Mapping liquid water content in snow at the millimeter scale: an intercomparison of mixed-phase optical property models using hyperspectral imaging and in situ measurements

It is well understood that the distribution and quantity of liquid water in snow is relevant for snow hydrology and avalanche forecasting, yet detecting and quantifying liquid water in snow remains a challenge from the micro- to the macro-scale. Using near-infrared (NIR) spectral reflectance measurements, previous case studies have demonstrated the capability to retrieve surface liquid water content (LWC) of wet snow by leveraging shifts in the complex refractive index between ice and water. However, different models to represent mixed-phase optical properties have been proposed, including (1) internally mixed ice and water spheres, (2) internally mixed water-coated ice spheres, and (3) externally mixed interstitial ice and water spheres. Here, from within a controlled laboratory environment, we determined the optimal mixed-phase optical property model for simulating wet snow reflectance using a combination of NIR hyperspectral imaging, radiative transfer simulations (Discrete Ordinate Radiative Transfer model, DISORT), and an independent dielectric LWC measurement (SLF Snow Sensor). Maps of LWC were produced by finding the lowest residual between measured reflectance and simulated reflectance in spectral libraries, generated for each model with varying LWC and grain size, and assessed against the in situ LWC sensor. Our results show that the externally mixed model performed the best, retrieving LWC with an uncertainty of ∼1 %, while the simultaneously retrieved grain size better represented wet snow relative to the established scaled band area method. Furthermore, the LWC retrieval method was demonstrated in the field by imaging a snowpit sidewall during melt conditions and mapping LWC distribution in unprecedented detail, allowing for visualization of pooling water and flow features.

CLOUD DROP SPECTRA IN MARITIME AND INLAND REGIONS

Measurements o f clo ud drop ..ire spectra on non-preci pitating cumulus clouds, 1·2 km thick,were made at differe nt levels o ver the Arabian Sea (maritime) and over r une (inland) regio n during the end ofthe summer monsoo n seasons of 1973, 1974 and 1979.The macimurn size of clo ud drops for the. Arabian Sea generally increased with height. while that for run eJiJ not show a systematic change with height. At bot h the local ions. the total concentration o f drops decreasedwith height. The maritime dist ributions were bimodal at all levels while those o..-er Punc were usually unimodal.The average values of liquid water content. mean vo lume diameter. dispersion and conccnt rarion of drops withdiameter > 50 «m were a lin le greater and total concentration a little smaller over the maritime region as ' om'pared to those over inland. The co ncentrations of drops with diameter < 14 ,...m and those > 78 I'm and thema ximum ~ i 7e were greater over Pune than o..er the sea. The ..'a riarions in cloud drop spectra and the clo udphysical parameters over beth the locations are discussed.Kc) words - Cloud drop size spectra, Drop co ncentration,

Convective and turbulent motions in non-precipitating Cu. Part II: LES simulated cloud represented by a starting plume

The dynamic structure of a small trade-wind Cu is analyzed using a novel approach. Cu developing in a shear-free environment was simulated by 10 m-resolution LES model with spectral bin microphysics. The aim is to clarify the dynamical nature of cloud updraft zone (CUZ) including entrainment and mixing in growing Cu. The validity of concept stating that a cloud at developing state can be represented by a parcel or a jet is tested. To investigate dynamical entrainment in CUZ performed by motions with scales larger than the turbulence scales, the modeled fields of air velocity were filtered by wavelet filter which separated convective motions from turbulent ones. Two types of objects in developing cloud were investigated: small volume ascending at maximal velocity (point parcel) and CUZ. It was found that the point parcel representing the upper part of cloud core is adiabatic. The motion of the air in this parcel ascending from cloud base determines cloud top height. The top hat (i.e., averaged) values of updraft velocity and adiabatic fraction in CUZ are substantially lower than those in the point parcel. Evaluation of the terms in the dynamical equation typically used in 1D cloud parcel models show that this equation can be applied for calculation of vertical velocities at the developing stage of small Cu, at least up to the heights of the inversion layer. Dynamically, the CUZ of developing cloud resembles the starting plume with the tail of non-stationary jet. Both the top hat vertical velocity and buoyancy acceleration linearly increase with the height, at least up to the inversion layer. An important finding is that lateral entrainment of convective (non-turbulent) nature has a little effect on the top hat CUZ velocity and cannot explain the vertical changes of conservative variables qt and θl. In contrast, entrained air lifting inside CUZ substantially decreases top hat liquid water content and its adiabatic fraction. Possible reasons of these effects are discussed.

