In Situ Observations Needed to Complement, Validate, and Interpret Satellite Altimetry

2017 ◽  
pp. 113-148 ◽  
Author(s):  
Dean Roemmich ◽  
Philip Woodworth ◽  
Svetlana Jevrejeva ◽  
Sarah Purkey ◽  
Matthias Lankhorst ◽  
...  
Keyword(s):  
Satellite Altimetry ◽  
In Situ Observations

scholarly journals Identifying and Estimating Biases between XBT and Argo Observations Using Satellite Altimetry

2010 ◽  
Vol 27 (1) ◽  
pp. 226-240 ◽  
Author(s):  
Pedro N. DiNezio ◽  
Gustavo J. Goni
Keyword(s):  
Rate Equation ◽  
Satellite Altimetry ◽  
Terminal Velocity ◽  
Height Anomaly ◽  
Fall Rate ◽  
Argo Data ◽  
Least Squares Adjustment ◽  
Systematic Biases ◽  
In Situ Observations

Abstract A methodology is developed to identify and estimate systematic biases between expendable bathythermograph (XBT) and Argo observations using satellite altimetry. Pseudoclimatological fields of isotherm depth are computed by least squares adjustment of in situ XBT and Argo data to altimetry-derived sea height anomaly (SHA) data. In regions where the correlations between isotherm depth and SHA are high, this method reduces sampling biases in the in situ observations by taking advantage of the high temporal and spatial resolution of satellite observations. Temperature profiles from deep XBTs corrected for a bias identified and adopted during the 1990s are considered in this study. The analysis shows that the pseudoclimatological isotherm depths derived from these corrected XBTs are predominantly deeper than the Argo-derived estimates during the 2000–07 period. The XBT-minus-Argo differences increase with depth consistent with hypothesized problems in the XBT fall-rate equation. The depth-dependent XBT-minus-Argo differences suggest a global positive bias of 3% of the XBT depths. The fact that this 3% error is robust among the different ocean basins provides evidence for changes in the instrumentation, such as changes in the terminal velocity of the XBTs. The value of this error is about the inverse of the correction to the XBT fall-rate equation (FRE) implemented in 1995, suggesting that this correction, while adequate during the 1990s, is no longer appropriate and could be the source of the 3% error. This result suggests that for 2000–07, the XBT dataset can be brought to consistency with Argo by using the original FRE coefficients without the 1995 correction.

scholarly journals From satellite altimetry to Argo and operational oceanography: three revolutions in oceanography

2013 ◽  
Vol 10 (4) ◽  
pp. 1127-1167 ◽  
Author(s):  
P. Y. Le Traon
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Sea Level ◽  
Ocean Circulation ◽  
Satellite Altimetry ◽  
Large Scale ◽  
Global Ocean ◽  
Operational Oceanography ◽  
In Situ Observations

Abstract. The launch of the US/French mission Topex/Poseidon (T/P) (CNES/NASA) in August 1992 was the start of a revolution in oceanography. For the first time, a very precise altimeter system optimized for large scale sea level and ocean circulation observations was flying. T/P alone could not observe the mesoscale circulation. In the 1990s, the ESA satellites ERS-1/2 were flying simultaneously with T/P. Together with my CLS colleagues, we demonstrated that we could use T/P as a reference mission for ERS-1/2 and bring the ERS-1/2 data to an accuracy level comparable to T/P. Near real time high resolution global sea level anomaly maps were then derived. These maps have been operationally produced as part of the SSALTO/DUACS system for the last 15 yr. They are now widely used by the oceanographic community and have contributed to a much better understanding and recognition of the role and importance of mesoscale dynamics. Altimetry needs to be complemented with global in situ observations. In the end of the 90s, a major international initiative was launched to develop Argo, the global array of profiling floats. This has been an outstanding success. Argo floats now provide the most important in situ observations to monitor and understand the role of the ocean on the earth climate and for operational oceanography. This is a second revolution in oceanography. The unique capability of satellite altimetry to observe the global ocean in near real time at high resolution and the development of Argo were essential to the development of global operational oceanography, the third revolution in oceanography. The Global Ocean Data Assimilation Experiment (GODAE) was instrumental in the development of the required capabilities. This paper provides an historical perspective on the development of these three revolutions in oceanography which are very much interlinked. This is not an exhaustive review and I will mainly focus on the contributions we made together with many colleagues and friends.

