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1
Koenderink, J. J., and W. A. Richards. "Why is snow so bright?" Journal of the Optical Society of America A 9, no. 5 (May 1, 1992): 643. http://dx.doi.org/10.1364/josaa.9.000643.
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Yi, Yang, Fan Yi, Fuchao Liu, Yunpeng Zhang, Changming Yu, and Yun He. "Microphysical process of precipitating hydrometeors from warm-front mid-level stratiform clouds revealed by ground-based lidar observations." Atmospheric Chemistry and Physics 21, no. 23 (December 3, 2021): 17649–64. http://dx.doi.org/10.5194/acp-21-17649-2021.
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Abstract. Mid-level stratiform precipitations during the passage of warm fronts were detailedly observed on two occasions (light and moderate rain) by a 355 nm polarization lidar and water vapor Raman lidar, both equipped with waterproof transparent roof windows. The hours-long precipitation streaks shown in the lidar signal (X) and volume depolarization ratio (δv) reveal some ubiquitous features of the microphysical process of precipitating hydrometeors. We find that for the light-rain case precipitation that reaches the surface begins as ice-phase-dominant hydrometeors that fall out of a shallow liquid cloud layer at altitudes above the 0 ∘C isotherm level, and the depolarization ratio magnitude of falling hydrometeors increases from the liquid-water values (δv<0.09) to the ice/snow values (δv>0.20) during the first 100–200 m of their descent. Subsequently, the falling hydrometeors yield a dense layer with an ice/snow bright band occurring above and a liquid-water bright band occurring below (separated by a lidar dark band) as a result of crossing the 0 ∘C level. The ice/snow bright band might be a manifestation of local hydrometeor accumulation. Most falling raindrops shrink or vanish in the liquid-water bright band due to evaporation, whereas a few large raindrops fall out of the layer. We also find that a prominent δv peak (0.10–0.40) always occurs at an altitude of approximately 0.6 km when precipitation reaches the surface, reflecting the collision–coalescence growth of falling large raindrops and their subsequent spontaneous breakup. The microphysical process (at ice-bright-band altitudes and below) of moderate rain resembles that of the light-rain case, but more large-sized hydrometeors are involved.
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Li, Haoran, Jussi Tiira, Annakaisa von Lerber, and Dmitri Moisseev. "Towards the connection between snow microphysics and melting layer: insights from multifrequency and dual-polarization radar observations during BAECC." Atmospheric Chemistry and Physics 20, no. 15 (August 14, 2020): 9547–62. http://dx.doi.org/10.5194/acp-20-9547-2020.
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Abstract. In stratiform rainfall, the melting layer (ML) is often visible in radar observations as an enhanced reflectivity band, the so-called bright band. Despite the ongoing debate on the exact microphysical processes taking place in the ML and on how they translate into radar measurements, both model simulations and observations indicate that the radar-measured ML properties are influenced by snow microphysical processes that take place above it. There is still, however, a lack of comprehensive observations to link the two. To advance our knowledge of precipitation formation in ice clouds and provide new insights into radar signatures of snow growth processes, we have investigated this link. This study is divided into two parts. Firstly, surface-based snowfall measurements are used to develop a new method for identifying rimed and unrimed snow from X- and Ka-band Doppler radar observations. Secondly, this classification is used in combination with multifrequency and dual-polarization radar observations collected during the Biogenic Aerosols – Effects on Clouds and Climate (BAECC) experiment in 2014 to investigate the impact of precipitation intensity, aggregation, riming and dendritic growth on the ML properties. The results show that the radar-observed ML properties are highly related to the precipitation intensity. The previously reported bright band “sagging” is mainly connected to the increase in precipitation intensity. Ice particle riming plays a secondary role. In moderate to heavy rainfall, riming may cause additional bright band sagging, while in light precipitation the sagging is associated with unrimed snow. The correlation between ML properties and dual-polarization radar signatures in the snow region above appears to be arising through the connection of the radar signatures and ML properties to the precipitation intensity. In addition to advancing our knowledge of the link between ML properties and snow processes, the presented analysis demonstrates how multifrequency Doppler radar observations can be used to get a more detailed view of cloud processes and establish a link to precipitation formation.
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Kahl, Annelen, Jérôme Dujardin, and Michael Lehning. "The bright side of PV production in snow-covered mountains." Proceedings of the National Academy of Sciences 116, no. 4 (January 7, 2019): 1162–67. http://dx.doi.org/10.1073/pnas.1720808116.
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Our work explores the prospect of bringing the temporal production profile of solar photovoltaics (PV) into better correlation with typical electricity consumption patterns in the midlatitudes. To do so, we quantify the potential of three choices for PV installations that increase production during the winter months when electricity is most needed. These are placements that favor (i) high winter irradiance, (ii) high ground-reflected radiation, and (iii) steeper-than-usual panel tilt angles. In addition to spatial estimates of the production potential, we compare the performance of different PV placement scenarios in urban and mountain environments for the country of Switzerland. The results show that the energy deficit in a future fully renewable production from wind power, hydropower, and geothermal power could be significantly reduced when solar PV is installed at high elevations. Because the temporal production patterns match the typical demand more closely than the production in urban environments, electricity production could be shifted from summer to winter without reducing the annual total production. Such mountain installations require significantly less surface area and, combined with steeper panel tilt angles, up to 50% of the winter deficit in electricity production can be mediated.
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Woodbridge, Linda. "Black and White and Red All Over: The Sonnet Mistress Amongst the Ndembu*." Renaissance Quarterly 40, no. 2 (1987): 247–97. http://dx.doi.org/10.2307/2861708.
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Among terminally ill figures of speech, the cliché of rosy cheeks, ruby lips, and snow-white skin may be counted downright deceased. Even in medieval and Renaissance love poetry, roses in the cheeks, lips like cherries or rubies, skin like ivory, lilies, or snow were stiffly conventional: freshness of complexion prompted no freshness of metaphor. The mistress's red-and-white face was relentlessly emblazoned, “red and white” becoming a short-hand notation for feminine beauty: “With lilies white / And roses bright / Doth strive thy colour fair” (Wyatt 65); “Fair is my love … / A lily pale, with damask dye to grace her” (Passionate Pilgrim no. 7); “Thou art not fair for all thy red and white” (Campion 264). The mistress in Spenser's Amoretti has “ruddy cheekes” and “snowy browes” (no. 64); the bride in his Epithalamion is a vision in red and white—cheeks like sun-reddened apples, lips like cherries, forehead like ivory, “breast like to a bowle of creame uncrudded, / Her paps lyke lyllies budded, / Her snowie necke”; when she blushes, “the red roses flush up in her cheekes, / and the pure snow with goodly vermill [vermillion] stayne, / Like crimsin dyde” (Il. 172-7, 226-8).
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Tanskanen, A., and T. Manninen. "Effective UV surface albedo of seasonally snow-covered lands." Atmospheric Chemistry and Physics Discussions 7, no. 1 (February 23, 2007): 2873–91. http://dx.doi.org/10.5194/acpd-7-2873-2007.
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Abstract. At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.
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Tanskanen, A., and T. Manninen. "Effective UV surface albedo of seasonally snow-covered lands." Atmospheric Chemistry and Physics 7, no. 10 (May 25, 2007): 2759–64. http://dx.doi.org/10.5194/acp-7-2759-2007.
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Abstract. At ultraviolet wavelengths the albedo of most natural surfaces is small with the striking exception of snow and ice. Therefore, snow cover is a major challenge for various applications based on radiative transfer modelling. The aim of this work was to determine the characteristic effective UV range surface albedo of various land cover types when covered by snow. First we selected 1 by 1 degree sample regions that met three criteria: the sample region contained dominantly subpixels of only one land cover type according to the 8 km global land cover classification product from the University of Maryland; the average slope of the sample region was less than 2 degrees according to the USGS's HYDRO1K slope data; the sample region had snow cover in March according to the NSIDC Northern Hemisphere weekly snow cover data. Next we generated 1 by 1 degree gridded 360 nm surface albedo data from the Nimbus-7 TOMS Lambertian equivalent reflectivity data, and used them to construct characteristic effective surface albedo distributions for each land cover type. The resulting distributions showed that each land cover type experiences a characteristic range of surface albedo values when covered by snow. The result is explained by the vegetation that extends upward beyond the snow cover and masks the bright snow covered surface.
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Carlin, Jacob T., and Alexander V. Ryzhkov. "Estimation of Melting-Layer Cooling Rate from Dual-Polarization Radar: Spectral Bin Model Simulations." Journal of Applied Meteorology and Climatology 58, no. 7 (July 2019): 1485–508. http://dx.doi.org/10.1175/jamc-d-18-0343.1.
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AbstractDiabatic cooling from hydrometeor phase changes in the stratiform melting layer is of great interest to both operational forecasters and modelers for its societal and dynamical consequences. Attempts to estimate the melting-layer cooling rate typically rely on either the budgeting of hydrometeor content estimated from reflectivity Z or model-generated lookup tables scaled by the magnitude of Z in the bright band. Recent advances have been made in developing methods to observe the unique polarimetric characteristics of melting snow and the additional microphysical information they may contain. However, to date no work has looked at the thermodynamic information available from the polarimetric radar brightband signature. In this study, a one-dimensional spectral bin model of melting snow and a coupled polarimetric operator are used to study the relation between the polarimetric radar bright band and the melting-layer cooling rate. Simulations using a fixed particle size distribution (PSD) and variable environmental conditions show that the height and thickness of the bright band and the maximum brightband Z and specific differential phase shift are all sensitive to the ambient environment, while the differential reflectivity is relatively insensitive. Additional simulations of 2700 PSDs based on in situ observations above the melting layer indicate that the maximum Z, , and within the melting layer are poorly correlated with the maximum cooling rate while is strongly correlated. Finally, model simulations suggest that, in addition to riming, concurrent changes in aggregation and precipitation intensity and the associated cooling may plausibly cause observed sagging brightband signatures.
