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This study derives polarimetric radar vertical profiles and microphysical retrievals for 25 Synoptic Snow (SS) and 23 Lake Effect Snow (LES) cases using the Range‐Defined Quasi‐Vertical Profiles (RD‐QVP), Columnar Vertical Profiles (CVP), and Process‐oriented Vertical Profiles (POVP) methods. For all vertical profile techniques, SS cases exhibit a near‐linear increase in reflectivity from −30 to 0°C whereas ZDR and Kdp locally peak in the dendritic growth layer. LES cases universally exhibit negative ZDR, rather high Z, negligible Kdp, and near‐unity ρhv. Ground measurements from the past OWLeS campaign provide direct evidence that conical graupel may strongly affect these polarimetric measurements in LES bands. Aggregation efficiencies for SS cases are estimated by optimizing the theoretical number concentration (Nt) and mean volume diameter (Dm) steady‐state vertical profiles against radar‐retrieved profiles derived from 20 of the 25 synoptic storm RD‐QVPs. The median estimated aggregation efficiency is approximately 0.15 with a relatively narrow interquartile range that spans from 0.1 to just over 0.2. Values of optimized aggregation efficiencies are nearly independent of the assumed gamma distribution shape parameter. These results are used to derive temperature‐dependent, climatological steady‐state relations for vertical profiles of Nt, Dm, and liquid‐equivalent snowfall rates. These results can be used in numerical weather prediction model aggregation parameterizations and can also provide climatologically representative vertical profiles of radar and microphysical quantities. Plain Language Summary: This study documents the climatology of the vertical profiles of polarimetric radar variables and microphysical parameters in synoptic snow (SS) and lake effect snow (LES) using polarimetric radars in the U.S. The SS vertical profiles show a generally enhanced signal from cloud top to the surface and a noticeable dendritic growth layer signature near −15°C. As for LES vertical profiles, we noticed a negative ZDR pattern with strong Z and weak KDP signals. Further investigation reveals the existence of conical graupel that caused negative ZDR near ground level. This study also summarizes estimated aggregation efficiencies for the SS cases. It shows that the aggregation efficiencies are nearly independent of the commonly used gamma distribution shape parameter. Equations are derived for representing parameters and vertical profiles resulting from aggregation. The overall work from this study provides climatologically representative vertical profiles of radar and microphysical quantities, and can be used as a reference for model parameterization improvement. Key Points: Climatological vertical profiles of synoptic snow and lake effect snow are summarized using polarimetric radarsLake effect snow exhibits negative values of ZDR which are caused by conical graupelSynoptic snow aggregation efficiencies are estimated by combining radar climatology with theoretical relations [ABSTRACT FROM AUTHOR]

Based on the data o£ daily snowfall and weather phenomena of 11 national meteorological stations in Ulanqab City from 1991 to 2020, the spatial and temporal distribution characteristics of snowstorm were analyzed. The results show that the snowstorm in Ulanqab had obvious seasonal distribution characteristics, mainly happening in spring (March - May) and autumn (September - November). It also had obvious regional distribution in space, and the snowstorm center appeared in Chahar Right Wing Middle Banner and lining District, namely the east side of the Yinshan Mountain. In the past 30 years, the amount of snowstorm in the whole year in Ulanqab showed a certain fluctuation trend, and the number of snowstorm days had shown an obvious upward trend since 2011. [ABSTRACT FROM AUTHOR]

It is a challenge to obtain accurate measurements of the microphysical properties of delicate, structurally complex, frozen, and semi-frozen hydrometeors. We present a new technique for the real-time measurement of the density of freshly fallen individual snowflakes. A new thermal-imaging instrument, the Differential Emissivity Imaging Disdrometer (DEID), has been shown through laboratory and field experiments to be capable of providing accurate estimates of individual snowflake and bulk snow hydrometeor density (which can be interpreted as the snow-to-liquid ratio or SLR). The method exploits the rate of heat transfer during the melting of a hydrometeor on a heated metal plate, which is a function of the temperature difference between the hotplate surface and the top of the hydrometeor. The product of the melting speed and melting time yields an effective particle thickness normal to the hotplate surface, which can then be used in combination with the particle mass and area on the plate to determine a particle density. Uncertainties in estimates of particle density are approximately 4 % based on calibrations with laboratory-produced particles made from water and frozen solutions of salt and water and field comparisons with both high-resolution imagery of falling snow and traditional snowpack density measurements obtained at 12 h intervals. For 17 storms, individual particle densities vary from 19 to 495 kg m -3 , and storm mean snow densities vary from 40 to 100 kg m -3. We observe probability distribution functions for hydrometeor density that are nearly Gaussian with kurtosis of ≈ 3 and skewness of ≈ 0.01. [ABSTRACT FROM AUTHOR]

