Production of the high resolution maps of biophysical variables based on SPOT imagery and in-situ measurements generated by PASTIS 57 for Hyytiala, Finland

Abstract. The mass balance of many valley glaciers is enhanced by the presence of ice cliffs within otherwise continuous debris cover. We assess the effect of debris and ice cliffs on the thinning of Kennicott Glacier in three companion papers. In Part A we report in situ measurements from the debris-covered tongue. Here, in Part B, we develop a method to delineate ice cliffs using high-resolution imagery and use empirical relationships from Part A to produce distributed mass balance estimates. In Part C we describe feedbacks that contribute to rapid thinning under thick debris. Ice cliffs cover 11.7 % of the debris-covered tongue, the most of any glacier studied to date, and they contribute 19 % of total melt. Ice cliffs contribute an increasing percentage of melt the thicker the debris cover. In the lowest 4 km of the glacier, where debris thicknesses are greater than 20 cm, ice cliffs contribute 40 % of total melt. Surface lake coverage doubled between 1957 and 2009, but lakes do not occur across the full extent of the zone of maximum glacier thinning. Despite abundant ice cliffs and expanding surface lakes, average melt rates are suppressed by debris, the pattern of which appears to reflect the debris thickness-melt relationship (or Østrem’s curve). This suggests that, in addition to melt hotspots, the decline in ice discharge from upglacier is an important contributor to the thinning of Kennicott glacier under thick debris.

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Enhancing WRF Model Forecasts by Assimilating High-Resolution GPS-Derived Water-Vapor Maps combined with METEOSAT-11 Data

10.5194/egusphere-egu21-4503 ◽

2021 ◽

Author(s):

Yuval Reuveni ◽

Anton Leontiev ◽

Dorita Rostkier-Edelstein

Keyword(s):

Water Vapor ◽

High Resolution ◽

Numerical Models ◽

Eastern Mediterranean ◽

Wrf Model ◽

In Situ Measurements ◽

Suggested Approach ◽

Positioning Systems ◽

The Mediterranean

<p>Improving the accuracy of numerical weather predictions still poses a challenging task. The lack of sufficiently detailed spatio-temporal real-time in-situ measurements constitutes a crucial gap concerning the adequate representation of atmospheric moisture fields, such as water vapor, which are critical for improving weather predictions accuracy. Information on total vertically integrated water vapor (IWV), extracted from global positioning systems (GPS) tropospheric path delays, can enhance various atmospheric models at global, regional, and local scales. Currently, numerous existing atmospheric numerical models predict IWV. Nevertheless, they do not provide accurate estimations compared with in-situ measurements such as radiosondes. In this work, we demonstrate a novel approach for assimilating 2D IWV regional maps estimations, extracted from GPS tropospheric path delays combined with METEOSAT satellite imagery data, to enhance Weather Research and Forecast (WRF) model predictions accuracy above the Eastern Mediterranean area. Unlike previous studies, which assimilated IWV point measurements, here, we assimilate quasi-continuous 2D GPS IWV maps, augmented by METEOSAT-11 data, over Israel and its surroundings. Using the suggested approach, our results show a decrease of more than 30% in the root mean square error (RMSE) of WRF forecasts after assimilation relative to the standalone WRF when verified against in-situ radiosonde measurements near the Mediterranean coast. Furthermore, substantial improvements along the Jordan Rift Valley and Dead Sea Valley areas are achieved when compared to 2D IWV regional maps. Improvements in these areas suggest the importance of the assimilated high resolution IWV maps, in particular when assimilation and initialization times coincide with the Mediterranean Sea Breeze propagation from the coastline to highland stations.</p>

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A Linear Array of Wind and Pressure Sensors for High Resolution in situ Measurements in Winter Tornadoes

IEEJ Transactions on Fundamentals and Materials ◽

10.1541/ieejfms.136.286 ◽

2016 ◽

Vol 136 (5) ◽

pp. 286-290

Author(s):

Kenichi Kusunoki ◽

Ken-ichiro Arai ◽

Ryohei Kato ◽

Eiichi Sato ◽

Chusei Fujiwara

Keyword(s):

High Resolution ◽

Linear Array ◽

Pressure Sensors ◽

In Situ Measurements

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Towards Estimating Land Evaporation at Field Scales Using GLEAM

Remote Sensing ◽

10.3390/rs10111720 ◽

2018 ◽

Vol 10 (11) ◽

pp. 1720 ◽

Cited By ~ 3

Author(s):

Brecht Martens ◽

Richard de Jeu ◽

Niko Verhoest ◽

Hanneke Schuurmans ◽

Jonne Kleijer ◽

...

