scholarly journals Validation of Landsat 8 high resolution Sea Surface Temperature using surfers

2021 ◽  
pp. 107650
Author(s):  
Quinten Vanhellemont ◽  
Robert J.W. Brewin ◽  
Philip J. Bresnahan ◽  
Tyler Cyronak
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Sea Surface ◽  
Landsat 8

scholarly journals High-Resolution Sea Surface Temperature Retrieval from Landsat 8 OLI/TIRS Data at Coastal Regions

2019 ◽  
Vol 11 (22) ◽  
pp. 2687 ◽  
Author(s):  
Jae-Cheol Jang ◽  
Kyung-Ae Park
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Korean Peninsula ◽  
Sea Surface ◽  
Global Ocean ◽  
Small Scale ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Coastal Regions

High-resolution sea surface temperature (SST) images are essential to study the highly variable small-scale oceanic phenomena in a coastal region. Most previous SST algorithms are focused on the low or medium resolution SST from the near polar orbiting or geostationary satellites. The Landsat 8 Operational Land Imager and Thermal Infrared Sensor (OLI/TIRS) makes it possible to obtain high-resolution SST images of coastal regions. This study performed a matchup procedure between 276 Landsat 8 images and in-situ temperature measurements of buoys off the coast of the Korean Peninsula from April 2013 to August 2017. Using the matchup database, we investigated SST errors for each formulation of the Multi-Channel SST (MCSST) and the Non-Linear SST (NLSST) by considering the satellite zenith angle (SZA) and the first-guess SST. The retrieved SST equations showed a root-mean-square error (RMSE) from 0.59 to 0.72 °C. The smallest errors were found for the NLSST equation that considers the SZA and uses the first-guess SST, compared with the MCSST equations. The SST errors showed characteristic dependences on the atmospheric water vapor, the SZA, and the wind speed. In spite of the narrow swath width of the Landsat 8, the effect of the SZA on the errors was estimated to be significant and considerable for all the formations. Although the coefficients were calculated in the coastal regions around the Korean Peninsula, these coefficients are expected to be feasible for SST retrieval applied to any other parts of the global ocean. This study also addressed the need for high-resolution coastal SST, by emphasizing the usefulness of the high-resolution Landsat 8 OLI/TIRS data for monitoring the small-scale oceanic phenomena in coastal regions.

scholarly journals Immense variability in the sea surface temperature near macro tidal flat revealed by high-resolution satellite data (Landsat 8)

2022 ◽  
Vol 12 (1) ◽  
Author(s):  
Seung-Tae Lee ◽  
Yang-Ki Cho ◽  
Duk-jin Kim
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Tidal Flat ◽  
Sea Water ◽  
Sea Surface ◽  
Landsat 8 ◽  
Open Sea ◽  
In Situ Observations

AbstractSea surface temperature (SST) is crucial for understanding the physical characteristics and ecosystems of coastal seas. SST varies near the tidal flat, where exposure and flood recur according to the tidal cycle. However, the variability of SST near the tidal flat is poorly understood owing to difficulties in making in-situ observations. The high resolution of Landsat 8 enabled us to determine the variability of SST near the macro tidal flat. The spatial distribution of the SST extracted from Landsat 8 changed drastically. The seasonal SST range was higher near the tidal flat than in the open sea. The maximum seasonal range of coastal SST exceeded 23 °C, whereas the range in the open ocean was approximately 18 °C. The minimum and maximum horizontal SST gradients near the tidal flat were approximately − 0.76 °C/10 km in December and 1.31 °C/10 km in June, respectively. The heating of sea water by tidal flats in spring and summer, and cooling in the fall and winter might result in a large horizontal SST gradient. The estimated heat flux from the tidal flat to the seawater based on the SST distribution shows seasonal change ranging from − 4.85 to 6.72 W/m2.

scholarly journals Data Assimilation of the High-Resolution Sea Surface Temperature Obtained from the Aqua-Terra Satellites (MODIS-SST) Using an Ensemble Kalman Filter