Measurement report: Characterization and source apportionment of coarse particulate matter in Hong Kong: Insights into the constituents of unidentified mass and source origins in a coastal city in southern China

Coarse particulate matter (i.e., PM with aerodynamic diameter between 2.5 and 10 micrometers or PMcoarse) has been increasingly recognized of its importance in PM10 regulation because of its growing proportion in PM10 and the accumulative evidence for its adverse health impact. In this work, we present comprehensive PMcoarse speciation results obtained through a one-year long (January 2020–February 2021) joint PM10 and PM2.5 chemical speciation study in Hong Kong, a coastal and highly urbanized city in southern China. The annual average concentration of PMcoarse is 14.9 ± 8.6 μg m–3 (±standard deviation), accounting for 45 % of PM10 (32.9 ± 18.5 μg m–3). The measured chemical components explain ~75 % of the PMcoarse mass. The unexplained part is contributed by unmeasured geological components and residue liquid water content, supported by analyses by positive matrix factorization (PMF) and the thermodynamic equilibrium model ISORROPIA II. The PMcoarse mass is apportioned to four sources resolved by PMF, namely soil dust, copper-rich dust, fresh sea salt, and an aged sea salt factor containing secondary inorganic aerosols (mostly nitrate). Back-trajectory cluster analysis reveals significant variations in source contributions with the air mass origin. Under the influence of marine air mass, PMcoarse is the lowest (average = 8.0 μg m–3) and sea salt is the largest contributor (47 %), followed by the two dust factors (38 % in total). When the site receives air mass from the northern continental region, PMcoarse increased substantially to 21.2 μg m–3, with the two dust factors contributing 90 % of the aerosol mass. The potential dust source areas are mapped using the Concentration-Weighted Trajectory technique, showing either the Greater Bay Area or the greater part of southern China as the origin of fugitive dust emissions leading to elevated ambient PMcoarse loadings in Hong Kong. This study, first of this kind in our region, provides highly relevant guidance to other locations with similar monitoring needs. Additionally, the study findings point to the needs for further research on the sources, transport, aerosol processes, and health effects of PMcoarse.

The ability of the ICE-T microphysics scheme in HARMONIE-AROME to predict aircraft icing

In-cloud icing is a major hazard for aviation traffic and forecasting of these events is an important task for weather agencies worldwide. A common tool utilised by aviation forecasters is an icing intensity index based on supercooled liquid water from numerical weather prediction models. We seek to validate the modified microphysics scheme, ICE-T, in the HARMONIE-AROME numerical weather prediction model with respect to aircraft icing. Icing intensities and supercooled liquid water derived from two 3-month winter season simulations with the original microphysics code, CTRL, and ICE-T are compared with pilot reports of icing and satellite retrieved values of liquid and ice water content from CloudSat-CALIPSO and liquid water path from AMSR-2. The results show increased supercooled liquid water and higher icing indices in ICE-T. Several different thresholds and sizes of neighbourhood areas for icing forecasts were tested out, and ICE-T captures more of the reported icing events for all thresholds and nearly all neighbourhood areas. With a higher frequency of forecasted icing, a higher false-alarm ratio cannot be ruled out, but is not possible to quantify due to the lack of no-icing observations. The increased liquid water content in ICE-T shows a better match with the retrieved satellite observations, yet the values are still greatly underestimated at lower levels. Future studies should investigate this issue further, as liquid water content also has implications for downstream processes such as the cloud radiative effect, latent heat release, and precipitation.

Urban aerosol chemistry at a land–water transition site during summer – Part 2: Aerosol pH and liquid water content

Particle acidity (aerosol pH) is an important driver of atmospheric chemical processes and the resulting effects on human and environmental health. Understanding the factors that control aerosol pH is critical when enacting control strategies targeting specific outcomes. This study characterizes aerosol pH at a land–water transition site near Baltimore, MD, during summer 2018 as part of the second Ozone Water-Land Environmental Transition Study (OWLETS-2) field campaign. Inorganic fine-mode aerosol composition, gas-phase NH3 measurements, and all relevant meteorological parameters were used to characterize the effects of temperature, aerosol liquid water (ALW), and composition on predictions of aerosol pH. Temperature, the factor linked to the control of NH3 partitioning, was found to have the most significant effect on aerosol pH during OWLETS-2. Overall, pH varied with temperature at a rate of −0.047 K−1 across all observations, though the sensitivity was −0.085 K−1 for temperatures > 293 K. ALW had a minor effect on pH, except at the lowest ALW levels (< 1 µg m−3), which caused a significant increase in aerosol acidity (decrease in pH). Aerosol pH was generally insensitive to composition (SO42-, SO42-:NH4+, total NH3 (Tot-NH3) = NH3 + NH4+), consistent with recent studies in other locations. In a companion paper, the sources of episodic NH3 events (95th percentile concentrations, NH3 > 7.96 µg m−3) during the study are analyzed; aerosol pH was higher by only ∼ 0.1–0.2 pH units during these events compared to the study mean. A case study was analyzed to characterize the response of aerosol pH to nonvolatile cations (NVCs) during a period strongly influenced by primary Chesapeake Bay emissions. Depending on the method used, aerosol pH was estimated to be either weakly (∼ 0.1 pH unit change based on NH3 partitioning calculation) or strongly (∼ 1.4 pH unit change based on ISORROPIA thermodynamic model predictions) affected by NVCs. The case study suggests a strong pH gradient with size during the event and underscores the need to evaluate assumptions of aerosol mixing state applied to pH calculations. Unique features of this study, including the urban land–water transition site and the strong influence of NH3 emissions from both agricultural and industrial sources, add to the understanding of aerosol pH and its controlling factors in diverse environments.

