scholarly journals Remote sensing of the Dead Sea surface temperature

2009 ◽  
Vol 114 (C5) ◽  
Author(s):  
R. Nehorai ◽  
I. M. Lensky ◽  
N. G. Lensky ◽  
S. Shiff
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Dead Sea ◽  
Sea Surface ◽  
The Dead

Spatial heterogeneity in Dead Sea surface temperature caused by evaporation

2021 ◽  
Author(s):  
Pavel Kishcha ◽  
Boris Starobinets ◽  
Pinhas Alpert
Keyword(s):  
Remote Sensing ◽  
Surface Temperature ◽  
Spatial Heterogeneity ◽  
Sea Surface Temperature ◽  
Land Surface ◽  
Dead Sea ◽  
Sea Surface ◽  
Water Mixing ◽  
Drying Up ◽  
The Dead

<p>The Dead Sea is a terminal hypersaline lake at a unique location at ~430 m below sea level. Over the last several decades the Dead Sea has been drying up due to climate change: its water level has dropped at the rate of ~1 m year<sup>-1</sup>. In this study we investigated the diurnal cycle of spatial heterogeneity in Dead Sea surface temperature (SST) using METEOSAT geostationary satellite data (2005-2015). METEOSAT data showed that, in the summer months, SST peaked at the same time, 13 LT (local time), as land surface temperature (LST) over surrounding land areas. In the presence of water mixing, the maximum of SST should be observed several hours later than that of LST due to thermal inertia of bulk water. The fact that SST and LST peaked at the same time, 13 LT, is evidence that there was no noticeable vertical water mixing. We consider that, in the absence of noticeable water mixing and under uniform solar radiation in the summer months, inhomogeneity in evaporation was the main causal factor of the observed spatial heterogeneity in Dead Sea SST. METEOSAT showed that spatial heterogeneity in SST was pronounced throughout the daytime. In summer, SST peaked at 13 LT, when SST reached 38.1 <sup>o</sup>C, 34.1 <sup>o</sup>C, and 35.4 <sup>o</sup>C being averaged over the east, middle and west parts of the lake, respectively. The above mentioned spatial heterogeneity in daytime SST caused a pronounced asymmetry in land surface temperature between land areas adjacent to the east and west sides of the lake. Maximal evaporation (causing maximal surface water cooling) took place at the middle part of the Dead Sea, while minimum evaporation took place at the east side of the lake. In the nighttime, METEOSAT data showed that SST values were minimal and SST spatial distribution was much more uniform compared to the daytime. We found that, in winter, when maximal solar radiation reached ~500 W/m<sup>2</sup> compared to ~900 W/m<sup>2</sup> in summer, daytime SST non-uniformity was less pronounced than that in summer. As the characteristic feature of the diurnal cycle, SST daily temperature range was equal to 7.2 °C, 2.5 °C, and 3.8 °C over the east, middle and west parts of the Dead Sea, respectively, in summer, compared to 5.3 °C, 1.2 °C, and 2.3 °C in winter.</p><p>Evaporation causes significant drying up of the Dead Sea, especially in the summer months, as the main contributor to maximal water level drop in the lake. However, no measurements of spatial distribution of Dead Sea evaporation have ever been conducted, either in situ or from space. Our findings allowed us to visualize spatial inhomogeneity in evaporation using the obtained heterogeneity in Dead Sea SST.</p><p><strong>Reference:</strong>   Kishcha P. and Starobinets B. (2021). Spatial heterogeneity in Dead Sea surface temperature associated with inhomogeneity in evaporation. <em>Remote Sensing</em>  (Special Issue: Remote Sensing of Lake Properties and Dynamics), 13(1), 93; https://doi.org/10.3390/rs13010093.</p>

scholarly journals Observations of positive sea surface temperature trends in the steadily shrinking Dead Sea

2018 ◽  
Vol 18 (11) ◽  
pp. 3007-3018 ◽  
Author(s):  
Pavel Kishcha ◽  
Rachel T. Pinker ◽  
Isaac Gertman ◽  
Boris Starobinets ◽  
Pinhas Alpert
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Feedback Loop ◽  
Sea Water ◽  
Dead Sea ◽  
Sea Surface ◽  
Positive Feedback Loop ◽  
Temperature Trends ◽  
The Dead