Keyword(s):

Water Management ◽

Soil Moisture ◽

High Resolution ◽

The Netherlands ◽

Weather Conditions ◽

Irrigation Scheduling ◽

In Situ Measurements ◽

Rainfall Interception ◽

Interception Loss

The evaporation of water from land into the atmosphere is a key component of the hydrological cycle. Accurate estimates of this flux are essential for proper water management and irrigation scheduling. However, continuous and qualitative information on land evaporation is currently not available at the required spatio-temporal scales for agricultural applications and regional-scale water management. Here, we apply the Global Land Evaporation Amsterdam Model (GLEAM) at 100 m spatial resolution and daily time steps to provide estimates of land evaporation over The Netherlands, Flanders, and western Germany for the period 2013–2017. By making extensive use of microwave-based geophysical observations, we are able to provide data under all weather conditions. The soil moisture estimates from GLEAM at high resolution compare well with in situ measurements of surface soil moisture, resulting in a median temporal correlation coefficient of 0.76 across 29 sites. Estimates of terrestrial evaporation are also evaluated using in situ eddy-covariance measurements from five sites, and compared to estimates from the coarse-scale GLEAM v3.2b, land evaporation from the Satellite Application Facility on Land Surface Analysis (LSA-SAF), and reference grass evaporation based on Makkink’s equation. All datasets compare similarly with in situ measurements and differences in the temporal statistics are small, with correlation coefficients against in situ data ranging from 0.65 to 0.95, depending on the site. Evaporation estimates from GLEAM-HR are typically bounded by the high values of the Makkink evaporation and the low values from LSA-SAF. While GLEAM-HR and LSA-SAF show the highest spatial detail, their geographical patterns diverge strongly due to differences in model assumptions, model parameterizations, and forcing data. The separate consideration of rainfall interception loss by tall vegetation in GLEAM-HR is a key cause of this divergence: while LSA-SAF reports maximum annual evaporation volumes in the Green Heart of The Netherlands, an area dominated by shrubs and grasses, GLEAM-HR shows its maximum in the national parks of the Veluwe and Heuvelrug, both densely-forested regions where rainfall interception loss is a dominant process. The pioneering dataset presented here is unique in that it provides observational-based estimates at high resolution under all weather conditions, and represents a viable alternative to traditional visible and infrared models to retrieve evaporation at field scales.

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In-situ measurements of low energy D plasma-driven permeation through He pre-damaged W

Nuclear Fusion ◽

10.1088/1741-4326/ac4716 ◽

2021 ◽

Author(s):

Xuechun Li ◽

Hai-Shan Zhou ◽

Hao-Dong Liu ◽

Lu Wang ◽

Guang-Nan Luo

Keyword(s):

High Resolution ◽

Thermal Desorption ◽

Thermal Desorption Spectroscopy ◽

In Situ Measurements ◽

Low Energy ◽

Plasma Exposure ◽

Defective Structure ◽

Microstructure Observation ◽

Linear Plasma

Abstract Experiments concerning the effect of helium (He) plasma exposure on deuterium (D) plasma-driven permeation (PDP) through tungsten (W) foils in a linear plasma facility has been performed. 0.05 mm thick W foils were exposed to ~2×1020 m-2s-1 He plasma with various fluences at 883 K. After He irradiating, D permeation tests were performed for the samples and retention was also measured by high-resolution thermal desorption spectroscopy (TDS). It was observed that He pre-irradiation resulted in a significant reduction of D permeation and retention in W. Microstructure observation indicated that the surfaces of samples after He irradiation turned rough and He nanobubbles were formed near the surface. The defective structure including He nanobubbles very likely enhances D reemission and accordingly reduces the permeation and retention in He pre-irradiated W.

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Evaluation of RapidEye-3 Satellite Data for Assessing Water Turbidity of Lake Borabey

Proceedings ◽

10.3390/ecws-4-06424 ◽

2019 ◽

Vol 48 (1) ◽

pp. 14

Author(s):

Gordana Kaplan ◽

Zehra Yigit Avdan ◽

Serdar Goncu ◽

Ugur Avdan

Keyword(s):

Remote Sensing ◽

Water Quality ◽

High Resolution ◽

Remote Sensing Data ◽

Quality Parameters ◽

In Situ Measurements ◽

Water Quality Parameters ◽

Water Turbidity ◽

Sensing Data

In water resources management, remote sensing data and techniques are essential in watershed characterization and monitoring, especially when no data are available. Water quality is usually assessed through in-situ measurements that require high cost and time. Water quality parameters help in decision making regarding the further use of water-based on its quality. Turbidity is an important water quality parameter and an indicator of water pollution. In the past few decades, remote sensing has been widely used in water quality research. In this study, we compare turbidity parameters retrieved from a high-resolution image with in-situ measurements collected from Borabey Lake, Turkey. Here, the use of RapidEye-3 images (5 m-resolution) allows for detailed assessment of spatio-temporal evaluation of turbidity, through the normalized difference turbidity index (NDTI). The turbidity results were then compared with data from 21 in-situ measurements collected in the same period. The actual water turbidity measurements showed high correlation with the estimated NDTI mean values with an R2 of 0.84. The research findings support the use of remote sensing data of RadipEye-3 to estimate water quality parameters in small water areas. For future studies, we recommend investigating different water quality parameters using high-resolution remote sensing data.

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