The application of numerical modelling of the snowpack in support of avalanche hazard prediction is increasing. Modelling, in complement to direct observations and weather forecasting, provides ...information otherwise unavailable on the present and future state of the snowpack and its mechanical stability. However, there is often a perceived mismatch between the capabilities of modelling tools developed by research organizations and implemented by some operational services, and the actual operational use of those by avalanche forecasters. This causes frustration on both sides. By summarizing currently implemented modelling tools specifically designed for avalanche forecasting, we intend to diminish and contribute to bridging this gap. We highlight specific features and potential added value, as well as challenges preventing a more widespread use of these modelling tools. Lessons learned from currently used methods are explored and provided, as well as prospects for the future, including a list of the most critical issues to be addressed.
Lightning is responsible for the most area annually burned by wildfires in the extratropical region of the Northern Hemisphere. Hence, predicting the occurrence of wildfires requires reliable ...forecasting of the chance of cloud-to-ground lightning strikes during storms. Here, we describe the development and verification of a probabilistic lightning-strike algorithm running on a uniform 20 km grid over the continental USA and Alaska. This is the first and only high-resolution lightning forecasting model for North America derived from 29-year-long data records. The algorithm consists of a large set of regional logistic equations parameterized on the long-term data records of observed lightning strikes and meteorological reanalysis fields from NOAA. Principal Component Analysis was employed to extract 13 principal components from a list of 611 potential predictors. Our analysis revealed that the occurrence of cloud-to-ground lightning strikes primarily depends on three factors: the temperature and geopotential heights across vertical pressure levels, the amount of low-level atmospheric moisture, and wind vectors. These physical variables isolate the conditions that are favorable for the development of thunderstorms and impact the vertical separation of electric charges in the lower troposphere during storms, which causes the voltage potential between the ground and the cloud deck to increase to a level that triggers electrical discharges. The results from a forecast verification using independent data showed excellent model performance, thus making this algorithm suitable for incorporation into models designed to forecast the chance of wildfire ignitions.
Acute respiratory distress syndrome (ARDS) is a leading cause of morbidity and mortality in polytrauma patients. Pharmacological treatments of ARDS are lacking, and ARDS patients rely on supportive ...care. Accurate diagnosis of ARDS is vital for early intervention and improved outcomes but is presently delayed up to days. The use of biomarkers for early identification of ARDS development is a potential solution. Inflammatory mediators high-mobility group box 1 (HMGB1), syndecan-1 (SDC-1), and C3a have been previously proposed as potential biomarkers. For this study, we analyzed these biomarkers in animals undergoing smoke inhalation and 40% total body surface area burns, followed by intensive care for 72 h post-injury (PI) to determine their association with ARDS and mortality. We found that the levels of inflammatory mediators in serum were affected, as well as the degree of HMGB1 and Toll-like receptor 4 (TLR4) signal activation in the lung. The results showed significantly increased HMGB1 expression levels in animals that developed ARDS compared with those that did not. Receiver operating characteristic (ROC) analysis showed that HMGB1 levels at 6 h PI were significantly associated with ARDS development (AUROC=0.77) and mortality (AUROC=0.82). Logistic regression analysis revealed that levels of HMGB1 ≥24.10 ng/ml are associated with a 13-fold higher incidence of ARDS OR:13.57 (2.76-104.3), whereas the levels of HMGB1 ≥31.39 ng/ml are associated with a 12-fold increase in mortality OR: 12.00 (2.36-93.47). In addition, we found that mesenchymal stem cell (MSC) therapeutic treatment led to a significant decrease in systemic HMGB1 elevation but failed to block SDC-1 and C3a increases. Immunohistochemistry analyses showed that smoke inhalation and burn injury induced the expression of HMGB1 and TLR4 and stimulated co-localization of HMGB1 and TLR4 in the lung. Interestingly, MSC treatment reduced the presence of HMGB1, TLR4, and the HMGB1-TLR4 co-localization. These results show that serum HMGB1 is a prognostic biomarker for predicting the incidence of ARDS and mortality in swine with smoke inhalation and burn injury. Therapeutically blocking HMGB1 signal activation might be an effective approach for attenuating ARDS development in combat casualties or civilian patients.
