Snow Properties Retrieval Using Passive Microwave Observations

Seasonal snow cover, the second-largest component of the cryosphere, is crucial in controlling the climate system, through its important role in modifying Earth’s albedo. The temporal variability of snow extent and its physical properties in the seasonal cycle also make up a significant element to the cryospheric energy balance. Thus, seasonal snowcover should be monitored not only for its climatological impacts but also for its rolein the surface-water supply, ground-water recharge, and its insolation properties at local scales. Snowpack physical properties strongly influence the emissions from the substratum, making feasible snow property retrieval by means of the surface brightness temperature observed by passive microwave sensors. Depending on the observing spatial resolution, the time series records of daily snow coverage and a snowpacks most-critical properties such as the snow depth and snow water equivalent (SWE) could be helpful in applications ranging from modeling snow variations in a small catchment to global climatologic studies. However, the challenge of including spaceborne snow water equivalent (SWE) products in operational hydrological and hydroclimate modeling applications is very demanding with limited uptake by these systems. Various causes have been attributed to this lack of up-take but most stem from insufficient SWE accuracy. The root causes of this challenge includes the coarse spatial resolution of passive microwave (PM) observations that observe highly aggregated snowpack properties at the spaceborne scale, and inadequacies during the retrieval process that are caused by uncertainties with the forward emission modeling of snow and challenges to find robust parameterizations of the models. While the spatial resolution problem is largely in the realm of engineering design and constrained by physical restrictions, a better understanding of the whole range of retrieval methodologies can provide the clarity needed to move the thinking forward in this important field. Following a review on snow depth and SWE retrieval methods using passive microwave remote sensing observations, this research employs a forward emission model to simulate snowpacks emission and compare the results to the PM airborne observations. Airborne radiometer observations coordinated with ground-based in-situ snow measurements were acquired in the Canadian high Arctic near Eureka, NT, in April 2011. The observed brightness temperatures (Tb) at 37 GHz from typical moderate density dry snow in mid-latitudes decreases with increasing snow water equivalent (SWE) due to the volume scattering of the ground emissions by the overlying snow. At a certain point, however, as SWE increases, the emission from the snowpack offsets the scattering of the sub-nivean emission. In tundra snow, the Tb slope reversal occurs at shallower snow thicknesses. While it has been postulated that the inflection point in the seasonal time series of observed Tb V 37 GHz of tundra snow is controlled by the formation of a thick wind slab layer, the simulation of this effect has yet to be confirmed. Therefore, the Dense Media Radiative Transfer Theory forMulti Layered (DMRT-ML) snowpack is used to predict the passive microwave response from airborne observations over shallow, dense, slab-layered tundra snow. The DMRT-ML was parameterized with the in-situ snow measurements using a two-layer snowpack and run in two configurations: a depth hoar and a wind slab dominated pack. Snow depth retrieval from passive microwave observations without a-priori information is a highly underdetermined system. An accurate estimate of snow depth necessitates a-priori information of snowpack properties, such as grain size, density, physical temperature and stratigraphy, and, very importantly, a minimization of this a prior information requirement. In previous studies, a Bayesian Algorithm for Snow Water Equivalent (SWE) Estimation (BASE) have been developed, which uses the Monte Carlo Markov Chain (MCMC) method to estimate SWE for taiga and alpine snow from 4-frequency ground-based radiometer Tb. In our study, BASE is used in tundra snow for datasets of 464 footprints inthe Eureka region coupled with airborne passive microwave observations—the same fieldstudy that forward modelling was evaluated. The algorithm searches optimum posterior probability distribution of snow properties using a cost function between physically based emission simulations and Tb observations. A two-layer snowpack based on local snow cover knowledge is assumed to simulate emission using the Dense Media Radiative Transfer-Multi Layered (DMRT-ML) model. Overall, the results of this thesis reinforce the applicability of a physics-based emission model in SWE retrievals. This research highlights the necessity to consider the two-part emission characteristics of a slab-dominated tundra snowpack and suggests performing inversion in a Bayesian framework

Human Figure Iconology is Two Pieces of Textile from Sassanid Era (With Images of the King’s Battle and the Tree of Life)