2013 ◽  
Vol 5 (6) ◽  
pp. 3123-3139 ◽  
Author(s):  
Yasumasa Miyazawa ◽  
Hiroshi Murakami ◽  
Toru Miyama ◽  
Sergey Varlamov ◽  
Xinyu Guo ◽  
...  
Keyword(s):  
Kalman Filter ◽  
High Resolution ◽  
Data Assimilation ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Ensemble Kalman Filter ◽  
Sea Surface

scholarly journals BCC-CSM2-HR: A High-Resolution Version of the Beijing Climate Center Climate System Model

2020 ◽  
Author(s):  
Tongwen Wu ◽  
Rucong Yu ◽  
Yixiong Lu ◽  
Weihua Jie ◽  
Yongjie Fang ◽  
...  
Keyword(s):  
High Resolution ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Climate System ◽  
Sea Surface ◽  
System Model ◽  
Quasi Biennial Oscillation ◽  
Climate System Model ◽  
Medium Resolution ◽  
The Tropics

Abstract. BCC-CSM2-HR is a high-resolution version of the Beijing Climate Center (BCC) Climate System Model. Its development is on the basis of the medium-resolution version BCC-CSM2-MR which is the baseline for BCC participation to the Coupled Model Intercomparison Project Phase 6 (CMIP6). This study documents the high-resolution model, highlights major improvements in the representation of atmospheric dynamic core and physical processes. BCC-CSM2-HR is evaluated for present-day climate simulations from 1971 to 2000, which are performed under CMIP6-prescribed historical forcing, in comparison with its previous medium-resolution version BCC-CSM2-MR. We focus on basic atmospheric mean states over the globe and variabilities in the tropics including the tropic cyclones (TCs), the El Niño–Southern Oscillation (ENSO), the Madden-Julian Oscillation (MJO), and the quasi-biennial oscillation (QBO) in the stratosphere. It is shown that BCC-CSM2-HR keeps well the global energy balance and can realistically reproduce main patterns of atmosphere temperature and wind, precipitation, land surface air temperature and sea surface temperature. It also improves in the spatial patterns of sea ice and associated seasonal variations in both hemispheres. The bias of double intertropical convergence zone (ITCZ), obvious in BCC-CSM2-MR, is almost disappeared in BCC-CSM2-HR. TC activity in the tropics is increased with resolution enhanced. The cycle of ENSO, the eastward propagative feature and convection intensity of MJO, the downward propagation of QBO in BCC-CSM2-HR are all in a better agreement with observation than their counterparts in BCC-CSM2-MR. We also note some weakness in BCC-CSM2-HR, such as the excessive cloudiness in the eastern basin of the tropical Pacific with cold Sea Surface Temperature (SST) biases and the insufficient number of tropical cyclones in the North Atlantic.

scholarly journals Validation of Sea Surface Temperature from GCOM-C Satellite Using iQuam Datasets and MUR-SST in Indonesian Waters

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Bambang Sukresno ◽  
Dinarika Jatisworo ◽  
Rizki Hanintyo
Keyword(s):  
High Resolution ◽  
Error Analysis ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Important Variable ◽  
Sea Surface ◽  
Analysis Method ◽  
Validation Process ◽  
Indonesian Seas

Sea surface temperature (SST) is an important variable in oceanography. One of the SST data can be obtained from the Global Observation Mission-Climate (GCOM-C) satellite. Therefore, this data needs to be validated before being applied in various fields. This study aimed to validate SST data from the GCOM-C satellite in the Indonesian Seas. Validation was performed using the data of Multi-sensor Ultra-high Resolution sea surface temperature (MUR-SST) and in situ sea surface temperature Quality Monitor (iQuam). The data used are the daily GCOM-C SST dataset from January to December 2018, as well as the daily dataset from MUR-SST and iQuam in the same period. The validation process was carried out using the three-way error analysis method. The results showed that the accuracy of the GCOM-C SST was 0.37oC.

scholarly journals RETRIEVAL OF SEA SURFACE TEMPERATURE OVER POTERAN ISLAND WATER OF INDONESIA WITH LANDSAT 8 TIRS IMAGE: A PRELIMINARY ALGORITHM