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Gao, Min, Xingfa Gu, Yan Liu, Yulin Zhan, Xiangqin Wei, Haidong Yu, Man Liang, Chenyang Weng, and Yaozong Ding. "An Improved Spatiotemporal Data Fusion Method for Snow-Covered Mountain Areas Using Snow Index and Elevation Information." Sensors 22, no. 21 (November 5, 2022): 8524. http://dx.doi.org/10.3390/s22218524.
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Remote sensing images with high spatial and temporal resolution in snow-covered areas are important for forecasting avalanches and studying the local weather. However, it is difficult to obtain images with high spatial and temporal resolution by a single sensor due to the limitations of technology and atmospheric conditions. The enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM) can fill in the time-series gap of remote sensing images, and it is widely used in spatiotemporal fusion. However, this method cannot accurately predict the change when there is a change in surface types. For example, a snow-covered surface will be revealed as the snow melts, or the surface will be covered with snow as snow falls. These sudden changes in surface type may not be predicted by this method. Thus, this study develops an improved spatiotemporal method ESTARFM (iESTARFM) for the snow-covered mountain areas in Nepal by introducing NDSI and DEM information to simulate the snow-covered change to improve the accuracy of selecting similar pixels. Firstly, the change in snow cover is simulated according to NDSI and DEM. Then, similar pixels are selected according to the change in snow cover. Finally, NDSI is added to calculate the weights to predict the pixels at the target time. Experimental results show that iESTARFM can reduce the bright abnormal patches in the land area compared to ESTARFM. For spectral accuracy, iESTARFM performs better than ESTARFM with the root mean square error (RMSE) being reduced by 0.017, the correlation coefficient (r) being increased by 0.013, and the Structural Similarity Index Measure (SSIM) being increased by 0.013. For spatial accuracy, iESTARFM can generate clearer textures, with Robert’s edge (Edge) being reduced by 0.026. These results indicate that iESTARFM can obtain higher prediction results and maintain more spatial details, which can be used to generate dense time series images for snow-covered mountain areas.
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Zhou, Yaping, Yuekui Yang, Meng Gao, and Peng-Wang Zhai. "Cloud detection over snow and ice with oxygen A- and B-band observations from the Earth Polychromatic Imaging Camera (EPIC)." Atmospheric Measurement Techniques 13, no. 3 (April 1, 2020): 1575–91. http://dx.doi.org/10.5194/amt-13-1575-2020.
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Abstract. Satellite cloud detection over snow and ice has been difficult for passive remote sensing instruments due to the lack of contrast between clouds and cold/bright surfaces; cloud mask algorithms often heavily rely on shortwave infrared (IR) channels over such surfaces. The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) does not have infrared channels, which makes cloud detection over snow and ice surfaces even more challenging. This study investigates the methodology of applying EPIC's two oxygen absorption band pair ratios in the A band (764, 780 nm) and B band (688, 680 nm) for cloud detection over the snow and ice surfaces. We develop a novel elevation and zenith-angle-dependent threshold scheme based on radiative transfer model simulations that achieves significant improvements over the existing algorithm. When compared against a composite cloud mask based on geosynchronous Earth orbit (GEO) and low Earth orbit (LEO) sensors, the positive detection rate over snow and ice surfaces increased from around 36 % to 65 % while the false detection rate dropped from 50 % to 10 % for observations of January 2016 and 2017. The improvement in July is less substantial due to relatively better performance in the current algorithm. The new algorithm is applicable for all snow and ice surfaces including Antarctic, sea ice, high-latitude snow, and high-altitude glacier regions. This method is less reliable when clouds are optically thin or below 3 km because the sensitivity is low in oxygen band ratios for these cases.
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Lundquist, Jessica D., Paul J. Neiman, Brooks Martner, Allen B. White, Daniel J. Gottas, and F. Martin Ralph. "Rain versus Snow in the Sierra Nevada, California: Comparing Doppler Profiling Radar and Surface Observations of Melting Level." Journal of Hydrometeorology 9, no. 2 (April 1, 2008): 194–211. http://dx.doi.org/10.1175/2007jhm853.1.
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Abstract The maritime mountain ranges of western North America span a wide range of elevations and are extremely sensitive to flooding from warm winter storms, primarily because rain falls at higher elevations and over a much greater fraction of a basin’s contributing area than during a typical storm. Accurate predictions of this rain–snow line are crucial to hydrologic forecasting. This study examines how remotely sensed atmospheric snow levels measured upstream of a mountain range (specifically, the bright band measured above radar wind profilers) can be used to accurately portray the altitude of the surface transition from snow to rain along the mountain’s windward slopes, focusing on measurements in the Sierra Nevada, California, from 2001 to 2005. Snow accumulation varies with respect to surface temperature, diurnal cycles in solar radiation, and fluctuations in the free-tropospheric melting level. At 1.5°C, 50% of precipitation events fall as rain and 50% as snow, and on average, 50% of measured precipitation contributes to increases in snow water equivalent (SWE). Between 2.5° and 3°C, snow is equally likely to melt or accumulate, with most cases resulting in no change to SWE. Qualitatively, brightband heights (BBHs) detected by 915-MHz profiling radars up to 300 km away from the American River study basin agree well with surface melting patterns. Quantitatively, this agreement can be improved by adjusting the melting elevation based on the spatial location of the profiler relative to the basin: BBHs decrease with increasing latitude and decreasing distance to the windward slope of the Sierra Nevada. Because of diurnal heating and cooling by radiation at the mountain surface, BBHs should also be adjusted to higher surface elevations near midday and lower elevations near midnight.
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White, Allen B., Daniel J. Gottas, Arthur F. Henkel, Paul J. Neiman, F. Martin Ralph, and Seth I. Gutman. "Developing a Performance Measure for Snow-Level Forecasts." Journal of Hydrometeorology 11, no. 3 (June 1, 2010): 739–53. http://dx.doi.org/10.1175/2009jhm1181.1.
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Abstract The snow level, or altitude in the atmosphere where snow melts to rain, is an important variable for hydrometeorological prediction in mountainous watersheds; yet, there is no operational performance measure associated with snow-level forecasts in the United States. To establish a performance measure, it is first necessary to establish the baseline performance associated with snow-level forecasts. Using data collected by vertically pointing Doppler radars, an automated algorithm has been developed to detect the altitude of maximum radar reflectivity in the radar bright band that results from the precipitation melting process. This altitude can be used as a proxy for the snow level, partly because it always exists below the freezing level, which is defined as the altitude of the 0°C isotherm. The skill of freezing-level forecasts produced by the California–Nevada River Forecast Center (CNRFC) is evaluated by comparing spatially interpolated and forecaster-adjusted numerical model freezing-level forecasts with observed freezing levels estimated by radars operating at 2875 MHz (S band). The freezing level was chosen instead of the snow level as the comparison parameter because the radar algorithm and the CNRFC have different interpretations of the snow level. The evaluation occurred at two sites: one in the coastal mountains north of San Francisco and the other in the Sierra Nevada. The evaluation was conducted for forecasts made during the winter wet season of 2005/06. Although the overall mean freezing-level forecast bias is small enough not to be hydrologically significant, about 15% of the forecasts had biases greater than 300 m (forecast too low). The largest forecast biases were associated with freezing levels above 2.3 km that were underforecasted by as much as 900 m. These high freezing-level events were accompanied by the heaviest precipitation intensities, exacerbating the flood threat and making the forecast even more challenging.
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Kim, Changwon. "Region Adaptive Single Image Dehazing." Entropy 23, no. 11 (October 30, 2021): 1438. http://dx.doi.org/10.3390/e23111438.
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Image haze removal is essential in preprocessing for computer vision applications because outdoor images taken in adverse weather conditions such as fog or snow have poor visibility. This problem has been extensively studied in the literature, and the most popular technique is dark channel prior (DCP). However, dark channel prior tends to underestimate transmissions of bright areas or objects, which may cause color distortions during dehazing. This paper proposes a new single-image dehazing method that combines dark channel prior with bright channel prior in order to overcome the limitations of dark channel prior. A patch-based robust atmospheric light estimation was introduced in order to divide image into regions to which the DCP assumption and the BCP assumption are applied. Moreover, region adaptive haze control parameters are introduced in order to suppress the distortions in a flat and bright region and to increase the visibilities in a texture region. The flat and texture regions are expressed as probabilities by using local image entropy. The performance of the proposed method is evaluated by using synthetic and real data sets. Experimental results show that the proposed method outperforms the state-of-the-art image dehazing method both visually and numerically.
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Borowska, L., D. Zrnić, A. Ryzhkov, P. Zhang, and C. Simmer. "Polarimetric Estimates of a 1-Month Accumulation of Light Rain with a 3-cm Wavelength Radar." Journal of Hydrometeorology 12, no. 5 (October 1, 2011): 1024–39. http://dx.doi.org/10.1175/2011jhm1339.1.
