scholarly journals Performance of long-chain mid-chan diol based temperature and productivity proxies at test: a five-years sediment trap record from the Mauritanian upwelling

2021 ◽  
Author(s):  
Gerard J. M. Versteegh ◽  
Karin A. F. Zonneveld ◽  
Jens Hefter ◽  
Oscar E. Romero ◽  
Gerhard Fischer ◽  
...  
Keyword(s):  
Wind Speed ◽  
Sediment Trap ◽  
Saturation Index ◽  
Sea Surface ◽  
Nutrient Concentrations ◽  
Upper Ocean ◽  
Trap Site ◽  
Trap Location ◽  
Upwelling Intensity ◽  
Long Chain

Abstract. Long-chain mid-chain diol (shortly diol) based proxies obtain increasing interest to reconstruct past upper ocean temperature and productivity. Here we evaluate performance of the sea surface temperature proxies; long chain diol index (LDI), the diol saturation index (DSI) and the diol chain-length index (DCI), productivity/upwelling intensity proxies: the two diol indices DIR (Rampen et al., 2008) and DIW (Willmott et al., 2010) and the combined diol index (CDI), as well as the nutrient diol index (NDI) as proxy for phosphate and nitrate levels. This evaluation is based on comparison of the diols in sediment trap samples from the upwelling region off NW Africa collected at 1.28 km water depth with daily satellite derived sea surface temperatures (SSTSAT), subsurface temperatures, productivity, the plankton composition from the trap location, monthly PO43− and NO3− concentrations, wind speed and wind direction from the nearby Nouadhibou airport. The diol based SST reconstructions are also compared the long chain alkenones based UK’37 proxy reconstructions (SSTUK). At the trap site, most diol proxies lag wind speed (phase φ = 30 days) and can be related to upwelling. Correlation with the abundance of upwelling species and wind speed is best for the DCI, DSI and NDI whereas the DI and CDI perform comparatively poorly. The nutrient proxy NDI shows no significant correlation to monthly PO43− and NO3− concentrations in the upper waters and a negative correlation with wind-induced upwelling (r2 = 0.28, φ = 32 days) as well as the abundance of upwelling species (r2 = 0.38; Table 4). It is suggested that this proxy reflects upwelling intensity rather than upper ocean nutrient concentrations. At the trap site, SSTSAT lags wind speed forced upwelling by about 4 months (φ = 129 d). The LDI based SST (SSTLDI) correlate poorly (r2 = 0.17) to SSTSAT which we attribute to variability in 1,13 diol abundance unrelated to SST such as productivity. The SSTUK correlates best with SSTSAT (r2 = 0.60). Also amplitude and absolute values agree very well and the flux corrected SSTUK time series average equals the SSTSAT annual average.

scholarly journals Relation between Upwelling Intensity and the Variability of Physical and Chemical Parameters in the Southern Benguela Upwelling System

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Hassan Ebrahiem Ismail ◽  
Johannes Jacobus Agenbag ◽  
Stephanie de Villiers ◽  
Bhekumusa Jabulani Ximba
Keyword(s):  
Temperature Gradient ◽  
Vertical Mixing ◽  
Surface Heating ◽  
Nutrient Concentrations ◽  
Upper Ocean ◽  
Ocean Temperature ◽  
Upwelling System ◽  
Benguela Upwelling ◽  
Upwelling Intensity ◽  
Upwelling Index

The extent to which wind-driven seasonal upwelling cycles manifest in surface ocean temperature and nutrient variability along a monitoring line in the Southern Benguela upwelling system was investigated. Monitoring conducted monthly over a six-year period shows that surface temperature and nutrient concentrations exhibit very poor seasonality and weak correlation with the upwelling index. This is, despite clear evidence for spatial inshore-offshore gradients in temperature, nutrients, and chlorophyll, consistent with an upwelling regime. The upper ocean temperature gradient shows a much better correspondence to the upwelling index but at the same time demonstrates that surface heating, and not vertical mixing related to upwelling, controls the upper ocean temperature gradient. The results suggest that remote sensing techniques would be inadequate tools to monitor upwelling events in the Southern Benguela. Also, the incidence of phytoplankton blooms is more likely triggered by stratified conditions associated with surface heating than relaxation of upwelling winds.

scholarly journals Measurement of the Sea Surface Height with Airborne GNSS Reflectometry and Delay Bias Calibration

