scholarly journals Large River Plumes Detection by Satellite Altimetry: Case Study of the Ob–Yenisei Plume

2021 ◽  
Vol 13 (24) ◽  
pp. 5014
Author(s):  
Dmitry Frey ◽  
Alexander Osadchiev

Satellite altimetry is an efficient instrument for detection dynamical processes in the World Ocean, including reconstruction of geostrophic currents and tracking of mesoscale eddies. Satellite altimetry has the potential to detect large river plumes, which have reduced salinity and, therefore, elevated surface level as compared to surrounding saline sea. In this study, we analyze applicability of satellite altimetry for detection of the Ob–Yenisei plume in the Kara Sea, which is among the largest river plumes in the World Ocean. Based on the extensive in situ data collected at the study area during oceanographic surveys in 2007–2019, we analyze the accuracy and efficiency of satellite altimetry in reproducing, first, the outer boundary of the plume and, second, the internal structure of the plume. We reveal that the value of positive level anomaly within the Ob–Yenisei plume strongly depends on the vertical plume structure and is prone to significant synoptic and seasonal variability due to wind forcing and mixing of the plume with subjacent sea. As a result, despite generally high statistical correlation between the ADT and surface salinity, straightforward usage of ADT for detection of the river plume is incorrect and produces misleading results. Satellite altimetry could provide correct information about spatial extents and shape of the Ob–Yenisei plume only if it is validated by synchronous in situ measurements.

2021 ◽  
Vol 13 (4) ◽  
pp. 728 ◽  
Author(s):  
Severine Fournier ◽  
Tong Lee

Large rivers are key components of the land-ocean branch of the global water and biogeochemical cycles. River discharges can have important influences on physical, biological, optical, and chemical processes in coastal oceans. It is, therefore, of importance to routinely monitor the time-varying dispersal patterns of river plumes. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and the NASA Soil Moisture Active Passive (SMAP) satellites provide Sea Surface Salinity (SSS) observations capable of characterizing the spatial and temporal variability of major river plumes. The main objective of this study is to examine the consistency of SSS products, from these two missions, and two in-situ gridded salinity products in depicting SSS variations on seasonal to interannual time scales within a few hundred kilometers of major river mouths. We show that SSS from SMOS and SMAP satellites have good consistency in depicting seasonal and interannual SSS variations near major river mouths. The two gridded in-situ products underestimate these variations substantially. This underestimation, most notably associated with the low SSS season following the high-discharge season, is attributable to the limited in-situ sampling of the river plumes when they are the most active. This work underscores the importance of using satellite SSS to study river plumes, as well as to evaluate and constrain models.


2021 ◽  
Vol 13 (1) ◽  
pp. 313-342
Author(s):  
Eric C.J. Oliver ◽  
Jessica A. Benthuysen ◽  
Sofia Darmaraki ◽  
Markus G. Donat ◽  
Alistair J. Hobday ◽  
...  

Ocean temperature variability is a fundamental component of the Earth's climate system, and extremes in this variability affect the health of marine ecosystems around the world. The study of marine heatwaves has emerged as a rapidly growing field of research, given notable extreme warm-water events that have occurred against a background trend of global ocean warming. This review summarizes the latest physical and statistical understanding of marine heatwaves based on how they are identified, defined, characterized, and monitored through remotely sensed and in situ data sets. We describe the physical mechanisms that cause marine heatwaves, along with their global distribution, variability, and trends. Finally, we discuss current issues in this developing research area, including considerations related to thechoice of climatological baseline periods in defining extremes and how to communicate findings in the context of societal needs.