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Abstract The authors evaluate rainfall estimates from the new polarimetric X-band radar at Bonn, Germany, for a period between mid-November and the end of December 2009 by comparison with rain gauges. The emphasis is on slightly more than 1-month accumulations over areas minimally affected by beam blockage. The rain regime was characterized by reflectivities mainly below 45 dBZ, maximum observed rain rates of 47 mm h−1, a mean rain rate of 0.1 mm h−1, and brightband altitudes between 0.6 and 2.4 km above the ground. Both the reflectivity factor and the specific differential phase are used to obtain the rain rates. The accuracy of rain total estimates is evaluated from the statistics of the differences between radar and rain gauge measurements. Polarimetry provides improvement in the statistics of reflectivity-based measurements by reducing the bias and RMS errors from −25% to 7% and from 33% to 17%, respectively. Essential to this improvement is separation of the data into those attributed to pure rain, those from the bright band, and those due to nonmeteorological scatterers. A type-specific (rain or wet snow) relation is applied to obtain the rain rate by matching on the average the contribution by wet snow to the radar-measured rainfall below the bright band. The measurement of rain using specific differential phase is the most robust and can be applied to the very low rain rates and still produce credible accumulation estimates characterized with a standard deviation of 11% but a bias of −25%. A composite estimator is also tested and discussed.
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Van Den Broeke, Matthew S., Dana M. Tobin, and Matthew R. Kumjian. "Polarimetric Radar Observations of Precipitation Type and Rate from the 2–3 March 2014 Winter Storm in Oklahoma and Arkansas." Weather and Forecasting 31, no. 4 (July 7, 2016): 1179–96. http://dx.doi.org/10.1175/waf-d-16-0011.1.
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Abstract A powerful winter storm affected the south-central United States in early March 2014, accompanied by elevated convective cells with hail and high rates of sleet, freezing rain, and snow. During portions of the event the thermal profile exhibited a shallow surface cold layer and warm, unstable air aloft. Precipitation falling into the cold layer refroze into ice pellets and was accompanied by a polarimetric refreezing signature and numerous crowdsourced surface ice pellet reports. Quasi-vertical profiles of the polarimetric variables indicated an enhanced reflectivity factor ZHH below the melting layer bright band and enhanced low-level differential reflectivity ZDR values coincident with surface ice pellet reports. Freezing rain rate was highest in areas with high ZHH and specific differential phase KDP values at low levels. High snow rates were most closely associated with 1- and 1.5-km ZHH values, though KDP and ZDR also appeared to show some ability to distinguish high snow rate. Numerous elevated convective cells contained rotating updrafts that appeared to contribute to storm longevity and intensity. Most contained well-defined ZDR maxima or columns and relatively high base-scan ZDR values. Several contained polarimetric signatures consistent with heavy mixed-phase precipitation and hail; social media reports indicated that large hail was produced by some of the storms.
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Lamare, Maxim, Marie Dumont, Ghislain Picard, Fanny Larue, François Tuzet, Clément Delcourt, and Laurent Arnaud. "Simulating optical top-of-atmosphere radiance satellite images over snow-covered rugged terrain." Cryosphere 14, no. 11 (November 14, 2020): 3995–4020. http://dx.doi.org/10.5194/tc-14-3995-2020.
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Abstract. The monitoring of snow-covered surfaces on Earth is largely facilitated by the wealth of satellite data available, with increasing spatial resolution and temporal coverage over the last few years. Yet to date, retrievals of snow physical properties still remain complicated in mountainous areas, owing to the complex interactions of solar radiation with terrain features such as multiple scattering between slopes, exacerbated over bright surfaces. Existing physically based models of solar radiation across rough scenes are either too complex and resource-demanding for the implementation of systematic satellite image processing, not designed for highly reflective surfaces such as snow, or tied to a specific satellite sensor. This study proposes a new formulation, combining a forward model of solar radiation over rugged terrain with dedicated snow optics into a flexible multi-sensor tool that bridges a gap in the optical remote sensing of snow-covered surfaces in mountainous regions. The model presented here allows one to perform rapid calculations over large snow-covered areas. Good results are obtained even for extreme cases, such as steep shadowed slopes or, on the contrary, strongly illuminated sun-facing slopes. Simulations of Sentinel-3 OLCI (Ocean and Land Colour Instrument) scenes performed over a mountainous region in the French Alps allow us to reduce the bias by up to a factor of 6 in the visible wavelengths compared to methods that account for slope inclination only. Furthermore, the study underlines the contribution of the individual fluxes to the total top-of-atmosphere radiance, highlighting the importance of reflected radiation from surrounding slopes which, in midwinter after a recent snowfall (13 February 2018), accounts on average for 7 % of the signal at 400 nm and 16 % at 1020 nm (on 13 February 2018), as well as of coupled diffuse radiation scattered by the neighbourhood, which contributes to 18 % at 400 nm and 4 % at 1020 nm. Given the importance of these contributions, accounting for slopes and reflected radiation between terrain features is a requirement for improving the accuracy of satellite retrievals of snow properties over snow-covered rugged terrain. The forward formulation presented here is the first step towards this goal, paving the way for future retrievals.
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Jung, Youngsun, Guifu Zhang, and Ming Xue. "Assimilation of Simulated Polarimetric Radar Data for a Convective Storm Using the Ensemble Kalman Filter. Part I: Observation Operators for Reflectivity and Polarimetric Variables." Monthly Weather Review 136, no. 6 (June 1, 2008): 2228–45. http://dx.doi.org/10.1175/2007mwr2083.1.
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Abstract A radar simulator for polarimetric radar variables, including reflectivities at horizontal and vertical polarizations, the differential reflectivity, and the specific differential phase, has been developed. This simulator serves as a test bed for developing and testing forward observation operators of polarimetric radar variables that are needed when directly assimilating these variables into storm-scale numerical weather prediction (NWP) models, using either variational or ensemble-based assimilation methods. The simulator takes as input the results of high-resolution NWP model simulations with ice microphysics and produces simulated polarimetric radar data that may also contain simulated errors. It is developed based on calculations of electromagnetic wave propagation and scattering at the S band of wavelength 10.7 cm in a hydrometeor-containing atmosphere. The T-matrix method is used for the scattering calculation of raindrops and the Rayleigh scattering approximation is applied to snow and hail particles. The polarimetric variables are expressed as functions of the hydrometeor mixing ratios as well as their corresponding drop size distribution parameters and densities. The presence of wet snow and wet hail in the melting layer is accounted for by using a new, relatively simple melting model that defines the water fraction in the melting snow or hail. The effect of varying density due to the melting snow or hail is also included. Vertical cross sections and profiles of the polarimetric variables for a simulated mature multicellular squall-line system and a supercell storm show that polarimetric signatures of the bright band in the stratiform region and those associated with deep convection are well captured by the simulator.
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Zhang, Jian, Carrie Langston, and Kenneth Howard. "Brightband Identification Based on Vertical Profiles of Reflectivity from the WSR-88D." Journal of Atmospheric and Oceanic Technology 25, no. 10 (October 1, 2008): 1859–72. http://dx.doi.org/10.1175/2008jtecha1039.1.
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Abstract The occurrence of a bright band, a layer of enhanced reflectivity due to melting of aggregated snow, increases uncertainties in radar-based quantitative precipitation estimation (QPE). The height of the brightband layer is an indication of 0°C isotherm and can be useful in identifying areas of potential icing for aviation and in the data assimilation for numerical weather prediction (NWP). Extensive analysis of vertical profiles of reflectivity (VPRs) derived from the Weather Surveillance Radar-1988 Doppler (WSR-88D) base level data showed that the brightband signature could be easily identified from the VPRs. As a result, an automated brightband identification (BBID) scheme has been developed. The BBID algorithm can determine from a volume scan mean VPR and a background freezing level height from a numerical weather prediction model whether a bright band exists and the height of the brightband layer. The paper presents a description of the BBID scheme and evaluation results from a large dataset from WSR-88D radars in different geographical regions and seasons.
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Yachmeneva, S. Yu. "ADAPTIVE POTENTIAL AND DECORATIVNESS OF BEARDED IRIS COLLECTIBLE VARIETIES IN THE INTRODUCTION TO THE CHERNOZEM ZONE." Pomiculture and small fruits culture in Russia 64 (March 30, 2021): 68–76. http://dx.doi.org/10.31676/2073-4948-2021-64-68-76.
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In the conditions of the Tambov region, the gene pool of the bearded iris of domestic and foreign breeding is studied. The collection of bearded iris is represented by varieties ('Snow White', 'Border Black', 'Guards', 'Count Tolstoy', 'Ancient Rome', etc.) of medium and late ('Cascade Springs', 'Green Quest', 'Gypsy Caravan', 'Spurna') flowering period. The duration of flowering of the studied varieties is from 7 to 11 days. The longest flowering period (10–11 days) is observed in varieties: 'Snow White', 'Guards', 'Count Tolstoy', 'Marshal Pokryshkin' and 'Gypsy Caravan'. The main disease of the bearded iris in the black earth region is rust (Puccinia iridis), the main pest is the bronze beetle (Cetonia aurata). Varieties with high decorative features with the largest flower diameter (up to 12.5 cm) and peduncle height (up to 90 cm) have been identified: 'Ancient Rome', 'Lilac Wreath', 'Cascade Springs', 'Gypsy Jewels', 'Stepping Out'. Varieties of bearded iris with a light color of the flower (from white to pale blue), severely damaged by a bronze beetle, were noted: 'Snow White' (pale blue), 'Belyanchik' (white), 'Kassandra' (white), etc. The most severe rust damage was observed on varieties of bearded iris with yellow flowers and its shades: 'Galatea' (bright yellow), 'Elf' (yellow-brown), 'Fiesta Time' (golden-amber), 'Invitation' (apricot). Recommendations are given for the introduction of the bearded iris culture in the landscaping of settlements and personal subsidiary farms.
