367 research outputs found
Consistency in the AMSR-E snow products: groundwork for a coupled snowfall and SWE algorithm
No full text2019 Fall.Includes bibliographical references.Snow is an important wintertime property because it is a source of freshwater, regulates land-atmosphere exchanges, and increases the surface albedo of snow-covered regions. Unfortunately, in-situ observations of both snowfall and snow water equivalent (SWE) are globally sparse and point measurements are not representative of the surrounding area, especially in mountainous regions. The total amount of land covered by snow, which is climatologically important, is fairly straightforward to measure using satellite remote sensing. The total SWE is hydrologically more useful, but significantly more difficult to measure. Accurately measuring snowfall and SWE is an important first step toward a better understanding of the impacts snow has for hydrological and climatological purposes. Satellite passive microwave retrievals of snow offer potential due to consistent overpasses and the capability to make measurements during the day, night, and cloudy conditions. However, passive microwave snow retrievals are less mature than precipitation retrievals and have been an ongoing area of research. Exacerbating the problem, communities that remotely sense snowfall and SWE from passive microwave sensors have historically operated independently while the accuracy of the products has suffered because of the physical and radiometric dependency between the two. In this study, we assessed the relationship between the Northern Hemisphere snowfall and SWE products from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E). This assessment provides insight into regimes that can be used as a starting point for future improvements using coupled snowfall and SWE algorithm. SnowModel, a physically-based snow evolution modeling system driven by the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) reanalysis, was employed to consistently compare snowfall and SWE by accounting for snow evolution. SnowModel has the ability to assimilate observed SWE values to scale the amount of snow that must have fallen to match the observed SWE. Assimilation was performed using AMSR-E, Canadian Meteorological Centre (CMC) Snow Analysis, and Snow Data Assimilation System (SNODAS) SWE to infer the required snowfall for each dataset. Observed AMSR-E snowfall and SWE were then compared to the MERRA-2 snowfall and SnowModel-produced SWE as well as SNODAS and CMC inferred snowfall and observed SWE. Results from the study showed significantly different snowfall and SWE bias patterns observed by AMSR-E. Specifically, snowfall was underestimated nearly globally and SWE had pronounced regions of over and underestimation. Snowfall and SWE biases were found to differ as a function of surface temperature, snow class, and elevation
Validity and reliability of the Swedish version of the Children’s Sleep Habits Questionnaire (CSHQ-SWE)
No full textBackground: To translate and culturally adapt the Children’s Sleep Habits Questionnaire (CSHQ) to a Swedish version, CSHQ-SWE, and to assess its validity and reliability for use with children with attention deficit hyperactivity disorder (ADHD). Methods: A total of 84 children with ADHD (51 boys and 33 girls; 6–12 years) and parents (7 men and 77 women; 28–51 years) were included in the study. CSHQ was translated and culturally adapted to Swedish, and assessed for concurrent validity with sleep actigraphy (analyzed by Kendall’s Tau) and for reliability by internal consistency (analyzed by McDonald’s Omega H). Face and content validity was evaluated by parents (n = 4) and healthcare professionals (n = 6) qualitatively (comprehensiveness, relevance, and comprehensibility assessed by interviews and analyzed by thematic analysis) and quantitatively (analyzed by content validity ratio and content validity index for 33 items and four non-scored inquiries). Results: Parent-reported sleep problems (CSHQ-SWE total score) were moderately correlated with less “Sleep Efficiency” (Tau = −0.305; p < 0.001) measured by sleep actigraphy. Parent-reported problems with “Sleep Onset Delay” was moderately correlated with measured time for ”Sleep Onset Latency” (Tau = 0.433; p < 0.001). Parent-reported problems with “Night Wakings” were weakly correlated with measured time for “Wake After Sleep Onset” (Tau = 0.282; p < 0.001). Parents estimation of “Total daily sleep duration” was moderately correlated with measured “Total Sleep Time” (Tau = 0.386; p < 0.001). Five of the seven subscales reached an acceptable level for internal consistency (McDonald’s Omega H > 0.700). Comprehensiveness, relevance, and comprehensibility of CSHQ-SWE were satisfactory overall. Content validity ratio was 0.80 to 1.00 for six items, 0.00 to 0.60 for 22 items, and < 0.00 for nine items. Content validity index was 0.22. Conclusions: CSHQ-SWE demonstrated acceptable concurrent validity with objectively measured sleep and internal consistency, whereas the overall results of face and content validity assessment varied. The instrument needs to be further evaluated regarding construct validity, responsiveness, test-retest reliability, and its generalization to other populations. © The Author(s) 2024</p
