scholarly journals Creation of a Gridded Dataset for the Southern Ocean with a Topographic Constraint Scheme

2017 ◽  
Vol 34 (3) ◽  
pp. 511-532 ◽  
Author(s):  
Keishi Shimada ◽  
Shigeru Aoki ◽  
Kay I. Ohshima
Keyword(s):  
Southern Ocean ◽  
Weighting Function ◽  
Interpolation Method ◽  
Potential Temperature ◽  
Interpolation Error ◽  
Horizontal Distance ◽  
Gridded Dataset ◽  
The Difference ◽  
Bottom Depth ◽  
Decorrelation Scale

AbstractThis study investigated a method for creating a climatological dataset with improved reproducibility and reliability for the Southern Ocean. Despite sparse observational sampling, the Southern Ocean has a dominant physical characteristic of a strong topographic constraint formed under weak stratification and strong Coriolis effect. To increase the fidelity of gridded data, the topographic constraint is incorporated into the interpolation method, the weighting function of which includes a contribution from bottom depth differences and horizontal distances. Spatial variability of physical properties was also analyzed to estimate a realistic decorrelation scale for horizontal distance and bottom depth differences using hydrographic datasets. A new gridded dataset, the topographic constraint incorporated (TCI), was then developed for temperature, salinity, and dissolved oxygen, using the newly derived weighting function and decorrelation scales. The root-mean-square (RMS) of the difference between the interpolated values and the neighboring observed values (RMS difference) was compared among available gridded datasets. That the RMS differences are smaller for the TCI than for the previous datasets by 12%–21% and 8%–20% for potential temperature and salinity, respectively, demonstrates the effectiveness of incorporating the topographic constraint and realistic decorrelation scales. Furthermore, a comparison of decorrelation scales and an analysis of interpolation error suggests that the decorrelation scales adopted in previous gridded datasets are 2 times or more larger than realistic scales and that the overestimation would increase the interpolation error. The interpolation method proposed in this study can be applied to other high-latitude oceans, which are weakly stratified but undersampled.

Algorithms for Density, Potential Temperature, Conservative Temperature, and the Freezing Temperature of Seawater

2006 ◽  
Vol 23 (12) ◽  
pp. 1709-1728 ◽  
Author(s):  
David R. Jackett ◽  
Trevor J. McDougall ◽  
Rainer Feistel ◽  
Daniel G. Wright ◽  
Stephen M. Griffies
Keyword(s):  
Thermal Expansion ◽  
Equation Of State ◽  
Thermodynamic Potential ◽  
Potential Temperature ◽  
Inverse Function ◽  
Freezing Temperature ◽  
Ocean Models ◽  
The Difference ◽  
New Equation ◽  
Density Equation

Abstract Algorithms are presented for density, potential temperature, conservative temperature, and the freezing temperature of seawater. The algorithms for potential temperature and density (in terms of potential temperature) are updates to routines recently published by McDougall et al., while the algorithms involving conservative temperature and the freezing temperatures of seawater are new. The McDougall et al. algorithms were based on the thermodynamic potential of Feistel and Hagen; the algorithms in this study are all based on the “new extended Gibbs thermodynamic potential of seawater” of Feistel. The algorithm for the computation of density in terms of salinity, pressure, and conservative temperature produces errors in density and in the corresponding thermal expansion coefficient of the same order as errors for the density equation using potential temperature, both being twice as accurate as the International Equation of State when compared with Feistel’s new equation of state. An inverse function relating potential temperature to conservative temperature is also provided. The difference between practical salinity and absolute salinity is discussed, and it is shown that the present practice of essentially ignoring the difference between these two different salinities is unlikely to cause significant errors in ocean models.

scholarly journals Subantarctic Mode Water Formation, Destruction, and Export in the Eddy-Permitting Southern Ocean State Estimate

2013 ◽  
Vol 43 (7) ◽  
pp. 1485-1511 ◽  
Author(s):  
Ivana Cerovečki ◽  
Lynne D. Talley ◽  
Matthew R. Mazloff ◽  
Guillaume Maze
Keyword(s):  
Southern Ocean ◽  
Buoyancy Flux ◽  
Differential Heat ◽  
Diapycnal Mixing ◽  
Mode Water ◽  
State Estimate ◽  
Surface Formation ◽  
Subantarctic Mode Water ◽  
The Pacific ◽  
The Difference

