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This paper presents recent efforts to understand the relative accuracies of different instrumentation and gauges with various windshield configurations to measure snowfall. Results from the National Center for Atmospheric Research (NCAR) Marshall Field Site will be highlighted. This site hosts a test bed to assess various solid precipitation measurement techniques and is a joint collaboration between the National Oceanic and Atmospheric Administration (NOAA), NCAR, the National Weather Service (NWS), and Federal Aviation Administration (FAA). The collaboration involves testing new gauges and other solid precipitation measurement techniques in comparison with World Meteorological Organization (WMO) reference snowfall measurements. This assessment is critical for any ongoing studies and applications, such as climate monitoring and aircraft deicing, that rely on accurate and consistent precipitation measurements.

Although precipitation has been measured for many centuries, precipitation measurements are still beset with significant inaccuracies. Solid precipitation is particularly difficult to measure accurately, and wintertime precipitation measurement biases between different observing networks or different regions can exceed 100 %. Using precipitation gauge results from the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), errors in precipitation measurement caused by gauge uncertainty, spatial variability in precipitation, hydrometeor type, crystal habit, and wind were quantified. The methods used to calculate gauge catch efficiency and correct known biases are described. Adjustments, in the form of transfer functions that describe catch efficiency as a function of air temperature and wind speed, were derived using measurements from eight separate WMO-SPICE sites for both unshielded and single-Alter-shielded precipitation-weighing gauges. For the unshielded gauges, the average undercatch for all eight sites was 0.50 mm h−1 (34 %), and for the single-Alter-shielded gauges it was 0.35 mm h−1 (24 %). After adjustment, the mean bias for both the unshielded and single-Alter measurements was within 0.03 mm h−1 (2 %) of zero. The use of multiple sites to derive such adjustments makes these results unique and more broadly applicable to other sites with various climatic conditions. In addition, errors associated with the use of a single transfer function to correct gauge undercatch at multiple sites were estimated.

Precipitation forecasts made by Numerical Weather Prediction (NWP) models are typically verified using precipitation gauge observations that are often prone to the wind‐induced undercatch of solid precipitation. Therefore, apparent model biases in solid precipitation forecasts may be due in part to the measurements and not the model. To reduce solid precipitation measurement biases, adjustments in the form of transfer functions were derived within the framework of the World Meteorological Organization Solid Precipitation Inter‐Comparison Experiment (WMO‐SPICE). These transfer functions were applied to single‐Alter shielded gauge measurements at selected SPICE sites during two winter seasons (2015–2016 and 2016–2017). Along with measurements from the WMO automated field reference configuration at each of these SPICE sites, the adjusted and unadjusted gauge observations were used to analyze the bias in a Global NWP model precipitation forecast. The verification of NWP winter precipitation using operational gauges may be subject to verification uncertainty, the magnitude and sign of which varies with the gauge‐shield configuration and the relation between model and site‐specific local climatologies. The application of a transfer function to alter‐shielded gauge measurements increases the amount of solid precipitation reported by the gauge and therefore reduces the NWP precipitation bias at sites where the model tends to overestimate precipitation, and increases the bias at sites where the model underestimates the precipitation. This complicates model verification when only operational (non‐reference) gauge observations are available. Modelers, forecasters, and climatologists must consider this when comparing modeled and observed precipitation. The verification of NWP winter precipitation using operational gauge is affected by wind‐induced undercatch. In the absence of a reference (DFAR), the application of a transfer function to (SA) gauge measurements partially corrects the undercatch, but introduces an additional source of uncertainty on verification results. The adjustment increases the amount of observed solid precipitation, and therefore reduces the NWP bias at sites where the model tends to overestimate precipitation, and increases the bias at sites where the model tends to underestimate precipitation. The issue is illustrated at SPICE sites in various climate regimes, which have the highest quality solid precipitation measurements that are available.

Accurate snowfall measurements are necessary for meteorology, hydrology, and climate research. Typical uses include creating and calibrating gridded precipitation products, the verification of model simulations, driving hydrologic models, input into aircraft deicing processes, and estimating streamflow runoff in the spring. These applications are significantly impacted by errors in solid precipitation measurements. The recent WMO Solid Precipitation Intercomparison Experiment (SPICE) attempted to characterize and reduce some of the measurement uncertainties through an international effort involving 15 countries utilizing over 20 types and models of precipitation gauges from various manufacturers. Key results from WMO-SPICE are presented herein. Recent work and future research opportunities that build on the results of WMO-SPICE are also highlighted.

Weighing precipitation gauges are used widely for the measurement of all forms of precipitation, and are typically more accurate than tipping-bucket precipitation gauges. This is especially true for the measurement of solid precipitation; however, weighing precipitation gauge measurements must still be adjusted for undercatch in snowy, windy conditions. In WMO-SPICE (World Meteorological Organization Solid Precipitation InterComparison Experiment), different types of weighing precipitation gauges and shields were compared, and adjustments were determined for the undercatch of solid precipitation caused by wind. For the various combinations of gauges and shields, adjustments using both new and previously existing transfer functions were evaluated. For most of the gauge and shield combinations, previously derived transfer functions were found to perform as well as those more recently derived. This indicates that wind shield type (or lack thereof) is more important in determining the magnitude of wind-induced undercatch than the type of weighing precipitation gauge. It also demonstrates the potential for widespread use of the previously developed transfer functions. Another overarching result was that, in general, the more effective shields, which were associated with smaller unadjusted errors, also produced more accurate measurements after adjustment. This indicates that although transfer functions can effectively reduce measurement biases, effective wind shielding is still required for the most accurate measurement of solid precipitation.

