Rain Size Research Articles

A Simple Model for the Evaporation of Hydrometeors and Their Isotopes.

Cloud condensation and hydrometeor evaporation fractionate stable isotopes of water, enriching liquid with heavy isotopes; whereupon updrafts, downdrafts, and rain vertically redistribute water and its isotopes in the lower troposphere. These vertical water fluxes through the marine boundary layer affect low cloud climate feedback and, combined with isotope fractionation, are hypothesized to explain the depletion of tropical precipitation at higher precipitation rates known as the "amount effect." Here, an efficient and numerically stable quasi-analytical model simulates the evaporation of raindrops and enrichment of their isotope composition. It is applied to a drop size distribution and subcloud environment representative of Atlantic trade cumulus clouds. Idealized physics experiments artificially zero out selected processes to discern the separate effects on the isotope ratio of raindrops, of exchange with the environment, evaporation, and kinetic molecular diffusion. A parameterization of size-dependent molecular and eddy diffusion is formulated that enriches raindrops much more strongly (+5‰ for deuterated water [HDO] and +3.5‰ for O) than equilibrium evaporation as they become smaller than 1mm. The effect on evaporated vapor is also assessed. Rain evaporation enriches subcloud vapor by +12‰ per mm rain (for HDO), explaining observations of enriched vapor in cold pools sourced by evaporatively cooled downdrafts. Drops smaller than 0.5mm evaporate completely before falling 700m in typical subtropical marine boundary layer conditions. The early and complete evaporation of these smaller drops in the rain size distribution enriches the vapor produced by rain evaporation.

Are turbulence effects on droplet collision–coalescence a key to understanding observed rain formation in clouds?

Rain formation is a critical factor governing the lifecycle and radiative forcing of clouds and therefore it is a key element of weather and climate. Cloud microphysics-turbulence interactions occur across a wide range of scales and are challenging to represent in atmospheric models with limited resolution. Based on past experiments and idealized numerical simulations, it has been postulated that cloud turbulence accelerates rain formation by enhancing drop collision-coalescence. We provide substantial evidence for significant impacts of turbulence on the evolution of cloud droplet size distributions and rain formation by comparing high-resolution observations of cumulus congestus clouds with state-of-the-art large-eddy simulations coupled with a Lagrangian particle-based microphysics scheme. Turbulent coalescence must be included in the model to accurately represent the observed drop size distributions, especially for drizzle drop sizes at lower heights in the cloud. Turbulence causes earlier rain formation and greater rain accumulation compared to simulations with gravitational coalescence only. The observed rain size distribution tail just above cloud base follows a power law scaling that deviates from theoretical scalings considering either a purely gravitation collision kernel or a turbulent kernel neglecting droplet inertial effects, providing additional evidence for turbulent coalescence in clouds. In contrast, large aerosols acting as cloud condensation nuclei ("giant CCN") do not significantly impact rain formation owing to their long timescale to reach equilibrium wet size relative to the lifetime of rising cumulus thermals. Overall, turbulent drop coalescence exerts a dominant influence on rain initiation in warm cumulus clouds, with limited impacts of giant CCN.

Grain size estimation in fluvial gravel bars using uncrewed aerial vehicles: A comparison between methods based on imagery and topography

AbstractGrain size assessments are necessary for understanding the various geomorphological, hydrological and ecological processes that occur within rivers. Recent research has shown that the application of Structure‐from‐Motion (SfM) photogrammetry to imagery from uncrewed aerial vehicles (UAVs) shows promise for rapidly characterising grain sizes along rivers in comparison to traditional field‐based methods. Here, we evaluated the applicability of different methods for estimating grain sizes in gravel bars along a study reach in the Olentangy River in Columbus, Ohio. We collected imagery of these gravel bars with a UAV and processed those images with SfM photogrammetry software to produce three‐dimensional point clouds and orthomosaics. Our evaluation compared statistical models calibrated on topographic roughness, which was computed from the point clouds, and to those based on image texture, which was computed from the orthomosaics. Our results showed that statistical models calibrated on image texture were more accurate than those based on topographic roughness. This might be because of site‐specific patterns of grain size, shape and imbrication. Such patterns would have complicated the detection of topographic signatures associated with individual grains. Our work illustrates that UAV‐SfM approaches show potential to be used as an accessible method for characterising surface grain sizes along rivers at higher spatial and temporal resolutions than those provided by traditional methods.