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Winther, Jan-Gunnar. "Studies of snow surface characteristics by Landsat TM in Dronning Maud Land, Antarctica." Annals of Glaciology 17 (1993): 27–34. http://dx.doi.org/10.3189/s026030550001257x.
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Large scale melting phenomena like meltwater drainage channels and meltwater accumulation basins or frozen “lakes” have been surveyed on the land ice mass in Dronning Maud Land, Antarctica. These melting features were also detected in a Landsat Thematic Mapper (TM) image recorded on 12 February 1990. Image processing techniques such as principal component (PC) analysis, band ratioing and histogram-equalizing are carried out to emphasize the melting phenomena. Interestingly, a histogram-equalized single TM Band 5 image appears to be a good discriminator, leaving the melting phenomena as bright areas in the TM scene. The largest frozen “lake” is close to 1km wide while some of the drainage channels stretch more than 5 km. There is also a comparison of satellite-derived and in situ reflectance and temperature. The atmospheric corrected satellite data underestimate surface snow albedo by about 16% while TM measurements of surface temperature are 2° to 6°C lower than that measured on the ground.
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Winther, Jan-Gunnar. "Studies of snow surface characteristics by Landsat TM in Dronning Maud Land, Antarctica." Annals of Glaciology 17 (1993): 27–34. http://dx.doi.org/10.1017/s026030550001257x.
Full textAbstract:
Large scale melting phenomena like meltwater drainage channels and meltwater accumulation basins or frozen “lakes” have been surveyed on the land ice mass in Dronning Maud Land, Antarctica. These melting features were also detected in a Landsat Thematic Mapper (TM) image recorded on 12 February 1990. Image processing techniques such as principal component (PC) analysis, band ratioing and histogram-equalizing are carried out to emphasize the melting phenomena. Interestingly, a histogram-equalized single TM Band 5 image appears to be a good discriminator, leaving the melting phenomena as bright areas in the TM scene. The largest frozen “lake” is close to 1km wide while some of the drainage channels stretch more than 5 km. There is also a comparison of satellite-derived and in situ reflectance and temperature. The atmospheric corrected satellite data underestimate surface snow albedo by about 16% while TM measurements of surface temperature are 2° to 6°C lower than that measured on the ground.
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Braun, Matthias, Frank Rau, Helmut Saurer, and Hermann Gobmann. "Development of radar glacier zones on the King George Island ice cap, Antarctica, during austral summer 1996/97 as observed in ERS-2 SAR data." Annals of Glaciology 31 (2000): 357–63. http://dx.doi.org/10.3189/172756400781819950.
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AbstractBased on a time series of European remote-sensing satellite (ERS-2) synthetic-aperture radar (SAR) images from 1996/97, ablation on the King George Island (Antarctica) ice cap is documented. Snowmelt patterns were monitored by mapping the dynamic evolution of radar glacier zones and their boundaries. On the ice cap, all major radar glacier zones except the dry-snow radar zone were identified during the observed period While winter was characterized by a frozen-percolation radar zone, the ablation season was characterized by wet-snow and bare-ice radar zones. A striking bright backscatter signature indicated the presence of a highly reflective zone in the lower parts of the wet-snow zone. It was attributed to a phase 2 melt (P2) radar zone, which is characterized by a metamorphosed and roughened surface of a melting snow cover. Due to the absence of simultaneously acquired ground-truth information, concurrent meteorological data proved to be essential for interpreting the SAR images. Although the maximum elevation of the ice cap does not exceed 680 ma.s.L, ablation patterns obviously reflect altitudinal control. Melt onset up to 530 m a.s.l. was initiated by an advection event at the end of October 1996. A wet snowpack on the entire ice cap corresponds with a prolonged period of high temperatures in January 1997. However, the highest parts of the ice cap were affected by occasional melt-freeze cycles. The transient snowline at the end of February was determined as being at 250 m a i l. This late-summer snowline was regarded as an approximation of the equilibrium-line altitude for the 1996/97 ablation season.
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Wang, X., W. Li, Y. Zhu, and B. Zhao. "Improved cloud mask algorithm for FY-3A/VIRR data over the northwest region of China." Atmospheric Measurement Techniques Discussions 5, no. 6 (November 6, 2012): 8189–222. http://dx.doi.org/10.5194/amtd-5-8189-2012.
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Abstract. The existence of various land surfaces has always been a difficult problem for researchers who study cloud detection using satellite observations, especially over bright surfaces such as snow and desert. To improve the cloud mask result over complex terrain, an unbiased daytime cloud detection algorithm for the Visible and InfRared Radiometer (VIRR) on board the Chinese FengYun-3A polar-orbiting meteorological satellite is applied over the northwest region of China. Based on the statistical seasonal threshold tests, the algorithm consists of six main channels centered on the wavelengths of 0.63, 0.865, 10.8, 1.595, 0.455, and 1.36 μm. The combination of the unbiased algorithm and the specific threshold tests for special surfaces has effectively improved the cloud mask results over complex terrain and decreased the false identifications of clouds. The visual images over snow and desert adopting the proposed scheme exhibit better correlations with true-color images than do the VIRR official cloud mask results. The validation with the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud mask product shows that the probability of detection for clear-sky regions over snow of the new scheme has increased nearly five times over the official method, and the false-alarm ratio for cloudy areas over desert has reduced by half compared with the official result. With regard to comparisons between ground measurements and cloud mask results, this approach also provides acceptable correspondence with the ground observations except for some cases, which are mainly obscured by cirrus clouds.
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Kuhn, Thomas, and Sandra Vázquez-Martín. "Microphysical properties and fall speed measurements of snow ice crystals using the Dual Ice Crystal Imager (D-ICI)." Atmospheric Measurement Techniques 13, no. 3 (March 16, 2020): 1273–85. http://dx.doi.org/10.5194/amt-13-1273-2020.
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Abstract. Accurate predictions of snowfall require good knowledge of the microphysical properties of the snow ice crystals and particles. Shape is an important parameter as it strongly influences the scattering properties of the ice particles, and thus their response to remote sensing techniques such as radar measurements. The fall speed of ice particles is another important parameter for both numerical forecast models as well as representation of ice clouds and snow in climate models, as it is responsible for the rate of removal of ice from these models. We describe a new ground-based in situ instrument, the Dual Ice Crystal Imager (D-ICI), to determine snow ice crystal properties and fall speed simultaneously. The instrument takes two high-resolution pictures of the same falling ice particle from two different viewing directions. Both cameras use a microscope-like setup resulting in an image pixel resolution of approximately 4 µm pixel−1. One viewing direction is horizontal and is used to determine fall speed by means of a double exposure. For this purpose, two bright flashes of a light-emitting diode behind the camera illuminate the falling ice particle and create this double exposure, and the vertical displacement of the particle provides its fall speed. The other viewing direction is close-to-vertical and is used to provide size and shape information from single-exposure images. This viewing geometry is chosen instead of a horizontal one because shape and size of ice particles as viewed in the vertical direction are more relevant than these properties viewed horizontally, as the vertical fall speed is more strongly influenced by the vertically viewed properties. In addition, a comparison with remote sensing instruments that mostly have a vertical or close-to-vertical viewing geometry is favoured when the particle properties are measured in the same direction. The instrument has been tested in Kiruna, northern Sweden (67.8∘ N, 20.4∘ E). Measurements are demonstrated with images from different snow events, and the determined snow ice crystal properties are presented.
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Vasilkov, A. P., J. Joiner, D. Haffner, P. K. Bhartia, and R. J. D. Spurr. "What do satellite backscatter ultraviolet and visible spectrometers see over snow and ice? A study of clouds and ozone using the A-train." Atmospheric Measurement Techniques Discussions 3, no. 1 (January 26, 2010): 237–68. http://dx.doi.org/10.5194/amtd-3-237-2010.
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Abstract. In this paper, we examine how clouds over snow and ice affect ozone absorption and how these effects may be accounted for in satellite retrieval algorithms. Over snow and ice, the Aura Ozone Monitoring Instrument (OMI) Raman cloud pressure algorithm derives an effective scene pressure. When this scene pressure differs appreciably from the surface pressure, the difference is assumed to be caused by a cloud that is shielding atmospheric absorption and scattering below cloud-top from satellite view. A pressure difference of 100 hPa is used as a crude threshold for the detection of clouds that significantly shield tropospheric ozone absorption. Combining the OMI effective scene pressure and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) cloud top pressure, we can distinguish between shielding and non-shielding clouds. To evaluate this approach, we performed radiative transfer simulations under various observing conditions. Using cloud vertical extinction profiles from the CloudSat Cloud Profiling Radar (CPR), we find that clouds over a bright surface can produce significant shielding (i.e., a reduction in the sensitivity of the top-of-the-atmosphere radiance to ozone absorption below the clouds). The amount of shielding provided by clouds depends upon the geometry (solar and satellite zenith angles) and the surface albedo as well as cloud optical thickness. We also use CloudSat observations to qualitatively evaluate our approach. The CloudSat, Aqua, and Aura satellites fly in an afternoon polar orbit constellation with ground overpass times within 15 min of each other. The current Total Ozone Mapping Spectrometer (TOMS) total column ozone algorithm (that has also been applied to the OMI) assumes no clouds over snow and ice. This assumption leads to errors in the retrieved ozone column. We show that the use of OMI effective scene pressures over snow and ice reduces these errors and leads to a more homogeneous spatial distribution of the retrieved total ozone.
