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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

A Theory for the Balance between Warm Rain and Ice Crystal Processes of Precipitation in Mixed-Phase Clouds

Abstract Mixed-phase clouds contain both supercooled cloud liquid and ice crystals. In principle, precipitation may be initiated either by the liquid phase or by the ice phase. Ice crystals may grow by vapor diffusion to become snow (“ice crystal process”), forming “cold” precipitation. Equally, cloud droplets, when large enough, coalesce to form “warm” precipitation by the “warm rain process.” Warm rain could be supercooled and freeze as “warm” graupel. In the present paper, a new simplified theoretical analysis is provided to examine the microphysical system consisting of three species of hydrometeor, namely, cloud liquid, “cold ice” (crystals, snow), and “warm rain” (frozen or supercooled). This is obtained by nondimensionalizing and simplifying the evolution equations for the mass of each species. Analytical formulas are given for equilibria. Feedback analysis shows that the sign of the feedback is linked to the abundance of precipitation, with a neutral surface in the 3D phase space. The system’s precipitation amount explodes while in the initial unstable regime, crossing the neutral surface and approaching the equilibrium point that is a stable attractor. Positive and negative feedbacks are elucidated. In a standard case, the cold ice mass is about 1000 times larger than the warm rain mass. To illustrate the physical behavior of the theory, sensitivity tests are performed with respect to environmental conditions (e.g., aerosol, updraft speed) and microphysical parameters (e.g., riming and sedimentation rates for cold ice). Cold ice prevails, especially in fast ascent, due to its low bulk density, favoring slow sedimentation and a wide cross-sectional area for riming. Significance Statement The theory elucidates how the ice phase can prevail in the precipitation from any mixed-phase clouds with supercooled cloud liquid and crystals. The ice phase radically suppresses cloud liquid by riming when active and “wins” the competition against coalescence. This prevalence of ice is shown to arise from the low bulk density of snow. The cloud is viewed as a system of negative and positive feedbacks that prevail in realms of stability and instability in a 3D phase space.

Meteorology & Atmospheric Sciences↗
DOE OSTI2017

Redistribution of ice nuclei between cloud and rain droplets: Parameterization and application to deep convective clouds: ICE NUCLEI IN RAIN DROPLETS

In model studies of aerosol-dependent immersion freezing in clouds, a common assumption is that each ice nucleating aerosol particle corresponds to exactly one cloud droplet. Conversely, the immersion freezing of larger drops—“rain”—is usually represented by a liquid volume-dependent approach, making the parameterizations of rain freezing independent of specific aerosol types and concentrations. This may lead to inconsistencies when aerosol effects on clouds and precipitation shall be investigated, since raindrops consist of the cloud droplets—and corresponding aerosol particles—that have been involved in drop-drop-collisions. We introduce an extension to a two-moment microphysical scheme in order to account explicitly for particle accumulation in raindrops by tracking the rates of selfcollection, autoconversion, and accretion. This also provides a direct link between ice nuclei and the primary formation of large precipitating ice particles. A new parameterization scheme of drop freezing is presented to consider multiple ice nuclei within one drop and effective drop cooling rates. In our test cases of deep convective clouds, we find that at altitudes which are most relevant for immersion freezing, the majority of potential ice nuclei have been converted from cloud droplets into raindrops. Compared to the standard treatment of freezing in our model, the less efficient mineral dust-based freezing results in higher rainwater contents in the convective core, affecting both rain and hail precipitation. The aerosol-dependent treatment of rain freezing can reverse the signs of simulated precipitation sensitivities to ice nuclei perturbations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

On the Realism of the Rain Microphysics Representation of a Squall Line in the WRF Model. Part II: Sensitivity Studies on the Rain Drop Size Distributions