Heated tipping-bucket (TB) gauges are used broadly in national weather monitoring networks, but their performance for the measurement of solid precipitation has not been well characterized. Manufacturer-provided TB gauges were evaluated at five test sites during the World Meteorological Organization Solid Precipitation Intercomparison Experiment (WMO-SPICE), with most gauge types tested at more than one site. The test results were used to develop and evaluate adjustments for the undercatch of solid precipitation by heated TB gauges. New methods were also developed to address challenges specific to measurements from heated TB gauges. Tipping-bucket transfer functions were created specifically to minimize the sum of errors over the course of the adjusted multiseasonal accumulation. This was based on the hypothesis that the best transfer function produces the most accurate long-term precipitation records, rather than accurate catch efficiency measurements or accurate daily or hourly precipitation measurements. Using this new approach, an adjustment function derived from multiple gauges was developed that performed better than traditional gauge-specific and multigauge catch efficiency derived adjustments. Because this new multigauge adjustment was developed using six different types of gauges tested at five different sites, it may be applicable to solid precipitation measurements from unshielded heated TB gauges that were not evaluated in WMO-SPICE. In addition, this new method of optimizing transfer functions may be useful for other types of precipitation gauges, as it has many practical advantages over the traditional catch efficiency methods used to derive undercatch adjustments.

Background and Objectives: Coronavirus disease-2019 (COVID-19) posed unique challenges worldwide, underscoring important gaps in healthcare preparedness for patients receiving immunosuppressive therapies, such as the individuals with axial spondyloarthritis (axSpA), a subgroup of spondyloarthritis (SpA) characterized by chronic inflammation and immune dysregulation. While global registry data exist for SpA, specific data on axSpA alone remain scarce, especially in Central and Eastern European populations. This study aims to identify predictive factors for severe COVID-19 outcomes and provide a descriptive analysis of axSpA patients infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), using real-world data from the Romanian Registry of Rheumatic Diseases (RRBR). Materials and Methods: This is a three-year retrospective observational cohort study that included 5.786 axSpA patients from the RRBR, of whom 183 (3.16%) were diagnosed with SARS-CoV-2 infection. Data were analyzed using R V4.4.1 and performing univariate and multivariate binary logistic regression to estimate associations using odds ratios (ORs), 95% confidence intervals (CIs), and p-values. A backward selection algorithm was applied to create the final predictive model, accounting for multicollinearity through variance inflation factors (VIFs). Results: The mean age of patients was 48.19 ± 12.26 years, with male predominance (64.5%). Serious COVID-19 (encompassing moderate to critical cases) occurred in 46 cases, with age ≥ 52.5 years (OR 2.64, 95% CI: 1.28–5.48, p = 0.009) and arterial hypertension (OR 2.57, 95% CI: 1.29–5.16, p = 0.007) identified as significant predictors. Individuals with advanced education levels had nearly three times lower odds of experiencing serious COVID-19 (OR 0.38, 95% CI: 0.18–0.76, p = 0.008). Furthermore, our findings confirm the lack of association between HLA-B27 and COVID-19 severity (p = 0.194), contributing to the ongoing discussion regarding its potential immunological role. Moreover, irrespective of the biological therapy administered, the likelihood of experiencing serious SARS-CoV-2 outcomes was not statistically significant (p = 0.882). In the final predictive model, only older age and higher education were deemed as predictive factors. Conclusions: This study highlights key predictors of COVID-19 severity in axSpA patients and emphasizes the protective role of higher education, an underexplored determinant of health outcomes in inflammatory diseases. The lessons learned during these last years can shape a more informed and compassionate healthcare system.

Hemochromatosis is a genetic disorder characterized by increased iron storage in various organs with progressive multisystemic damage. Despite the reports dating back to 1865, the diagnosis of hemochromatosis poses a challenge to clinicians due to its non-specific symptoms and indolent course causing significant delay in disease recognition. The key organ that is affected by iron overload is the liver, suffering from fibrosis, cirrhosis or hepatocellular carcinoma, complications that can be prevented via early diagnosis and treatment. This review aims to draw attention to the pitfalls in diagnosing hemochromatosis. We present a case with multiorgan complaints, abnormal iron markers and a consistent genetic result. We then examine the relevant literature and discuss hemochromatosis subtypes and liver involvement, including transplant outcome and treatment options. In summary, hemochromatosis remains difficult to diagnose due to its symptom heterogeneity and rarity; thus, further education for practitioners of all disciplines is useful in facilitating its early recognition and management.

Integrated Care Settings (ICS) provide a holistic approach to the transition from chronic kidney disease into renal replacement therapy (RRT), offering at least both types of dialysis. To analyze which factors determine type of referral, modality provision and dialysis start on final RRT in ICS clinics. Retrospective analysis of 626 patients starting dialysis in 25 ICS clinics in Poland, Hungary and Romania during 2012. Scheduled initiation of dialysis with a permanent access was considered as planned RRT start. Modality information (80% of patients) and renal education (87%) were more frequent (p<0.001) in Planned (P) than in Non-Planned (NP) start. Median time from information to dialysis start was 2 months. 89% of patients started on hemodialysis, 49% were referred late to ICS (<3 months from referral to RRT) and 58% were NP start. Late referral, non-vascular renal etiology, worse clinical status, shorter time from information to RRT and less peritoneal dialysis (PD) were associated with NP start (p<0.05). In multivariate logistic regression analysis, P start (p≤0.05) was associated with early referral, eGFR >8.2 ml/min, >2 months between information and RRT initiation and with vascular etiology after adjustment for age and gender. \"Optimal care,\" defined as ICS follow-up >12 months plus modality information and P start, occurred in 23%. Despite the high rate of late referrals, information and education were widely provided. However, NP start was high and related to late referral and may explain the low frequency of PD.