Abstract. Increasing warming of steadily shrinking Dead Sea surface water compensates for surface water cooling (due to increasing evaporation) and even causes observed positive Dead Sea sea surface temperature trends. This warming is caused by two factors: increasing daytime heat flow from land to sea (as a result of the steady shrinking) and regional atmospheric warming. Using observations from the Moderate Resolution Imaging Spectroradiometer (MODIS), positive trends were detected in both daytime and nighttime Dead Sea sea surface temperature (SST) over the period of 2000–2016. These positive SST trends were observed in the absence of positive trends in surface solar radiation, measured by the Dead Sea buoy pyranometer. We also show that long-term changes in water mixing in the uppermost layer of the Dead Sea under strong winds could not explain the observed SST trends. There is a positive feedback loop between the positive SST trends and the steady shrinking of the Dead Sea, which contributes to the accelerating decrease in Dead Sea water levels during the period under study. Satellite-based SST measurements showed that maximal SST trends of over 0.8 ∘C decade−1 were observed over the northwestern and southern sides of the Dead Sea, where shrinking of the Dead Sea water area was pronounced. No noticeable SST trends were observed over the eastern side of the lake, where shrinking of the Dead Sea water area was insignificant. This finding demonstrates correspondence between the positive SST trends and the shrinking of the Dead Sea indicating a causal link between them. There are two opposite processes taking place in the Dead Sea: sea surface warming and cooling. On the one hand, the positive feedback loop leading to sea surface warming every year accompanied by long-term increase in SST; on the other hand, the measured acceleration of the Dead Sea water-level drop suggests a long-term increase in Dead Sea evaporation accompanied by a long-term decrease in SST. During the period under investigation, the total result of these two opposite processes is the statistically significant positive sea surface temperature trends in both daytime (0.6 ∘C decade−1) and nighttime (0.4 ∘C decade−1), observed by the MODIS instrument. Our findings of the existence of a positive feedback loop between the positive SST trends and the shrinking of the Dead Sea imply the following significant point: any meteorological, hydrological or geophysical process causing the steady shrinking of the Dead Sea will contribute to positive trends in SST. Our results shed light on continuing hazards to the Dead Sea.

scholarly journals Observations of positive sea surface temperature trends in the steadily shrinking Dead Sea

2018 ◽  
Author(s):  
Pavel Kishcha ◽  
Rachel T. Pinker ◽  
Isaac Gertman ◽  
Boris Starobinets ◽  
Pinhas Alpert
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Water ◽  
Dead Sea ◽  
Water Levels ◽  
Sea Surface ◽  
Surface Warming ◽  
Temperature Trends ◽  
The Dead

Abstract. The steadily shrinking Dead Sea followed by sea surface warming compensates surface water cooling due to increasing evaporation, and even causes the observed positive Dead Sea surface temperature trends. Using observations from Moderate Resolution Imaging Spectroradiometer (MODIS), positive trends were detected in both daytime (0.06 °C year−1) and nighttime (0.04 °C year−1) Dead Sea surface temperature (SST) over the period of 2000–2016. These positive SST trends were observed in the absence of positive trends in surface solar radiation measured by the Dead Sea buoy pyranometer. Neither changes in water mixing in the Dead Sea nor changes in evaporation could explain surface temperature trends. There is a positive feedback loop between the shrinking of the Dead Sea and positive SST trends, which leads to the accelerating decrease in Dead Sea water levels during the period under study. Note that there are two opposite processes based on available measurements: on the one hand, the measured accelerating rate of Dead Sea water levels suggests a long-term increase in Dead Sea evaporation which is expected to be accompanied by a long-term decrease in sea surface temperature. On the other hand, the positive feedback loop leads to the observed shrinking of the Dead Sea area followed by sea surface warming year on year. The total result of these two opposite processes is the statistically significant positive sea surface temperature trends in both daytime (0.06 °C year−1) and nighttime (0.04 °C year−1) during the period under investigation, observed by the MODIS instrument. Our results shed light on the continuing hazard to the Dead Sea and possible disappearance of this unique site.

