Among the essential tools to address global environmental information requirements are the Earth-Observing (EO) satellites with free and open data access. This paper reviews those EO satellites from international space programs that already, or will in the next decade or so, provide essential data of importance to the environmental sciences that describe Earth's status. We summarize factors distinguishing those pioneering satellites placed in space over the past half century, and their links to modern ones, and the changing priorities for spaceborne instruments and platforms. We illustrate the broad sweep of instrument technologies useful for observing different aspects of the physio-biological aspects of the Earth's surface, spanning wavelengths from the UV-A at 380 nanometers to microwave and radar out to 1 m. We provide a background on the technical specifications of each mission and its primary instrument(s), the types of data collected, and examples of applications that illustrate these observations. We provide websites for additional mission details of each instrument, the history or context behind their measurements, and additional details about their instrument design, specifications, and measurements.

The SCATSAT-1 (Scatterometer Satellite) was launched by ISRO (Indian Space Research Organisation) on September 26, 2016 from the Satish Dhawan Space Centre, Sriharikota, India. With nearly five years of its journey, the Ku-band (13.5 GHz) based SCATSAT-1 made a profound impact on many scientific domains such as ocean-atmosphere dynamics, soil moisture and vegetation dynamics, climate change, hydrology and polar sea-ice and snowmelt studies. As a successor of the Oceansat-2 Scatterometer (OSCAT), the SCATSAT-1 supports the long-term analysis in climate studies, crop yield prediction, and forecasting analysis. In addition, the SCATSAT-1 provides the four different levels of data products at an enhanced resolution to improve the scope of the scatterometer in different applications. Recently the SCATSAT-1 has been explored in many emerging applications apart from oceanography e.g., crop growth, snow cover analysis, jute crop detection and river level estimation with advanced algorithms i.e., machine learning-based classification, information fusion, and super-resolution mapping. Therefore, it is desired to summarise all operational SCATSAT-1 products, applications, and their emerging trends at the global level in the various scientific domains. This paper has summarized the progress made by SCATSAT-1 in different scientific domains since its launch. A meta-analysis has also been conducted in this paper (using the SCOPUS database) to analyse the current research status of SCATSAT-1 in terms of study area targets. This study highlights the features, challenges, and future directions for the scatterometer improvements.

The of the Yellow River between its source and Hekou Town in Inner Mongolia is known as the Upper Yellow River Basin. It is the main source area of water resources in the Yellow River Basin, providing reliable water resources for 120 million people. Studying the hydrometeorological changes in the Upper Yellow River Basin is crucial for the development of human society. However, in the past, there has been limited research on hydrometeorological changes in the Upper Yellow River Basin. In order to clarify the four-dimensional spatiotemporal variation characteristics of hydrometeorological elements in the Upper Yellow River Basin, satellite and reanalysis hydrometeorological elements products need to be used. Unfortunately, there is currently a lack of precise evaluation studies on satellite and reanalysis hydrometeorological elements products in the Upper Yellow River Basin, and the geomorphic characteristics of this area have raised doubts about the accuracy of satellite and reanalysis hydrometeorological elements products. Thus, the evaluation study in the Upper Yellow River Basin is an important prerequisite for studying the four-dimensional spatiotemporal changes of hydrometeorological elements. When conducting evaluation study, we found that previous evaluation studies had a very confusing understanding of the spatiotemporal characteristics of datasets. Some papers even treated the spatiotemporal characteristics of evaluation metrics as the spatiotemporal characteristics of datasets. Therefore, we introduced a four-dimensional spacetime of both datasets and evaluation metrics to rectify the chaotic spatiotemporal view in the past. Our research results show that satellite and reanalysis hydrometeorological elements products have different abilities in describing the temporal and spatial distribution and change characteristics of hydrometeorological elements. The difference in the ability of satellite and reanalysis hydrometeorological elements products to describe temporal and spatial distribution and change characteristics requires us to select data at different temporal and spatial scales according to research needs when conducting hydrometeorological research, in order to ensure the credibility of the research results.