Global re-analysis datasets to improve hydrological assessment and snow water equivalent estimation in a sub-Arctic watershed
No full textHydrological modelling in the Canadian sub-Arctic is hindered by sparse meteorological and snowpack data. The snow water equivalent (SWE) of the winter snowpack is a key predictor and driver of spring flow, but the use of SWE data in hydrological applications is limited due to high uncertainty. Global re-analysis datasets that provide gridded meteorological and SWE data may be well suited to improve hydrological assessment and snowpack simulation. To investigate representation of hydrological processes and SWE for application in hydropower operations, global re-analysis datasets covering 1979-2014 from the European Union FP7 eartH2Observe project are applied to global and local conceptual hydrological models. The recently developed Multi-Source Weighted-Ensemble Precipitation (MSWEP) and the WATCH Forcing Data applied to ERA-Interim data (WFDEI) are used to simulate snowpack accumulation, spring snowmelt volume and annual streamflow. The GlobSnow-2 SWE product funded by the European Space Agency with daily coverage from 1979 to 2014 is evaluated against in situ SWE measurement over the local watershed. Results demonstrate the successful application of global datasets for streamflow prediction, snowpack accumulation and snowmelt timing in a snowmelt-driven sub-Arctic watershed. The study was unable to demonstrate statistically significant correlations (p/0.05) among the measured snowpack, global hydrological model and GlobSnow-2 SWE compared to snowmelt runoff volume or peak discharge. The GlobSnow-2 product is found to under-predict late-season snowpacks over the study area and shows a premature decline of SWE prior to the true onset of the snowmelt. Of the datasets tested, the MSWEP precipitation results in annual SWE estimates that are better predictors of snowmelt volume and peak discharge than the WFDEI or GlobSnow-2. This study demonstrates the operational and scientific utility of the global re-analysis datasets in the sub-Arctic, although knowledge gaps remain in global satellite-based datasets for snowpack representation, for example the relationship between passive-microwave-measured SWE to snowmelt runoff volume.Water Resource
Improved Parameterization of Snow Albedo in WRF + Noah: Methodology Based on a Severe Snow Event on the Tibetan Plateau
No full textSnowfall and the subsequent evolution of the snowpack have a large effect on the surface energy balance and water cycle of the Tibetan Plateau (TP). The effects of snow cover can be represented by the WRF coupled with a land surface scheme. The widely used Noah scheme is computationally efficient, but its poor representation of albedo needs considerable improvement. In this study, an improved albedo scheme is developed using a satellite-retrieved albedo that takes snow depth and age into account. Numerical experiments were then conducted to simulate a severe snow event in March 2017. The performance of the coupled WRF/Noah model, which implemented the improved albedo scheme, is compared against the model’s performance using the default Noah albedo scheme and against the coupled WRF/CLM that applied CLM albedo scheme. When the improved albedo scheme is implemented, the albedo overestimation in the southeastern TP is reduced, reducing the RMSE of the air temperature by 0.7°C. The improved albedo scheme also attains the highest correlation between the satellite-derived and the model-estimated albedo, which provides for a realistic representation of both the snow water equivalent (SWE) spatial distribution in the heavy snowbelt (SWE > 6 mm) and the maximum SWE in the eastern TP. The underestimated albedo in the coupled WRF/CLM leads to underestimating the regional maximum SWE and a consequent failure to estimate SWE in the heavy snowbelt accurately. Our study demonstrates the feasibility of improving the Noah albedo scheme and provides a theoretical reference for researchers aiming to improve albedo schemes further.Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Optical and Laser Remote Sensin
AGU hydrology days 2017
No full text2017 annual AGU hydrology days was held at Colorado State University on March 20 - March 22, 2017.Includes bibliographical references.The seasonal snowpack in Rocky Mountain National Park is critical to the local and downstream water supply and the ecosystem of the park, and is important for winter recreational opportunities. Recent regional studies of trends in observed snow water equivalent (SWE) over the past three and a half decades have illustrated that temperatures are rising. Snow accumulation is decreasing, averaging on the order of a 2 to 4 cm/decade decline with snowmelt tending to be earlier, averaging on the order of 2 to 4 days/decade sooner. To place these SWE trends observed over the past few decades into a longer-term context, multi-century SWE reconstructions were derived from tree-ring widths and examined to determine whether similar multi-decade trends have occurred in the past. Possible SWE trends were examined into the future using projections from the Coupled Model Inter-comparison Project-Phase 5 (CMIP5) climate models linked to hydrologic models to identify models that best fit the observed data. From these model projections, possible SWE trends were estimated for the remainder of the 21st century. Results of the paleo-analysis suggest that similar multi-decade declining trends in SWE have occurred in the study area at certain times over the past four centuries. Results of the model projections suggest that recently observed trends (past 3+ decades) are likely to continue over the next eight or so decades