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Knowledge of the effect of harsh weather on the phenotypic traits of organisms is essential for understanding the environmental influence on phenotype evolution and holds implications for predicting how species respond to current climate change. For many birds, harsh weather in winter often imposes a strong selective effect on their survival, and only the individuals with certain phenotypes may survive. However, whether the selective effect on phenotype varies with winter weather conditions has been poorly investigated. Here, we explored the selective effect of winter weather on black-throated tit's (Aegithalos concinnus) morphological traits under winters with and without severe snowstorms. We found that for males, the sizes of their bills, heads and wings significantly affected their overwinter survival, but the effects varied with winter conditions. In relatively benign winters, males with smaller bill depths, smaller bill surface areas, and greater head lengths survived better; whereas, in winters with severe snowstorms, a reverse pattern was found. This phenomenon was likely driven by selection pressures from heat retention and foraging requirements, with their relative importance depending on winter conditions. Additionally, wing length was positively correlated with male survival and the relationship was stronger in harsher winters, which was probably due to longer wings' higher flight efficiency in adverse weather. By contrast, we found no correlation between morphological traits and survival in females. These results suggest a sex-specific and condition-dependent selective effect of environment on bird phenotypes, implying complicated interactions between different selection pressures and phenotype evolution. [ABSTRACT FROM AUTHOR]

Lake‐effect snow (LES) storms, characterized by heavy convective precipitation downwind of large lakes, pose significant coastal hazards with severe socioeconomic consequences in vulnerable areas. In this study, we investigate how devastating LES storms could evolve in the future by employing a storyline approach, using the LES storm that occurred over Buffalo, New York, in November 2022 as an example. Using a Pseudo‐Global Warming method with a fully three‐dimensional two‐way coupled lake‐land‐atmosphere modeling system at a cloud‐resolving 4 km resolution, we show a 14% increase in storm precipitation under the end‐century warming. This increase in precipitation is accompanied by a transition in the precipitation form from predominantly snowfall to nearly equal parts snowfall and rainfall. Through additional simulations with isolated atmospheric and lake warming, we discerned that the warmer lake contributes to increased storm precipitation through enhanced evaporation while the warmer atmosphere contributes to the increase in the storm's rainfall, at the expense of snowfall. More importantly, this shift from snowfall to rainfall was found to nearly double the area experiencing another winter hazard, Rain‐on‐Snow. Our study provides a plausible future storyline for the Buffalo LES storm, focusing on understanding the intricate interplay between atmospheric and lake warming in shaping the future dynamics of LES storms. It emphasizes the importance of accurately capturing the changing lake‐atmosphere dynamics during LES storms under future warming. Plain Language Summary: A lake‐effect snow (LES) storm is a heavy snowfall that occurs when a cold dry air mass travels over a relatively warm lake. LES storms have been particularly known to decimate regions downwind of the North American Great Lakes with several meters of snow and millions of dollars in damages. In this study, we use a fully 3D comprehensive lake‐land‐atmosphere modeling system, along with the Pseudo‐Global Warming technique that incorporates large‐scale climate changes into our simulation, to investigate how such devastating LES storms could unfold in a warming climate. We used the LES storm that hit Buffalo, New York in November 2022 as a case study. Our results revealed that under a warmer future climate, LES storms can produce a higher precipitation amount by up to 14%. More notably, our results showed a transition in the form of storm precipitation from mostly snowfall to nearly equal parts snowfall and rainfall. The warmer lake in the future was found to be the primary reason behind the increase in precipitation through enhanced evaporation from the lake. The warmer atmosphere in the future explained why rainfall replaced snowfall in the LES storm. Key Points: Future of lake‐effect snow storms is explored using Pseudo‐Global Warming with a 3D two‐way coupled lake‐land‐atmosphere modeling systemFuture climate amplifies storm precipitation via higher lake evaporation and boosts rainfall at snowfall's expense via a warmer atmosphereLake evaporation plays a critical role in storm precipitation amount and accurately resolving the future lake‐atmosphere dynamics is vital [ABSTRACT FROM AUTHOR]

