentation due to ice–ice collision processes leads to ice crystal number concentrations close to observed values, thereby reducing discrepancies by two orders of magnitude. Our simulations also indicates that fragmentation of freezing drops affect minimally the properties of the cloud at its mature stage. Furthermore, we investigate the impact of fragments sizes resulting from SIP processes and show that the size of fragments generated from fragmentation due to ice–ice collision significantly influences the shape of ice particle size distribution. Employing various parameterizations of the ice crystal sticking efficiency reveals a notable impact on cloud properties. This study shows that SIP mechanisms are important and have to be considered for cold and mixed-phase clouds. However their parameterization lack reliability, highlighting the need for better quantifying these mechanisms. The companion paper, investigates the effects of SIP processes on the formation and the evolution of the deep convective system.

A fully coupled solid-particle microphysics scheme for stratospheric aerosol injections within the aerosol–chemistry–climate model SOCOL-AERv2

Abstract. Recent studies have suggested that injection of solid particles such as alumina and calcite particles for stratospheric aerosol injection (SAI) instead of sulfur-based injections could reduce some of the adverse side effects of SAI such as ozone depletion and stratospheric heating. Here, we present a version of the global aerosol–chemistry–climate model SOCOL-AERv2 and the Earth system model (ESM) SOCOLv4 which incorporate a solid-particle microphysics scheme for assessment of SAI of solid particles. Microphysical interactions of the solid particle with the stratospheric sulfur cycle were interactively coupled to the heterogeneous chemistry scheme and the radiative transfer code (RTC) for the first time within an ESM. Therefore, the model allows simulation of heterogeneous chemistry at the particle surface as well as feedbacks between microphysics, chemistry, radiation and climate. We show that sulfur-based SAI results in a doubling of the stratospheric aerosol burden compared to the same mass injection rate of calcite and alumina particles with a radius of 240 nm. Most of the sulfuric acid aerosol mass resulting from SO2 injection does not need to be lifted to the stratosphere but is formed after in situ oxidation and subsequent water uptake in the stratosphere. Therefore, to achieve the same radiative forcing, larger injection rates are needed for calcite and alumina particle injection than for sulfur-based SAI. The stratospheric sulfur cycle would be significantly perturbed, with a reduction in stratospheric sulfuric acid burden by 53 %, when injecting 5 Mt yr−1 (megatons per year) of alumina or calcite particles of 240 nm radius. We show that alumina particles will acquire a sulfuric acid coating equivalent to about 10 nm thickness if the sulfuric acid is equally distributed over the whole available particle surface area in the lower stratosphere. However, due to the steep contact angle of sulfuric acid on alumina particles, the sulfuric acid coating would likely not cover the entire alumina surface, which would result in available surface for heterogeneous reactions other than the ones on sulfuric acid. When applying realistic uptake coefficients of 1.0, 10−5 and 10−4 for H2SO4, HCl and HNO3, respectively, the same scenario with injections of calcite particles results in 94 % of the particle mass remaining in the form of CaCO3. This likely keeps the optical properties of the calcite particles intact but could significantly alter the heterogeneous reactions occurring on the particle surfaces. The major process uncertainties of solid-particle SAI are (1) the solid-particle microphysics in the injection plume and degree of agglomeration of solid particles on the sub-ESM grid scale, (2) the scattering properties of the resulting agglomerates, (3) heterogeneous chemistry on the particle surface, and (4) aerosol–cloud interactions. These uncertainties can only be addressed with extensive, coordinated experimental and modelling research efforts. The model presented in this work offers a useful tool for sensitivity studies and incorporating new experimental results on SAI of solid particles.

The Cycle 46 Configuration of the HARMONIE-AROME Forecast Model

The aim of this technical note is to describe the Cycle 46 reference configuration of the HARMONIE-AROME convection-permitting numerical weather prediction model. HARMONIE-AROME is one of the canonical system configurations that is developed, maintained, and validated in the ACCORD consortium, a collaboration of 26 countries in Europe and northern Africa on short-range mesoscale numerical weather prediction. This technical note describes updates to the physical parametrizations, both upper-air and surface, configuration choices such as lateral boundary conditions, model levels, horizontal resolution, model time step, and databases associated with the model, such as for physiography and aerosols. Much of the physics developments are related to improving the representation of clouds in the model, including developments in the turbulence, shallow convection, and statistical cloud scheme, as well as changes in radiation and cloud microphysics concerning cloud droplet number concentration and longwave cloud liquid optical properties. Near real-time aerosols and the ICE-T microphysics scheme, which improves the representation of supercooled liquid, and a wind farm parametrization have been added as options. Surface-wise, one of the main advances is the implementation of the lake model FLake. An outlook on upcoming developments is also included.