Abstract Subantarctic Mode Water (SAMW) is examined using the data-assimilating, eddy-permitting Southern Ocean State Estimate, for 2005 and 2006. Surface formation due to air–sea buoyancy flux is estimated using Walin analysis, and diapycnal mixing is diagnosed as the difference between surface formation and transport across 30°S, accounting for volume change with time. Water in the density range 26.5 < σθ < 27.1 kg m−3 that includes SAMW is exported northward in all three ocean sectors, with a net transport of (18.2, 17.1) Sv (1 Sv ≡ 106 m3 s−1; for years 2005, 2006); air–sea buoyancy fluxes form (13.2, 6.8) Sv, diapycnal mixing removes (−14.5, −12.6) Sv, and there is a volume loss of (−19.3, −22.9) Sv mostly occurring in the strongest SAMW formation locations. The most vigorous SAMW formation is in the Indian Ocean by air–sea buoyancy flux (9.4, 10.9) Sv, where it is partially destroyed by diapycnal mixing (−6.6, −3.1) Sv. There is strong export to the Pacific, where SAMW is destroyed both by air–sea buoyancy flux (−1.1, −4.6) Sv and diapycnal mixing (−5.6, −8.4) Sv. In the South Atlantic, SAMW is formed by air–sea buoyancy flux (5.0, 0.5) Sv and is destroyed by diapycnal mixing (−2.3, −1.1) Sv. Peaks in air–sea flux formation occur at the Southeast Indian and Southeast Pacific SAMWs (SEISAMWs, SEPSAMWs) densities. Formation over the broad SAMW circumpolar outcrop windows is largely from denser water, driven by differential freshwater gain, augmented or decreased by heating or cooling. In the SEISAMW and SEPSAMW source regions, however, formation is from lighter water, driven by differential heat loss.

scholarly journals A Multivariate Empirical Orthogonal Function Method to Construct Nitrate Maps in the Southern Ocean

2018 ◽  
Vol 35 (7) ◽  
pp. 1505-1519 ◽  
Author(s):  
Yu-Chiao Liang ◽  
Matthew R. Mazloff ◽  
Isabella Rosso ◽  
Shih-Wei Fang ◽  
Jin-Yi Yu
Keyword(s):  
Southern Ocean ◽  
General Circulation ◽  
Model Simulation ◽  
Potential Temperature ◽  
Circulation Model ◽  
Empirical Orthogonal Functions ◽  
Cluster Method ◽  
Sampling Strategies ◽  
Data Sampling ◽  
Mean Square Errors

AbstractThe ability to construct nitrate maps in the Southern Ocean (SO) from sparse observations is important for marine biogeochemistry research, as it offers a geographical estimate of biological productivity. The goal of this study is to infer the skill of constructed SO nitrate maps using varying data sampling strategies. The mapping method uses multivariate empirical orthogonal functions (MEOFs) constructed from nitrate, salinity, and potential temperature (N-S-T) fields from a biogeochemical general circulation model simulation Synthetic N-S-T datasets are created by sampling modeled N-S-T fields in specific regions, determined either by random selection or by selecting regions over a certain threshold of nitrate temporal variances. The first 500 MEOF modes, determined by their capability to reconstruct the original N-S-T fields, are projected onto these synthetic N-S-T data to construct time-varying nitrate maps. Normalized root-mean-square errors (NRMSEs) are calculated between the constructed nitrate maps and the original modeled fields for different sampling strategies. The sampling strategy according to nitrate variances is shown to yield maps with lower NRMSEs than mapping adopting random sampling. A k-means cluster method that considers the N-S-T combined variances to identify key regions to insert data is most effective in reducing the mapping errors. These findings are further quantified by a series of mapping error analyses that also address the significance of data sampling density. The results provide a sampling framework to prioritize the deployment of biogeochemical Argo floats for constructing nitrate maps.

