In-Situ Data Research Articles

Spatial Assessment and Mapping of Water Quality in Lake Sentani (Indonesia) Using In-Situ Data and Satellite Imagery

Spatial Assessment and Mapping of Water Quality in Lake Sentani (Indonesia) Using In-Situ Data and Satellite Imagery

Long short term memory deep net performance on fused Planet-Scope and Sentinel-2 imagery for detection of agricultural crop.

In view of the challenges faced by organizations and departments concerned with agricultural capacity observations, we collected In-Situ data consisting of diverse crops (More than 11 consumable vegetation types) in our pilot region of Harichand Charsadda, Khyber Pakhtunkhwa (KP), Pakistan. Our proposed Long Short-Term Memory based Deep Neural network model was trained for land cover land use statistics generation using the acquired ground truth data, for a synergy between Planet-Scope Dove and European Space Agency's Sentinel-2. Total of 4 bands from both sentinel-2 and planet scope including Red, Green, Near-Infrared (NIR) and Normalised Difference Vegetation Index (NDVI) were used for classification purpose. Using short temporal frame of Sentinel-2 comprising 5 date images, we propose an realistic and implementable procedure for generating accurate crop statistics using remote sensing. Our self collected data-set consists of a total number of 107,899 pixels which was further split into 70% and 30% for training and testing purpose of the model respectively. The collected data is in the shape of field parcels, which has been further split for training, validation and test sets, to avoid spatial auto-correlation. To ensure the quality and accuracy 15% of the training data was left out for validation purpose, and 15% for testing. Prediction was also performed on our trained model and visual analysis of the area from the image showed significant results. Further more a comparison between Sentinel-2 time series is performed separately from the fused Planet-Scope and Sentinel-2 time-series data sets. The results achieved shows a weighted average of 93% for Sentinel-2 time series and 97% for fused Planet-Scope and Sentinel-2 time series.

Forages and pastures symposium: an update on in vitro and in situ experimental techniques for approximation of ruminal fiber degradation.

Static quantification measures of chemical components are commonly used to make certain assumptions about forage or feed nutritive value and quality. In order for modern nutrient requirement models to estimate intake and digestibility more accurately, kinetic measures of ruminal fiber degradation are necessary. Compared to in vivo experiments, in vitro (IV) and in situ (IS) experimental techniques are relatively simple and inexpensive methods to determine the extent and rate of ruminal fiber degradation. This paper summarizes limitations of these techniques and statistical analyses of the resulting data, highlights key updates to these techniques in the last 30 yr, and presents opportunities for further improvements to these techniques regarding ruminal fiber degradation. The principle biological component of these techniques, ruminal fluid, is still highly variable because it is influenced by ruminally fistulated animal diet type and timing of feeding, and in the case of the IV technique by collection and transport procedures. Commercialization has contributed to the standardization, mechanization, and automation of the IV true digestibility technique, for example, the well-known DaisyII Incubator. There has been limited commercialization of supplies for the IS technique and several review papers focused on standardization in the last 30 yr; however, the IS experimental technique is not standardized and there remains variation within and among laboratories. Regardless of improved precision resulting from enhancements of these techniques, the accuracy and precision of determining the indigestible fraction are fundamental to modeling digestion kinetics and the use of these estimates in more complex dynamic nutritional modeling. Opportunities for focused research and development are additional commercialization and standardization, methods to improve the precision and accuracy of indigestible fiber fraction, data science applications, and statistical analyses of results, especially for IS data. In situ data is typically fitted to one of a few first-order kinetic models, and parameters are estimated without determining if the selected model has the best fit. Animal experimentation will be fundamental to the future of ruminant nutrition and IV and IS techniques will remain vital to bring together nutritive value with forage quality. It is feasible and important to focus efforts on improving the precision and accuracy of IV and IS results.