A direct comparison of natural and acoustic-radiation-force-induced cardiac mechanical waves
No full textNatural and active shear wave elastography (SWE) are potential ultrasound-based techniques to non-invasively assess myocardial stiffness, which could improve current diagnosis of heart failure. This study aims to bridge the knowledge gap between both techniques and discuss their respective impacts on cardiac stiffness evaluation. We recorded the mechanical waves occurring after aortic and mitral valve closure (AVC, MVC) and those induced by acoustic radiation force throughout the cardiac cycle in four pigs after sternotomy. Natural SWE showed a higher feasibility than active SWE, which is an advantage for clinical application. Median propagation speeds of 2.5–4.0 m/s and 1.6–4.0 m/s were obtained after AVC and MVC, whereas ARF-based median speeds of 0.9–1.2 m/s and 2.1–3.8 m/s were reported for diastole and systole, respectively. The different wave characteristics in both methods, such as the frequency content, complicate the direct comparison of waves. Nevertheless, a good match was found in propagation speeds between natural and active SWE at the moment of valve closure, and the natural waves showed higher propagation speeds than in diastole. Furthermore, the results demonstrated that the natural waves occur in between diastole and systole identified with active SWE, and thus represent a myocardial stiffness in between relaxation and contraction.ImPhys/Medical Imagin
Evaluating the spatial variability of snowpack properties across a northern Colorado basin
No full text2012 Fall.Includes bibliographical references.Knowledge of seasonal mountain snowpack distribution and estimates of its snow water equivalent (SWE) can provide insight for water resources forecasting and earth system process understanding, thus, it is important to improve our ability to describe the spatial variability of SWE at the basin scale. The objectives of this thesis are to: (1) develop a reliable method of estimating SWE from snow depth for the Cache la Poudre basin, and (2) characterize the spatial variability of SWE at the basin scale within the Cache la Poudre basin. A combination of field and Natural Resource Conservation Service (NRCS) operational-based snow measurements were used in this study. Historic (1936 - 2010) snow course data were obtained for the study area to evaluate snow density. A multiple linear regression model (based on the historical snow course data) for estimating snow density across the study area was developed to estimate SWE directly from snow depth measurements. To investigate the spatial variability and observable patterns of SWE at the basin scale, snow surveys were completed on or about April 1, 2011 and 2012 and combined with NRCS operational measurements. Bivariate relations and multiple linear regression models were developed to understand the relation of SWE with physiographic variables derived using a geographic information system (GIS). SWE was interpolated across the Cache la Poudre basin on a pixel by pixel basis using the model equations and masked to observe SCA (from an 8-day MODIS product). The independent variables of snow depth, day of year, elevation, and UTM Easting were used in the model to estimate snow density. Calculation of SWE directly from snow depth measurement using the snow density model has strong statistical performance and model verification suggests the model is transferable to independent data within the bounds of the original dataset. This pathway of estimating SWE directly from snow depth measurement is useful when evaluating snowpack properties at the basin scale, where many time consuming measurements of SWE are often not feasible. Bivariate relations of SWE and snow depth measurements (from WY 2011 and WY 2012) with physiographic variables show that elevation and location (UTM Easting and UTM Northing) are most strongly correlated with SWE and snow depth. Multiple linear regression models developed for WY 2011 and WY 2012 include elevation and location as independent variables and also include others (e.g., eastness, slope, solar radiation, curvature, canopy density) depending on the model dataset. The final interpolated SWE surfaces, masked to observed SCA, generally show similar patterns across space despite differences in the 2011 and 2012 snow years and differing estimation of SWE magnitude between the combined dataset of field-based and operational-based measurements (modelO+F) and the dataset of operational-based measurements only (modelO). Within each of the model surfaces, interpolated volume of SWE was greatest within Elevation Zone 5 (3,043 - 3,405 m). The percentage of the total interpolated SWE volume for each model was distributed similarly among elevation zones