A comparison between retrieved properties of the rain drop size distributions (DSDs) from multifrequency cloud radar observations and WRF Model results using either the Morrison or the Thompson bulk microphysics scheme is performed in order to evaluate the model’s ability to predict the rain microphysics. This comparison reveals discrepancies in the vertical profile of the rain DSDs for the stratiform region of the squall-line system observed on 12 June 2011 over Oklahoma. Based on numerical sensitivity analyses, this study addresses the bias at the top of the rain layer and the vertical evolution of the DSD properties (i.e., of D m and N$^{*}_{0}$). In this way, the Thompson scheme is used to explore the sensitivity to the melting process. Moreover, using the Thompson and Morrison schemes, the sensitivity of the DSD vertical evolution to different breakup and self-collection parameterizations is studied. Results show that the DSDs are strongly dependent on the representation of the melting process in the Thompson scheme. In the Morrison scheme, the simulations with more efficient breakup reproduce the DSD properties with better fidelity. Here, this study highlights how the inaccuracies in simulated D m and N$^{*}_{0}$ for both microphysics schemes can impact the evaporation rate, which is systematically underestimated in the model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Long-term observations of cloud condensation nuclei over the Amazon rain forest - Part 2: Variability and characteristics of biomass burning, long-range transport, and pristine rain forest aerosols

For this study, size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted over a full seasonal cycle at the remote Amazon Tall Tower Observatory (ATTO, March 2014–February 2015). In a preceding companion paper, we presented annually and seasonally averaged data and parametrizations (Part 1; Pöhlker et al., 2016a). In the present study (Part 2), we analyze key features and implications of aerosol and CCN properties for the following characteristic atmospheric conditions: Empirically pristine rain forest (PR) conditions, where no influence of pollution was detectable, as observed during parts of the wet season from March to May. The PR episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode with D Ait ≈ 70nm and N Ait ≈ 160cm -3 , weak accumulation mode with D acc ≈ 160nm and N acc ≈ 90cm -3 ), a chemical composition dominated by organic compounds, and relatively low particle hygroscopicity (κ Ait ≈ 0.12, κ acc ≈ 0.18). Long-range-transport (LRT) events, which frequently bring Saharan dust, African biomass smoke, and sea spray aerosols into the Amazon Basin, mostly during February to April. The LRT episodes are characterized by a dominant accumulation mode ( DAit ≈ 80nm, N Ait ≈ 120cm -3 vs. D acc ≈ 180nm, N acc ≈ 310cm -3 ), an increased abundance of dust and salt, and relatively high hygroscopicity (κ Ait ≈ 0.18, κ acc ≈ 0.35). The coarse mode is also significantly enhanced during these events. Biomass burning (BB) conditions characteristic for the Amazonian dry season from August to November. The BB episodes show a very strong accumulation mode (D Ait ≈ 70nm, N Ait ≈ 140cm -3 vs. D acc ≈ 170nm, N acc ≈ 3400cm -3 ), very high organic mass fractions (~90%), and correspondingly low hygroscopicity (κ Ait ≈ 0.14, κ acc ≈ 0.17). Mixed-pollution (MPOL) conditions with a superposition of African and Amazonian aerosol emissions during the dry season. During the MPOL episode presented here as a case study, we observed African aerosols with a broad monomodal distribution (D ≈ 130nm, N CN, 10 ≈ 1300cm -3 ), with high sulfate mass fractions (~20%) from volcanic sources and correspondingly high hygroscopicity (κ < 100 nm ≈ 0.14, κ > 10 nm ≈ 0.22), which were periodically mixed with fresh smoke from nearby fires (D ≈ 110nm, N CN, 10 ≈ 2800cm -3 ) with an organic-dominated composition and sharply decreased hygroscopicity (κ < 150 nm ≈ 0.10, κ > 150 nm ≈ 0.20). Insights into the aerosol mixing state are provided by particle hygroscopicity (κ) distribution plots, which indicate largely internal mixing for the PR aerosols (narrow κ distribution) and more external mixing for the BB, LRT, and MPOL aerosols (broad κ distributions). The CCN spectra (CCN concentration plotted against water vapor supersaturation) obtained for the different case studies indicate distinctly different regimes of cloud formation and microphysics depending on aerosol properties and meteorological conditions. The measurement results suggest that CCN activation and droplet formation in convective clouds are mostly aerosol-limited under PR and LRT conditions and updraft-limited under BB and MPOL conditions. Normalized CCN efficiency spectra (CCN divided by aerosol number concentration plotted against water vapor supersaturation) and corresponding parameterizations (Gaussian error function fits) provide a basis for further analysis and model studies of aerosol–cloud interactions in the Amazon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Rain-aerosol relationships influenced by wind speed: RAIN-AEROSOL RELATIONSHIPS