A Physically Based Algorithm for Non-Blackbody Correction of Cloud-Top Temperature and Application to Convection Study

2014 ◽  
Vol 53 (7) ◽  
pp. 1844-1857 ◽  
Author(s):  
Chunpeng Wang ◽  
Zhengzhao Johnny Luo ◽  
Xiuhong Chen ◽  
Xiping Zeng ◽  
Wei-Kuo Tao ◽  
...  
Keyword(s):  
Brightness Temperature ◽  
Weighting Function ◽  
Convective Cloud ◽  
Transfer Model ◽  
Height Range ◽  
Convective Clouds ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Cloud Top Temperature

AbstractCloud-top temperature (CTT) is an important parameter for convective clouds and is usually different from the 11-μm brightness temperature due to non-blackbody effects. This paper presents an algorithm for estimating convective CTT by using simultaneous passive [Moderate Resolution Imaging Spectroradiometer (MODIS)] and active [CloudSat + Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO)] measurements of clouds to correct for the non-blackbody effect. To do this, a weighting function of the MODIS 11-μm band is explicitly calculated by feeding cloud hydrometer profiles from CloudSat and CALIPSO retrievals and temperature and humidity profiles based on ECMWF analyses into a radiation transfer model. Among 16 837 tropical deep convective clouds observed by CloudSat in 2008, the averaged effective emission level (EEL) of the 11-μm channel is located at optical depth ~0.72, with a standard deviation of 0.3. The distance between the EEL and cloud-top height determined by CloudSat is shown to be related to a parameter called cloud-top fuzziness (CTF), defined as the vertical separation between −30 and 10 dBZ of CloudSat radar reflectivity. On the basis of these findings a relationship is then developed between the CTF and the difference between MODIS 11-μm brightness temperature and physical CTT, the latter being the non-blackbody correction of CTT. Correction of the non-blackbody effect of CTT is applied to analyze convective cloud-top buoyancy. With this correction, about 70% of the convective cores observed by CloudSat in the height range of 6–10 km have positive buoyancy near cloud top, meaning clouds are still growing vertically, although their final fate cannot be determined by snapshot observations.

scholarly journals A Novel TODIM with Probabilistic Hesitant Fuzzy Information and Its Application in Green Supplier Selection

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Xiaoli Tian ◽  
Meiling Niu ◽  
Jiangshui Ma ◽  
Zeshui Xu
Keyword(s):  
Weighting Function ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Sensitivity Analyses ◽  
Fuzzy Information ◽  
Probability Weighting Function ◽  
The Difference ◽  
The Stability ◽  
Gains And Losses

TODIM is a well-known multiple-criteria decision-making (MCDM) which considers the bounded rationality of decision makers (DMs) based on prospect theory (PT). However, in the classical TODIM, the perceived probability weighting function and the difference of the risk attitudes for gains and losses are not consistent with the original idea of PT. Moreover, probabilistic hesitant fuzzy information shows its superiority in handling the situation that the DMs hesitate among several possible values with different possibilities. Hence, a novel TODIM with probabilistic hesitant fuzzy information is proposed in this paper to simulate the perceptions of the DMs in PT. To show the advantages of the proposed method, a novel TODIM is combined with hesitant fuzzy information. Finally, a case study is carried out to demonstrate the feasibility of the proposed method, and a series of comparative analyses and the sensitivity analyses are used to show the stability of the proposed method.

scholarly journals Analysis and Comparison of GPS Precipitable Water Estimates between Two Nearby Stations on Tahiti Island

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5578
Author(s):  
Fangzhao Zhang ◽  
Jean-Pierre Barriot ◽  
Guochang Xu ◽  
Marania Hopuare
Keyword(s):  
Mapping Function ◽  
Precipitable Water ◽  
Satellite System ◽  
Tropospheric Delay ◽  
Horizontal Distance ◽  
International Gnss Service ◽  
Weighted Mean Temperature ◽  
The Difference ◽  
Global Navigation Satellite ◽  
The Impact

