Abstract. Rapid improvements in the precision and spatial resolution of distributed temperature sensing (DTS) technology now allow its use in hydrological and atmospheric sciences. Introduced by Euser et al. (2014) is the use of DTS for measuring the Bowen ratio (BR-DTS), to estimate the sensible and latent heat flux. The Bowen ratio is derived from DTS-measured vertical profiles of the air temperature and wet-bulb temperature. However, in previous research the measured temperatures were not validated, and the cables were not shielded from solar radiation. Additionally, the BR-DTS method has not been tested above a forest before, where temperature gradients are small and energy storage in the air column becomes important.In this paper the accuracy of the wet-bulb and air temperature measurements of the DTS are verified, and the resulting Bowen ratio and heat fluxes are compared to eddy covariance data. The performance of BR-DTS was tested on a 46 m high tower in a mixed forest in the centre of the Netherlands in August 2016. The average tree height is 26 to 30 m, and the temperatures are measured below, in, and above the canopy. Using the vertical temperature profiles the storage of latent and sensible heat in the air column was calculated.We found a significant effect of solar radiation on the temperature measurements, leading to a deviation of up to 3 K. By installing screens, the error caused by sunlight is reduced to under 1 K. Wind speed seems to have a minimal effect on the measured wet-bulb temperature, both below and above the canopy. After a simple quality control, the Bowen ratio measured by DTS correlates well with eddy covariance (EC) estimates (r 2 = 0.59). The average energy balance closure between BR-DTS and EC is good, with a mean underestimation of 3.4 W m −2 by the BR-DTS method. However, during daytime the BR-DTS method overestimates the available energy, and during night-time the BR-DTS method estimates the available energy to be more negative. This difference could be related to the biomass heat storage, which is neglected in this study.The BR-DTS method overestimates the latent heat flux on average by 18.7 W m −2 , with RMSE = 90 W m −2 . The sensible heat flux is underestimated on average by 10.6 W m −2 , with RMSE = 76 W m −2 . Estimates of the BR-DTS can be improved once the uncertainties in the energy balance are reduced. However, applying, for example, Monin-Obukhov similarity theory could provide independent estimates for the sensible heat flux. This would make the determination of the highly uncertain and difficult to determine net available energy redundant.

Measurements of ice temperature provide crucial constraints on ice viscosity and the thermodynamic processes occurring within a glacier. However, such measurements are presently limited by a small number of relatively coarse-spatial-resolution borehole records, especially for ice sheets. Here, we advance our understanding of glacier thermodynamics with an exceptionally high-vertical-resolution (~0.65 m), distributed-fiber-optic temperature-sensing profile from a 1043-m borehole drilled to the base of Sermeq Kujalleq (Store Glacier), Greenland. We report substantial but isolated strain heating within interglacial-phase ice at 208 to 242 m depth together with strongly heterogeneous ice deformation in glacial-phase ice below 889 m. We also observe a high-strain interface between glacial- and interglacial-phase ice and a 73-m-thick temperate basal layer, interpreted as locally formed and important for the glacier’s fast motion. These findings demonstrate notable spatial heterogeneity, both vertically and at the catchment scale, in the conditions facilitating the fast motion of marine-terminating glaciers in Greenland.

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Distributed temperature sensing (DTS) systems can be used to estimate the temperature along optic fibers of several kilometers at a sub-meter interval. DTS systems function by shooting laser pulses through a fiber and measuring its backscatter intensity at two distinct wavelengths in the Raman spectrum. The scattering-loss coefficients for these wavelengths are temperature-dependent, so that the temperature along the fiber can be estimated using calibration to fiber sections with a known temperature. A new calibration approach is developed that allows for an estimate of the uncertainty of the estimated temperature, which varies along the fiber and with time. The uncertainty is a result of the noise from the detectors and the uncertainty in the calibrated parameters that relate the backscatter intensity to temperature. Estimation of the confidence interval of the temperature requires an estimate of the distribution of the noise from the detectors and an estimate of the multi-variate distribution of the parameters. Both distributions are propagated with Monte Carlo sampling to approximate the probability density function of the estimated temperature, which is different at each point along the fiber and varies over time. Various summarizing statistics are computed from the approximate probability density function, such as the confidence intervals and the standard uncertainty (the estimated standard deviation) of the estimated temperature. An example is presented to demonstrate the approach and to assess the reasonableness of the estimated confidence intervals. The approach is implemented in the open-source Python package "dtscalibration".Sensors 2020, 20, 2235 2 of 21 scattering), but a small fraction has different wavelengths (Raman scattering). The detectors in DTS systems measure the intensity of the backscatter at two distinct wavelengths: Stokes (-Raman) and anti-Stokes (-Raman) scatter. The temperature at the point of reflection is estimated from these two types of scatter. Stokes scatter has a longer wavelength than the laser and its intensity does not vary much with temperature, while anti-Stokes scatter has a shorter wavelength than the laser and its intensity varies significantly with temperature. The location of the measurement along the fiber is estimated from the time between sending the laser pulse and receiving the scatter. Temperature along the fiber is estimated from the measured intensities of the Stokes and anti-Stokes scatter by calibrating to reference sections with a known temperature. In practice, these fiber sections are submerged in water baths of which the temperature is continuously measured with a separate temperature sensor. The water can be mixed with small pumps in an attempt to equalize the temperature of the water in the baths. Sequential temperature measurements require continuous calibration due to varying gains and losses in the DTS system. Detailed calibration procedures are available in the literature [11][12][13][14]. The uncertainty in the temperature estimates is strongly aff...

Abstract. Near-surface wind speed is typically only measured by point observations. The actively heated fiber-optic (AHFO) technique, however, has the potential to provide high-resolution distributed observations of wind speeds, allowing for better spatial characterization of fine-scale processes. Before AHFO can be widely used, its performance needs to be tested in a range of settings. In this work, experimental results on this novel observational wind-probing technique are presented. We utilized a controlled wind tunnel setup to assess both the accuracy and the precision of AHFO under a range of operational conditions (wind speed, angles of attack and temperature difference). The technique allows for wind speed characterization with a spatial resolution of 0.3 m on a 1 s timescale. The flow in the wind tunnel was varied in a controlled manner such that the mean wind ranged between 1 and 17 m s−1. The AHFO measurements are compared to sonic anemometer measurements and show a high coefficient of determination (0.92–0.96) for all individual angles, after correcting the AHFO measurements for the angle of attack. Both the precision and accuracy of the AHFO measurements were also greater than 95 % for all conditions. We conclude that AHFO has the potential to measure wind speed, and we present a method to help choose the heating settings of AHFO. AHFO allows for the characterization of spatially varying fields of mean wind. In the future, the technique could potentially be combined with conventional distributed temperature sensing (DTS) for sensible heat flux estimation in micrometeorological and hydrological applications.