The aerosol optical depth (AOD) has been shown to correlate with precipitation rate (R) in recent studies. The relationships between R and AOD are examined in this study using 150-year simulations in preindustrial conditions with the CESM model. Through partial correlation analysis, with the impact from 10-m wind speed removed, relationships between modeled AOD and R exert a significant change from positive to negative over the mid-latitude oceans, indicating that the wind speed has the largest contribution to the relationships over the mid-latitude oceans. Sensitivity simulation shows that variations in wind speed lead to increasing R by +0.99 mm day-1 averaged globally, offsetting 64% of the wet scavenging induced decrease in precipitation between polluted and clean conditions. These demonstrate that wind speed is one of the major drivers of R-AOD relationships. Relative humidity can also result in the positive relationships; however, its role is smaller than that of wind speed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

The Green Ocean Amazon Experiment (GoAmazon2014/5) Observes Pollution Affecting Gases, Aerosols, Clouds, and Rainfall over the Rain Forest

The Observations and Modeling of the Green Ocean Amazon 2014–2015 (GoAmazon2014/5) experiment took place around the urban region of Manaus in central Amazonia across 2 years. The urban pollution plume was used to study the susceptibility of gases, aerosols, clouds, and rainfall to human activities in a tropical environment. Many aspects of air quality, weather, terrestrial ecosystems, and climate work differently in the tropics than in the more thoroughly studied temperate regions of Earth. GoAmazon2014/5, a cooperative project of Brazil, Germany, and the United States, employed an unparalleled suite of measurements at nine ground sites and on board two aircraft to investigate the flow of background air into Manaus, the emissions into the air over the city, and the advection of the pollution downwind of the city. Here in this paper, to visualize this train of processes and its effects, observations aboard a low-flying aircraft are presented. Comparative measurements within and adjacent to the plume followed the emissions of biogenic volatile organic carbon compounds (BVOCs) from the tropical forest, their transformations by the atmospheric oxidant cycle, alterations of this cycle by the influence of the pollutants, transformations of the chemical products into aerosol particles, the relationship of these particles to cloud condensation nuclei (CCN) activity, and the differences in cloud properties and rainfall for background compared to polluted conditions. The observations of the GoAmazon2014/5 experiment illustrate how the hydrologic cycle, radiation balance, and carbon recycling may be affected by present-day as well as future economic development and pollution over the Amazonian tropical forest.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Rain footprints on C-band synthetic aperture radar images of the ocean - Revisited

It is well known that rain leaves footprints on the sea surface that sometimes become visible on synthetic aperture radar (SAR) images. Rain cells can easily be detected on SAR images at all radar frequencies when they are associated with a downdraft pattern. But rain cells are not always associated with downdraft and rain can also occur in other forms, as stratified rain, rain bands, and squall lines. It turns out that radar signatures of rain at C-band are much more complex than at L- or X-band radar and that it is particularly difficult to identify unambiguously rain events on C-band SAR images acquired over the ocean. This is because C-band lies in the transition region where raindrops impinging onto the sea surface can increase (usually) or decrease the backscattered radar power and where volume scattering and attenuation by rain drops in the atmosphere are not always negligible (at very high rain rates). In order to get an insight into the physical mechanisms causing the C-band radar signatures of rain, we first revisit results obtained from historic laboratory and field experiments and multi-frequency/multi-polarization SAR data acquired during the SIR-C/X-SAR spaceshuttle mission in 1994. Then we analyze several C-band SAR images acquired by the European satellites Envisat and Sentinel-1A, and the Canadian satellite Radarsat-2 and compare them, whenever possible, with quasi-coincident and collocated weather radar images. The observational data show that, at low to medium rain rates, the main physical mechanism causing C-band radar signatures of rain is Bragg scattering at ring waves generated by the rain drops impinging onto the sea surface, which increase the radar backscatter. However, areas of increased radar backscatter are often accompanied by adjacent areas of decreased radar backscatter, which is due to attenuation of the Bragg waves by turbulence also generated by the impinging rain drops. Furthermore, we present a full-polarimetric Radarsat-2 SAR image of a rain cell together with a polarimetric decomposition analysis, which shows that the C-band radar signature of a rain cell is caused by surface scattering. The observation show that radar signatures of rain cells often contain segments, where the co-polarized as well the cross-polarized radar backscatter are strongly enhanced, which indicates non-Bragg scattering contributions to the scattering process. Furthermore, the polarimetric decomposition analysis shows that the C-band radar signature of a rain cell is dominated by surface scattering. Possible mechanisms, like scattering at splash products, are discussed. Whether the normalized radar cross section (NRCS) due to rain is increased or decreased depends on rain rate, wind speed, incidence angle, and history of the rain event. At low to moderate wind speeds (< 10 ms - 1 ) and low to medium high rain rates (< 50 mm h - 1 ), the NRCS is usually increased by up to 8 dB, and at high wind speeds (> 10 m s - 1 ) and low to high rain rates (but < 50 mm h - 1 ), the NRCS is usually decreased by up to 3 dB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Multi–year analysis of rain–snow levels at Marquette, Michigan