Based on the observation data of meteorological stations, Doppler radar observation data of Ulanqab City, and ERA-5 reanalysis data, a snowstorm process in Ulanqab City from March 17 to 18, 2022 was analyzed. The results show that this was a type II snowstorm process generated under the joint influence of upper trough and ground low inverted trough and frontal cyclone. The main period of snowfall can be divided into two time stages, and the total snowfall was more in the south and less in the north, which was consistent with that of average specific humidity field. Water vapor conditions provided by strong water vapor transport and convergence, strong upward movement shown by large vertical velocity field, and the suction action of highand low-layer divergence and convergence were the reasons for the hourly heavy snowfall on the 18"'. During the process, radar echoes were mainly sheetshaped, and composite reflectivity was 15 -25 dBZ in most areas. The zero speed line in the first period was positively "S" -shaped, and there was warm advection and southwest wind. On the morning of the 18"', after the cold front transited the city, Ulanqab City was gradually controlled by northwest wind, and the snow tended to end. [ABSTRACT FROM AUTHOR]

Background: Diffuse sclerosing variant of papillary thyroid carcinoma (DSVPTC) is a rare but high invasive subtype of papillary thyroid carcinoma, which mandates an aggressive clinical strategy. Few studies have focused on the sonographic characteristics of DSVPTC and the role of ultrasound in diagnosis and treatment of this variant remains unknown. This study aimed to identify and understand DSVPTC more accurately under ultrasound in correlation with pathology. Methods: The ultrasound characteristics and histopathologic sections of 10 lesions in 10 DSVPTC patients who underwent thyroid surgery at our center between 2014 and 2020 were reviewed and compared with 184 lesions in 168 classic variant of papillary thyroid carcinoma (cPTC) patients. Results: 6 DSVPTC cases (60%) showed the "snowstorm" pattern on sonogram and 4 cases (40%) presented hypoechoic solid nodules only. Vague borders (100.0% vs. 18.5%, P = 0.019) and abundant microcalcifications (66.7% vs. 10.9%, P = 0.037) were more common in DSVPTC nodules than in cPTC nodules, corresponding to the infiltrating boundaries and numerous psammoma bodies under the microscope respectively. Most of the DSVPTC cases had a heterogeneous background (80%) and suspicious metastatic cervical lymph nodes (80%) on sonograms. All DSVPTC cases had histopathological metastatic cervical lymph nodes. Conclusion: The sonographic "snowstorm" pattern indicated DSVPTC with whole-lobe occupation. Hypoechoic solid nodules with vague borders and abundant microcalcifications on sonogram suggested DSVPTC lesion with an ongoing invasion. Regardless of which of the two sonograms was shown, the corresponding DSVPTC lesions were aggressive and required the same attention from the surgeons. [ABSTRACT FROM AUTHOR]

The complexity of ice particles in the atmosphere makes it difficult to model microphysical growth processes accurately. In this study, we simulated a snowfall case over Northern China Plain using two different microphysics schemes, that is, Thompson and Morrison schemes, in the Advanced Research WRF (Weather Research and Forecasting) model. Both schemes are able to reproduce the event, albeit with a slightly weaker precipitation compared with the surface observation. However, the radar reflectivity factor in Morrison simulation is higher than the radar observation to ∼10 dBZ. Further analysis reveals that such stronger radar reflectivity in the Morrison simulation might be caused by larger collection efficiency, which would lead to more active self‐aggregation process in prediction of snow number concentration and then larger snow particle size. Sensitivity tests show that using an alternative formula of collection efficiency produces smaller radar reflectivity that is in better agreement with observations. This study highlights the accurate representation of self‐aggregation process and underscores the needs of further improvement of ice microphysics schemes for the better snowfall simulations. Plain Language Summary: Understanding how snow forms in the atmosphere is complicated. We did a case study using two different microphysics schemes in numerical weather model to simulate a snowfall event over Northern China. Both schemes did a pretty good job in simulating the snowfall, but one of them, the Morrison scheme, showed much larger radar signal compared to what was really happening. We do further analysis to find out why this was the case. It turned out that the Morrison scheme simulated the snowflakes stick together more than they actually do in nature. This made the size of snowflakes in the simulation much larger. We ran more tests by changing the way the Morrison scheme making snowflakes stick together. When we did this, the simulation results showed more accurate radar reflectivity factor. So, what did we learn? How the snowflakes stick together is a big deal. If we get it wrong, the models will give us the unreasonable estimation of radar signal. This study helps remind scientists that they need to be very careful when they use these microphysics schemes. Key Points: Radar reflectivity factor from Morrison simulation exceeds 10 dBZ compared with observations, but Thompson scheme performs betterThe overestimation of radar reflectivity factor in Morrison simulation could be attributed to larger snow particlesLarger snow particles in Morrison simulation are caused by active self‐aggregation process of snow and higher collection efficiency [ABSTRACT FROM AUTHOR]