Modeling efforts for multi-mission science

AbstractThe Solar Orbiter spacecraft, launched in February 2020, is equipped with both remote-sensing (RS) and in-situ (IS) instruments to record novel and unprecedented measurements of the solar atmosphere and the inner heliosphere. To take full advantage of these new datasets, we have developed tools and techniques to facilitate multi-instrument and multi-spacecraft studies. In particular the yet inaccessible low solar corona below 2 R⊙ can only be observed remotely and techniques must be used to retrieve coronal plasma properties in time and in 3-D space. These properties are useful to drive numerical models and test the different theories proposed to describe the fundamental processes of the solar atmosphere. In addition, the last decades of research have shown that the coupling between the solar corona and the heliosphere is most efficiently studied by combining RS with IS data. During one of the last Solar Orbiter remote sensing windows (March 2022), planned for the Solar Orbiter instruments, we ran complex observation campaigns to maximize the likelihood of linking IS data to their source region near the Sun, by directing some RS instruments to specific targets on the solar disk just days before data acquisition. We show how it is possible to achieve these results directed to improve our understanding of how heliospheric probes connect magnetically to the solar disk.

Climatic, Decadal, and Interannual Variability in the Upper Layer of the Mediterranean Sea Using Remotely Sensed and In-Situ Data

The Mediterranean Sea is considered a hot spot of global warming because it has been changing faster than the global ocean, creating a strong impact on the marine environment. Recent studies agree on the increase in the sea level, in the sea surface temperature, and in the sea surface salinity in the Mediterranean Sea over the last two decades. In this research, the possible interconnection between these and other parameters that contribute to the regulatory effect of the sea on the climate are identified and discussed. Spatio-temporal variability of four oceanographic and air–sea interaction parameters (sea-level, sea surface temperature, sea surface salinity, and freshwater flux) are estimated over the last 27 years by performing the empirical orthogonal function analysis. Climatic trends, and interannual and decadal variability of the different datasets are delineated and described in the whole Mediterranean and in its sub-basins. On the climatic scale, the Mediterranean and its sub-basins behave in a coherent way, showing the seal level, temperature, salinity, and freshwater flux rise. On the interannual scale, the temporal evolution of the sea level and sea surface temperature are highly correlated, whereas freshwater flux affects the variability of sea level, temperature, and the salinity field mainly in the Western and Central Mediterranean. The decadal signal associated with the Northern Ionian Gyre circulation reversals is clearly identified in three of the four parameters considered, with different intensities and geographical extents. This signal also affects the intermediate layer of the Eastern Mediterranean, from where it is advected to the other sub-basins. Decadal signal not associated with the Northern Ionian Gyre reversals is strongly related to the variability of main sub-basin scale local structures.

Four years of global carbon cycle observed from the Orbiting Carbon Observatory 2 (OCO-2) version 9 and in situ data and comparison to OCO-2 version 7

Abstract. The Orbiting Carbon Observatory 2 (OCO-2) satellite has been providing information to estimate carbon dioxide (CO2) fluxes at global and regional scales since 2014 through the combination of CO2 retrievals with top–down atmospheric inversion methods. Column average CO2 dry-air mole fraction retrievals have been constantly improved. A bias correction has been applied in the OCO-2 version 9 retrievals compared to the previous OCO-2 version 7r improving data accuracy and coverage. We study an ensemble of 10 atmospheric inversions all characterized by different transport models, data assimilation algorithms, and prior fluxes using first OCO-2 v7 in 2015–2016 and then OCO-2 version 9 land observations for the longer period 2015–2018. Inversions assimilating in situ (IS) measurements have also been used to provide a baseline against which the satellite-driven results are compared. The time series at different scales (going from global to regional scales) of the models emissions are analyzed and compared to each experiment using either OCO-2 or IS data. We then evaluate the inversion ensemble based on the dataset from the Total Carbon Column Observing Network (TCCON), aircraft, and in situ observations, all independent from assimilated data. While we find a similar constraint of global total carbon emissions between the ensemble spread using IS and both OCO-2 retrievals, differences between the two retrieval versions appear over regional scales and particularly in tropical Africa. A difference in the carbon budget between v7 and v9 is found over this region, which seems to show the impact of corrections applied in retrievals. However, the lack of data in the tropics limits our conclusions, and the estimation of carbon emissions over tropical Africa require further analysis.

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions.