This study uses observations from a ground-based instrument suite to investigate the rain-snow level in stratiform rainfall from January 2014 to April 2020 in the Upper Great Lakes Region. The height above the surface where ice melts to rain, the rain-snow level (RSL), influences microphysical assumptions in remote sensing precipitation retrievals and the ability of space-based radar to discriminate surface precipitation phase because of ground clutter. The instrument suite is installed at the Marquette, MI (MQT) National Weather Service station adjacent to Lake Superior. Rain events and the RSL are studied through a ground-based vertically profiling radar (Micro Rain Radar), a custom NASA-developed video disdrometer (Precipitation Imaging Package), and reanalyses products from ECMWF ERA5 and NASA MERRA-2. Further, distinct macro and micro physical characteristics are observed in precipitation events with shallow RSL ( < 1.8 km above ground level [AGL]) and intermediate RSL ( > 1.8 km AGL). Intermediate RSL correspond to rain events with relatively higher rain rates and a higher concentration of small drops in the drop size distributions (DSDs). Shallow RSL DSDs contain relatively higher concentrations of large drops with lower fall speeds suggesting that partially melted snowflakes may be reaching the surface. Reflectivity-rain-rate relationships are also impacted by microphysical differences associated with RSL regimes. Radar-detected RSL agree with reanalysis-derived melt levels- especially at wet-bulb isotherms of 0.5°C and 1°C. Seasonal differences such as shallow rain-snow levels in winter, fall, and spring have subsequent implications for satellite detectability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Light rain exacerbates extreme humid heat

Abstract Humid heat waves pose significant risks to human health and the ecosystem. Intuitively, rainfall often alleviates extreme humid heat. However, here we show that light rain often accompanies extreme humid heat, exacerbating its frequency and intensity, especially over arid and semi-arid regions compared to no rain and moderate-to-heavy rain cases. This is because light rain does not dramatically reduce solar radiation but increases near-surface humidity through enhanced surface evaporation. The water replenishment from light rain as well as a shallower planetary boundary layer is crucial for consecutive extremes where there are commonly sporadic drizzle days amidst several rain-free days. These extremes last longer than rain-free extremes. Current global climate models (GCMs) overestimate light rain. After reducing this bias in a GCM, underestimations of humid heat waves in energy-limited regions and overestimations in water-limited regions are largely alleviated. These findings underscore the underappreciated impact of light rain on extreme humid heat.

Science & Technology - Other Topics↗
DOE OSTI2025

Widespread underestimation of rain-induced soil carbon emissions from global drylands

Dryland carbon fluxes, particularly those driven by ecosystem respiration, are highly sensitive to water availability and rain pulses. However, the magnitude of rain-induced carbon emissions remains unclear globally. Here we quantify the impact of rain-pulse events on the carbon balance of global drylands and characterize their spatiotemporal controls. Using eddy-covariance observations of carbon, water and energy fluxes from 34 dryland sites worldwide, we produce an inventory of over 1,800 manually identified rain-induced CO2 pulse events. Based on this inventory, a machine learning algorithm is developed to automatically detect rain-induced CO2 pulse events. Our findings show that existing partitioning methods underestimate ecosystem respiration and photosynthesis by up to 30% during rain-pulse events, which annually contribute 16.9 ± 2.8% of ecosystem respiration and 9.6 ± 2.2% of net ecosystem productivity. We show that the carbon loss intensity correlates most strongly with annual productivity, aridity and soil pH. Finally, we identify a universal decay rate of rain-induced CO2 pulses and use it to bias-correct respiration estimates. Our research highlights the importance of rain-induced carbon emissions for the carbon balance of global drylands and suggests that ecosystem models may largely underrepresent the influence of rain pulses on the carbon cycle of drylands.