Humidity is a basic and crucial meteorological indicator commonly measured in several forms, including specific humidity, relative humidity, and absolute humidity. These different forms can be inter-derived based on the saturation vapor pressure (SVP). In past decades, dozens of formulae have been developed to calculate the SVP with respect to, and in equilibrium with, liquid water and solid ice surfaces, but many prior studies use a single function for all temperature ranges, without considering the distinction between over the liquid water and ice surfaces. These different approaches can result in humidity estimates that may impact our understanding of surface-subsurface thermal-hydrological dynamics in cold regions. In this study, we compared the relative humidity (RH) downloaded and calculated from four data sources in Alaska based on five commonly used SVP formulas. These RHs, along with other meteorological indicators, were then used to drive physics-rich land surface models at a permafrost-affected site. We found that higher values of RH (up to 40 %) were obtained if the SVP was calculated with the over-ice formulation when air temperatures were below freezing, which could lead to a 30 % maximum difference in snow depths. The choice of whether to separately calculate the SVP over an ice surface in winter also produced a significant range (up to 0.2 m) in simulated annual maximum thaw depths. The sensitivity of seasonal thaw depth to the formulation of SVP increases with the rainfall rate and the height of above-ground ponded water, while it diminishes with warmer air temperatures. These results show that RH variations based on the calculation of SVP with or without over-ice calculation meaningfully impact physicallybased predictions of snow depth, sublimation, soil temperature, and active layer thickness. Under particular conditions, when severe flooding (inundation) and cool air temperatures are present, care should be taken to evaluate how humidity data is estimated for land surface and earth system modeling

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan city of China in late December 2019 and identified as a novel coronavirus. Due to its contagious nature, the virus spreads rapidly and causes coronavirus disease 2019 (COVID-19). The global tally of COVID-19 was 28 million in early September 2020. The fears and stress associated with SARS-CoV-2 has demolished the socio-economic status worldwide. Researchers are trying to identify treatments, especially antiviral drugs and/or vaccines, that could potentially control the viral spread and manage the ongoing unprecedented global crisis. To date, more than 300 clinical trials have been conducted on various antiviral drugs, and immunomodulators are being evaluated at various stages of COVID-19. This review aims to collect and summarize a list of drugs used to treat COVID-19, including dexamethasone, chloroquine, hydroxychloroquine, lopinavir/ritonavir, favipiravir, remdesivir, tociluzimab, nitazoxanide and ivermectin. However, some of these drugs are not effective and their use has been suspended by WHO. (C) 2020 The Authors. Published by Elsevier Ltd.

The increase in temperatures and changing precipitation patterns resulting from climate change are accelerating the occurrence and development of landslides in cold regions, especially in permafrost environments. Although the boundary regions between permafrost and seasonally frozen ground are very sensitive to climate warming, slope failures and their kinematics remain barely characterized or understood in these regions. Here, we apply multisource remote sensing and field investigation to study the activity and kinematics of two adjacent landslides (hereafter referred to as twin landslides) along the Datong River in the Qilian Mountains of the Qinghai-Tibet Plateau. After failure, there is no obvious change in the area corresponding to the twin landslides. Based on InSAR measurements derived from ALOS PALSAR-1 and -2, we observe significant downslope movements of up to 15 mm/day within the twin landslides and up to 5 mm/day in their surrounding slopes. We show that the downslope movements exhibit distinct seasonality; during the late thaw and early freeze season, a mean velocity of about 4 mm/day is observed, while during the late freeze and early thaw season the downslope velocity is nearly inactive. The pronounced seasonality of downslope movements during both pre- and post-failure stages suggest that the occurrence and development of the twin landslide are strongly influenced by freeze-thaw processes. Based on meteorological data, we infer that the occurrence of twin landslides are related to extensive precipitation and warm winters. Based on risk assessment, InSAR measurements, and field investigation, we infer that new slope failure or collapse may occur in the near future, which will probably block the Datong River and cause catastrophic disasters. Our study provides new insight into the failure mechanisms of slopes at the boundaries of permafrost and seasonally frozen ground.