Based on ground observed data, S-band dual-polarization radar data, and ERA-5 reanalysis data, the statistical characteristics of polarimetric parameters and the application of melting layer (ML) and hydrometeor classification (HCL) products during eight snowstorm events in Jiangsu Province from 2020 to 2022 were investigated. A heavy snowstorm that went through different phases of rain, sleet, and pure snow and that occurred on 29 December 2020 was also analyzed as a typical example. The results showed the following: During the phase transition between rain and snow in the Jiangsu region, the basic reflectivity factor ZH ≥ 27 dBZ, the zero-order lag correlation coefficient CC ≤ 0.93, and the differential reflectivity ZDR ≥ 1.0 dB were important indicators for judging the melting layer while the specific differential phase KDP changed slightly. The snowstorm event was well observed and recorded by the Yancheng dual-polarimetric radar, whose low value area of CC coincided mostly with the melting layer. The ML products and HCL products based on fuzzy-logic hydrometeor classification algorithms can help identify the melting layer and the properties of precipitation particles. ML products are more reliable when the melting layer is high and can better show the trends of melting layer decline. They can certainly serve as a reference for detecting and judging precipitation phase changes in winter in Jiangsu Province. [ABSTRACT FROM AUTHOR]

In May 2023, a major snowstorm occurred in Canaan Valley, West Virginia, dropping 20 inches of snow. This event was unusual because it contradicted global and local warming trends that typically decrease snowfall in warmer months. While some people use events like this to deny global warming, there is evidence that extreme weather events are increasing in frequency and intensity alongside overall warming. The Canaan Valley has a cold, humid-type climate, and its high elevation allows for more snowfall. The storm was well-forecasted, and weather watchers can analyze how forecasters handle such unusual events. [Extracted from the article]

In early 2022, there were four low‐temperature weather processes with rain and snow in Hunan Province, China. Two processes occurred on January 28–29 (referred to as the "0128" process) and February 6–7 (referred to as the "0206" process), and they have overlapping areas of heavy snowfall and high intensity of short‐term snowfall. Multi‐source observation data and the National Centers for Environmental Prediction (NCEP) reanalysis data are used to analyze the characteristics of circulation background and mesoscale. In addition, the causes of heavy snowfall processes under the influence of the southern branch trough are discussed based on the dual‐polarization radar products at Changsha station. The results show that two processes are characterized by the rapid phase transformation of rain and snow, concentrated snowfall periods, and heavy snowfall at night. The short‐term snowfall intensity of the "0206" process is greater than that of the "0128" process. The high‐latitude blocking high of the "0206" process is stronger than that of the "0128" process, and the water vapor transport of the southerly jet in low levels in the "0206" process is also stronger. The organized development of cold cloud clusters from the meso‐β scale to the meso‐α scale indicates that the snowfall intensifies, and the maximum blackbody temperature gradient corresponds well to the center of heavy snowfall. The propagation that is similar to the train effect is an important reason for the heavy snowfall process. The vertical variation of the ZH and the bright band of dual‐polarization parameters can determine the phase transformation between rain and snow. When the ZH and ZDR bright bands are 1–3 km away from the ground, the phase state is rain if the ZH near the ground is greater than 0 dBZ and the CC is close to 1; the phase state is the rain‐snow mixed phase if the CC is less than 0.95. When the bottom of the ZH bright band decreases, the CC/ZDR bright band disappears, the near‐surface CC is greater than 0.99 and the ZDR is less than 1 dB, the rain turns to snow. Compared with the "0128" process, the characteristics of the bright ring during the rainfall period of the "0206" process are more obvious, the precipitation intensity judged from the larger ZH and KDP is larger, and the phase transformation is faster due to more significant cooling effect caused by precipitation. [ABSTRACT FROM AUTHOR]