Extreme precipitation over complex terrain using multiple remote sensing observation: A case study in the Great Bandung, Indonesia

Intense precipitation events are the main cause triggering hydrometeorological hazards over complex terrain. Two extreme precipitation (EP) events led to major flooding on 23–25 March 2021 and produced a rain-hail mixture (RHM) on 11 April 2021 in the Greater Bandung (GB) basin area, Indonesia. We investigated the spatial and vertical structure of precipitating cloud systems and the plausible mechanism triggering the two case studies with combined multiple remote sensing observations using an X-band polarimetric Doppler Weather Radar (Xpol) and X-band rain scanner radar (RSR) network, supported by rain gauges and satellite observation. The local processes controlling the intense rainfall events over the complex topography were quantified for the first time using an observational campaign in Indonesia. During the first EP event (23–25 March 2021), the modified satellite algorithm successively confirmed that the mesoscale convective system triggered the local anomalous circulation. The RSR network reveals that the EP in eastern GB contributed to the overflow of the Citarum River alongside the basin, coinciding with the eastward propagating convective system that produced oblate-shaped water droplets without hail. Nevertheless, during the second EP event on 11 April 2021, the strengthening of mountain-based convection played a main role in producing RHM, confirmed by a hail differential reflectivity larger than 12 dB and exhibited hail early stage over two height levels in different locations (981 m and 1033 m) in the GB. Our study also found Doppler vorticity-based and rain sizes combination indicators using RSR data networks in capturing such extreme weather events over complex topography with 35 min early times to support the early warning system of hydrometeorological disaster mitigation over GB, Indonesia.

Modeling Multi‐Fraction Coastal Aeolian Sediment Transport With Horizontal and Vertical Grain‐Size Variability

AbstractGrain size affects the rates of aeolian sediment transport on beaches. Sediment in coastal environments typically consists of multiple grain‐size fractions and exhibits spatiotemporal variations. Still, conceptual and numerical aeolian transport models are simplified and often only include a single fraction that is constant over the model domain. It is unclear to what extent this simplification is valid and if the inclusion of multi‐fraction transport and spatial grain‐size variations affects aeolian sediment transport simulations and predictions of coastal dune development. This study applies the numerical aeolian sediment transport model AeoLiS to compare single‐fraction to multi‐fraction approaches for a range of grain‐size distributions and spatial grain‐size scenarios. The results show that on timescales of days to years, single‐fraction simulations with the median grain size, D50, often give similar results to multi‐fraction simulations, provided the wind is able to mobilize all fractions within that time frame. On these timescales, vertical variability in grain size has a limited effect on total transport rates, but it does influence the simulation results on minute timescales. Horizontal grain‐size variability influences both the total transport rates and the downwind bed grain‐size composition. The results provide new insights into the influence of beach sediment composition and spatial variability on total transport rates toward the dunes. The findings of this study can guide the implementation of grain‐size variability in numerical aeolian sediment transport models.

Development of an automated mobile grain size mapping of a mixed sediment beach

AbstractGrain sizes influence beach morphologies, processes, and states (e.g., dissipative, reflective and intermediate), however previous studies analysing beach grain size are often spatially and temporarily sparse. In this study, an automated mobile grain size estimation method using digital photographs (mobile digital grain size, MDGS) was developed and tested at a mixed sediment beach consisting of sand and gravels. The data collection system consisted of a downward‐looking camera, Real Time Kinematic Global Navigation Satellite System, and a camera‐triggering single‐board computer, attached to an all‐terrain vehicle. Digital photographs were collected monthly from January 2021 to March 2022 over a section spanning ~700 m alongshore and processed automatically using an existing (non‐mobile) DGS estimation method. The MDGS results were generally consistent with manually estimated grain sizes (n = 962, r2 = 0.74, RMSE = 5.9 mm) and UAV orthomosaic imagery, although the MDGS sometimes overestimated manually estimated grain sizes particularly for photographs with relatively small sediments. Modelled nearshore waves and subaerial beach survey data from mobile terrestrial LiDAR were used to explore using MDGS in morphological studies. Seasonal grain size trends, observed relationships between nearshore wave height and spatially averaged beach grain size, and the general increasing trends of grain sizes with both beach elevation and local roughness/slope were consistent with previous studies, highlighting the use of MDGS for morpho‐sedimentary mixed sediment beach research. The MDGS provides a unique method to conduct spatially and temporarily high‐resolution mapping of gravel size sediments over large areas (>102 m alongshore). Potential improvements of the MDGS include additional low elevation cameras for improved fine (e.g., sand) grain size estimates, decreased time between photo triggering, and automated removal of erroneous photographs containing surface irregularities (e.g., tire tracks) and non‐sediment features (e.g., seaweed). Overall, the MDGS provides improved surface grain size mapping and investigations of complex grain size–morphology relationships of mixed sediment beaches.