Nguyen, Ngoc B↗
DOE OSTI2024

Impacts of stochastic coalescence variability on warm rain initiation using Lagrangian microphysics in box and large-eddy simulations

Various coalescence methods for Lagrangian microphysics schemes are tested in box and large-eddy simulation (LES) models, including the stochastic all-or-nothing super-droplet method (SDM) and a version of SDM (dSDM) that applies a fractional approach similar to the average impact method. In LES, variabilities driven by microphysics and by flow realizations are separated using the “piggybacking” technique. Rain initiation averaged over many realizations of the box model is delayed and rain variability increases as the number of super-drops per collision volume ( N SD ) is decreased using SDM. In contrast, rain initiation time using SDM in LES is insensitive to N SD for 32 ≤ N SD ≤ 512. This is explained through the interaction between LES grid boxes, each acting as a separate collision volume. Variability across the ensemble of LES collision volumes using SDM results in rain quickly initiating in some of the LES grid cells at low N SD and leading to a similar overall timing of rain initiation from the cloud compared to simulations with high N SD . There is a ~20% decrease in the total rain mass and mean rain flux as N SD is increased from 32 to 256, with little additional change as N SD is increased from 256 to 512. The fractional coalescence approach in dSDM leads to reduced microphysical variability and a 15-18 min delay in rain initiation compared to SDM. Finally, an additional LES ensemble with microphysical variability feeding back to the dynamics shows that flow variability dominates the impact of microphysical variability on rain properties. Thus, flow variability must be constrained to isolate impacts of microphysical variability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

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.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

Evaluation of Cloud-resolving and Limited Area Model Intercomparison Simulations using TWP-ICE Observations. Part 2: Rain Microphysics

Ten 3D cloud-resolving model (CRM) simulations and four 3D limited area model (LAM) simulations of an intense mesoscale convective system observed on January 23-24, 2006 during the Tropical Warm Pool – International Cloud Experiment (TWP-ICE) are compared with each other and with observations and retrievals from a scanning polarimetric radar, co-located UHF and VHF vertical profilers, and a Joss-Waldvogel disdrometer in an attempt to explain published results showing a low bias in simulated stratiform rainfall. Despite different forcing methodologies, similar precipitation microphysics errors appear in CRMs and LAMs with differences that depend on the details of the bulk microphysics scheme used. One-moment schemes produce too many small raindrops, which biases Doppler velocities low, but produces rain water contents (RWCs) that are similar to observed. Two-moment rain schemes with a gamma shape parameter (μ) of 0 produce excessive size sorting, which leads to larger Doppler velocities than those produced in one-moment schemes, but lower RWCs than observed. Two moment schemes also produce a convective median volume diameter distribution that is too broad relative to observations and thus, may have issues balancing raindrop formation, collision coalescence, and raindrop breakup. Assuming a μ of 2.5 rather than 0 for the raindrop size distribution improves one-moment scheme biases, and allowing μ to have values greater than 0 may improve two-moment schemes. Under-predicted stratiform rain rates are associated with under-predicted ice water contents at the melting level rather than excessive rain evaporation, in turn likely associated with convective detrainment that is too high in the troposphere and mesoscale circulations that are too weak. In addition to stronger convective updrafts than observed, limited domain size prevents a large, well-developed stratiform region from developing in CRMs, while a dry bias in ECMWF analyses does the same to the LAMs.

cloud-resolving↗
DOE OSTI2018

Investigation of Liquid Cloud Microphysical Properties of Deep Convective Systems: 2. Parameterization of Raindrop Size Distribution and its Application for Convective Rain Estimation