As a major real‐world problem, snow plowing has been studied extensively. However, most studies focus on deterministic settings with little urgency yet enough time to plan. In contrast, we assume a severe snowstorm with little known data and little time to plan. We introduce a novel time‐dependent multi‐visit dynamic safe street snow plowing problem and formulate it on a rolling‐horizon‐basis. To solve this problem, we develop an adaptive large neighborhood search as the underlying method and validate its efficacy on team orienteering arc routing problem benchmark instances. We create real‐world‐based instances for the city of Vienna and examine the effect of (i) different snowstorm movements, (ii) having perfect information, and (iii) different information‐updating intervals and look‐aheads for the rolling horizon method. Our findings show that different snowstorm movements have no significant effect on the choice of rolling horizon settings. They also indicate that (i) larger updating intervals are beneficial, if prediction errors are low, and (ii) larger look‐aheads are better suited for larger updating intervals and vice versa. However, we observe that less look‐ahead is needed when prediction errors are low. [ABSTRACT FROM AUTHOR]

Disaster information content is an objective mapping of disaster situations, social response, and public opinions. Social response to emergency is an important mechanism for implementing and guaranteeing emergency management of major natural hazard-related disasters. Understanding how disaster information content affects social response to emergencies is helpful for managing risk communication and efficient disaster response. Based on the 2008 freezing-rain and snowstorm disasters in southern China, this study used Python to extract 7,857 case-related media reports and applied natural language processing for text analysis. It used three typical cases to identify and analyze disaster media report content and the relationship between these reports and the social response to the emergency. Eight categories of disaster response—such as prewarning and forecasting, announcements by the authorities, and social mobilization—appeared in the disaster information in the media, along with disaster impact information, that is, real-time disaster status. Disaster response information and an appropriate amount of disaster impact information played important roles in prewarning, disaster relief, public opinion guidance, and social stability maintenance and can serve important functions in communicating with all stakeholders of emergency management, assisting or influencing emergency departments or individuals in decision making, and eliminating "information islands." Empathy caused the general public to become "disaster responders" through receiving information. Rumors and an excess of negative information may have a perverse amplification effect on public opinion and increase the unpredictability of the disaster situation and the risk of social crisis. [ABSTRACT FROM AUTHOR]

Because plumage coloration is frequently involved in sexual selection, for both male and female mate choice, birds with aberrant plumage should have fewer mating opportunities and thus lower reproductive output. Here we report an Eastern Bluebird (Sialia sialis) female with a brown phenotype that raised a brood of four chicks to fledging. The brown female and her mate were only related to their social offspring to the second degree and one of the offspring was a half‐sibling. We propose four family tree scenarios and discuss their implications (e.g., extra‐pair paternity, conspecific brood parasitism). Regardless of the tree, the brown female was able to find a mate, which may have been facilitated by the bottleneck created by the severe snowstorms in February 2021. [ABSTRACT FROM AUTHOR]

The Mediterranean Sea is affected by cyclonic activity often associated with extreme weather. Intense snowfall events are rare, but when they occur they can lead to severe impacts especially due to the lack of infrastructure and public awareness. This study focuses on the mechanisms that can trigger extreme snowstorms over the eastern Mediterranean and the quantification of the influence of sea‐surface temperature (SST) anomalies on them. Different scenarios show that positive SST anomalies lead to more severe snowfall over higher altitudes, whereas negative anomalies lead to longer duration of snow cover on lower altitudes and seaside areas. [ABSTRACT FROM AUTHOR]