2020 ◽  
Author(s):  
Encarni Medina-Lopez

<p>The aim of this work is to obtain high-resolution values of sea surface salinity (SSS) and temperature (SST) in the global ocean by using raw satellite data (i.e., without any band data pre-processing or atmospheric correction). Sentinel-2 Level 1-C Top of Atmosphere (TOA) reflectance data is used to obtain accurate SSS and SST information. A deep neural network is built to link the band information with in situ data from different buoys, vessels, drifters, and other platforms around the world. The neural network used in this paper includes shortcuts, providing an improved performance compared with the equivalent feed-forward architecture. The in situ information used as input for the network has been obtained from the Copernicus Marine In situ Service. Sentinel-2 platform-centred band data has been processed using Google Earth Engine in areas of 100 m x 100 m. Accurate salinity values are estimated for the first time independently of temperature. Salinity results rely only on direct satellite observations, although it presented a clear dependency on temperature ranges. Results show the neural network has good interpolation and extrapolation capabilities. Test results present correlation coefficients of 82% and 84% for salinity and temperature, respectively. The most common error for both SST and SSS is 0.4 C and 0.4 PSU. The sensitivity analysis shows that outliers are present in areas where the number of observations is very low. The network is finally applied over a complete Sentinel-2 tile, presenting sensible patterns for river-sea interaction, as well as seasonal variations. The methodology presented here is relevant for detailed coastal and oceanographic applications, reducing the time for data pre-processing, and it is applicable to a wide range of satellites, as the information is directly obtained from TOA data.</p>


2018 ◽  
Vol 10 (11) ◽  
pp. 1772 ◽  
Author(s):  
Estrella Olmedo ◽  
Carolina Gabarró ◽  
Verónica González-Gambau ◽  
Justino Martínez ◽  
Joaquim Ballabrera-Poy ◽  
...  

This paper aims to present and assess the quality of seven years (2011–2017) of 25 km nine-day Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) objectively analyzed maps in the Arctic and sub-Arctic oceans ( 50 ∘ N– 90 ∘ N). The SMOS SSS maps presented in this work are an improved version of the preliminary three-year dataset generated and freely distributed by the Barcelona Expert Center. In this new version, a time-dependent bias correction has been applied to mitigate the seasonal bias that affected the previous SSS maps. An extensive database of in situ data (Argo floats and thermosalinograph measurements) has been used for assessing the accuracy of this product. The standard deviation of the difference between the new SMOS SSS maps and Argo SSS ranges from 0.25 and 0.35. The major features of the inter-annual SSS variations observed by the thermosalinographs are also captured by the SMOS SSS maps. However, the validation in some regions of the Arctic Ocean has not been feasible because of the lack of in situ data. In those regions, qualitative comparisons with SSS provided by models and the remotely sensed SSS provided by Aquarius and SMAP have been performed. Despite the differences between SMOS and SMAP, both datasets show consistent SSS variations with respect to the model and the river discharge in situ data, but present a larger dynamic range than that of the model. This result suggests that, in those regions, the use of the remotely sensed SSS may help to improve the models.


Author(s):  
Felix N. Kogan

Operational polar-orbiting environmental satellites launched in the early 1960s were designed for daily weather monitoring around the world. In the early years, they were mostly applied for cloud monitoring and for advancing skills in satellite data applications. The new era was opened with the series of TIROS-N launched in 1978, which has continued until present. These satellites have such instruments as the advanced very high resolution radiometer (AVHRR) and the TIROS operational vertical sounder (TOVS), which included a microwave sounding unit (MSU), a stratospheric sounding unit (SSU), and high-resolution infrared radiation sounder/2 (HIRS/2). These instruments helped weather forecasters improve their skills. AVHRR instruments were also useful for observing and monitoring earth surface. Specific advances were achieved in understanding vegetation distribution. Since the late 1980s, experience gained in interpreting vegetation conditions from satellite images has helped develop new applications for detecting phenomenon such as drought and its impacts on agriculture. The objective of this chapter is to introduce AVHRR indices that have been useful for detecting most unusual droughts in the world during 1990–2000, a decade identified by the United Nations as the International Decade for Natural Disasters Reduction. Radiances measured by the AVHRR instrument onboard National Oceanic Atmospheric Administration (NOAA) polar-orbiting satellites can be used to monitor drought conditions because of their sensitivity to changes in leaf chlorophyll, moisture content, and thermal conditions (Gates, 1970; Myers, 1970). Over the last 20 years, these radiances were converted into indices that were used as proxies for estimating various vegetation conditions (Kogan, 1997, 2001, 2002). The indices became indispensable sources of information in the absence of in situ data, whose measurements and delivery are affected by telecommunication problems, difficult access to environmentally marginal areas, economic disturbances, and political or military conflicts. In addition, indices have advantage over in situ data in terms of better spatial and temporal coverage and faster data availability. The AVHRR-based indices used for monitoring vegetation can be divided into two groups: two-channel indices, and three-channel indices.