Cold-Frontal Rainbands over the United Kingdom: Sensitivity of Precipitation Processes to Microphysics Schemes in WRF Simulations

Abstract A narrow cold-frontal rainband (NCFR) and wide cold-frontal rainband (WCFR) over the United Kingdom on 24 January 2018 are selected to evaluate the sensitivity of cold-season precipitation to three bulk cloud microphysics schemes in the Weather Research and Forecasting (WRF) Model. The three simulations tend to overpredict the intensity and the areal coverage of NCFRs but underpredict those of WCFRs against the Met Office radar imagery. Nonetheless, the WRF double-moment 6-class (WDM6) simulation produces the most realistic NCFR and WCFR. More specifically, the intensity of the NCFR in the WDM6 simulation is overpredicted in the developing stage and underpredicted in the dissipating stage when compared to the Thompson and Morrison simulations. This phenomenon is mainly attributed to the rain mixing ratio at 1 km. The more intense and larger area of the WCFR in the WDM6 simulation is associated with more low-level snow, graupel, and rain than the other two simulations. In the WDM6 simulation, the larger low-level snow mixing ratios are due to the higher rates of aggregation between cloud ice and snow, whereas the larger rain mixing ratio is due to higher melting rates. Thus, differences in low-level ice-phase processes between microphysics schemes are large, strongly influencing the intensity of WCFRs, but the differences in warm-rain processes are smaller. Additionally, the small size of raindrops in the WDM6 simulation leads to wider and more intense WCFR as these raindrops are preferentially sent rearward relative to the cold front. Significance Statement Models are useful tools to predict weather but have errors in predicting different weather types. In the United Kingdom, precipitation is often predicted to be too strong at cold fronts and too weak behind the fronts compared to radar observations. Choosing different options for how precipitation is represented in one model produced different precipitation forecasts, with WDM6 being the best. One reason why WDM6 was the best was because it produced more and smaller raindrops, which would be transported behind the front, and it had higher melting rates at low levels, resulting in more precipitation behind the fronts than other options. Our results help identify why different options produce different forecasts, leading to possible future improvements in these options.

Modeling Nonspherical Hailstones

Abstract Hail research and forecasting models necessarily involve explicit or implicit—and uncertain—physical assumptions regarding hailstones’ shape, tumbling behavior, fall speed, and thermal energy transfer. Whereas most models assume spherical hailstones, we relax this assumption by using hailstone shape data from field observations to establish empirical size–shape relationships with reasonable degrees of randomness considering hailstones’ natural shape variability, capturing the observed distribution of triaxial ellipsoidal shapes. We also incorporate explicit, random tumbling of individual hailstones during their growth to simulate their free-falling behavior and the resultant changes in cross-sectional area (which affects growth by hydrometeor collection). These physical attributes are incorporated in calculating hailstones’ fall speeds, using either empirical relationships or analytical relationships based on each hailstone’s Best and Reynolds numbers. Options for drag coefficient modification are added to emulate hailstones’ rough surfaces (lobes), which then modifies their thermal energy and vapor exchange with the environment. We investigate how applying these physical assumptions about nonspherical hail to the Penn State hail growth trajectory model, coupled with Cloud Model 1 supercell simulations, impacts hail production and examine the reasons behind the resulting variability in hail statistics. The choice of hailstone size–mass relation and fall speed scheme have the strongest influence on hail sizes. Using nonspherical, tumbling hailstones reduces the number of large hailstones produced. Applying shape-specific thermal energy transfer coefficients subtly increases sizes; the effects of lobes vary depending on the fall speed scheme used. These physical assumptions, although adding complexity to modeling, can be parameterized efficiently and potentially used in microphysics schemes. Significance Statement In numerical modeling of hailstorms, we usually consider hailstones to be spherical to simplify calculations, but in nature, hailstones generally are not spheres and can be rather lumpy and have spikes. The purpose of this study is to examine how the model result would change when nonspherical hailstone shape is implemented. We examine the relationship between hailstone shape and physical processes during hail growth in effort to explain why these changes occur and offer insights on how nonspherical hailstone shape may be parameterized in bulk microphysics schemes.

Investigating the Impact of Multiphysics on Modeled Planetary Boundary Layer Height Estimates during the PECAN Field Campaign

Abstract Accurate representation of the planetary boundary layer (PBL) in numerical weather prediction is crucial to air quality, weather forecasting, and climate change research and operations. Here, we evaluate the estimates of PBL height (PBLH) from a set of convective-permitting simulations conducted using the Weather Research and Forecasting (WRF) Model during the Plains Elevated Convection at Night (PECAN) campaign (from June to mid-July 2015). Our analysis aims to quantify the variability in PBLH, along with its associated surface variables and atmospheric profiles, to gauge the influence of model physics on the accuracy of simulated PBL properties. Specifically, we conducted twenty-four 45-day retrospective simulations encompassing different combinations of three PBL and two microphysics schemes, two initial and boundary condition (ICBC) datasets, and two model vertical grid spacings. We compare these simulations with measurements from surface sites and radiosonde launches across four sites in the southern Great Plains during PECAN. Our findings indicate that deriving PBLH from modeled atmospheric profiles yields a narrower spread (200–300 m) compared to PBLH calculated from the model’s PBL scheme (400–500 m) relative to radiosonde-derived PBLH under fair weather conditions. The choice of PBL scheme and ICBCs exerts the most significant impact (by up to 400 m) on the spread of modeled PBLH and associated atmospheric profiles, primarily influencing the representation of surface heating, transport, and mixing processes in the model. The model has difficulty reproducing the correct thermodynamic profile under cloud-intense conditions. These results underscore the benefit of using the physically consistent approach in retrieving, evaluating, and assimilating PBLH estimates, as well as the utility of multiphysics to better address model uncertainties. Significance Statement Studies on weather forecast models typically involve running the model multiple times and adjusting model inputs slightly each time to produce a range of predicted variables. This range is crucial for evaluating forecast probabilities and integrating observations into the model. We found that using different model physics schemes can result in an equal or greater spread for predicted variables (here, we focus on boundary layer height and related variables), compared to input tweaks alone. Additionally, a particular scheme can introduce biases. These findings underscore the importance of employing multiple physics schemes in the model, as they widen the coverage (potentially doubling) of outputs, and thus better address forecast uncertainties.