In 2008 the National Institutes of Health established the Research, Condition and Disease Categorization Database (RCDC) that reports the amount spent by NIH institutes for each disease. Its goal is ...to allow the public "to know how the NIH spends their tax dollars," but it has been little used. The RCDC for 2018 was used to assess 428 schizophrenia-related research projects funded by the National Institute of Mental Health. Three senior psychiatrists independently rated each on its likelihood ("likely", "possible", "very unlikely") of improving the symptoms and/or quality of life for individuals with schizophrenia within 20 years. At least one reviewer rated 386 (90%), and all three reviewers rated 302 (71%), of the research projects as very unlikely to provide clinical improvement within 20 years. Reviewer agreement for the "very unlikely" category was good; for the "possible" category was intermediate; and for the "likely" category was poor. At least one reviewer rated 30 (7%) of the research projects as likely to provide clinical improvement within 20 years. The cost of the 30 projects was 5.5% of the total NIMH schizophrenia-related portfolio or 0.6% of the total NIMH budget. Study results confirm previous 2016 criticisms that the NIMH schizophrenia-related research portfolio disproportionately underfunds clinical research that might help people currently affected. Although the results are preliminary, since the RCDC database has not previously been used in this manner and because of the subjective nature of the assessment, the database would appear to be a useful tool for disease advocates who wish to ascertain how NIH spends its public funds.
It has been claimed that the National Institute of Mental Health (NIMH) budget, which traditionally has been evenly balanced between basic and clinical research, has shifted sharply and that 90% of ...NIMH resources are funding basic research. The authors used public data sources to assess this claim: the Research Condition and Disease Categorization Database, ClinicalTrials.gov, and the NIMH Strategic Plan for Research for 2020–2024. From 2016 to 2019, NIMH expenditures on bipolar disorder research decreased 25%, and those for schizophrenia research decreased 17.5%. From 2003 to 2019, NIMH support for treatment trials for schizophrenia, bipolar disorder, and major depressive disorder decreased 90%. NIMH’s Strategic Plan for Research for 2020–2024 suggests that the shift toward basic research will continue. Because NIMH’s primary purpose is to develop better treatments for current patients as well as future ones, the authors recommend that the ratio of basic to clinical research be readjusted to approximately 50:50.
Abstract
ARDS is one of the leading causes of high morbidity and mortality in trauma patients. Previously our data demonstrated autologous MSCs treatment improved survival in a swine model of smoke ...inhalation and burn injury. However, the pathophysiological mechanisms are still largely unknown.
Twenty anesthetized female swine underwent smoke inhalation injury and 40% TBSA burns, were then randomly assigned to either mock treatment (IC, n=10), or autologous MSCs treatment (MSCs, n=10), followed by ICU care up to 72 hours except in case of early death. Three doses of MSCs collected by bone marrow aspiration and concentrated using a bedside cell concentrator device were applied at 2, 24, and 48 hours of post-injury (PI). Blood and tissue samples were collected for ELISA and IHC analyses.
In IC group, 10/10 injured pigs developed ARDS, but only 6/10 pigs in MSCs group developed ARDS. Serum analysis revealed that the HMGB1 level gradually increased after injury and reached a peak at 48h PI (5.7-fold increase vs. baseline). The SDC-1 and C3a levels also increased after injury but reached a peak at 24h (2.9-fold) and 72h PI (2.2-fold), respectively. The MSCs treatment significantly reduced the HMGB1 level in the serum, especially at 6h and 12h PI compared to the IC group but failed to inhibit the SDC-1 and C3a increases. IHC analyses showed that injury triggered a significantly higher expressions of HMGB1 and TLR4, as well as co-localization of HMGB1 and TLR4 in the lung; while MSCs treatment was able to disrupt the HMGB1-TLR4 interaction and significantly reduce their expressions.
Our data indicate that the way MSCs treatment mitigates ARDS might be by reducing HMGB1 release and inhibiting the HMGB1-TLR4 signal pathway activation in pigs after smoke and burn injury.