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Vasilkov, A. P., J. Joiner, D. Haffner, P. K. Bhartia, and R. J. D. Spurr. "What do satellite backscatter ultraviolet and visible spectrometers see over snow and ice? A study of clouds and ozone using the A-train." Atmospheric Measurement Techniques 3, no. 3 (May 18, 2010): 619–29. http://dx.doi.org/10.5194/amt-3-619-2010.
Full textAbstract:
Abstract. In this paper, we examine how clouds over snow and ice affect ozone absorption and how these effects may be accounted for in satellite retrieval algorithms. Over snow and ice, the Aura Ozone Monitoring Instrument (OMI) Raman cloud pressure algorithm derives an effective scene pressure. When this scene pressure differs appreciably from the surface pressure, the difference is assumed to be caused by a cloud that is shielding atmospheric absorption and scattering below cloud-top from satellite view. A pressure difference of 100 hPa is used as a crude threshold for the detection of clouds that significantly shield tropospheric ozone absorption. Combining the OMI effective scene pressure and the Aqua MODerate-resolution Imaging Spectroradiometer (MODIS) cloud top pressure, we can distinguish between shielding and non-shielding clouds. To evaluate this approach, we performed radiative transfer simulations under various observing conditions. Using cloud vertical extinction profiles from the CloudSat Cloud Profiling Radar (CPR), we find that clouds over a bright surface can produce significant shielding (i.e., a reduction in the sensitivity of the top-of-the-atmosphere radiance to ozone absorption below the clouds). The amount of shielding provided by clouds depends upon the geometry (solar and satellite zenith angles) and the surface albedo as well as cloud optical thickness. We also use CloudSat observations to qualitatively evaluate our approach. The CloudSat, Aqua, and Aura satellites fly in an afternoon polar orbit constellation with ground overpass times within 15 min of each other. The current Total Ozone Mapping Spectrometer (TOMS) total column ozone algorithm (that has also been applied to the OMI) assumes no clouds over snow and ice. This assumption leads to errors in the retrieved ozone column. We show that the use of OMI effective scene pressures over snow and ice reduces these errors and leads to a more homogeneous spatial distribution of the retrieved total ozone.
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Thurai, Merhala, Viswanathan N. Bringi, David B. Wolff, David A. Marks, and Charanjit S. Pabla. "Drop Size Distribution Measurements in Outer Rainbands of Hurricane Dorian at the NASA Wallops Precipitation-Research Facility." Atmosphere 11, no. 6 (June 1, 2020): 578. http://dx.doi.org/10.3390/atmos11060578.
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Hurricane rainbands are very efficient rain producers, but details on drop size distributions are still lacking. This study focuses on the rainbands of hurricane Dorian as they traversed the densely instrumented NASA precipitation-research facility at Wallops Island, VA, over a period of 8 h. Drop size distribution (DSD) was measured using a high-resolution meteorological particle spectrometer (MPS) and 2D video disdrometer, both located inside a double-fence wind shield. The shape of the DSD was examined using double-moment normalization, and compared with similar shapes from semiarid and subtropical sites. Dorian rainbands had a superexponential shape at small normalized diameter values similar to those of the other sites. NASA’s S-band polarimetric radar performed range height-indicator (RHI) scans over the disdrometer site, showing some remarkable signatures in the melting layer (bright-band reflectivity peaks of 55 dBZ, a dip in the copolar correlation to 0.85 indicative of 12–15 mm wet snow, and a staggering reflectivity gradient above the 0 °C level of −10 dB/km, indicative of heavy aggregation). In the rain layer at heights < 2.5 km, polarimetric signatures indicated drop break-up as the dominant process, but drops as large as 5 mm were detected during the intense bright-band period.
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Banko, Thomas J., and Marcia A. Stefani. "Evaluation of Bedding Plant Varieties for Resistance to Phytophthora." Journal of Environmental Horticulture 18, no. 1 (March 1, 2000): 40–44. http://dx.doi.org/10.24266/0738-2898-18.1.40.
Full textAbstract:
Abstract Seedlings of several annual and perennial bedding plant species were inoculated with an isolate of Phytophthora nicotianae (synonym = P. parasitica) and planted into field beds in a simulated landscape situation. Throughout the growing season, growth measurements and disease ratings of the inoculated plants were compared with those of non-inoculated control plants of the same species in identical beds. Phytophthora-inoculated plants that continued to thrive through most of the growing season included Ageratum houstonianum, Celosia ‘Apricot Brandy’, and ‘New Look’; Dahlia ‘Harlequin’; Eustoma grandiflorum (prairie gentian); Lobularia ‘Carpet of Snow’; Nicotiana ‘Alta Dwarf White’, ‘Domino Salmon’, and ‘Nicki Red’; Pelargonium (geranium) ‘Multibloom Scarlet Eye’; Petunia ‘Polo Salmon’, and ‘Sugar Daddy’; Portulaca ‘Sundial Peppermint’; Rudbeckia ‘Rustic Dwarf’; Salvia ‘Lady in Red’, and ‘Victoria Blue’; Tagetes (marigold) ‘Disco Mix’, ‘Inca Orange’, ‘Inca Yellow’, ‘Janie Harmony Improved’, and ‘Gold Fireworks’; and Zinnia angustifolia. Plants that performed poorly following inoculation with Phytophthora include Antirrhinum (snapdragon) ‘Liberty White’, and ‘Liberty Mix’; Catharanthus (vinca) ‘Little Bright Eye’, and ‘Tropicana Rose’; Hibiscus ‘Disco Belle Mix’; Impatiens ‘Accent Bright Eye’; Leucanthemum x ‘Alaska’; Melampodium ‘Medallion’; Salvia ‘Turkestanica’; Torenia ‘Clown Mix’; Verbena ‘Imagination’; and Viola (pansy) ‘Fama See Me’. This study identifies bedding plant taxa which will provide an acceptable display in landscape beds infested with Phytopthora nicotianae (synonym = P. parasitica).
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Erb, Angela M., Zhan Li, Qingsong Sun, Ian Paynter, Zhuosen Wang, and Crystal Schaaf. "Evaluation of the Landsat-8 Albedo Product across the Circumpolar Domain." Remote Sensing 14, no. 21 (October 24, 2022): 5320. http://dx.doi.org/10.3390/rs14215320.
Full textAbstract:
Land surface albedo plays an extremely important role in the surface energy budget, by determining the proportion of incoming solar radiation, which is available to drive photosynthesis and surface heating, and that which is reflected directly back to space. In northern high latitude regions, the albedo of snow-covered vegetation and open, leafless forest canopies in winter, is quite high, while the albedo of boreal evergreen conifers can either be quite low (even with extensive snow lying under the canopy) or rather bright depending on the structure and density of the canopy. Here, we present the further development and evaluation of a 30 m Landsat albedo product, including an operational blue-sky albedo product, for application in the circumpolar domain. The surface reflectances from the Landsat satellite constellation are coupled with surface anisotropy information (Bidirectional Reflectance Distribution Function, BRDF) from the MODerate-resolution Imaging Spectroradiometer (MODIS). The product is extensively validated across diverse land cover and conditions and performs well with root mean squared error of 0.0395 and negligible bias when compared to coincident tower-based albedo measurements. The development of this Landsat albedo products allows for better capture of ephemeral, heterogeneous and dynamic surface conditions at the landscape scale across the circumpolar domain.
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Qi, Youcun, and Jian Zhang. "Correction of Radar QPE Errors Associated with Low and Partially Observed Brightband Layers." Journal of Hydrometeorology 14, no. 6 (November 22, 2013): 1933–43. http://dx.doi.org/10.1175/jhm-d-13-040.1.
Full textAbstract:
Abstract The melting of aggregated snow/crystals often results in an enhancement of the reflectivity observed by weather radars, and this is commonly referenced as the bright band (BB). The locally high reflectivity often causes overestimation in radar quantitative precipitation estimates (QPE) if no appropriate correction is applied. When the melting layer is high, a complete BB layer profile (including top, peak, and bottom) can be observed by the ground radar, and a vertical profile of reflectivity (VPR) correction can be made to reduce the BB impact. When a melting layer is near the ground and the bottom part of the bright band cannot be observed by the ground radar, a VPR correction cannot be made directly from the Weather Surveillance Radar-1988 Doppler (WSR-88D) radar observations. This paper presents a new VPR correction method under this situation. From high-resolution precipitation profiler data, an empirical relationship between BB peak and BB bottom is developed. The empirical relationship is combined with the apparent BB peak observed by volume scan radars and the BB bottom is found. Radar QPEs are then corrected based on the estimated BB bottom. The new method was tested on 13 radars during seven low brightband events over different areas in the United States. It is shown to be effective in reducing the radar QPE overestimation under low brightband situations.