scholarly journals From satellite altimetry to Argo and operational oceanography: three revolutions in oceanography

Ocean Science ◽  
2013 ◽  
Vol 9 (5) ◽  
pp. 901-915 ◽  
Author(s):  
P. Y. Le Traon
Keyword(s):  
High Resolution ◽  
Real Time ◽  
Sea Level ◽  
Ocean Circulation ◽  
Satellite Altimetry ◽  
Large Scale ◽  
Global Ocean ◽  
Operational Oceanography ◽  
In Situ Observations

Abstract. The launch of the French/US mission Topex/Poseidon (T/P) (CNES/NASA) in August 1992 was the start of a revolution in oceanography. For the first time, a very precise altimeter system optimized for large-scale sea level and ocean circulation observations was flying. T/P alone could not observe the mesoscale circulation. In the 1990s, the ESA satellites ERS-1/2 were flying simultaneously with T/P. Together with my CLS colleagues, we demonstrated that we could use T/P as a reference mission for ERS-1/2 and bring the ERS-1/2 data to an accuracy level comparable to T/P. Near-real-time high-resolution global sea level anomaly maps were then derived. These maps have been operationally produced as part of the SSALTO/DUACS system for the last 15 yr. They are now widely used by the oceanographic community and have contributed to a much better understanding and recognition of the role and importance of mesoscale dynamics. Altimetry needs to be complemented with global in situ observations. At the end of the 90s, a major international initiative was launched to develop Argo, the global array of profiling floats. This has been an outstanding success. Argo floats now provide the most important in situ observations to monitor and understand the role of the ocean on the earth climate and for operational oceanography. This is a second revolution in oceanography. The unique capability of satellite altimetry to observe the global ocean in near-real-time at high resolution and the development of Argo were essential for the development of global operational oceanography, the third revolution in oceanography. The Global Ocean Data Assimilation Experiment (GODAE) was instrumental in the development of the required capabilities. This paper provides an historical perspective on the development of these three revolutions in oceanography which are very much interlinked. This is not an exhaustive review and I will mainly focus on the contributions we made together with many colleagues and friends.

In situ observations of electromigration induced void behavior

1995 ◽  
Vol 53 ◽  
pp. 244-245
Author(s):  
T. Marieb ◽  
J. C. Bravman ◽  
P. Flinn ◽  
D. Gardner ◽  
M. Madden
Keyword(s):  
Electron Microscopy ◽  
Void Nucleation ◽  
Plan View ◽  
Transmission Electron ◽  
Nucleation Sites ◽  
Microelectronics Industry ◽  
In Situ Observations ◽  
Backscatter Electron Detector ◽  
Voltage Scanning

Electromigration and stress voiding have been active areas of research in the microelectronics industry for many years. While accelerated testing of these phenomena has been performed for the last 25 years[1-2], only recently has the introduction of high voltage scanning electron microscopy (HVSEM) made possible in situ testing of realistic, passivated, full thickness samples at high resolution.With a combination of in situ HVSEM and post-testing transmission electron microscopy (TEM) , electromigration void nucleation sites in both normal polycrystalline and near-bamboo pure Al were investigated. The effect of the microstructure of the lines on the void motion was also studied.The HVSEM used was a slightly modified JEOL 1200 EX II scanning TEM with a backscatter electron detector placed above the sample[3]. To observe electromigration in situ the sample was heated and the line had current supplied to it to accelerate the voiding process. After testing lines were prepared for TEM by employing the plan-view wedge technique [6].

scholarly journals In situ observations of coral spawning and spawn slick at Lankayan Island, Sabah, Malaysia

2021 ◽  
Vol 51 (1) ◽  
Author(s):  
Sze Hoon Gan ◽  
Zarinah Waheed ◽  
Fung Chen Chung ◽  
Davies Austin Spiji ◽  
Leony Sikim ◽  
...  
Keyword(s):  
Coral Spawning ◽  
In Situ Observations

scholarly journals Snow Depth Fusion Based on Machine Learning Methods for the Northern Hemisphere