Manipulation of ZrO2/CaZrO3 fibrous membrane with high thermal stability and NIR reflectivity

AbstractGrain size control is an important aspect to manipulate the microstructure and high temperature stability of ceramic fibers. In the present work, phase competition mechanism was proposed to regulate the grain size of ZrO2/CaZrO3 composite fibers. Calcium precursor with different molar ratio of Ca/Zr was introduced to the zirconia system not only for phase stabilization of ZrO2 but also for phase competition between solid‐solution CaxZr1‐xO2‐x and new phase CaZrO3. Effects of Ca/Zr molar ratio on the thermal pyrolysis, crystallization, solid reaction of precursor fibers were fully explored. The change of grain size of fibers with various Ca/Zr molar ratio was characterized and discussed. Furthermore, the near‐infrared reflectivity and high‐temperature stability of fibrous membranes were also presented. The results indicated that ZrO2/CaZrO3 fibrous membrane has promising applications in high‐temperature for the excellent thermal stability and high near infrared (NIR) reflectivity.

Tracing the Rain Formation Pathways in Numerical Simulations of Deep Convection

AbstractQuantifying the microphysical process contributions to surface precipitation in numerical simulations can be challenging. This is due to the fact that many microphysical processes contribute to the formation and depletion of rain drops and there is almost always a spatial/temporal mismatch between where/when rain is formed and where/when it strikes the surface. In this work, we develop a tracing method that tracks the sources and sinks of raindrop mass and number as they are advected by the Weather Research and Forecasting model. Applying the method to an idealized squall line confirms that convective precipitation is dominated by warm rain processes (autoconversion and accretion) while stratiform precipitation is dominated by the melting of rimed and unrimed ice crystals. Sensitivity experiments in which the prescribed cloud drop number concentration is increased confirm the conventional wisdom that weakened autoconversion increases the fraction of raindrops originating from cold rain processes. The method also reveals that when applied to deep convection the Khairoutdinov and Kogan autoconversion scheme produces an excessive number of raindrops which are subsequently clipped in P3 microphysics to keep the rain size distribution within prescribed limits. This problem can mostly be mitigated by increasing the assumed radius for raindrops created by autoconversion.

Grain size characterization of Ti-6Al-4V titanium alloy based on laser ultrasonic random forest regression.

In this paper, a random forest regression (RFR) rain size characterization method based on a laser ultrasound technique is investigated to predict the grain size of titanium alloy (Ti-6Al-4V). The longitudinal wave velocity of the ultrasound signal and the attenuation coefficient at different frequencies are used as the input and the grain size is used as the output. An RFR algorithm was used to develop a grain size prediction model. Meanwhile, the grain size calculation model based on conventional scattering attenuation was established by calibrating the n value in the classical scattering theory using the attenuation coefficients at different frequencies of ultrasonic signals. The results show that the RFR algorithm is feasible for the grain size characterization of titanium alloys.

An endoplasmic reticulum-associated degradation-related E2-E3 enzyme pair controls grain size and weight through the brassinosteroid signaling pathway in rice.

Grain size is an important agronomic trait, but our knowledge about grain size determination in crops is still limited. Endoplasmic reticulum (ER)-associated degradation (ERAD) is a special ubiquitin proteasome system that is involved in degrading misfolded or incompletely folded proteins in the ER. Here, we report that SMALL GRAIN 3 (SMG3) and DECREASED GRAIN SIZE 1 (DGS1), an ERAD-related E2-E3 enzyme pair, regulate grain size and weight through the brassinosteroid (BR) signaling pathway in rice (Oryza sativa). SMG3 encodes a homolog of Arabidopsis (Arabidopsis thaliana) UBIQUITIN CONJUGATING ENZYME 32, which is a conserved ERAD-associated E2 ubiquitin conjugating enzyme. SMG3 interacts with another grain size regulator, DGS1. Loss of function of SMG3 or DGS1 results in small grains, while overexpression of SMG3 or DGS1 leads to long grains. Further analyses showed that DGS1 is an active E3 ubiquitin ligase and colocates with SMG3 in the ER. SMG3 and DGS1 are involved in BR signaling. DGS1 ubiquitinates the BR receptor BRASSINOSTEROID INSENSITIVE 1 (BRI1) and affects its accumulation. Genetic analysis suggests that SMG3, DGS1, and BRI1 act together to regulate grain size and weight. In summary, our findings identify an ERAD-related E2-E3 pair that regulates grain size and weight, which gives insight into the function of ERAD in grain size control and BR signaling.