2015 ◽  
Vol XL-2/W4 ◽  
pp. 87-90 ◽  
Author(s):  
M. A. Syariz ◽  
L. M. Jaelani ◽  
L. Subehi ◽  
A. Pamungkas ◽  
E. S. Koenhardono ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Brightness Temperature ◽  
Sea Surface ◽  
Coefficient Of Determination ◽  
Landsat 8 ◽  
In Situ Data ◽  
The North ◽  
Thermal Band

The Sea Surface Temperature (SST) retrieval from satellites data Thus, it could provide SST data for a long time. Since, the algorithms of SST estimation by using Landsat 8 Thermal Band are sitedependence, we need to develop an applicable algorithm in Indonesian water. The aim of this research was to develop SST algorithms in the North Java Island Water. The data used are in-situ data measured on April 22, 2015 and also estimated brightness temperature data from Landsat 8 Thermal Band Image (band 10 and band 11). The algorithm was established using 45 data by assessing the relation of measured in-situ data and estimated brightness temperature. Then, the algorithm was validated by using another 40 points. The results showed that the good performance of the sea surface temperature algorithm with coefficient of determination (<i>R</i><sup>2</sup>) and Root Mean Square Error (<i>RMSE</i>) of 0.912 and 0.028, respectively.

scholarly journals Impact of high-resolution sea surface temperature representation on the forecast of small Mediterranean catchments' hydrological responses to heavy precipitation

2020 ◽  
Vol 24 (1) ◽  
pp. 269-291 ◽  
Author(s):  
Alfonso Senatore ◽  
Luca Furnari ◽  
Giuseppe Mendicino
Keyword(s):  
High Resolution ◽  
Boundary Conditions ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
Circulation Model ◽  
Sea Surface ◽  
Sources Of Uncertainty ◽  
Operational Forecasting ◽  
Forecasting System

Abstract. Operational meteo-hydrological forecasting chains are affected by many sources of uncertainty. In coastal areas characterized by complex topography, with several medium-to-small size catchments, quantitative precipitation forecast becomes even more challenging due to the interaction of intense air–sea exchanges with coastal orography. For such areas, which are quite common in the Mediterranean Basin, improved representation of sea surface temperature (SST) space–time patterns can be particularly important. The paper focuses on the relative impact of different resolutions of SST representation on regional operational forecasting chains (up to river discharge estimates) over coastal Mediterranean catchments, with respect to two other fundamental options while setting up the system, i.e. the choice of the forcing general circulation model (GCM) and the possible use of a three-dimensional variational assimilation (3D-Var) scheme. Two different kinds of severe hydro-meteorological events that affected the Calabria region (southern Italy) in 2015 are analysed using the WRF-Hydro atmosphere–hydrology modelling system in its uncoupled version. Both of the events are modelled using the 0.25∘ resolution global forecasting system (GFS) and the 16 km resolution integrated forecasting system (IFS) initial and lateral atmospheric boundary conditions, which are from the European Centre for Medium-Range Weather Forecasts (ECMWF), applying the WRF mesoscale model for the dynamical downscaling. For the IFS-driven forecasts, the effects of the 3D-Var scheme are also analysed. Finally, native initial and lower boundary SST data are replaced with data from the Medspiration project by Institut Français de Recherche pour L'Exploitation de la Mer (IFREMER)/Centre European Remote Sensing d'Archivage et de Traitement (CERSAT), which have a 24 h time resolution and a 2.2 km spatial resolution. Precipitation estimates are compared with both ground-based and radar data, as well as discharge estimates with stream gauging stations' data. Overall, the experiments highlight that the added value of high-resolution SST representation can be hidden by other more relevant sources of uncertainty, especially the choice of the general circulation model providing the boundary conditions. Nevertheless, in most cases, high-resolution SST fields show a non-negligible impact on the simulation of the atmospheric boundary layer processes, modifying flow dynamics and/or the amount of precipitated water; thus, this emphasizes the fact that uncertainty in SST representation should be duly taken into account in operational forecasting in coastal areas.

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