Understanding Temporal Changes in Snow Water Equivalency in the Kootenay Boundary Region
No full textIntegrated Environmental PlanningSnow and ice are highly important elements in the cryosphere (Earth's frozen water component) as they are a vital source of stored freshwater (Langlois et al. 2009). It stores freshwater through the winter months are release [sic] water into our ecosystems in the spring as spring freshet, and in the warmer drier months of summer (PyneK, Callegari G 2019). The water that is stored as snow and ice is what hydrologists call Snow Water Equivalency (SWE). It is this SWE that is of primary importance for climatological and hydrological processes (Langlois et al. 2009)
Shear-wave elastography for the differential diagnosis of breast papillary lesions
No full textObjective To evaluate the diagnostic performance of shear-wave elastography (SWE) for the differential diagnosis of breast papillary lesions. Methods This study was an institutional review board-approved retrospective study, with a waiver of informed consent. A total of 79 breast papillary lesions in 71 consecutive women underwent ultrasound and SWE prior to biopsy. Ultrasound features and quantitative SWE parameters were recorded for each lesion. All lesions were surgically excised or excised using an ultrasound-guided vacuum-assisted method. The diagnostic performances of the quantitative SWE parameters were compared using the area under the receiver operating characteristic curve (AUC). Results Of the 79 lesions, six (7.6%) were malignant and 12 (15.2%) were atypical. Orientation, margin, and the final BI-RADS ultrasound assessments were significantly different for the papillary lesions (p &amp;lt; 0.05). All qualitative SWE parameters were significantly different (p &amp;lt; 0.05). The AUC values for SWE parameters of benign and atypical or malignant papillary lesions ranged from 0.707 to 0.757 (sensitivity, 44.4-94.4%; specificity, 42.6-88.5%). The maximum elasticity and the mean elasticity showed the highest AUC (0.757) to differentiate papillary lesions. Conclusion SWE provides additional information for the differential diagnosis of breast papillary lesions. Quantitative SWE features were helpful to differentiate breast papillary lesions. © 2016 Chung et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited
Spatial accumulation patterns of snow water equivalent in the southern Rocky Mountains
No full text2016 Spring.Includes bibliographical references.Only several point measurements may be taken within a given watershed to estimate snow water equivalent (SWE) due to cost limitations, which necessitates basin-scale estimation of SWE. Modeling often assumes consistency in the spatial distribution of SWE, which may not be correct. Identifying patterns and variability in the spatial distribution of SWE can improve snow hydrology models and result in more accurate modeling. Most previous snow distribution studies focused on small domains, less than 10 km. This study examined SWE distribution at a domain of 757 km. This study used variogram analysis for SWE data from 90 long-term SNOTEL stations to determine if a physical distance exists at which snow accumulation patterns across the southern Rocky Mountains vary abruptly. The concurrent accumulation period from SNOTEL stations were paired one-by-one until all 90 stations were compared among each other for all years on record. This comparison generated a relative accumulation slope (relative to the accumulation slope of all other 89 SNOTEL stations from the period of record) and along with physical distance between station pairs, variograms were computed using the semi-variance of the relative accumulation slopes. A physical divide (a break in high-elevation terrain) exists in the topography of the study region that runs East-West about the parallel 38°45’N. Two subset variograms were computed, one by dividing station pairs by their location relative the parallel 38°45’N into a north zone and a south zone, and the second by the pair’s land cover type, specifically evergreen, non-evergreen, or mixed. From the variogram analyses two physical distances were determined (100 and 340 km) at which snow accumulation patterns in the southern Rocky Mountains vary abruptly. There was more variance in snow accumulation south of the 38°45’N parallel, as the zone north of the 38°45’N parallel experiences storm tracks different from the storm tracks that dominate the zone south of this dividing parallel. Land cover was shown to have little effect on snow accumulation patterns. The amount of variability in individual day SWE was found to be correlated to the magnitude of the average SWE among all SNOTEL stations, such that the greater the average SWE, the larger the variability in SWE across the southern Rock Mountains
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