The Relationship Between Reflectivity and Rainfall Rate From Rain Size Distributions Observed in Hurricanes

Raindrop Size Distributions (RSDs) collected by the Droplet Measurement Technologies (DMT) Precipitation Imaging Probe (PIP) from 17 flights through 6 hurricanes during National Oceanic and Atmospheric Administration’s hurricane field program in 2020 are used to study reflectivity (Z) and rainfall rate (R) relationship (i.e. Z-R relationship). The results show that the Z-R distribution is highly scattered and the scatter increases with rainfall rate and reflectivity up to 48 dBZ or 25 mm h-1, after which it decreases rapidly. The range of the estimated rainfall rate from a power-law Z-R relationship can be as large as 50 mm h-1 at reflectivity of 40 dBZ. The result from random forest regression model demonstrates that including the information of mass-weighted-diameter (Dm) along with radar reflectivity improves the estimated rainfall rate significantly.

Limitations of Separate Cloud and Rain Categories in Parameterizing Collision‐Coalescence for Bulk Microphysics Schemes

AbstractWarm rain collision‐coalescence has been persistently difficult to parameterize in bulk microphysics schemes. We use a flexible bulk microphysics scheme with bin scheme process parameterizations, called AMP, to investigate reasons for the difficulty. AMP is configured in a variety of ways to mimic bulk schemes and is compared to simulations with the bin scheme upon which AMP is built. We find that an important limitation in traditional bulk schemes is the use of separate cloud and rain categories. When the drop size distribution is instead represented by a continuous distribution, the simulation of cloud‐to‐rain conversion is substantially improved. We also find large sensitivity to the threshold size to distinguish cloud and rain in traditional schemes; substantial improvement is found by decreasing the threshold from 40 to 25 μm. Neither the use of an assumed functional form for the size distribution nor the choice of predicted distribution moments has a large impact on the ability of AMP to simulate rain production. When predicting four total moments of the liquid drop size distribution, either with a traditional two‐category, two‐moment scheme with a reduced size threshold, or a four‐moment single‐category scheme, errors in the evolution of mass and the cloud size distribution are similar, but the single‐category scheme has a substantially better representation of the rain size distribution. Optimal moment combinations for the single‐category approach are investigated and appear to be linked more to the information content they provide for constraining the size distributions than to their correlation with collision‐coalescence rates.

Scanning the rice Global MAGIC population for dynamic genetic control of seed traits under vegetative drought

AbstractGrain size and shape are important yield components in rice (Oryza sativa L.), and their genetic control under adverse environmental conditions, such as drought stress, remains uncertain. This lack of knowledge is due to the laborious, time‐consuming phenotyping of seed attributes in large rice populations. We developed a new high‐throughput phenotyping method based on a desktop scanner and the open‐source package Plant Computer Vision (PlantCV). We used this method to investigate seed size and shape variability within the rice Global multi‐parent advanced generation intercross population, grown under well‐watered and vegetative drought conditions. Besides being affordable, rapid, and accurate, our method captured the phenotypic divergence between drought and well‐watered samples, expressed as 12 different traits, including new grain shape metrics. Our method facilitates the identification of outperforming genotypes under drought stress so is potentially very valuable for crop breeders seeking to make selection based on kernel attributes. We ran a marker–trait association analysis for the measured seed traits, demonstrating that our method also provides adequate phenotypes for genetic studies. We observed dynamic genetic control of seed‐related traits under vegetative drought stress, highlighting the importance of understanding the contribution of genotype × environment interactions on trait variation to develop resilient, high‐yielding rice cultivars.