Inter and intra-seasonal, variation of thermodynamic parameters of the atmosphere over coastal Tamilnadu during northeast monsoon

The thermodynamic structure of the atmosphere over coastal Tamilnadu during the northeast monsoon season has been studied in detail based on the daily 0000 UTC upper air data between 1000 and 500 hPa levels of Madras for October-January for the l0 year period 1976-77 to 1985-86. Normal upper air soundings have been computed for dry and wet spells of northeast monsoon and for the brief period of southwest monsoon prior to northeast monsoon onset. The moisture flux crossing Madras and the liquid water content over Madras have been computed for various categories of monsoon activity. It has been shown that the onset of easterlies over Madras is accompanied by a cooling of 1C of the atmosphere over Madras at all levels upto 500 hPa. An east to west moisture flux of 21.1 x 108 metric tons per day across one degree wall over Madras has been found to cross coast during typical wet spell of northeast monsoon. The moisture flux crossing coast for good northeast monsoon and also the normal flux computed for the period of study compared fairly well with the moisture flux crossing west coast during southwest monsoon obtained in various other studies. The energy of an air column over coastal Tamilnadu was found to decrease subsequent to the onset of northeast monsoon. Analysis of variation of liquid water content revealed that even during deficit rainfall years there was considereable amount of low level moisture in the atmosphere. Neither during dryspells of northeast monsoon nor after its retreat was there any clear sign of spreading of continental air mass over coastal Tamilnadu.

Measurement report: Impact of African aerosol particles on cloud evolution in a tropical montane cloud forest in the Caribbean

African aerosol particles, traveling thousands of kilometers before reaching the Americas and the Caribbean, directly scatter and absorb solar radiation and indirectly impact climate by serving as cloud condensation nuclei (CCN) or ice-nucleating particles (INPs) that form clouds. These particles can also affect the water budget by altering precipitation patterns that subsequently affect ecosystems. As part of the NSF-funded Luquillo Critical Zone Observatory, field campaigns were conducted during the summers of 2013 (23 d), 2014 (11 d), and 2015 (92 d) at Pico del Este, a site in a tropical montane cloud forest on the Caribbean Island of Puerto Rico. Cloud microphysical properties, which included liquid water content, droplet number concentration, and droplet size, were measured. Using products from models and satellites, as well as in situ measurements of aerosol optical properties, periods of high- and low-dust influence were identified. The results from this study suggest that meteorology and air mass history have a more important effect on cloud processes than aerosols transported from Africa. In contrast, air masses that arrived after passing over the inhabited islands to the southeast led to clouds with much higher droplet concentrations, presumably due to aerosols formed from anthropogenic emissions.

A kriging-based analysis of cloud Liquid Water Content using CloudSat data

Spatiotemporal statistical learning has received increased attention in the past decade, due to spatially and temporally indexed data proliferation, especially collected from satellite remote sensing. In the mean time, observational studies of clouds are recognized as an important step to improve cloud representation in weather and climate models. Since 2006, the satellite CloudSat of NASA carries a 94 GHz cloud profiling radar and is able to retrieve, from radar reflectivity, microphysical parameter distribution such as water or ice content. The collected data is piled up with the successive satellite orbits of nearly two hours, leading to a large compressed database of 2 Tb (http://cloudsat.atmos.colostate.edu/). These observations give the opportunity to extend the cloud microphysical properties beyond the actual measurement locations using an interpolation and prediction algorithm. In order to do so, we introduce a statistical estimator based on the spatiotemporal covariance and mean of the observations known as kriging. An adequate parametric model for the covariance and the mean is chosen from an exploratory data analysis. Beforehand, it is necessary to estimate the parameters of this spatiotemporal model; This is performed in a Bayesian setting. The approach is then applied to a subset of the CloudSat dataset.