2005 ◽  
Vol 35 (11) ◽  
pp. 2054-2075 ◽  
Author(s):  
Trevor J. McDougall ◽  
David R. Jackett

Abstract Orthobaric density has recently been advanced as a new density variable for displaying ocean data and as a coordinate for ocean modeling. Here the extent to which orthobaric density surfaces are neutral is quantified and it is found that orthobaric density surfaces are less neutral in the World Ocean than are potential density surfaces referenced to 2000 dbar. Another property that is important for a vertical coordinate of a layered model is the quasi-material nature of the coordinate and it is shown that orthobaric density surfaces are significantly non-quasi-material. These limitations of orthobaric density arise because of its inability to accurately accommodate differences between water masses at fixed values of pressure and in situ density such as occur between the Northern and Southern Hemisphere portions of the World Ocean. It is shown that special forms of orthobaric density can be quite accurate if they are formed for an individual ocean basin and used only in that basin. While orthobaric density can be made to be approximately neutral in a single ocean basin, this is not possible in both the Northern and Southern Hemisphere portions of the Atlantic Ocean. While the helical nature of neutral trajectories (equivalently, the ill-defined nature of neutral surfaces) limits the neutrality of all types of density surface, the inability of orthobaric density surfaces to accurately accommodate more than one ocean basin is a much greater limitation.


2021 ◽  
Vol 6 (24) ◽  
pp. 139-151
Author(s):  
Mohammad Hanif Hamden ◽  
Ami Hassan Md Din ◽  
Dudy Darmawan Wijaya

Satellite altimetry technology has been widely used in exploring Earth’s Ocean activities. Achieving a remarkable accuracy in measuring sea level for ocean tide analysis has led the local researchers to investigate more details on tidal behaviour in the regional area. This study is an attempt to assess the reliability of derived tidal constituents between satellite radar altimetry and in-situ data which is referred to as coastal tide gauges. Three satellite missions denoted as TOPEX class missions namely TOPEX, Jason-1, and Jason-2 were used to derive along-track sea surface height (SSH) time series over 23 years. Besides, four selected coastal tide gauges were used for tidal analysis and validation where the tidal data have at least 19 years of hourly observation. Derivation of tidal constituents from both satellite altimetry and tide gauges were executed by adopting the harmonic analysis method. The comparisons were made by calculating the Root Mean Square Misfit (RMSmisfit) of each tidal constituent between the nearest altimetry point to the tide gauges. After RMSmisfit, Root Sum Square (RSS) values of tidal constituents at each tide gauge were also calculated. The results displayed the RMSmisfit of tidal constituents agreed well with the selected tide gauges which are within 10 cm except for M2 constituents which recorded 10.2 cm. Pelabuhan Kelang tide gauge station showed the highest RSS value followed by Pulau Langkawi which recorded 21.2 cm and 9.8 cm, respectively. In conclusion, overall results can be inferred that the satellite-derived tidal constituents are likely to have good agreement with the selected tide gauge stations. Nevertheless, further analysis should be executed in determining high precision satellite-derived tidal constituents, especially in the complex regional area.


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