Since Bevis first proposed Global Positioning System (GPS) meteorology in 1992, the precipitable water (PW) estimates retrieved from Global Navigation Satellite System (GNSS) networks with high accuracy have been widely used in many meteorological applications. The proper estimation of GNSS PW can be affected by the GNSS processing strategy as well as the local geographical properties of GNSS sites. To better understand the impact of these factors, we compare PW estimates from two nearby permanent GPS stations (THTI and FAA1) in the tropical Tahiti Island, a basalt shield volcano located in the South Pacific, with a mean slope of 8% and a diameter of 30 km. The altitude difference between the two stations is 86.14 m, and their horizontal distance difference is 2.56 km. In this paper, Bernese GNSS Software Version 5.2 with precise point positioning (PPP) and Vienna mapping function 1 (VMF1) was applied to estimate the zenith tropospheric delay (ZTD), which was compared with the International GNSS Service (IGS) Final products. The meteorological parameters sourced from the European Center for Medium-Range Weather Forecasts (ECMWF) and the local weighted mean temperature ( T m ) model were used to estimate the GPS PW for three years (May 2016 to April 2019). The results show that the differences of PW between two nearby GPS stations is nearly a constant with value 1.73 mm. In our case, this difference is mainly driven by insolation differences, the difference in altitude and the wind being only second factors.

scholarly journals Mapping of Snow Depth by Blending Satellite and In-Situ Data Using Two-Dimensional Optimal Interpolation—Application to AMSR2

2019 ◽  
Vol 11 (24) ◽  
pp. 3049 ◽  
Author(s):  
Cezar Kongoli ◽  
Jeffrey Key ◽  
Thomas M. Smith
Keyword(s):  
North America ◽  
Snow Depth ◽  
Weather Prediction ◽  
Weighted Average ◽  
Optimal Interpolation ◽  
Horizontal Distance ◽  
Two Dimensional ◽  
In Situ Data ◽  
The Difference

The development of a snow depth product over North America is investigated by applying two-dimensional optimal interpolation to passive microwave satellite-derived and in-situ measured snow depth. At each snow-covered satellite footprint, the technique computes a snow depth increment as the weighted average of data increments, and updates the satellite-derived snow depth accordingly. Data increments are computed as the difference between the in-situ-measured and satellite snow depth at station locations surrounding the satellite footprint. Calculation of optimal weights is based on spatial lag autocorrelation of snow depth increments, modelled as functions of horizontal distance and elevation difference between pairs of observations. The technique is applied to Advanced Microwave Scanning Radiometer 2 (AMSR2) snow depth and in-situ snow depth obtained from the Global Historical Climatology Network. The results over North America during January–February 2017 indicate that the technique greatly enhances the performance of the satellite estimates, especially over mountain terrain, albeit with an accuracy inferior to that over low elevation areas. Moreover, the technique generates more accurate output compared to that from NOAA’s Global Forecast System, with implications for improving the utilization of satellite data in snow assessments and numerical weather prediction.

scholarly journals An iron budget during the natural iron fertilisation experiment KEOPS (Kerguelen Islands, Southern Ocean)

2009 ◽  
Vol 6 (4) ◽  
pp. 6803-6837 ◽  
Author(s):  
F. Chever ◽  
G. Sarthou ◽  
E. Bucciarelli ◽  
S. Blain ◽  
A. R. Bowie
Keyword(s):  
Southern Ocean ◽  
Dissolved Iron ◽  
Heard Island ◽  
Natural Iron ◽  
Particulate Iron ◽  
The Difference ◽  
The One ◽  
Iron Pool ◽  
Lateral Advection ◽  
Very High