Validation of the EUMETSAT H-SAF H10 Snow Detection Product for the 2018-2019 Snow Season in Turkey using in-Situ Data and Sentinel 2 Imagery

Kar örtüsünün özellikleriyle ilgili bilgiler, özellikle hidrolojik amaçlar için yürütülen çeşitli bilimsel çalışmalar ve operasyonel uygulamalar için kritik öneme sahiptir. Uzaktan algılama mevsimsel kar örtüsünün geniş alanlarda ve sürekli olarak izlenebilmesi için oldukça uygun bir kaynaktır. Bu çalışmanın temel amacı Avrupa Meteorolojik Uydulardan Yararlanma Teşkilatı'nın (EUMETSAT - European Organization for the Exploitation of Meteorological Satellites) Operasyonel Hidroloji ve Su Yönetimine Destek (H-SAF - Satellite Application Facility on Support to Operational Hydrology and Water Management) projesi kapsamında üretilmekte olan düşük çözünürlüklü günlük operasyonel H10 (SN-OBS-1) kar algılama ürününün yer istasyon verisi ve daha yüksek çözünürlüğe sahip Sentinel 2 uydu görüntüleri kullanılarak 2018-2019 Türkiye kar sezonu için doğrulamasının yapılmasıdır. Çalışmada 101 yer istasyon verisinden elde edilen kar derinliği ölçümleri ile 106 Sentinel 2 görüntüsünden üretilen ikili kar haritaları referans veri olarak kullanılmıştır. Yer verisiyle yapılan doğrulama sonuçlarına göre H-SAF H10 kar ürününün algılama olasılığı 0.60 olurken, referans uydu görüntüleri ürünün 2018-2019 kar sezonu için algılama olasılığının 0.89 olduğunu ortaya koymaktadır. Her iki referans veriye göre ürünün yanlış algılama oranının ise oldukça düşük olduğu görülmektedir (≤ 0,11).

Bioecology of coral reef in Panjang Island of Central Java Indonesia

Coral reefs currently are suffered from natural factors along with increasing anthropogenic activity. Panjang Island, a small reef island located in Jepara Regency, may also be experiencing such conditions. Therefore, this work was aimed to observe the condition of the coral cover of Panjang Island. Line intercept transect was applied to survey the coral cover and mortality index from fourteen stations. Insitu data consisted of the bottom substrate composition of the reefs and the physical parameters of the sea. The secondary data, i.e. coral reef area maps from 2001 to 2019 were taken from Landsat Image 7 and 8, data of wind were obtained from www.ogimet.com, while tidal data were collected from BMKG. The bathymetry was determined from the Geospatial Information Agency data, salinity global analysis forecast Phy 001.024 (CMEMS). Sea surface temperature (SST), and chlorophyll-a distribution were analyzed using ENVI software. The result showed that Panjang Island has a poor to the moderate condition of hard coral. Two out of six categories of abiotic and dead coral were found to be high. The mortality index of coral was in the high category (average 0.52). During research periods the sea waters were characterized by high sea surface temperature (29.34-30.94°C), chlorophyll-a was also tended to be high (0-2.65 mg.m-3), and an average of salinity was high 32 ‰. The weak currents came to all sides of the island, therefore the coral reef was not exposed to extreme currents. The waves came from the east, then the energy decreases after being blocked by coral reefs on the eastern side of the island, so that coral reefs in the northeast and south sides were safer to be exposed. The results suggest that hydrodynamic ecology directly or indirectly affected the percentage of coral cover and mortality index at the reefs of Panjang Island.

