High-resolution temperature sensing in the Dead Sea using fiber optics

Abstract

The thermal stratification of the Dead Sea was observed in high spatial and temporal resolution by means of fiber-optics temperature sensing. The aim of the research was to employ the novel highresolution profiler in studying the dynamics of the thermal structure of the Dead Sea and the related processes including the investigation of the metalimnion fluctuations. The 18 cm resolution profiling system was placed vertically through the water column supported by a buoy 450 m from shore, from 2 m above to 53 m below the water surface (just above the local seafloor), covering the entire seasonal upper layer (the metalimnion had an average depth of $20 m). Temperature profiles were recorded every 5 min. The May to July 2012 data set allowed quantitative investigation of the thermal morphology dynamics, including objective definitions of key locations within the metalimnion based on the temperature depth profile and its first and second depth derivatives. Analysis of the fluctuation of the defined metalimnion locations showed strong anticorrelation to measured sea level fluctuations. The slope of the sea level versus metalimnion depth was found to be related to the density ratio of the upper layer and the underlying main water body, according to the prediction of a two-layer model. The heat content of the entire water column was calculated by integrating the temperature profiles. The vertically integrated apparent heat content was seen to vary by 50% in a few hours. These fluctuations were not correlated to the atmospheric heat fluxes, nor to the momentum transfer, but were highly correlated to the metalimnion and the sea level fluctuations (r 5 0.84). The instantaneous apparent heat flux was 3 orders of magnitude larger than that delivered by radiation, with no direct correlation to the frequency of radiation and wind in the lake. This suggests that the source of the momentary heat flux is lateral advection due to internal waves (with no direct relation to the diurnal cycle). In practice, it is shown that snap-shot profiles of the Dead Sea as obtained with standard thermal profilers will not represent the seasonal typical status in terms of heat content of the upper layer.

Seasonal dynamics of internal waves governed by stratification stability and wind: Analysis of high‐resolution observations from the Dead Sea

“…The profiles were calibrated to be accurate to ±0.02 ° C, for 5 min integration time, thus maintaining high enough frequency to observe structural changes in the water profile. The observational setup and calibration procedure were described in detail by Arnon et al (). The system recorded profiles during the stratification period, from May 2012 to January 2013.…”

“…Thermocline depth fluctuations of up to 15 m within a few hours were documented based on measurements having 5 min temporal and 9 cm depth resolution. High correlations between metalimnion depth fluctuations and the sea‐level fluctuations were found (Arnon et al ). But, the dynamics of internal waves in the Dead Sea was not documented during the course of the seasonal stratification cycle, specifically as a response to the seasonally varying stratification stability and wind regime.…”

“…D). Thus, the oscillations of pycnocline depth ( D ) can be determined by measuring high spatial resolution temperature profiles at high temporal frequency (e.g., Arnon et al ). The equation of state for the Dead Sea is …”

“…A recent study of the fine thermal stratification structure in the Dead Sea (Arnon et al ) enabled analysis of the metalimnion, using fiber optics for high‐resolution temperature sensing (Selker et al ; Tyler et al ). Thermocline depth fluctuations of up to 15 m within a few hours were documented based on measurements having 5 min temporal and 9 cm depth resolution.…”

An axisymmetric non-hydrostatic model for double-diffusive water systems

“…Recently, the modelling of these phenomena in smallerscale water bodies has started to be developed. For example, double-diffusive processes like thermohaline staircasing have been successfully modelled in lakes (Schmid et al, 2003), although these systems are generally modelled with analytical or empirical formulations (Kelley et al, 2003;Schmid et al, 2004;Arnon et al, 2014). Other known numerical modelling studies consider double-diffusive convection in monitoring wells (Berthold and Börner, 2008) and the collection of thermal energy in solar ponds (Cathcart and Wheaton, 1987;Giestas et al, 2009;Suárez et al, 2010Suárez et al, , 2014.…”