2021 ◽  
Vol 13 (15) ◽  
pp. 3014
Author(s):  
Feng Wang ◽  
Dongkai Yang ◽  
Guodong Zhang ◽  
Jin Xing ◽  
Bo Zhang ◽  
...  
Keyword(s):  
Wind Speed ◽  
Arrival Time ◽  
Elevation Angle ◽  
Satellite System ◽  
Sea Surface Height ◽  
Antenna Pattern ◽  
Sea Surface ◽  
Observation Method ◽  
Global Navigation Satellite ◽  
The Impact

Sea surface height can be measured with the delay between reflected and direct global navigation satellite system (GNSS) signals. The arrival time of a feature point, such as the waveform peak, the peak of the derivative waveform, and the fraction of the peak waveform is not the true arrival time of the specular signal; there is a bias between them. This paper aims to analyze and calibrate the bias to improve the accuracy of sea surface height measured by using the reflected signals of GPS CA, Galileo E1b and BeiDou B1I. First, the influencing factors of the delay bias, including the elevation angle, receiver height, wind speed, pseudorandom noise (PRN) code of GPS CA, Galileo E1b and BeiDou B1I, and the down-looking antenna pattern are explored based on the Z-V model. The results show that (1) with increasing elevation angle, receiver height, and wind speed, the delay bias tends to decrease; (2) the impact of the PRN code is uncoupled from the elevation angle, receiver height, and wind speed, so the delay biases of Galileo E1b and BeiDou B1I can be derived from that of GPS CA by multiplication by the constants 0.32 and 0.54, respectively; and (3) the influence of the down-looking antenna pattern on the delay bias is lower than 1 m, which is less than that of other factors; hence, the effect of the down-looking antenna pattern is ignored in this paper. Second, an analytical model and a neural network are proposed based on the assumption that the influence of all factors on the delay bias are uncoupled and coupled, respectively, to calibrate the delay bias. The results of the simulation and experiment show that compared to the meter-level bias before the calibration, the calibrated bias decreases the decimeter level. Based on the fact that the specular points of several satellites are visible to the down-looking antenna, the multi-observation method is proposed to calibrate the bias for the case of unknown wind speed, and the same calibration results can be obtained when the proper combination of satellites is selected.

scholarly journals A Novel Sea Surface Roughness Parameterization Based on Wave State and Sea Foam

2021 ◽  
Vol 9 (3) ◽  
pp. 246
Author(s):  
Difu Sun ◽  
Junqiang Song ◽  
Xiaoyong Li ◽  
Kaijun Ren ◽  
Hongze Leng
Keyword(s):  
Surface Roughness ◽  
Wind Speed ◽  
Drag Coefficient ◽  
Sea Surface ◽  
High Wind Speed ◽  
Wave State ◽  
Wind Speeds ◽  
Sea Surface Roughness ◽  
Extreme Wind ◽  
The Impact

A wave state related sea surface roughness parameterization scheme that takes into account the impact of sea foam is proposed in this study. Using eight observational datasets, the performances of two most widely used wave state related parameterizations are examined under various wave conditions. Based on the different performances of two wave state related parameterizations under different wave state, and by introducing the effect of sea foam, a new sea surface roughness parameterization suitable for low to extreme wind conditions is proposed. The behaviors of drag coefficient predicted by the proposed parameterization match the field and laboratory measurements well. It is shown that the drag coefficient increases with the increasing wind speed under low and moderate wind speed conditions, and then decreases with increasing wind speed, due to the effect of sea foam under high wind speed conditions. The maximum values of the drag coefficient are reached when the 10 m wind speeds are in the range of 30–35 m/s.

Modeling the Atmospheric Boundary Layer Wind Response to Mesoscale Sea Surface Temperature Perturbations

2014 ◽  
Vol 142 (11) ◽  
pp. 4284-4307 ◽  
Author(s):  
Natalie Perlin ◽  
Simon P. de Szoeke ◽  
Dudley B. Chelton ◽  
Roger M. Samelson ◽  
Eric D. Skyllingstad ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Coupling Coefficient ◽  
Eddy Viscosity ◽  
Sea Surface ◽  
Coupling Coefficients ◽  
Wind Response ◽  
Speed Response