Due to the unique topography and geographical location, severe snowfall is the main disastrous weather in winter in the Hunan Province of China. Based on the daily precipitation data in Hunan Province from 1961 to 2021, the regional heavy snowfall processes are classified by using the synoptic diagnostic method. In addition, the water vapor transport characteristics of typical heavy snowfall processes are analyzed by the hybrid single-particle Lagrangian integrated trajectory (HYSPLIT) air mass backward trajectory model. Then, the responses of the differences in water vapor transport to heavy snowfall under different weather situations are discussed. The results show that the spatial distribution of climatic mean heavy snowfall days in Hunan Province is extremely uneven, and the heavy snowfall days decrease from north to south, with the most in the Dongting Lake area and the least in the Nanling Mountains. In the past decades, snowstorms mainly occur in local areas, and there are fewer widespread snowstorms. The frequency of heavy snowfall days generally shows a decreasing trend, with three peaks all appearing before 1990. After the 2010s, the number of days and stations of heavy snowfall decreased noticeably, and so did the number of regional heavy snowfall processes. This result indicates that global warming has remarkable effects on the snowstorm events in Hunan Province. Heavy snowfall mainly occurs from December to February, and peaks from mid-January to early February. Over the past 61 years, more than 50% of heavy snowstorm events occurred after 2000. According to the main weather systems affecting regional heavy snowfall processes, these weather processes in Hunan Province can be classified into three categories: southern branch trough (SBT) type, blocking high collapse (BHC) type, and stepped trough type. Among them, the SBT type accounts for more than 60% of the heavy snowfall events in Hunan. In terms of the SBT type and the stepped trough type, the water vapor from the high-latitude inland and low-latitude sea surface accounts for a comparable proportion, each accounting for nearly 50%. For the SBT type, the proportion of the water vapor from warm-humid airflows is slightly higher than that from cold-humid airflows. However, in terms of the stepped trough type, the water vapor transported by cold-humid airflows from the north contributes more than that by warm-humid airflows. For the BHC type, the specific humidity and the water vapor from the high-latitude inland contribute 70% of heavy snowfall processes. In addition, the contribution of the two southwesterly water vapor channels to heavy snowfall processes is small. The water vapor sources differ remarkably for different heavy snowfall types, but all of them are dominated by the water vapor transport in the middle and lower troposphere, which is the main reason why the formation of snowfall areas under different weather types is obviously different. [ABSTRACT FROM AUTHOR]

The role of the Tibetan Plateau (TP) in Asian hydrological climate is crucial, yet there is a lack of quantitative estimates regarding its impact on snowfall in China. Some opinions suggest that the TP functions as a large barrier that obstructs cold outbreaks, protecting southern China from severe snowstorms. Through topography experiments with and without the TP, our study suggests that the TP's presence results in a 60% decrease in snowfall in northern China by significantly reducing moisture. In contrast, it promotes a 1500% increase in snowfall in southern China, particularly from November to March, by drawing cold air from the north and moisture from the south to southern China. The presence of TP significantly enhances winter relative humidity in southern China, causing discomfort for humans. This research refutes some trending views and improves our understanding of the TP's role in China's winter climate. [ABSTRACT FROM AUTHOR]

B This weather map depicts conditions around midnight in January. b Draw isobars every four millibars (996, 1000, 1004 millibars, etc) using the plot model example at the lower right as a guide. No. copies of single issue published nearest to filing date: 3518. g. Copies not distrib-uted. Forecasting heavy snow The weather map shows the classic appearance of a Great Plains or Midwest blizzard. No. copies of single issue published nearest to filing date: 3922. i. Percent paid. [Extracted from the article]

Frequent heavy snowfall in Xinjiang plays an important role in the land water cycle. In this study, 18 groups of simulation experiments are conducted on the heavy snowfall event in Xinjiang during 9–13 December of 2015 using the Weather Research and Forecasting (WRF) model. In these experiments, the combination of six land surface parameterization schemes (the Noah scheme, Noah-MP scheme, RUC scheme, CLM4 scheme, PX scheme, and TD scheme) with three microphysical parameterization schemes (the WSM6 scheme, Thompson scheme, and Lin scheme) are adopted, where the observed snowfall data are used for performance evaluation. Results show that the simulated snowfall intensity and snowfall range in different areas are very sensitive to the selection of the land surface scheme. The snowfall in southern Xinjiang is overestimated by almost all six schemes, where the Noah-MP scheme performs more reasonably than the others. The Noah scheme shows its advantage in northwestern Xinjiang. The three different microphysical schemes vary significantly in producing snowfall amount. The WSM6 scheme produced the largest snowfall amount, and the Lin scheme resulted in the smallest snowfall amount. In addition, the accumulated snowfall amounts above 10 mm are generally underestimated by all six land surface schemes, while the accumulated snowfall amounts below 10 mm are overestimated by most of the schemes. The Noah-MP scheme performs the best in the simulation of the snowfall amount in the whole region. However, the Noah scheme shows an advantage in areas with a large snowfall amount. [ABSTRACT FROM AUTHOR]