Climate changes significantly impact the hydrological cycle. Precipitation is one of the most important atmospheric inputs to the terrestrial hydrologic system, and its variability considerably influences environmental and socioeconomic development. Atmospheric warming intensifies the hydrological cycle, increasing both atmospheric water vapor concentration and global precipitation. The relationship between heavy precipitation and temperature has been extensively investigated in literature. However, the relationship in different percentile ranges has not been thoroughly analyzed. Moreover, a percentilebased regression provides a simple but effective framework for investigation into other factors (precipitation type) affecting this relationship. Herein, a comprehensive investigation is presented on the temperature dependence of daily precipitation in various percentile ranges over the Qinghai-Tibet Plateau. The results show that 1) most stations exhibit a peaklike scaling structure, while the northeast part and south margin of the plateau exhibit monotonic positive and negative scaling structures, respectively. The scaling structure is associated with the precipitation type, and 2) the positive and negative scaling rates exhibit similar spatial patterns, with stronger (weaker) sensitivity in the south (north) part of the plateau. The overall increase rate of daily precipitation with temperature is scaled by Clausius-Clapeyron relationship. 3) The higher percentile of daily precipitation shows a larger positive scaling rate than the lower percentile. 4) The peak-point temperature is closely related to the local temperature, and the regional peak-point temperature is roughly around 10 degrees C.

As one of the best indicators of the periglacial environment, ice-wedge polygons (IWPs) are important for arctic landscapes, hydrology, engineering, and ecosystems. Thus, a better understanding of the spatiotemporal dynamics and evolution of IWPs is key to evaluating the hydrothermal state and carbon budgets of the arctic permafrost environment. In this paper, the dynamics of ground surface deformation (GSD) in IWP zones (2018-2019) and their influencing factors over the last 20 years in Saskylakh, northwestern Yakutia, Russia were investigated using the Interferometric Synthetic Aperture Radar (InSAR) and Google Earth Engine (GEE). The results show an annual ground surface deformation rate (AGSDR) in Saskylakh at -49.73 to 45.97 mm/a during the period from 1 June 2018 to 3 May 2019. All the selected GSD regions indicate that the relationship between GSD and land surface temperature (LST) is positive (upheaving) for regions with larger AGSDR, and negative (subsidence) for regions with lower AGSDR. The most drastic deformation was observed at the Aeroport regions with GSDs rates of -37.06 mm/a at tower and 35.45 mm/a at runway. The GSDs are negatively correlated with the LST of most low-centered polygons (LCPs) and high-centered polygons (HCPs). Specifically, the higher the vegetation cover, the higher the LST and the thicker the active layer. An evident permafrost degradation has been observed in Saskylakh as reflected in higher ground temperatures, lusher vegetation, greater active layer thickness, and fluctuant numbers and areal extents of thermokarst lakes and ponds.

Arctic zone of the Russian Federation (AZRF) is the region of intensive economic development. In this regard, it is critical to give an adequate assessment of natural factors that may have a negative impact on the growing technological infrastructure. Rapid climate change effects show a significant influence on this activity, including the railway network development. Hence, the decision-making community requires relevant information on climatic variations that can put at hazard the construction and operation of railway facilities. This paper presents the analysis of climatic changes within the region of Central and Western Russian Arctic in 1980-2021. It was performed using the new electronic Atlas of climatic variations in main hydrometeorological parameters, created for the Russian Railways in 2023. This geoinformatic product includes about 400 digital maps reflecting the variability of seven climatic parameters over more than four decades within the studied region. These parameters are air temperature, total precipitation, wind speed, soil temperature, soil moisture content, air humidity, and snow cover thickness. The analysis of climatic maps and their comparison between selected periods showed spatial and temporal heterogeneity of climatic variations in this region. This justifies the feasibility of further research using additional analytical instruments, such as Hovm & ouml;ller diagrams, time series graphs, etc. The implementation of advanced geoinformatic products in the practice of the Russian Railways will facilitate sustainable development of its infrastructure in rapidly altering climatic conditions.

The addition of coating to the black carbon (BC) enhances its absorption as more light is focused by the coating lens. The absorption enhancement factor (E-abs) of BC is difficult to quantify due to an inadequate representation of its mixing structure and the interaction with radiation. Here, by tracking the evolution of the fresh BC particles in the ambient, we found a transitional stage of the particle E-abs with the non-BC-to-BC mass ratio (R-BC) at similar to 2, below which there were insufficient coating materials to encapsulate the BC core and the absorption enhancement was not significant (similar to 14%). When the R-BC >similar to 2, obvious absorption enhancement occurred as the BC cores were fully covered. Secondary inorganic species played the most critical role in the coating materials to enhance the lensing effect. We suppose the particle-resolved core-shell Mie model can be applied in the E-abs prediction for most cases.