Estimation of Water Surface Temperature by Infrared Remote Sensing at Shiozu Bay in Lake Biwa.

An effective method for evaluating chlorophyll “a” is remote sensing in the optical range by satellite spectroradiometers. To study the concentration of chlorophyll “a” in the bio-productive regions of the ocean, we used data from the MODIS-Aqua scanner of the NASA GIOVANNI system, which provides access to satellite data archives at the same time as tools for their processing and analysis. The variability of the chlorophyll “a” concentration in surface waters may indicate the state of water productivity. The paper considers the temporal and spatial variability of chlorophyll “a” concentration and water surface temperature from satellite data and the influence of water surface temperature on this variability in the Gulf of Alaska and in the area of the Peruvian upwelling. As a result, a direct relationship between changes in the concentration of chlorophyll “a” and the water surface temperature was revealed. It is possible to assess the bio-productivity depending on the variability of the concentration of chlorophyll “a”.

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Water surface temperature estimates using active and passive microwave remote sensing: preliminary results from an outdoor wind-wave tank

Proceedings of IGARSS '94 - 1994 IEEE International Geoscience and Remote Sensing Symposium ◽

10.1109/igarss.1994.399331 ◽

2005 ◽

Cited By ~ 2

Author(s):

J.F. Vesecky ◽

R.G. Onstott ◽

N.-Y. Wang ◽

E. Lettvin ◽

J. Slawski ◽

...

Keyword(s):

Remote Sensing ◽

Surface Temperature ◽

Water Surface ◽

Wind Wave ◽

Microwave Remote Sensing ◽

Passive Microwave ◽

Passive Microwave Remote Sensing ◽

Wave Tank ◽

Preliminary Results ◽

Water Surface Temperature

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The effect of water surface temperature on lake breezes and thermal internal boundary layers

Boundary-Layer Meteorology ◽

10.1007/bf00140071 ◽

1987 ◽

Vol 40 (1-2) ◽

pp. 101-125 ◽

Cited By ~ 61

Author(s):

Raymond W. Arritt

Keyword(s):

Surface Temperature ◽

Boundary Layers ◽

Water Surface ◽

Internal Boundary ◽

Effect Of Water ◽

Water Surface Temperature ◽

Internal Boundary Layers ◽

Lake Breezes

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Analysis and Modelling of Temperature at Lake’s Water – Atmosphere Interface

10.21203/rs.3.rs-843456/v1 ◽

2021 ◽

Author(s):

Vassilis Z. Antonopoulos ◽

Soultana K. Gianniou

Keyword(s):

Heat Transfer ◽

Energy Balance ◽

Surface Temperature ◽

Water Surface ◽

Heat Transfer Model ◽

Transfer Model ◽

Net Radiation ◽

Water Surface Temperature ◽

Simulation Results ◽

Input Variables

Abstract The knowledge of micrometeorological conditions on water surface of impoundments is crucial for the better modeling of the temperature and water quality parameters distribution in the water body and against the climatic changes. Water temperature distribution is an important factor that affects most physical, chemical and biological processes and reactions occurring in lakes. In this work, different processes of water surface temperature of lake’s estimation based on the energy balance method are considered. The daily meteorological data and the simulation results of energy balance components from an integrated heat transfer model for two complete years as well as the lake’s characteristics for Vegoritis lake in northern Greece were used is this analysis.The simulation results of energy balance components from a heat transfer model are considered as the reference and more accurate procedure to estimate water surface temperature. These results are used to compare the other processes. The examined processes include a) models of heat storage changes in relationship to net radiation (Qt(Rn) values, b) net radiation estimation with different approaches, as the process of Slob’s equation with adjusted coefficients to lake data, and c) ANNs models with different architecture and input variables. The results show that the model of heat balance describes the water surface temperature with high accuracy (r2=0.916, RMSE=2.422oC). The ANN(5,6,1) model in which Tsw(i-1) is incorporated in the input variables was considered the better of all other ANN structures (r2=0.995, RMSE=0.490oC). The use of different approaches for simulating net radiation (Rn) and Qt(Rn) in the equation of water surface temperature gives results with lower accuracy.

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