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Wang, X., W. Li, Y. Zhu, and B. Zhao. "Improved cloud mask algorithm for FY-3A/VIRR data over the northwest region of China." Atmospheric Measurement Techniques 6, no. 3 (March 1, 2013): 549–63. http://dx.doi.org/10.5194/amt-6-549-2013.
Full textAbstract:
Abstract. The existence of various land surfaces always leads to more difficulties in cloud detection based on satellite observations, especially over bright surfaces such as snow and deserts. To improve the cloud mask result over complex terrain, an unbiased, daytime cloud detection algorithm for the Visible and InfRared Radiometer (VIRR) on board the Chinese FengYun-3A polar-orbiting meteorological satellite is applied over the northwest region of China. The algorithm refers to the concept of the clear confidence level from Moderate Resolution Imaging Spectroradiometer (MODIS) and the unbiased structure of the CLoud and Aerosol Unbiased Decision Intellectual Algorithm (CLAUDIA). Six main channels of VIRR centered at the wavelengths of 0.455, 0.63, 0.865, 1.595, 1.36, and 10.8 μm are designed to estimate the degree of a pixel's cloud contamination judged by the clear confidence level. Based on the statistical data set during four months (January, April, July, and October) in 2010, seasonal thresholds are applied to improve the accuracy of the cloud detection results. Flags depicting snow and water are also generated by the specific threshold tests for special surfaces. As shown in image inspections, the cloud detection results over snow and deserts, adopting the proposed scheme, exhibit better correlations with true-color images than the VIRR official cloud mask results do. The performance of the proposed algorithm has been evaluated in detail for four seasons in 2011, using cloud mask products from MODIS and the ground-based observations. The evaluation is based on, overall, 47 scenes collocated with MODIS and 96 individual matchups between VIRR and the ground-based observations from two weather stations located in the research region. The quantitative validations suggest that the estimations of clear-sky regions have been greatly improved by the proposed algorithm, while a poor identification of the cirrus clouds occurs over deserts.
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Griffin, Erica M., Terry J. Schuur, Alexander V. Ryzhkov, Heather D. Reeves, and Joseph C. Picca. "A Polarimetric and Microphysical Investigation of the Northeast Blizzard of 8–9 February 2013." Weather and Forecasting 29, no. 6 (December 1, 2014): 1271–94. http://dx.doi.org/10.1175/waf-d-14-00056.1.
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Abstract On 8–9 February 2013, the northeastern United States experienced a historic winter weather event ranking among the top five worst blizzards in the region. Heavy snowfall and blizzard conditions occurred from northern New Jersey, inland to New York, and northward through Maine. Storm-total snow accumulations of 30–61 cm were common, with maximum accumulations up to 102 cm and snowfall rates exceeding 15 cm h−1. Dual-polarization radar measurements collected for this winter event provide valuable insights into storm microphysical processes. In this study, polarimetric data from the Weather Surveillance Radar-1988 Doppler (WSR-88D) in Upton, New York (KOKX), are investigated alongside thermodynamic analyses from the 13-km Rapid Refresh model and surface precipitation type observations from both Meteorological Phenomena Identification Near the Ground (mPING) and the National Weather Service (NWS) Forecast Office in Upton, New York, for interpretation of polarimetric signatures. The storm exhibited unique polarimetric signatures, some of which have never before been documented for a winter system. Reflectivity values were unusually large, reaching magnitudes >50 dBZ in shallow regions of heavy wet snow near the surface. The 0°C transition line was exceptionally distinct in the polarimetric imagery, providing detail that was often unmatched by the numerical model output. Other features include differential attenuation of magnitudes typical of melting hail, depolarization streaks that provide evidence of electrification, nonuniform beamfilling, a “snow flare” signature, and localized downward excursions of the melting-layer bright band collocated with observed transitions in surface precipitation types. In agreement with previous studies, widespread elevated depositional growth layers, located at temperatures near the model-predicted −15°C isotherm, appear to be correlated with increased snowfall and large reflectivity factors ZH near the surface.
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Li, Zhiwei, Huanfeng Shen, Yancong Wei, Qing Cheng, and Qiangqiang Yuan. "CLOUD DETECTION BY FUSING MULTI-SCALE CONVOLUTIONAL FEATURES." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-3 (April 23, 2018): 149–52. http://dx.doi.org/10.5194/isprs-annals-iv-3-149-2018.
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Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.
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Lindsay, R., and D. Rothrock. "The calculation of surface temperature and albedo of Arctic sea ice from AVHRR." Annals of Glaciology 17 (1993): 391–97. http://dx.doi.org/10.3189/s026030550001315x.
Full textAbstract:
The temperature and albedo distributions of Arctic sea ice are calculated from images obtained from the AVHRR satellite sensor. The temperature estimate uses a split window correction incorporating regression coefficients appropriate for the arctic atmosphere. The albedo estimate is found assuming a clear and dry atmosphere. Both estimates are made with published correction techniques. Inherent errors due to the uncertainty of the atmospheric interference produced by humidity, aerosols, and diamond dust are judged to be 2–5°C in surface temperature and 0.10–0.20 in surface albedo. Cloudy regions are masked out manually using data from all five channels. The relationship between temperature and albedo is shown for a sample scene. A simple model of a surface composed of only cold, bright ice and warm, dark water is inadequate. Model calculations based on the surface energy balance allow us to relate albedo and temperature to ice thickness and snow-cover thickness and to further assess the accuracy of the surface estimates.
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Lindsay, R., and D. Rothrock. "The calculation of surface temperature and albedo of Arctic sea ice from AVHRR." Annals of Glaciology 17 (1993): 391–97. http://dx.doi.org/10.1017/s026030550001315x.
Full textAbstract:
The temperature and albedo distributions of Arctic sea ice are calculated from images obtained from the AVHRR satellite sensor. The temperature estimate uses a split window correction incorporating regression coefficients appropriate for the arctic atmosphere. The albedo estimate is found assuming a clear and dry atmosphere. Both estimates are made with published correction techniques. Inherent errors due to the uncertainty of the atmospheric interference produced by humidity, aerosols, and diamond dust are judged to be 2–5°C in surface temperature and 0.10–0.20 in surface albedo. Cloudy regions are masked out manually using data from all five channels. The relationship between temperature and albedo is shown for a sample scene. A simple model of a surface composed of only cold, bright ice and warm, dark water is inadequate. Model calculations based on the surface energy balance allow us to relate albedo and temperature to ice thickness and snow-cover thickness and to further assess the accuracy of the surface estimates.
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Pešek, Ondřej, Michal Segal-Rozenhaimer, and Arnon Karnieli. "Using Convolutional Neural Networks for Cloud Detection on VENμS Images over Multiple Land-Cover Types." Remote Sensing 14, no. 20 (October 18, 2022): 5210. http://dx.doi.org/10.3390/rs14205210.
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In most parts of the electromagnetic spectrum, solar radiation cannot penetrate clouds. Therefore, cloud detection and masking are essential in image preprocessing for observing the Earth and analyzing its properties. Because clouds vary in size, shape, and structure, an accurate algorithm is required for removing them from the area of interest. This task is usually more challenging over bright surfaces such as exposed sunny deserts or snow than over water bodies or vegetated surfaces. The overarching goal of the current study is to explore and compare the performance of three Convolutional Neural Network architectures (U-Net, SegNet, and DeepLab) for detecting clouds in the VENμS satellite images. To fulfil this goal, three VENμS tiles in Israel were selected. The tiles represent different land-use and cover categories, including vegetated, urban, agricultural, and arid areas, as well as water bodies, with a special focus on bright desert surfaces. Additionally, the study examines the effect of various channel inputs, exploring possibilities of broader usage of these architectures for different data sources. It was found that among the tested architectures, U-Net performs the best in most settings. Its results on a simple RGB-based dataset indicate its potential value for any satellite system screening, at least in the visible spectrum. It is concluded that all of the tested architectures outperform the current VENμS cloud-masking algorithm by lowering the false positive detection ratio by tens of percents, and should be considered an alternative by any user dealing with cloud-corrupted scenes.
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Schuur, Terry J., Hyang-Suk Park, Alexander V. Ryzhkov, and Heather D. Reeves. "Classification of Precipitation Types during Transitional Winter Weather Using the RUC Model and Polarimetric Radar Retrievals." Journal of Applied Meteorology and Climatology 51, no. 4 (April 2012): 763–79. http://dx.doi.org/10.1175/jamc-d-11-091.1.
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AbstractA new hydrometeor classification algorithm that combines thermodynamic output from the Rapid Update Cycle (RUC) model with polarimetric radar observations is introduced. The algorithm improves upon existing classification techniques that rely solely on polarimetric radar observations by using thermodynamic information to help to diagnose microphysical processes (such as melting or refreezing) that might occur aloft. This added information is especially important for transitional weather events for which past studies have shown radar-only techniques to be deficient. The algorithm first uses vertical profiles of wet-bulb temperature derived from the RUC model output to provide a background precipitation classification type. According to a set of empirical rules, polarimetric radar data are then used to refine precipitation-type categories when the observations are found to be inconsistent with the background classification. Using data from the polarimetric KOUN Weather Surveillance Radar-1988 Doppler (WSR-88D) located in Norman, Oklahoma, the algorithm is tested on a transitional winter-storm event that produced a combination of rain, freezing rain, ice pellets, and snow as it passed over central Oklahoma on 30 November 2006. Examples are presented in which the presence of a radar bright band (suggesting an elevated warm layer) is observed immediately above a background classification of dry snow (suggesting the absence of an elevated warm layer in the model output). Overall, the results demonstrate the potential benefits of combining polarimetric radar data with thermodynamic information from numerical models, with model output providing widespread coverage and polarimetric radar data providing an observation-based modification of the derived precipitation type at closer ranges.