Background and Objectives: Psoriatic arthritis (PsA) and gout are conditions sharing several common risk factors. Serum uric acid levels are commonly raised in both, and it is observed that many patients presenting with gout have either clinical or family history of psoriasis. There are case report of overlapping PsA and gout called "Psout." So the objective of this study was to find out ultrasonographic features of gout in patients with PsA. Methods: This was a prospective observational study conducted on 105 PsA patients. Serum uric acid and ultrasonography (USG) with color Doppler of the affected joint were performed to look for the presence of the double contour (DC) sign, snowstorm sign, and erosion that is specific for gout. The sensitivity of "tophus," "snowstorm," and the DC sign-on USG were 46%, 30.3%, and 60.1%, while the specificity was 94.9%, 90.9%, and 91.4%, respectively, for gouty arthritis. The sensitivity, specificity, positive predictive value, and negative predictive value of hyperuricemia (uric acid levels >6.8 mg/dL) were compared with USG findings in diagnosis of psout. Results: The prevalence of gout in PsA was 11.4% (12/105); 10/12, 2/12, 6/12, and 1/12 had DC sign, tophi, erosions, and snowstorm appearance, respectively. The sensitivity, specificity, positive predictive value, and negative predictive value of hyperuricemia in diagnosis of gout in PsA was 33.3%, 86%, 23.5%, and 90.9%, respectively. Conclusion: Psoriasis and gout can co-exist or mimic each other. Good presence of DC sign-on USG is a noninvasive method to diagnose gout in PsA patients. Those patients not responding to treatment for PsA may have co-existing gout, so we recommend USG in all patients with PsA, especially if they are not responding to treatment. [ABSTRACT FROM AUTHOR]

Operating an effective winter road maintenance program is a necessity for cities that face severe winter seasons. Snowstorms leave roads in a slippery surface condition that disrupts traffic flows and compromises drivers' safety. Decision-makers use a variety of tools to control snow and ice on the roads, which include applying anti-icing chemicals before snowstorms, applying deicing substances on fresh snow, and clearing snow off the roads using snowplows. However, the influence of these tools on improving the overall road surface conditions has not been investigated. In this study, a location-specific and event-based framework was utilized to understand the impact of the different weather variables as well as maintenance operations on the variability of the pavement friction coefficients during snowstorms in urban environments. Using multilinear regression and ordinary least squares, friction coefficient models were calibrated. The final model was found to be a good fit for the data (R2 = 0.723). The model showed that the total precipitation during snowstorms, extremely low temperatures, and the potential for black ice formation worsen pavement friction significantly. On the other hand, plowing operations, the application of anti-icing chemicals before snowstorms, and frequent deicing operations all have a statistically significant impact on improving pavement friction. The model presented in this paper can be used to predict pavement friction on urban arterial and collector roads during snowstorms of different magnitudes, which could help the authorities in predicting the road surface conditions during forecasted snowstorms and deciding on the best course of action under these conditions. [ABSTRACT FROM AUTHOR]

In 2021, Snowstorm Uri caused significant damage in Texas, disrupting business and activities, energy distribution, and access to critical resources. To improve the preparedness of vulnerable communities for future extreme events, this study uses SafeGraph data to investigate mobility challenges in Harris County, Texas, during the Snowstorm Uri by aggregating foot traffic and then examining the varied impacts on people of different socioeconomic statuses. Results show that while everyone suffered the same level of mobility constraint during the snowstorm, lower socioeconomic households experienced greater loss of mobility, but had a higher mobility recovery rate. Elderly people were less resilient to mobility recovery. The findings highlight the need for enhancing critical resources and building well-prepared emergency management programs to foster greater adaptability and care for vulnerable groups. [ABSTRACT FROM AUTHOR]