scholarly journals Spatial Heterogeneity in Dead Sea Surface Temperature Associated with Inhomogeneity in Evaporation

2020 ◽  
Vol 13 (1) ◽  
pp. 93
Author(s):  
Pavel Kishcha ◽  
Boris Starobinets
Keyword(s):  
Surface Temperature ◽  
Spatial Heterogeneity ◽  
Sea Surface Temperature ◽  
Land Surface ◽  
Dead Sea ◽  
Bulk Water ◽  
Sea Surface ◽  
Maximal Surface ◽  
Water Mixing ◽  
The Dead

Spatial heterogeneity in Dead Sea surface temperature (SST) was pronounced throughout the daytime, based on METEOSAT geostationary satellite data (2005–2015). In summer, SST peaked at 13 LT (local time), when SST reached 38.1 °C, 34.1 °C, and 35.4 °C being averaged over the east, middle, and west parts of the lake, respectively. In winter, daytime SST heterogeneity was less pronounced than that in summer. As the characteristic feature of the diurnal cycle, the SST daily temperature range (the difference between daily maxima and minima) was equal to 7.2 °C, 2.5 °C, and 3.8 °C over the east, middle, and west parts of the Dead Sea, respectively, in summer, compared to 5.3 °C, 1.2 °C, and 2.3 °C in winter. In the presence of vertical water mixing, the maximum of SST should be observed several hours later than that of land surface temperature (LST) over surrounding land areas due to thermal inertia of bulk water. However, METEOSAT showed that, in summer, maxima of SST and LST were observed at the same time, 13 LT. This fact is evidence that there was no noticeable vertical water mixing. Our findings allowed us to consider that, in the absence of water mixing and under uniform solar radiation in the summer months, spatial heterogeneity in SST was associated with inhomogeneity in evaporation. Maximal evaporation (causing maximal surface water cooling) took place at the middle part of the Dead Sea, while minimum evaporation took place at the east side of the lake.

Asymmetry in surface temperature between the east and west sides of the Dead Sea under uniform solar radiation

2020 ◽  
Author(s):  
Pavel Kishcha ◽  
Boris Starobinets ◽  
Rachel Pinker ◽  
Pavel Kunin ◽  
Pinhas Alpert
Keyword(s):  
Remote Sensing ◽  
Surface Water ◽  
Heat Flow ◽  
Solar Radiation ◽  
Surface Temperature ◽  
Dead Sea ◽  
Surface Heat ◽  
Sea Surface ◽  
The West ◽  
The Dead

<p>The Dead Sea is a terminal hypersaline lake with a depth of ~300 m, at a unique location approximately 430 m below sea level. Because of very high salinity of ~300 g/kg of Dead Sea water, the non-linear absorption of solar radiation is of an order of magnitude greater than that in fresh-water lakes. Consequently, by contrast to surface water temperature in fresh-water lakes, Dead Sea surface temperature is influenced by wind speed and water mixing. In the absence of vertical water mixing under weak winds, solar radiation in the summer months leads to significant warming of Dead Sea surface water. Under such conditions, daytime sea surface temperature (SST) could reach land surface temperature (LST) over land areas adjacent to the lake. This could lead to an essential reduction of surface heat flow from land to sea and, consequently, significant surface heating of land areas adjacent to the lake.</p><p>Pronounced asymmetry has been obtained in daytime surface temperature between the east and west sides of the Dead Sea. This asymmetry was observed in the summer months, under uniform solar radiation. Our findings are based on MODIS data (2002–2016) on board the Terra and Aqua satellites. MODIS data showed that, on average for the 15-year study period, daytime SST over the eastern part of the lake exceeded that over the western part by 5 °C. This SST asymmetry (observed in the absence of surface heat flow from land to sea at the eastern side) was accompanied by the asymmetry in LST over areas adjacent to the Dead Sea. Specifically, LST over areas adjacent to the east side exceeded that over areas adjacent to the west side by 10 °C. Such LST difference is the characteristic feature of the hypersaline Dead Sea. In addition to MODIS records (on board the two orbital satellites - Terra and Aqua), Meteosat Second Generation records (on board the geostationary satellites) proved the presence of daytime SST/LST asymmetry.</p><p>Regional atmospheric warming led to a decrease in the SST asymmetry during the study period. Temperature difference between daytime SST over the east part and that over the west of the Dead Sea steadily decreased at the rate of 0.32 °C decade<sup>-1</sup>, based on MODIS/Terra data, and 0.54 °C decade<sup>-1</sup>, based on MODIS/Aqua data.</p><p>We found that the Weather Forecast and Research (WRF) model distribution of skin temperature over land and sea does not correspond to satellite observations. At midday, over the sea, WRF was incapable of reproducing the observed SST asymmetry. Over land areas adjacent to both the west and east sides of the lake, WRF incorrectly showed that modeled skin temperature increases with its approach to the coastline. The application to modeling of the observed SST/LST asymmetry in existing regional models will improve simulations of atmospheric dynamics over the Dead Sea.</p><p> </p><p><strong>Reference:</strong>  Kishcha P., Starobinets B., Pinker R., Kunin P., Alpert P. (2020). Spatial non-uniformity of surface temperature of the Dead Sea and adjacent land areas. <em>Remote Sensing,</em> Special Issue: Lake Remote Sensing, 12(1), 107; doi:10.3390/rs12010107.</p>