Throughout centuries, artistic creations have represented the culture and beliefs of every ethnic group, becoming inseparable from their art history. What remains from the Sasanian era is of special significance because of the political, religious and economic events of the day, and interpreting them helps discover more of the secrets buried in the period. Motifs are the most prominent feature of Sasanian art. The fabrics remaining from the Sassanid period are an important source to study the motifs of this period. These fabrics include elements with broad structural, religious, and mythological concepts. Studies show that there are many basic approaches to literary and artistic studies, including the iconology approach which has a relatively special place. Studying art, especially textiles, and reading the motifs of fabrics through iconology can remove many ambiguities in this regard, because this method uses description and analysis to examine the motifs and elements of fabrics and identify their implicit meanings and the reasons for their coincidence. With this in mind, this article aims to delve deeper into the symbols and signs of the fabrics of the Sassanid period and analyze their semantic layers. Aiming to fulfil this objective, the present study seeks to answer this question: “What are the hidden and semantic layers ofthe human figures on the two pieces of textile from Sassanid Era with images of king’s battle and tree of life, based on the iconological approach?” The hypothesis is that by exploring the superficial forms of the motifs of these two pieces of fabric and determining and interpreting the symbols, it is possible to come to their iconographic interpretation and identify at least some of the most meaningful symbolic meanings as a decorative element and a feature of Iranian art. Many studies have dealt with the motifs and symbols of the Sassanid period and the iconology approach. For example, Neda Akhavanaqdam (2017) studied the metal utensils of this period from an iconographic point of view, introducing symbols and discussing the motifs of hunting, ritual and court ceremonies in this period based on the metal art of the Sassanid era. An Introduction to Iconology by Nahid Abdi (2012) has described this approach and clarified the path of this theoretical study to the reader. This book can be a useful guide to the study of Sassanid motifs with this approach

Management of compassion fatigue in clinical nurses: A qualitative content analysis

Background: Compassion fatigue (CF) is a progressive process of absorbing patients’ pain and suffering resulting from caring interactions between caregivers and patients. Since compassion fatigue is strongly influenced by cultural and ethnic differences, the question arose, "How do Iranian deal with CF?”Objectives: This study aimed to obtain a deep understanding of Iranian nurses’ strategies in dealing with CF.Methods: The study was conducted using the conventional content analysis method. Purposive sampling was conducted to select clinical nurses working in hospitals of Tehran and Kashan Universities of Medical Sciences, Iran. Using semi-structured face-to-face interviews, data were collected from 13 nurses who had experienced CF. Data analysis was performed according to the steps proposed by Graneheim and Lundman. To prove the trustworthiness of the data, the four criteria of credibility, dependability, confirmability, and transferability were used.Results: Participants included 13 nurses whose average age was 31 years. Three categories emerged from the participants' experiences, namely "creating a work-life balance," "trying to ignore," and "use of support circle." All categories were placed under the theme of “struggling to survive in a turbulent workplace”.Conclusion: Nurses make lots of effort to deal with CF in personal and social levels. Healthcare managers can help nurses by providing them with more support, such as spiritual and organizational ones

Building children and adolescents’ electronic book reading system: a conceptual model

Regarding to design an applicable electronic book reading system for children and adolescent, this study’s struggle is to prepare a conceptual model. We used quantitative approach and Delphi method in order to analyze data. In this regard, criterion based sampling is used to identify the research population. 15 experts were identified which had criteria such as having subjective publications, teaching experience, and so on. We supposed that these experts could present more information that we expected to collect. Moreover, 8 electronic book systems were selected to be reviewed, because of their plenty of active audiences, and their international and also standard presence. Firstly identified practical criteria in designing electronic books by extracting them from related resources and checking active systems. These data helped us to prepare primitive version of the checklist and it completed after passing validity control step with participation of three experts. Then the checklist presented to experts in Delphi panel. Finally, consensus on the components was reached after three rounds of Delphi panel. The results showed that in designing electronic books for children, there are five original components. The components are display screen features with 12 criteria, screen organization with 13 criteria, interaction and feedback with 8 criteria, search and retrieval features with 10 criteria, and help and guidance features with 10 criteria. Consequently, display screen features with score of 3,706 and interaction and feedback with score of 3,700 were selected as the most important components in designing electronic book systems by the viewpoints of Delphi experts

Passive Microwave Sea Ice Edge Displacement Error over the Eastern Canadian Arctic for the period 2013-2021