Models and data analysis tools for the Solar Orbiter mission

Context.The Solar Orbiter spacecraft will be equipped with a wide range of remote-sensing (RS) and in situ (IS) instruments to record novel and unprecedented measurements of the solar atmosphere and the inner heliosphere. To take full advantage of these new datasets, tools and techniques must be developed to ease multi-instrument and multi-spacecraft studies. In particular the currently inaccessible low solar corona below two solar radii can only be observed remotely. Furthermore techniques must be used to retrieve coronal plasma properties in time and in three dimensional (3D) space. Solar Orbiter will run complex observation campaigns that provide interesting opportunities to maximise the likelihood of linking IS data to their source region near the Sun. Several RS instruments can be directed to specific targets situated on the solar disk just days before data acquisition. To compare IS and RS, data we must improve our understanding of how heliospheric probes magnetically connect to the solar disk.Aims.The aim of the present paper is to briefly review how the current modelling of the Sun and its atmosphere can support Solar Orbiter science. We describe the results of a community-led effort by European Space Agency’s Modelling and Data Analysis Working Group (MADAWG) to develop different models, tools, and techniques deemed necessary to test different theories for the physical processes that may occur in the solar plasma. The focus here is on the large scales and little is described with regards to kinetic processes. To exploit future IS and RS data fully, many techniques have been adapted to model the evolving 3D solar magneto-plasma from the solar interior to the solar wind. A particular focus in the paper is placed on techniques that can estimate how Solar Orbiter will connect magnetically through the complex coronal magnetic fields to various photospheric and coronal features in support of spacecraft operations and future scientific studies.Methods.Recent missions such as STEREO, provided great opportunities for RS, IS, and multi-spacecraft studies. We summarise the achievements and highlight the challenges faced during these investigations, many of which motivated the Solar Orbiter mission. We present the new tools and techniques developed by the MADAWG to support the science operations and the analysis of the data from the many instruments on Solar Orbiter.Results.This article reviews current modelling and tool developments that ease the comparison of model results with RS and IS data made available by current and upcoming missions. It also describes the modelling strategy to support the science operations and subsequent exploitation of Solar Orbiter data in order to maximise the scientific output of the mission.Conclusions.The on-going community effort presented in this paper has provided new models and tools necessary to support mission operations as well as the science exploitation of the Solar Orbiter data. The tools and techniques will no doubt evolve significantly as we refine our procedure and methodology during the first year of operations of this highly promising mission.

Testing Urban Flood Mapping Approaches from Satellite and In-Situ Data Collected during 2017 and 2019 Events in Eastern Canada

The increasing frequency of flooding worldwide has driven research to improve near real-time flood mapping from remote-sensing data. Improved automation and processing speed to map both open water and vegetated area flooding have resulted from these research efforts. Despite these achievements, flood mapping in urban areas where a significant number of overall impacts are felt remains a challenge. Near real-time data availability, shadowing caused by manmade infrastructure, spatial resolution, and cloud cover inhibiting optical transmission, are all factors that complicate detailed urban flood mapping needed to inform response efforts. This paper uses numerous data sources collected during two major flood events that impacted the same region of Eastern Canada in 2017 and 2019 to test different urban flood mapping approaches presented as case studies in three separate urban boroughs. Cloud-free high-resolution 3 m PlanetLab optical data acquired near peak-flood in 2019 were used to generate a maximum flood extent product for that year. Approaches using new Lidar Digital Elevation Models (DEM)s and water height estimated from nineteen RADARSAT-2 flood maps, point-based flood perimeter observations from citizen geographic information, and simulated traffic camera or other urban sensor network data were tested and verified using independent data. Coherent change detection (CCD) using multi-temporal Interferometric Wide (IW) Sentinel-1 data was also tested. Results indicate that while clear-sky high-resolution optical imagery represents the current gold standard, its availability is not guaranteed due to timely coverage and cloud cover. Water height estimated from 8 to 12.5 m resolution RADARSAT-2 flood perimeters were not sufficiently accurate to flood adjacent urban areas using a Lidar DEM in near real-time, but all nineteen scenes combined captured boroughs that flooded at least once in both flood years. CCD identified flooded boroughs and roughly captured their flood extents, but lacked timeliness and sufficient detail to inform street-level decision-making in near real-time. Point-based flood perimeter observation, whether from in-situ sensors or high-resolution optical satellites combined with Lidar DEMs, can generate accurate full flood extents under certain conditions. Observed point-based flood perimeters on manmade features with low topographic variation produced the most accurate flood extents due to reliable water height estimation from these points.

In-Situ Pipeline Monitoring System Design for Identifying and Locating Damaging Activities Based on Wireless Sensor Network

Due to the recent advancements in the fields of Micro Electromechanical Sensors (MEMS), communication, and operating systems, wireless remote monitoring methods became easy to build and low cost option compared to the conventional methods such as wired cameras and vehicle patrols. Pipeline Monitoring Systems (PMS) benefit the most of such wireless remote monitoring since each pipeline would span for long distances up to hundreds of kilometers. However, precise monitoring requires moving large amounts of data between sensor nodes and base station for processing which require high bandwidth communication protocol. To overcome this problem, In-Situ processing can be practiced by processing the collected data locally at each node instead of the base station. This Paper presents the design and implementation of In-situ pipeline monitoring system for locating damaging activities based on wireless sensor network. The system built upon a WSN of several nodes. Each node contains high computational 1.2GHz Quad-Core ARM Cortex-A53 (64Bit) processor for In-Situ data processing and equipped in 3-axis accelerometer. The proposed system was tested on pipelines in Al-Mussaib gas turbine power plant. During test knocking events are applied at several distances relative to the nodes locations. Data collected at each node are filtered and processed locally in real time in each two adjacent nodes. The results of the estimation is then sent to the supervisor at base-station for display. The results show the proposed system ability to estimate the location of knocking event.