This work was supported by the US Army Medical Research and Development Command (USAMRDC) under Grant No. W81XWH-13-2-0005.
Abstract
The weather and climate greatly affect socioeconomic activities on multiple temporal and spatial scales. From a climate perspective, atmospheric and ocean characteristics have determined the ...life, evolution, and prosperity of humans and other species in different areas of the world. On smaller scales, the atmospheric and sea conditions affect various sectors such as civil protection, food security, communications, transportation, and insurance. It becomes evident that weather and ocean forecasting is high-value information highlighting the need for state-of-the-art forecasting systems to be adopted. This importance has been acknowledged by the authorities of Saudi Arabia entrusting the National Center for Meteorology (NCM) to provide high-quality weather and climate analytics. This led to the development of a numerical weather prediction (NWP) system. The new system includes weather, wave, and ocean circulation components and has been operational since 2020 enhancing the national capabilities in NWP. Within this article, a description of the system and its performance is discussed alongside future goals.
A devastating winter storm affected the Rocky Mountain states over the 3-day period of 24-26 October 1997. Blizzard conditions persisted over the foothills and adjoining plains from Wyoming to ...southern New Mexico, with maximum total snowfall amounts near 1.5 m. (Part I of this two-part paper describes the observations and modeling of this blizzard event.) During the morning of 25 October 1997, wind gusts in excess of 50 m s^sup -1^ were estimated west of the Continental Divide near Steamboat Springs in northern Colorado. These winds flattened approximately 5300 ha (13 000 acres) of old-growth forest in the Routt National Forest and Mount Zirkel Wilderness. Observations, analysis, and numerical modeling were used to examine the kinematics of this extreme event. A high-resolution, local-area model (the Regional Atmospheric Modeling System) was used to investigate the ability of a local model to capture the timing and strength of the windstorm and the aforementioned blizzard. Results indicated that a synergistic combination of strong cross-barrier easterly How; very cold lower-tropospheric air over Colorado, which modified the stability profile; and the presence of a critical layer led to devastating downslope winds. The high-resolution simulations demonstrated the potential for accurately capturing mesoscale spatial and temporal features of a downslope windstorm more than 1 day in advance. These simulations were quasi forecast in nature, because a combination of two 48-h Eta Model forecasts were used to specify the lateral boundary conditions. Increased predictive detail of the windstorm was also found by decreasing the horizontal grid spacing from 5 to 1.67 km in the local-area model simulations. PUBLICATION ABSTRACT
Over the 3-day period of 24-26 October 1997, a powerful winter storm was the cause of two exceptional weather phenomena: 1) blizzard conditions from Wyoming to southern New Mexico along the Front ...Range of the Rocky Mountains and 2) hurricane-force winds at the surface near Steamboat Springs, Colorado, with the destruction of about 5300 ha of old-growth forest. This rare event was caused by a deep, cutoff low pressure system that provided unusually strong, deep easterly flow over the Front Range for an extended period. The event was characterized by highly variable snowfall and some very large snowfall totals; over a horizontal distance of 15 km, in some cases, snowfall varied by as much as 1.0 m, with maximum total snowfall depths near 1.5 m. Because this variability was caused, in part, by terrain effects, this work investigates the capability of a mesoscale model constructed in terrain-following coordinates (the Regional Atmospheric Modeling System: RAMS) to forecast small-scale (meso gamma), orographically forced spatial variability of the snowfall. There are few investigations of model-forecast liquid precipitation versus observations at meso-gamma-scale horizontal grid spacing. Using a limited observational dataset, mean absolute percent errors of precipitation (liquid equivalent) of 41% and 9% were obtained at horizontal grid spacings of 5.00 and 1.67 km, respectively. A detailed, high-temporal-resolution (30-min intervals) comparison of modeled versus actual snowfall rates at a fully instrumented snow measurement testing site shows significant model skill. A companion paper, Part II, will use the same RAMS simulations to describe the observations and modeling of the simultaneous mountain-windstorm-induced forest blowdown event.
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