Abstract. Total dissolvable iron (TDFe) was measured in the water column above and in the surrounding of the Kerguelen Plateau (Indian sector of the Southern Ocean) during the KErguelen Ocean Plateau compared Study (KEOPS) cruise. TDFe concentrations ranged from 0.90 to 65.6 nmol L−1 above the plateau and from 0.34 to 2.23 nmol L−1 offshore of the plateau. Station C1 located south of the plateau, near Heard Island, exhibited very high values (329–770 nmol L−1). Apparent particulate iron (Feapp), calculated as the difference between the TDFe and the dissolved iron measured on board (DFe) represented 95±5% of the TDFe above the plateau, suggesting that particles and refractory colloids largely dominated the iron pool. This paper presents a budget of DFe and Feapp above the plateau. Lateral advection of water that had been in contact with the continental shelf of Heard Island seems to be the predominant source of Feapp and DFe above the plateau, with a supply of 9.7±2.3×106 and 8.3±6.7×103 mol d−1, respectively. The residence times of 1.7 and 48 days estimated for Feapp and DFe, respectively, indicate a rapid turnover in the surface water. A comparison between Feapp and total particulate iron (TPFe) suggests that the total dissolved fraction is mainly constituted of small refractory colloids. This fraction does not seem to be a potential source of iron to the phytoplankton in our study. Finally, when taking into account the lateral supply of dissolved iron, the seasonal carbon sequestration efficiency was estimated at 154 000 mol C (mol Fe)−1, which is 4-fold lower than the previously estimated value in this area but still 18-fold higher than the one estimated during the other study of a natural iron fertilisation experiment, CROZEX.

scholarly journals Tropical Cyclone–Relative Environmental Helicity and the Pathways to Intensification in Shear

2016 ◽  
Vol 73 (2) ◽  
pp. 869-890 ◽  
Author(s):  
Matthew J. Onderlinde ◽  
David S. Nolan
Keyword(s):  
Tropical Cyclone ◽  
Tropical Cyclones ◽  
Latent Heat ◽  
Wind Shear ◽  
Potential Temperature ◽  
Reanalysis Data ◽  
Heat Fluxes ◽  
Equivalent Potential ◽  
Vertical Variations ◽  
The Difference

Abstract Tropical cyclone–relative environmental helicity (TCREH) is a measure of how the wind vector changes direction with height, and it has been shown to modulate the rate at which tropical cyclones (TCs) develop both in idealized simulations and in reanalysis data. The channels through which this modulation occurs remain less clear. This study aims to identify the mechanisms that lead to the observed variations in intensification rate. Results suggest that the difference in intensification rate between TCs embedded in positive versus negative TCREH primarily results from the position of convection and associated latent heat fluxes relative to the wind shear vector. When TCREH is positive, convection is more readily advected upshear and air parcels that experience larger fluxes are more frequently ingested into the TC core. Trajectories computed from high-resolution simulations demonstrate the recovery of equivalent potential temperature downwind of convection, latent heat flux near the TC core, and parcel routes through updrafts in convection. Differences in trajectory characteristics between TCs embedded in positive versus negative TCREH are presented. Contoured frequency-by-altitude diagrams (CFADs) show that convection is distributed differently around TCs embedded in environments characterized by positive versus negative TCREH. They also show that the nature of the most intense convection differs only slightly between cases of positive and negative TCREH. The results of this study emphasize the fact that significant variability in TC-intensification rate results from vertical variations in the environmental wind direction, even when the 850–200-hPa wind shear vector remains unchanged.

AMS-14C Ages Measured in Deep Sea Cores from the Southern Ocean: Implications for Sedimentation Rates during Isotope Stage 2

1989 ◽  
Vol 31 (2) ◽  
pp. 309-317 ◽  
Author(s):  
Edouard Bard ◽  
Laurent Labeyrie ◽  
Maurice Arnold ◽  
Monique Labracherie ◽  
Jean-Jacques Pichon ◽  
...  
Keyword(s):  
Southern Ocean ◽  
Sedimentation Rate ◽  
Deep Sea ◽  
Sediment Cores ◽  
Sea Surface ◽  
Sedimentation Rates ◽  
Deep Sea Sediment ◽  
The Difference ◽  
The Last Glacial Maximum ◽  
The Last Glacial

Abstract14C dates obtained by accelerator mass spectrometry (AMS) on monospecific foraminiferal samples from two deep-sea sediment cores raised in the Indian sector of the Southern Ocean have been corrected for the difference in 14C composition between atmosphere and sea surface by using a reconstruction of the latitudinal 14C gradient which existed in the Southern Ocean prior to 1962. The corrected AMS-14C data show a reduced sedimentation rate in core MD 84-527 between 25,000 and 10,000 yr BP. For core MD 84-551 the available data suggest that the sedimentation rate was higher during the Holocene than during the glacial period. These changes in sedimentation rates may be attributed to an increased opal dissolution during the last glacial maximum.

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