2021 ◽  
Vol 13 (7) ◽  
pp. 1250
Author(s):  
Yanxing Hu ◽  
Tao Che ◽  
Liyun Dai ◽  
Lin Xiao
Keyword(s):  
Machine Learning ◽  
Northern Hemisphere ◽  
Snow Depth ◽  
Learning Algorithm ◽  
Random Forest Regression ◽  
Machine Learning Methods ◽  
Long Time ◽  
In Situ Observations ◽  
Input Variables

In this study, a machine learning algorithm was introduced to fuse gridded snow depth datasets. The input variables of the machine learning method included geolocation (latitude and longitude), topographic data (elevation), gridded snow depth datasets and in situ observations. A total of 29,565 in situ observations were used to train and optimize the machine learning algorithm. A total of five gridded snow depth datasets—Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) snow depth, Global Snow Monitoring for Climate Research (GlobSnow) snow depth, Long time series of daily snow depth over the Northern Hemisphere (NHSD) snow depth, ERA-Interim snow depth and Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2) snow depth—were used as input variables. The first three snow depth datasets are retrieved from passive microwave brightness temperature or assimilation with in situ observations, while the last two are snow depth datasets obtained from meteorological reanalysis data with a land surface model and data assimilation system. Then, three machine learning methods, i.e., Artificial Neural Networks (ANN), Support Vector Regression (SVR), and Random Forest Regression (RFR), were used to produce a fused snow depth dataset from 2002 to 2004. The RFR model performed best and was thus used to produce a new snow depth product from the fusion of the five snow depth datasets and auxiliary data over the Northern Hemisphere from 2002 to 2011. The fused snow-depth product was verified at five well-known snow observation sites. The R2 of Sodankylä, Old Aspen, and Reynolds Mountains East were 0.88, 0.69, and 0.63, respectively. At the Swamp Angel Study Plot and Weissfluhjoch observation sites, which have an average snow depth exceeding 200 cm, the fused snow depth did not perform well. The spatial patterns of the average snow depth were analyzed seasonally, and the average snow depths of autumn, winter, and spring were 5.7, 25.8, and 21.5 cm, respectively. In the future, random forest regression will be used to produce a long time series of a fused snow depth dataset over the Northern Hemisphere or other specific regions.

scholarly journals Pelagic deep-sea fauna observed on video transects in the southern Norwegian Sea

Polar Biology ◽  
2021 ◽  
Author(s):  
Philipp Neitzel ◽  
Aino Hosia ◽  
Uwe Piatkowski ◽  
Henk-Jan Hoving
Keyword(s):  
First Record ◽  
Observation System ◽  
In Situ Observation ◽  
Norwegian Sea ◽  
Video Recordings ◽  
In Situ Observations ◽  
Abundance And Distribution ◽  
Oceanic Food Webs ◽  
Deep Sea Fauna

AbstractObservations of the diversity, distribution and abundance of pelagic fauna are absent for many ocean regions in the Atlantic, but baseline data are required to detect changes in communities as a result of climate change. Gelatinous fauna are increasingly recognized as vital players in oceanic food webs, but sampling these delicate organisms in nets is challenging. Underwater (in situ) observations have provided unprecedented insights into mesopelagic communities in particular for abundance and distribution of gelatinous fauna. In September 2018, we performed horizontal video transects (50–1200 m) using the pelagic in situ observation system during a research cruise in the southern Norwegian Sea. Annotation of the video recordings resulted in 12 abundant and 7 rare taxa. Chaetognaths, the trachymedusaAglantha digitaleand appendicularians were the three most abundant taxa. The high numbers of fishes and crustaceans in the upper 100 m was likely the result of vertical migration. Gelatinous zooplankton included ctenophores (lobate ctenophores,Beroespp.,Euplokamissp., and an undescribed cydippid) as well as calycophoran and physonect siphonophores. We discuss the distributions of these fauna, some of which represent the first record for the Norwegian Sea.

In situ observations of isothermal cuspidine crystallization in molten mould fluxes with varying basicity

2020 ◽  
pp. 1-6
Author(s):  
Jiangling Li ◽  
Feifei Lai ◽  
Mei Leng ◽  
Qingcai Liu ◽  
Jian Yang ◽  
...  
Keyword(s):  
In Situ Observations
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