In this study, sea ice edge derived from three passive microwave (PM) algorithms, ARTIST sea ice (ASI), enhanced NASA Team 2 (NT2), and Bootstrap (BT), are compared to those derived from the daily Canadian Ice Service charts over a primarily seasonal ice zone in the eastern Canadian Arctic for 2013–2021. To determine the ice edge error, we introduced an edge-length-based displacement measure called the edge displacement error (EDE), a dimensionless measurement obtained by dividing the weighted average Hausdorff distance by the ice edge length. We found that the ASI algorithm has the highest EDE on average, while the BT algorithm has the lowest one. In October (the beginning of the freeze-up period), the ice edge exhibits significant meandering, and the EDE is less sensitive to changes in the charted area. In the freeze-up period, the PM algorithms have the highest mean EDE value relative to other months due to the appearance of thin ice. A greater range of EDE values was observed in April than in other months. Throughout this region, the wind speed varies the most in April and May, whereas in April, the air temperature fluctuates more than in the other months

Incorporating Aleatoric Uncertainties in Lake Ice Mapping Using RADARSAT–2 SAR Images and CNNs

With the increasing availability of SAR imagery in recent years, more research is being conducted using deep learning (DL) for the classification of ice and open water; however, ice and open water classification using conventional DL methods such as convolutional neural networks (CNNs) is not yet accurate enough to replace manual analysis for operational ice chart mapping. Understanding the uncertainties associated with CNN model predictions can help to quantify errors and, therefore, guide efforts on potential enhancements using more–advanced DL models and/or synergistic approaches. This paper evaluates an approach for estimating the aleatoric uncertainty [a measure used to identify the noise inherent in data] of CNN probabilities to map ice and open water with a custom loss function applied to RADARSAT–2 HH and HV observations. The images were acquired during the 2014 ice season of Lake Erie and Lake Ontario, two of the five Laurentian Great Lakes of North America. Operational image analysis charts from the Canadian Ice Service (CIS), which are based on visual interpretation of SAR imagery, are used to provide training and testing labels for the CNN model and to evaluate the accuracy of the model predictions. Bathymetry, as a variable that has an impact on the ice regime of lakes, was also incorporated during model training in supplementary experiments. Adding aleatoric loss and bathymetry information improved the accuracy of mapping water and ice. Results are evaluated quantitatively (accuracy metrics) and qualitatively (visual comparisons). Ice and open water scores were improved in some sections of the lakes by using aleatoric loss and including bathymetry. In Lake Erie, the ice score was improved by ∼2 on average in the shallow near–shore zone as a result of better mapping of dark ice (low backscatter) in the western basin. As for Lake Ontario, the open water score was improved by ∼6 on average in the deepest profundal off–shore zone

Building children and adolescents’ electronic book reading system: a conceptual model

Regarding to design an applicable electronic book reading system for children and adolescent, this study’s struggle is to prepare a conceptual model. We used quantitative approach and Delphi method in order to analyze data. In this regard, criterion based sampling is used to identify the research population. 15 experts were identified which had criteria such as having subjective publications, teaching experience, and so on. We supposed that these experts could present more information that we expected to collect. Moreover, 8 electronic book systems were selected to be reviewed, because of their plenty of active audiences, and their international and also standard presence. Firstly identified practical criteria in designing electronic books by extracting them from related resources and checking active systems. These data helped us to prepare primitive version of the checklist and it completed after passing validity control step with participation of three experts. Then the checklist presented to experts in Delphi panel. Finally, consensus on the components was reached after three rounds of Delphi panel. The results showed that in designing electronic books for children, there are five original components. The components are display screen features with 12 criteria, screen organization with 13 criteria, interaction and feedback with 8 criteria, search and retrieval features with 10 criteria, and help and guidance features with 10 criteria. Consequently, display screen features with score of 3,706 and interaction and feedback with score of 3,700 were selected as the most important components in designing electronic book systems by the viewpoints of Delphi experts

Modeling the Observed Microwave Emission from Shallow Multi-Layer Tundra Snow Using DMRT-ML