The liquid cloud microphysical properties for stratiform rain (SR) have been investigated in Part 1 of this series. Since convective rain (CR) has characteristics in raindrop size distribution (DSD) and precipitation that are distinct from SR, we investigate the CR properties in this study by using 20 hr of CR samples collected by 17 Automatic Parsivel Units disdrometers during the Midlatitude Continental Convective Clouds Experiment over the Atmospheric Radiation Measurement Southern Great Plains site. A full spectrum of DSD is constructed based on a total of 23 size channels (0.321 to 9.785 mm), and both Gamma and Exponential fitted functions are applied to extract the DSD shape parameters. Compared to SR properties, CR has distinct features including broader size range and narrower exponential slope parameter (λ E ). These results indicate that the assumption of constant exponential intercept parameter ( N 0E ) is inappropriate for CR rain rate estimates. Additionally, the subsetting scheme of the CR DSD spectra also has a strong impact on the Gamma/Exponential functions. Therefore, a new CR DSD parameterization scheme is developed by choosing the appropriate spectra subset with the constraint of rain rate and using the constant λ E instead of constant N 0E . With the input of the radar reflectivity at the lowest observed height, the newly calculated CR rain rates match well with the collocated surface rain gauge measurements (127 Mesonet stations and 17 Automatic Parsivel Units), while the rain rates calculated using traditional Z-R relationship are 3–4 times larger, indicating that constant λ E is a better assumption for CR DSD.

58 GEOSCIENCES↗
DOE OSTI2019

Three‐Moment Representation of Rain in a Bulk Microphysics Model

Abstract A bulk three‐moment representation for rain microphysics is developed and implemented in the Predicted Particle Properties (P3) microphysics scheme. In addition, a new parameterization for rain self‐collection and collisional breakup (RSCB) is presented using a lookup table approach, based on the Spectral‐Bin Model (SBM). To quantify the impacts of sedimentation, evaporation, and RSCB on drop size distributions (DSDs), a rain shaft model is applied to a wide range of atmospheric scenarios (i.e., initial conditions and regimes) and compared against results from the SBM. DSD shapes are mainly determined by both sedimentation and evaporation, except in heavy rain where the impact of RSCB on DSD shape becomes more important than evaporation. The new parameterization for RSCB has a considerable impact on the mean drop size, improving the agreement between P3 and SBM. Only 4% of the original two‐moment rainshaft simulations have mean drop sizes and rain rates within ±20% of the SBM results, but this increases to more than 95% agreement when the three‐moment rain representation is used together with the new parameterization for RSCB. Generally, the improvement is more significant for heavy rain than for light drizzle. Remaining differences between bin and bulk model are attributable to treatments of evaporation, and the restriction to gamma DSDs in P3.

precipitation↗
DOE OSTI2022

Occurrence of Warm Freezing Rain: Observation and Modeling Study

Freezing rain has been normally considered to be composed of supercooled raindrops when the 2 m air temperature (hereafter T as ) is below freezing. However, according to a statistical survey of freezing rain observations in China from 2000 to 2019, we find that there were 656 events that occurred at T as greater than 0°C (hereafter warm freezing rain and denoted by WFR), which account for 7% of the total freezing rain observations. Additionally, nearly 3% (266 observations) of freezing rain events occurred when the near-surface wet-bulb temperature was greater than 0°C. The modeling and sensitivity experiments on the nonequilibrium raindrop temperature (hereafter T r ) how that the temperature difference between raindrops and the atmosphere is the main cause of WFR. The magnitudes of the Δ T ar (difference between raindrop temperature T r and air temperature T a ) and Δ T ur (difference between T r and wet-bulb temperature T w ) are determined by the raindrop diameter D, temperature lapse rate $\Gamma$, and relative humidity RH. Increases of D and $\Gamma$, and a decrease of RH enhance Δ T ar and Δ T ur and thus the occurrence of WFR. Further simulations of 4 idealized and 370 real sounding profiles reveal that either the T a or the T w cannot properly distinguish the WFR events. When considering the temperature difference between raindrops and the atmosphere, the WFR can form by the “melting of solid hydrometeors” or “supercooled warm rain process.” This study can also deepen our understanding of the conditions of WFR and freezing rain formation at different altitudes.

54 ENVIRONMENTAL SCIENCES↗