Assessment with Controlled In-Situ Data of the Dependence of L-Band Radiometry on Sea-Ice Thickness

The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) missions are providing brightness temperature measurements at 1.4 GHz (L-band) for about 10 and 4 years respectively. One of the new areas of geophysical exploitation of L-band radiometry is on thin (i.e., less than 1 m) Sea Ice Thickness (SIT), for which theoretical and empirical retrieval methods have been proposed. However, a comprehensive validation of SIT products has been hindered by the lack of suitable ground truth. The in-situ SIT datasets most commonly used for validation are affected by one important limitation: They are available mainly during late winter and spring months, when sea ice is fully developed and the thickness probability density function is wider than for autumn ice and less representative at the satellite spatial resolution. Using Upward Looking Sonar (ULS) data from the Woods Hole Oceanographic Institution (WHOI), acquired all year round, permits overcoming the mentioned limitation, thus improving the characterization of the L-band brightness temperature response to changes in thin SIT. State-of-the-art satellite SIT products and the Cumulative Freezing Degree Days (CFDD) model are verified against the ULS ground truth. The results show that the L-band SIT can be meaningfully retrieved up to 0.6 m, although the signal starts to saturate at 0.3 m. In contrast, despite the simplicity of the CFDD model, its predicted SIT values correlate very well with the ULS in-situ data during the sea ice growth season. The comparison between the CFDD SIT and the current L-band SIT products shows that both the sea ice concentration and the season are fundamental factors influencing the quality of the thickness retrieval from L-band satellites.

Mapping of Snow Depth by Blending Satellite and In-Situ Data Using Two-Dimensional Optimal Interpolation—Application to AMSR2

The development of a snow depth product over North America is investigated by applying two-dimensional optimal interpolation to passive microwave satellite-derived and in-situ measured snow depth. At each snow-covered satellite footprint, the technique computes a snow depth increment as the weighted average of data increments, and updates the satellite-derived snow depth accordingly. Data increments are computed as the difference between the in-situ-measured and satellite snow depth at station locations surrounding the satellite footprint. Calculation of optimal weights is based on spatial lag autocorrelation of snow depth increments, modelled as functions of horizontal distance and elevation difference between pairs of observations. The technique is applied to Advanced Microwave Scanning Radiometer 2 (AMSR2) snow depth and in-situ snow depth obtained from the Global Historical Climatology Network. The results over North America during January–February 2017 indicate that the technique greatly enhances the performance of the satellite estimates, especially over mountain terrain, albeit with an accuracy inferior to that over low elevation areas. Moreover, the technique generates more accurate output compared to that from NOAA’s Global Forecast System, with implications for improving the utilization of satellite data in snow assessments and numerical weather prediction.

Multiple modeling to estimate sediment loss and transport capacity employing hourly rainfall and In-Situ data: A prioritization of highland watershed in Awash River basin, Ethiopia

In present study, the sediment yield/loss and Transport Capacity (TC) has been estimated in a highland watershed of Adama Woreda, part of Awash River Basin in Ethiopia. For the study, average hourly 14 years rainfall data obtained from different gauging stations in the study area during 2001–2014 was utilized to calculate rain erosivity (R factor). Subsequently, soil erodibility K, length-slope LS factors of Revised Universal Soil Loss Equation (RUSLE) were adopted for the calculation of WATEM/SEDEM sediment delivery algorithm. The average R factor value for the watershed was evaluated as 2075.27 MJ/ha mm/year. The grid based KTC (Transport Capacity Coefficient) was determined for the WATEM/SEDEM sediment transport estimation through the results of Soil Water Assessment Tool (SWAT) and Revised/Modified USLE. The SWAT simulated suspended solids (SS) versus two years (2013 and 2014) rainfall measured records at single observatory was used for the SWAT calibration and validation. The SWAT sediment yields and Transport Capacity (TC) were used to determine the KTC at each sub-watershed. The mean value of KTC was estimated 8.033 and minimum and maximum values were found 0.080 and 51.49 respectively. Moreover, the Sediment Deliver Ratio (SDR) model equation was calculated and resulted values were found >0.7 in the main streams. For the prioritization, sediment yield and loss estimated values using Sediment Yield Index (SYI) and RUSLE along with SWAT models were employed. The results generated through these models were averaged and accordingly the ranks and severity classes were determined.