The observed brightness temperatures (Tb) at 37 GHz from typical moderate density dry snow in mid-latitudes decreases with increasing snow water equivalent (SWE) due to volume scattering of the ground emissions by the overlying snow. At a certain point, however, as SWE increases, the emission from the snowpack offsets the scattering of the sub-nivean emission. In tundra snow, the Tb slope reversal occurs at shallower snow thicknesses. While it has been postulated that the inflection point in the seasonal time series of observed Tb V 37 GHz of tundra snow is controlled by the formation of a thick wind slab layer, the simulation of this effect has yet to be confirmed. Therefore, the Dense Media Radiative Transfer Theory for Multi Layered (DMRT-ML) snowpack is used to predict the passive microwave response from airborne observations over shallow, dense, slab-layered tundra snow. Airborne radiometer observations coordinated with ground-based in situ snow measurements were acquired in the Canadian high Arctic near Eureka, NT, in April 2011. The DMRT-ML was parameterized with the in situ snow measurements using a two-layer snowpack and run in two configurations: a depth hoar and a wind slab dominated pack. With these two configurations, the calibrated DMRT-ML successfully predicted the Tb V 37 GHz response (R correlation of 0.83) when compared with the observed airborne Tb footprints containing snow pits measurements. Using this calibrated model, the DMRT-ML was applied to the whole study region. At the satellite observation scale, observations from the Advanced Microwave Scanning Radiometer-Earth Observing System (AMSR-E) over the study area reflected seasonal differences between Tb V 37 GHz and Tb V 19 GHz that supports the hypothesis of the development of an early season volume scattering depth hoar layer, followed by the growth of the late season emission-dominated wind slab layer. This research highlights the necessity to consider the two-part emission characteristics of a slab-dominated tundra snowpack at 37 GHz Tb

Effects of Different Target Solar Fractions on Providing Heat Required for Space Heating, Sanitary Hot Water, and Swimming Pool in Iran: A Case Study in Cold Climate

Due to limited fossil fuel resources, population growth, and the need to save energy and prevent the emission of pollutants, solar heating is of great importance as a strategic solution. Due to these cases, in the present work, for the first time, the use of flat plate solar water heaters (SWHs) in Shahrekord located in the cold climate of Iran has been studied. The aim is to supply heating for space, sanitary hot water, and swimming pool of a residential apartment. Also, technical-economic-energy-environmental analyses have been done. Three low, medium, and high solar fraction scenarios have been selected for evaluations, and one-year dynamic analysis has been performed by TSOL 2018 commercial software. The required climatic data have been extracted by Meteonorm 7.3 software. The results showed that in most cases of heat supply, i.e., high solar fraction scenario, the percentage of solar heat supply for sanitary hot water, space heating, and swimming pool is 97.8%, 22.3%, and 44.3%, respectively, and the total solar fraction is 41%. Also, in this case, the release of more than 4 tons of CO2 pollutants has been prevented. Energy balance diagrams for different scenarios showed that 60% of losses are optical and thermal and also the highest rate of losses was related to the swimming pool. The lowest cost of heat generated and the lowest payback time were $ 0.028/kWh and 11.4 years, respectively, which were related to the high solar fraction scenario

Preparation of nanoliposomes containing HER2/neu (P5+435) peptide and evaluation of their immune responses and anti-tumoral effects as a prophylactic vaccine against breast cancer.

HER2/neu is an immunogenic protein inducing both humoral and cell-mediated immune responses. The antigen-specific cytotoxic T lymphocytes (CTLs) are the main effector immune cells in the anti-tumor immunity. To induce an effective CTL specific response against P5+435 single peptide derived from rat HER2/neu oncogene, we used a liposome delivery vehicle. In vivo enhancement of liposome stability and intracytoplasmic delivery of peptides are the main strategies which elevate the liposome-mediated drug delivery. Liposomes containing high transition temperature phospholipids, such as DSPC, are stable with prolonged in vivo circulation and more accessibility to the immune system. Incorporation of DOPE phospholipid results in the effective delivery of peptide into the cytoplasm via the endocytotic pathway. To this end, the P5+435 peptide was linked to Maleimide-PEG2000-DSPE and coupled on the surface of nanoliposomes containing DSPC: DSPG: Cholesterol with/without DOPE. We observed that mice vaccinated with Lip-DOPE-P5+435 formulation had the highest number of IFN-γ- producing CTLs with the highest cytotoxic activity that consequently led to significantly smallest tumor size and prolonged survival rate in the TUBO mice model. In conclusion, our study indicated that the liposomal form of P5+435 peptide containing DOPE can be regarded as a promising prophylactic anti-cancer vaccine to generate potent antigen-specific immunity