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Lyubimov, Nikolay Ivanovich. "The Philosophy of nature in the lyrics of Albert Vasiliev." Litera, no. 7 (July 2022): 91–101. http://dx.doi.org/10.25136/2409-8698.2022.7.38466.
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In the article, the artistic natural philosophy of Albert Vasiliev is considered as part of the study of the poetics of modern Mari philosophical lyrics. Based on the material of poems included in his collection "Osh lumyshto chever polan" ("Red Viburnum on white snow", 2017), revealed the semantics and artistic functions of natural images that represent the philosophical attitude and worldview of the author and characterize his lyrical hero in a certain way. In this aspect, Albert Vasiliev's lyrics are analyzed for the first time in regional literary studies. The methodological basis of the research is the structural and semantic analysis of the poems of the Mari poet; this approach allows us to determine and describe the structural and semantic levels of natural images that reveal the artistic and philosophical concept of the author and the personality features of the lyrical hero. The article proves that natural images in Albert Vasiliev's lyrics occupy a significant place, they are not only a bright emotional background of his works (in this sense, they usually express the psycho-emotional state of the lyrical hero), but also recreate the natural philosophical views of the author and his lyrical hero (in this sense, they are mostly symbolic, projected on human life, accumulate both universal and ethnically significant values of the poet). Thanks to the natural images-symbols (phenomena and processes) used by the author in the collection "Red Viburnum on white Snow", Albert Vasiliev's natural philosophy is highlighted, inscribed in the context of the author's socio-philosophical reflections; its substantial basis is nature and power, order and harmony, universal connection and interdependence, the art of dialogue, personal certainty and inner freedom.
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van Terwisga, S. E., E. F. van Dishoeck, M. Ansdell, N. van der Marel, L. Testi, J. P. Williams, S. Facchini, et al. "V1094 Scorpii: A rare giant multi-ringed disk around a T Tauri star." Astronomy & Astrophysics 616 (August 2018): A88. http://dx.doi.org/10.1051/0004-6361/201832862.
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Context. A wide variety of ring-like dust structures have been detected in protoplanetary disks, but their origin and frequency are still unclear. Aims. We aim to characterize the structure of an extended, multi-ringed disk discovered serendipitously in the Atacama Large Millimeter/submillimeter Array (ALMA) Lupus disk survey and put it in the context of the Lupus disk population. Methods. ALMA observations in Band 6 at 234 GHz and Band 7 at 328 GHz at 0.3″ resolution toward the K6 star V1094 Sco in Lupus III are presented, and its disk structure analyzed. The spectral index αmm is determined in the inner 150 AU of the disk. Results. The ALMA continuum data show a very extended disk with two gap-ring pairs. The gaps are located at 100 AU and 170 AU, the bright rings at 130 AU and 220 AU. Continuum emission is detected out to a 300 AU distance, similar to IM Lup but a factor of five larger than typically found for Lupus disks at this sensitivity and resolution. The bright central region of the disk (within 35 AU) is possibly optically thick at 1 mm wavelengths, and has a brightness temperature of only 13 K. The spectral index increases between the inner disk and the first ring at the location of the first gap. Conclusions. Due to the low temperature of the disk midplane, snow lines can be excluded as the drivers behind the ring and gap formation in this disk. Disks the size of V1094 Sco are rare, and only 2.1 ± 1.5% of disks in Lupus show continuum emission beyond 200 AU. Possible connections between the large primordial disk population, transition disks, and exoplanets are discussed.
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Danilenko, Petr. "Who invented the glasses and when." Spravočnik vrača obŝej praktiki (Journal of Family Medicine), no. 7 (July 1, 2020): 57–62. http://dx.doi.org/10.33920/med-10-2007-08.
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Glasses, if to sort things out, are one of the most remarkable inventions of mankind, which has given millions of people the opportunity to perceive the world through vision. Prototype of the first glasses — they were the thinnest emerald plates enclosed in a bronze frame — was found in the tomb of Tutankhamun according to historical information. Ancient Greeks and Romans did not know the glasses unlike the ancient Egyptians and used pieces of rock crystal for reading, they preferred to use monocle prototypes, i.e., devices for one eye. Medieval monks also tried to use pieces of rock crystal or quartzite as lenses, which after some time they began to place in a frame. Arabs were the first to come up with a glass ball as an optical device. It is believed that glasses for the protection against the sun and sun glare were invented even earlier than glasses for vision correction. It is noteworthy that this invention belongs not to the southern, but to the northern peoples –inhabitants of Greenland were the first to come up with the use of bone plates with narrow slots that protected eyes from the snow shining in the bright sun.
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Pan, C. J., K. Krishna Reddy, H. C. Lai, and S. S. Yang. "Role of mixed precipitating cloud systems on the typhoon rainfall." Annales Geophysicae 28, no. 1 (January 8, 2010): 11–16. http://dx.doi.org/10.5194/angeo-28-11-2010.
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Abstract. L-band wind profiler data are utilized to diagnose the vertical structure of the typhoon precipitating cloud systems in Taiwan. For several typhoons, a pronounced bright band (BB) around 5 km is commonly observed from the observation. Since strong convection within typhoon circulation may disturb and/or disrupt the melting layer, the BB shall not appear persistently. Hence, an understanding of the vertical structure of the BB region is important because it holds extensive hydrometeors information on the type of precipitation and its variability. Wind profiler observational results suggest that the mixture of convective and stratiform (embedded type) clouds are mostly associated with typhoons. In the case of one typhoon, BB is appeared around 5.5 km with embedded precipitation and also BB height of 1 km higher than ordinary showery precipitation. This is evident from the long-term observations of wind profiler and Tropical Rainfall Measuring Mission. The Doppler velocity profiles show hydrometers (ice/snow) at 6 km but liquid below 5 km for typhoons and 4 km for showery precipitation. In the BB region the melting particles accelerations of 5.8 ms−1 km−1 and 3.2 ms−1 km−1 are observed for typhoon and showery precipitation, respectively.
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Klebonaitė, Aldona, and Marytė Trinkūnienė. "THE NATURAL SCIENCE EDUCATION PROJECT „CHILDREN TO CHILDREN. LET‘S DO EXPERIMENTS TOGETHER“." Natural Science Education in a Comprehensive School (NSECS) 20, no. 1 (April 20, 2014): 72–76. http://dx.doi.org/10.48127/gu/14.20.72.
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„Children to children. Let‘s do experiments together“ is the project where senior students share their experience and knowledge among primary school students. The senior students prepare for such kind of activities very responsibly: they search for information not only in the student‘s books, but also in extra literature and prepare the interesting worksheets. Every experiment starts from the theoretical part where the senior students try to introduce the primary students to activities. Later they do experiments: examine the snow cover, the amount of starch in different kinds of potatoes, identify the tree age and compare the prints of tree trunks, study the fingerprints using the microscopes, produce lemonade, construct the fountain in the classroom, learn to make a fire without matches, construct the robots from the material for recycling. We are glad that students can do the experiments themselves. Such kind of collaboration is very useful. The bright students can actualize their abilities, develop their competencies in studying. The adaptation process is much easier at the beginning of the school year in the fifth grade because the students are still in close relationship with their first teacher. All students approve that such kind of lessons are very interesting and useful. Key words: senior and primary school students, collaboration, an experiment, competency.
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Bringi, Viswanathan, Axel Seifert, Wei Wu, Merhala Thurai, Gwo-Jong Huang, and Christoph Siewert. "Hurricane Dorian Outer Rain Band Observations and 1D Particle Model Simulations: A Case Study." Atmosphere 11, no. 8 (August 18, 2020): 879. http://dx.doi.org/10.3390/atmos11080879.
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The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate, and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called McSnow) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near −15 °C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops >5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops <0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical experiments were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution.
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Lim, Kyo-Sun Sunny, and Song-You Hong. "Development of an Effective Double-Moment Cloud Microphysics Scheme with Prognostic Cloud Condensation Nuclei (CCN) for Weather and Climate Models." Monthly Weather Review 138, no. 5 (May 1, 2010): 1587–612. http://dx.doi.org/10.1175/2009mwr2968.1.
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Abstract A new double-moment bulk cloud microphysics scheme, the Weather Research and Forecasting (WRF) Double-Moment 6-class (WDM6) Microphysics scheme, which is based on the WRF Single-Moment 6-class (WSM6) Microphysics scheme, has been developed. In addition to the prediction for the mixing ratios of six water species (water vapor, cloud droplets, cloud ice, snow, rain, and graupel) in the WSM6 scheme, the number concentrations for cloud and rainwater are also predicted in the WDM6 scheme, together with a prognostic variable of cloud condensation nuclei (CCN) number concentration. The new scheme was evaluated on an idealized 2D thunderstorm test bed. Compared to the simulations from the WSM6 scheme, there are greater differences in the droplet concentration between the convective core and stratiform region in WDM6. The reduction of light precipitation and the increase of moderate precipitation accompanying a marked radar bright band near the freezing level from the WDM6 simulation tend to alleviate existing systematic biases in the case of the WSM6 scheme. The strength of this new microphysics scheme is its ability to allow flexibility in variable raindrop size distribution by predicting the number concentrations of clouds and rain, coupled with the explicit CCN distribution, at a reasonable computational cost.