The Niwot Ridge Subalpine Forest US-NR1 AmeriFlux site – Part 1: Data acquisition and site record-keeping

Abstract. The Niwot Ridge Subalpine Forest AmeriFlux site (US-NR1) has been measuring eddy-covariance ecosystem fluxes of carbon dioxide, heat, and water vapor since 1 November 1998. Throughout this 17-year period there have been changes to the instrumentation and improvements to the data acquisition system. Here, in Part 1 of this three-part series of papers, we describe the hardware and software used for data-collection and metadata documentation. We made changes to the data acquisition system that aimed to reduce the system complexity, increase redundancy, and be as independent as possible from any network outages. Changes to facilitate these improvements were (1) switching to a PC/104-based computer running the National Center for Atmospheric Research (NCAR) In-Situ Data Acquisition Software (NIDAS) that saves the high-frequency data locally and over the network, and (2) time-tagging individual 10 Hz serial data samples using network time protocol (NTP) coupled to a GPS-based clock, providing a network-independent, accurate time base. Since making these improvements almost 2 years ago, the successful capture of high-rate data has been better than 99.98 %. We also provide philosophical concepts that shaped our design of the data system and are applicable to many different types of environmental data collection.

Multi-dimensional interpolation of SMOS sea surface salinity with surface temperature and in situ salinity data

Availability of accurate remotely-sensed sea surface salinity (SSS) measurements is crucial to investigating fundamental aspects of the global hydrological cycle, ocean dynamics and marine biogeochemistry. The European Space Agency (ESA) Soil Moisture Ocean Salinity (SMOS) mission has been specifically designed for this aim. However, SMOS data display a high level of noise with respect to the signal they have to detect. Space–time averaging over relatively large sampling periods/areas is thus generally carried out to increase SSS accuracy, and further interpolation is required to fill in data gaps resulting from both mission geometry and other instrumental/physical limitations. Here, a daily, 1/4° nominal resolution, mesoscale-resolving SSS field product is obtained by using a multidimensional optimal interpolation (OI) algorithm combining SMOS salinity retrievals and satellite sea surface temperature data with in situ salinity measurements. The methodology has been developed in the framework of the ESA OSMOSIS (Ocean ecoSystem Modelling based on Observations from Satellite and In-Situ data) project and it is applied here to a wide zonal portion of the Southern Hemisphere (10°S–65°S). The interpolated SSS has been validated by looking at the differences with respect to fully independent in situ observations and by performing a wavenumber spectrum analysis. Despite minor progress being obtained in terms of root mean square of the differences with respect to in situ observations, a significant improvement in terms of effective spatial resolution is obtained with the new technique with respect to presently available SSS observation-based analyses.

Gas Pressure and Temperature Measuring System (GTM) for In-Situ Data Acquisition during Planetary Ball Milling

Gas Pressure and Temperature Measuring System (GTM) for In-Situ Data Acquisition during Planetary Ball Milling

Gas Pressure and Temperature Measuring System (GTM) for In-Situ Data Acquisition during Planetary Ball Milling

Gas Pressure and Temperature Measuring System (GTM) for In-Situ Data Acquisition during Planetary Ball Milling

Major solar flares and long-term variability in Antarctic ice cores

In-Situ data acquisition of high-resolution nitrate concentration in Antarctic snow resulting from ionization in the polar atmosphere reveals (a) very large solar proton events can be resolved, (b) a signal from thermospheric and mesospheric sources is found across Antarctica within the average boundaries of the auroral oval, (c) long-term periods of high or low solar activity, such as the Maunder Minimum are present in the nitrate record.