Deep Learning for Sea Temperature Eddy signature Classification

2021 ◽  
Author(s):  
Evangelos Moschos ◽  
Alexandre Stegner ◽  
Olivier Schwander ◽  
Patrick Gallinari
Keyword(s):  
Remote Sensing ◽  
Deep Learning ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Mediterranean Sea ◽  
Satellite Imagery ◽  
Mesoscale Eddies ◽  
Sea Surface ◽  
Sea Temperature ◽  
Cloud Coverage

<p>Mesoscale eddies are oceanic vortices with radii of tens of kilometers, which live on for several months or even years. They carry large amounts of heat, salt, nutrients, and pollutants from their regions of formation to remote areas, making it important to detect and track them. Using satellite altimetric maps, mesoscale eddies have been detected via remote sensing with advancing performance over the last years <strong>[1]</strong>. However, the spatio-temporal interpolation between satellite track measurements, needed to produce these maps, induces a limit to the spatial resolution (1/12° in the Med Sea) and large amounts of uncertainty in non-measured areas.</p><p>Nevertheless, mesoscale oceanic eddies also have a visible signature on other satellite imagery such as Sea Surface Temperature (SST), portraying diverse patterns of coherent vortices, temperature gradients, and swirling filaments. Learning the regularities of such signatures defines a challenging pattern recognition task, due to their complex structure but also to the cloud coverage which can corrupt a large fraction of the image.</p><p>We introduce a novel Deep Learning approach to classify sea temperature eddy signatures <strong>[2]</strong>. We create a large dataset of SST patches from satellite imagery in the Mediterranean Sea, containing Anticyclonic, Cyclonic, or No Eddy signatures, based on altimetric eddy detections of the DYNED-Atlas <strong>[3]</strong>. Our trained Convolutional Neural Network (CNN) can differentiate between these signatures with an accuracy of more than 90%, robust to a high level of cloud coverage.</p><p>We furtherly evaluate the efficiency of our classifier on SST patches extracted from oceanographic numerical model outputs in the Mediterranean Sea. Our promising results suggest that the CNN could complement the detection, tracking, and prediction of the path of mesoscale oceanic eddies.</p><p><strong>[1]</strong> <em>Chelton, D. B., Schlax, M. G. and Samelson, R. M. (2011). Global observations of nonlinear mesoscale eddies. Progress in oceanography, 91(2),167-216.</em></p><p><strong>[2]</strong> <em>E. Moschos, A. Stegner, O. Schwander and P. Gallinari, "Classification of Eddy Sea Surface Temperature Signatures Under Cloud Coverage," in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 13, pp. 3437-3447, 2020, doi: 10.1109/JSTARS.2020.3001830.</em></p><p><strong>[3]</strong> <em>https://www.lmd.polytechnique.fr/dyned/</em></p>

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