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Zhang, Jian, and Youcun Qi. "A Real-Time Algorithm for the Correction of Brightband Effects in Radar-Derived QPE." Journal of Hydrometeorology 11, no. 5 (October 1, 2010): 1157–71. http://dx.doi.org/10.1175/2010jhm1201.1.
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Abstract The bright band (BB) is a layer of enhanced reflectivity due to melting of aggregated snow and ice crystals. The locally high reflectivity causes significant overestimation in radar precipitation estimates if an appropriate correction is not applied. The main objective of the current study is to develop a method that automatically corrects for large errors due to BB effects in a real-time national radar quantitative precipitation estimation (QPE) product. An approach that combines the mean apparent vertical profile of reflectivity (VPR) computed from a volume scan of radar reflectivity observations and an idealized linear VPR model was used for computational efficiency. The methodology was tested for eight events from different regions and seasons in the United States. The VPR correction was found to be effective and robust in reducing overestimation errors in radar-derived QPE, and the corrected radar precipitation fields showed physically continuous distributions. The correction worked consistently well for radars in flat land regions because of the relatively uniform spatial distributions of the BB in those areas. For radars in mountainous regions, the performance of the correction is mixed because of limited radar visibility in addition to large spatial variations of the vertical precipitation structure due to underlying topography.
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Wilkins, Arnold J., Bruce JW Evans, and Gordon T. Plant. "Potential Uses for Precision Tinted Lenses in a Neurology Clinic." US Neurology 18, no. 2 (2022): 93. http://dx.doi.org/10.17925/usn.2022.18.2.93.
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Photophobia is a complex disorder that can involve aversion not simply to bright light but to spatial patterns, colour and flicker. The use of tinted lenses to reduce photophobia in neurological diseases has a long history. Rarely has the possibility that different individuals might require lenses individually tailored to their needs been considered. Here we explore this possibility using the Intuitive Colorimeter system. The colorimeter illuminates text with coloured light and permits the colour, strength of colour and brightness to be manipulated separately. Many individuals find that a colour other than white is comfortable for viewing text. This colour is optimized in the colorimeter by a search strategy that allows for colour adaptation. Spectacle lenses are then individually tinted so that the chosen colour is experienced under conventional lighting. In this article, we review the use of the Intuitive Colorimeter in photosensitive epilepsy, autism, migraine, cluster headache, visual snow, stroke, multiple sclerosis and concussion; these are disorders in which individually coloured tints have featured in scientific and clinical reports. The evidence is preliminary rather than conclusive, but it suggests that precision tints can reduce photophobia. In patients with autism, the perception of emotion in facial expression is improved. Occasionally, the clinical benefit extends to the reduction of seizures and headaches and to an increase in reading speed.
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Paridy, Raissa Dina, Masitah Masitah, and Doddy Ismunandar Bahari. "Marketing Channel Analysis in an Effort to Develop the Potential of Bananas in Pinrang Regency." Agribusiness Journal 3, no. 2 (December 10, 2020): 1–7. http://dx.doi.org/10.31327/aj.v3i2.1358.
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Banana is one of the agriculture that has bright prospects in both the domestic and export markets, but banana farmers do not understand the potential of this banana. Therefore, a system is needed so that farmers know about the banana prospects. In marketing, until now there are still some discussions about the marketing patterns used are still quite long from farmers to consumers, increasing marketing costs incurred, marketing large margins, the benefits of each marketing institution and marketing of banana assistance. It dramatically affects the marketing of bananas in Pinrang Regency. The purpose of this study was to analyze the marketing patterns of Kepok bananas in Pinrang Regency. Determination of the sample in a study involving banana farmers, collector traders, wholesalers and retailers using the snow-balling method, samples related to all that was questioned, with the sample calculation were 30 banana farmers and 7 traders. The analytical method uses descriptive qualitative (quantitative) and quantitative (margin calculation) analysis. The results of this study indicate that farmers market their banana through two marketing channels in Pinrang Regency. There are two marketing channels, 1st channel is Farmer to Consumer, 2nd channel is Farmer to Collector Trader then to Retailer Trader and ends in Consumer. The involved marketing institutions require costs to operate marketing functions such as loading costs, transportation costs, fees, consumption and so forth.
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Zeng, S., J. Riedi, F. Parol, C. Cornet, and F. Thieuleux. "An assessment of cloud top thermodynamic phase products obtained from A-Train passive and active sensors." Atmospheric Measurement Techniques Discussions 6, no. 5 (September 12, 2013): 8371–411. http://dx.doi.org/10.5194/amtd-6-8371-2013.
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Abstract. The A-Train observations provide an unprecedented opportunity for the production of high quality dataset describing cloud properties. We illustrate in this study the use of one year of coincident POLDER (Polarization and Directionality of the Earth Reflectance), MODIS (MODerate Resolution Imaging Spectroradiometer) and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations to establish a reference dataset for the description of cloud top thermodynamic phase at global scale. We present the results of an extensive comparison between POLDER and MODIS cloud top phase products and discuss those in view of cloud vertical structure and optical properties derived simultaneously from collocated CALIOP active measurements. These results allow to identify and quantify potential biases present in the 3 considered dataset. Among those, we discuss the impacts of observation geometry, thin cirrus in multilayered and single layered cloud systems, supercooled liquid droplets, aerosols, fractional cloud cover and snow/ice or bright surfaces on global statistics of cloud phase derived from POLDER and MODIS passive measurements. Based on these analysis we define criteria for the selection of high confidence cloud phase retrievals which in turn can serve for the establishment of a reference cloud phase product. This high confidence joint product derived from POLDER/PARASOL and MODIS/Aqua can be used in the future as a benchmark for the evaluation of other cloud climatologies, for the assessment of cloud phase representation in models and the development of better cloud phase parametrization in the general circulation models (GCMs).
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Casassa, G., and H. H. Brecher. "Relief and decay of flow stripes on Byrd Glacier, Antarctica." Annals of Glaciology 17 (1993): 255–61. http://dx.doi.org/10.3189/s0260305500012933.
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Curvilinear flow stripes appear on aerial photographs and satellite imagery of polar ice. On Byrd Glacier, Antarctica, flow stripes are especially prominent and can be detected on AVHRR imagery down to the ice shelf margin.Aerial photographs of Byrd Glacier (Brecher, 1986) are used to determine photogrammetrically the relief associated with flow stripes on two transverse profiles separated by a distance of 65 km. Two kinds of stripes are found, topographic and textural flow stripes. Topographic flow stripes are associated with a ridge-trough topography with double amplitudes of 7 m to 45 m and slopes of 1–7 %. The valleys of the topographic flow stripes appear bright in the photographs and correspond to snow-covered areas, while ridges appear in general as dark stripes that correspond to bare ice areas with abundant crevasses. Textural flow stripes correspond to bands of distinct crevasse pattern which are not associated with topography.The photogrammetric information is correlated with the brightness pattern across flow stripes that appears on Advanced Very High Resolution Radiometer (AVHRR) data. Flow stripes decay rapidly on the AVHRR imagery over the first 40 km downstream from Byrd Glacier and some persist for nearly 400 km to the front of the Ross Ice Shelf.Velocity was measured across a transect on the upstream photogrammetric profile. There are no velocity discontinuities across the boundaries of flow stripes, which shows that lateral shear between flow stripes is not a valid mechanism for explaining their persistence.
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Chakrabarty, Rajan K., Madhu Gyawali, Reddy L. N. Yatavelli, Apoorva Pandey, Adam C. Watts, Joseph Knue, Lung-Wen A. Chen, et al. "Brown carbon aerosols from burning of boreal peatlands: microphysical properties, emission factors, and implications for direct radiative forcing." Atmospheric Chemistry and Physics 16, no. 5 (March 9, 2016): 3033–40. http://dx.doi.org/10.5194/acp-16-3033-2016.
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Abstract. The surface air warming over the Arctic has been almost twice as much as the global average in recent decades. In this region, unprecedented amounts of smoldering peat fires have been identified as a major emission source of climate-warming agents. While much is known about greenhouse gas emissions from these fires, there is a knowledge gap on the nature of particulate emissions and their potential role in atmospheric warming. Here, we show that aerosols emitted from burning of Alaskan and Siberian peatlands are predominantly brown carbon (BrC) – a class of visible light-absorbing organic carbon (OC) – with a negligible amount of black carbon content. The mean fuel-based emission factors for OC aerosols ranged from 3.8 to 16.6 g kg−1. Their mass absorption efficiencies were in the range of 0.2–0.8 m2 g−1 at 405 nm (violet) and dropped sharply to 0.03–0.07 m2 g−1 at 532 nm (green), characterized by a mean Ångström exponent of ≈ 9. Electron microscopy images of the particles revealed their morphologies to be either single sphere or agglomerated “tar balls”. The shortwave top-of-atmosphere aerosol radiative forcing per unit optical depth under clear-sky conditions was estimated as a function of surface albedo. Only over bright surfaces with albedo greater than 0.6, such as snow cover and low-level clouds, the emitted aerosols could result in a net warming (positive forcing) of the atmosphere.