Dissection of two quantitative trait loci for grain length linked on the long arm of chromosome 5 in rice

AbstractGrain size is the major determinant of grain weight and has an important role in grain quality. It is controlled by several major quantitative trait loci (QTL) and many minor QTL. Identification of QTL for grain size is important for understanding the genetic and molecular network regulating grain size in rice (Oryza sativa L.). Following previous identification of QTL for grain weight and size using an F2:3 family derived from the indica rice cross Teqing/IRBB52, one QTL, qTGW5, having significant effects on grain length and weight, was targeted for validation, dissection, and fine‐mapping. First, the effect of qTGW5 was validated using two near‐isogenic line (NIL)‐F2 populations. Then, qTGW5 was dissected into two closely linked QTL using four NIL populations. One of them, qGL5.1, having significant effects on grain length, width, and weight, was located within an 1,896.4‐kb region. The other one, qGL5.2, controlling grain length, was further delimited into a 68.8‐kb region using seven NIL‐F2 populations. Six annotated genes were found in the qGL5.2 region, of which five showed nucleotide polymorphisms between the two parental lines. Three of the six annotated genes showed significant expression differences between NILTeqing and NILIRBB52 in young panicles using quantitative real‐time polymerase chain reaction. The results will facilitate cloning the minor QTL and understanding the genetic architecture for grain size in rice.

Studying the Effects of Roads Geometry and Design Parameters on the Pavement Drainage System

Background: Water floods have a considerable impact on roads sustainability by creating roads cracks, breaking down and holes, and failure for some other parts. The existence of good drainage system serviced the road and draining the water resulted from rain floods is crucial. These significant influences can be classified as positive or negative, low, moderate, or high. Aim and Objectives: This paper discusses the water floods and rainfall effects on roads and highways in Jordan as well as the drainage system on road sustainability and performance. The main aim of this paper is to investigate and analyse water as rainfall or floods affecting roads and highways in Jordan. The importance of this study is represented by studying and analysing the effects of rainfall and water floods on road construction and sustainability in Jordan after the latest high rain sizes of this winter and water floods, which affect the roads and highways in a good percentage. The other importance of the study is represented in offering solutions to problems caused by the environmental effects, specially floods and high rainfall rates. Methodology: all data and information about status of Jordanian roads during winter and floods are collected from real cases of about 40 main and semi-main roads in Jordan. Results and Conclusions: A good drainage system and repair operations and maintenance generally have a positive impact on road sustainability and survival age. The effects of slopes of the road and surface of the asphalt, rainfall intensity, and water flow velocity on drainage length and drainage time and water depth are discussed here. Doi: 10.28991/cej-2021-03091636 Full Text: PDF

Seismo‐Turbidites in Aysén Fjord (Southern Chile) Reveal a Complex Pattern of Rupture Modes Along the 1960 Megathrust Earthquake Segment

AbstractGrain size analysis and end‐member modeling of a long sediment core from Aysén Fjord (southern Chile) allows to identify over 25 seismo‐turbidites in the last 9,000 years. Considering the shaking intensities required to trigger these turbidites (V½‐VI½), the majority can be related to megathrust earthquakes. Multiple studies in south‐central Chile have aimed at finding traces of giant, tsunamigenic megathrust earthquakes leading to the current 5,500‐year‐long paleoseismological record of the Valdivia segment. However, none of these cover the southern third of the segment. Aysén Fjord allows to fill this data gap and presents the first, crucial paleoseismic data to demonstrate that the 1960 event was not unique for the Valdivia segment, yielding a recurrence rate of 321 ± 116 years in the last two millennia. Moreover, the oldest identified events in Aysén Fjord date back to 9,000 cal years BP and, thus, also extend the regional paleoseismological record in time. We infer a large temporal variability in rupture modes, with successions of full‐segment ruptures alternating with partial and cascading ruptures. The latter seems to significantly postpone the occurrence of another full rupture when consecutively occurring in different parts of the segment. Additionally, one outstanding period of seismic quiescence—during which no megathrust earthquake evidence has been found at any paleoseismic site—occurred after a full rupture in AD ~745 that presents an unusual uplift/subsidence pattern. Such variability makes it highly speculative to anticipate the rupture mode of the next megathrust earthquake along the Valdivia segment.

Impacts of Predicting the Liquid Fraction of Mixed-Phase Particles on the Simulation of an Extreme Freezing Rain Event: The 1998 North American Ice Storm

Abstract A prognostic equation for the liquid fraction of mixed-phase particles has been recently added to the Predicted Particle Properties (P3) bulk microphysics scheme. Mixed-phase particles are necessary to simulate key microphysical processes leading to various winter precipitation types, such as ice pellets and freezing rain. To illustrate the impacts of predicting the bulk liquid fraction, the 1998 North American Ice Storm is simulated using the Weather Research and Forecasting (WRF) Model with the modified P3 scheme. It is found that simulating partial melting by predicting the bulk liquid fraction produces higher mass and number mixing ratios of rain. This leads to smaller rain sizes reaching the refreezing layer as well as a decrease in the freezing rain accumulation at the surface by up to 30% in some locations compared to when no liquid fraction is predicted. The increase in fall speed and density and decrease of particle diameter during partial melting combined with an improved representation of the refreezing process in the modified P3 leads to generally higher total solid surface precipitation rates than using the original P3 scheme. There is also an increase of solid precipitation in regions of ice pellet accumulation. Overall, the simulation of mixed-phase particles notably impacts the vertical and spatial distributions of precipitation properties.

Grain Size Analysis and Permeametry for Estimating Hydraulic Conductivity in Engineered Porous Media

AbstractGrain size analysis and permeametry are common methods for estimating the hydraulic conductivity (K) of porous media. It is well known that these methods have limited accuracy when they are used to characterize natural sediments. However, hydrogeological research has increasingly introduced technologies dependent on engineered porous media that may be less problematic because complex geologic structures are eliminated in the lab and field‐scale packings. The recently introduced Horizontal Reactive Media Treatment Wells (HRX® Wells), for in situ, passive remediation of groundwater is one such example. The HRX Well passively collects groundwater and directs it through a horizontal pipe packed with an engineered porous medium. In this project, grain size analysis was conducted for sand and sand‐iron mixtures to estimate K using the 16 algorithms provided in the HydrogeoSieveXL2.3.2 software. The results were compared to K determined by permeametry and a field‐scale column, 30 cm long and 25 cm in diameter, representing an HRX Well. The best comparability of K estimates from grain size analysis and permeametry were obtained using the USBR, Slichter, and Shepherd K estimation methods. These also showed good agreement between lab‐scale and field‐scale K estimations, with reproducibility within the range ±20%. This study shows that laboratory K estimations can be representative across various relevant scales, including the field‐scale, for engineered porous media. This finding extends to filter packs, and other engineered porous media design methods by emphasizing and demonstrating one case of accuracy in lab‐scale permeability estimation for field‐scale implementations.

Origin of Grain Size Effects on Voltage‐Driven Ferroelastic Domain Evolution in Polycrystalline Tetragonal Lead Zirconate Titanate Thin Film

AbstractGrain size effects on electromechanical properties and voltage‐driven ferroelastic domain wall motion are a well‐known phenomenon in polycrystalline ferroelectrics. Here, the origin of the grain size effects on voltage‐driven ferroelastic domain wall motion is presented with the direct observation of ferroelastic domain evolution with applied DC voltage by piezoelectric force microscopy and polarization hysteresis loop. It is demonstrated that the microstructure parameter for controlling the voltage‐driven ferroelastic domain wall motion is the number of colonies of stripe domains in a grain rather than the grain size. Single colony grains do not show considerable out‐of‐plane (001) domain width change whereas multiple colony grains exhibit significant domain width increase with an applied DC voltage. No independent grain size effect on ferroelastic domain wall motion is observed in the grain size range 0.6–1.6 µm.

Improving the representation of supercooled liquid water in the HARMONIE-AROME weather forecast model

A realistic representation of mixed-phase clouds in weather and climate models is essential to accurately simulate the model’s radiative balance and water cycle. In addition, it is important for providing downstream applications with physically realistic model data for computation of, for instance, atmospheric icing on societal infrastructure and aircraft. An important quantity for forecasts of atmospheric icing is to model accurately supercooled liquid water (SLW). In this study, we implement elements from the Thompson cloud microphysics scheme into the numerical weather prediction model HARMONIE-AROME, with the aim to improve its ability to predict SLW. We conduct an idealised process-level evaluation of microphysical processes, and analyse the water phase budget of clouds and precipitation to compare the modified and original schemes, and also identify the processes with the most impact to form SLW. Two idealised cases representing orographic lift and freezing drizzle, both known to generate significant amounts of SLW, are setup in a 1 D column version of HARMONIE-AROME. The experiments show that the amount of SLW is largely sensitive to the ice initiation processes, snow and graupel collection of cloud water, and the rain size distribution. There is a doubling of the cloud water maximum mixing ratio, in addition to a prolonged existence of SLW, with the modified scheme compared with the original scheme. The spatial and temporal extent of cloud ice and snow are reduced, due to stricter conditions for ice nucleation. The findings are important as the HARMONIE-AROME models is used for operational forecasting in many countries in northern Europe having a colder climate, as well as for climate assessments over the Arctic region.