Abstract The wind speed response to mesoscale SST variability is investigated over the Agulhas Return Current region of the Southern Ocean using the Weather Research and Forecasting (WRF) Model and the U.S. Navy Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model. The SST-induced wind response is assessed from eight simulations with different subgrid-scale vertical mixing parameterizations, validated using Quick Scatterometer (QuikSCAT) winds and satellite-based sea surface temperature (SST) observations on 0.25° grids. The satellite data produce a coupling coefficient of sU = 0.42 m s−1 °C−1 for wind to mesoscale SST perturbations. The eight model configurations produce coupling coefficients varying from 0.31 to 0.56 m s−1 °C−1. Most closely matching QuikSCAT are a WRF simulation with the Grenier–Bretherton–McCaa (GBM) boundary layer mixing scheme (sU = 0.40 m s−1 °C−1), and a COAMPS simulation with a form of Mellor–Yamada parameterization (sU = 0.38 m s−1 °C−1). Model rankings based on coupling coefficients for wind stress, or for curl and divergence of vector winds and wind stress, are similar to that based on sU. In all simulations, the atmospheric potential temperature response to local SST variations decreases gradually with height throughout the boundary layer (0–1.5 km). In contrast, the wind speed response to local SST perturbations decreases rapidly with height to near zero at 150–300 m. The simulated wind speed coupling coefficient is found to correlate well with the height-averaged turbulent eddy viscosity coefficient. The details of the vertical structure of the eddy viscosity depend on both the absolute magnitude of local SST perturbations, and the orientation of the surface wind to the SST gradient.

scholarly journals Surface signature of Mediterranean water eddies in the Northeastern Atlantic: effect of the upper ocean stratification

Ocean Science ◽  
2012 ◽  
Vol 8 (6) ◽  
pp. 931-943 ◽  
Author(s):  
I. Bashmachnikov ◽  
X. Carton
Keyword(s):  
Potential Vorticity ◽  
Initial Period ◽  
Relative Vorticity ◽  
Sea Surface ◽  
Upper Ocean ◽  
Buoyancy Frequency ◽  
Coriolis Parameter ◽  
Ocean Stratification ◽  
Surface Signature ◽  
Mediterranean Water

Abstract. Meddies, intra-thermocline eddies of Mediterranean water, can often be detected at the sea surface as positive sea-level anomalies. Here we study the surface signature of several meddies tracked with RAFOS floats and AVISO altimetry. While pushing its way through the water column, a meddy raises isopycnals above. As a consequence of potential vorticity conservation, negative relative vorticity is generated in the upper layer. During the initial period of meddy acceleration after meddy formation or after a stagnation stage, a cyclonic signal is also generated at the sea-surface, but mostly the anticyclonic surface signal follows the meddy. Based on geostrophy and potential vorticity balance, we present theoretical estimates of the intensity of the surface signature. It appears to be proportional to the meddy core radius and to the Coriolis parameter, and inversely proportional to the core depth and buoyancy frequency. This indicates that surface signature of a meddy may be strongly reduced by the upper ocean stratification. Using climatic distribution of the stratification intensity, we claim that the southernmost limit for detection in altimetry of small meddies (with radii on the order of 10–15 km) should lie in the subtropics (35–45° N), while large meddies (with radii of 25–30 km) could be detected as far south as the northern tropics (25–35° N). Those results agree with observations.

scholarly journals Sea surface wind perturbations over the Kashevarov Bank of the Okhotsk Sea: a satellite study

2011 ◽  
Vol 29 (2) ◽  
pp. 393-399
Author(s):  
T. I. Tarkhova ◽  
M. S. Permyakov ◽  
E. Yu. Potalova ◽  
V. I. Semykin
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Wind ◽  
Sea Surface ◽  
Cold Spot ◽  
Okhotsk Sea ◽  
Autumn Period ◽  
Sea Surface Wind ◽  
Spot Center

Abstract. Sea surface wind perturbations over sea surface temperature (SST) cold anomalies over the Kashevarov Bank (KB) of the Okhotsk Sea are analyzed using satellite (AMSR-E and QuikSCAT) data during the summer-autumn period of 2006–2009. It is shown, that frequency of cases of wind speed decreasing over a cold spot in August–September reaches up to 67%. In the cold spot center SST cold anomalies reached 10.5 °C and wind speed lowered down to ~7 m s−1 relative its value on the periphery. The wind difference between a periphery and a centre of the cold spot is proportional to SST difference with the correlations 0.5 for daily satellite passes data, 0.66 for 3-day mean data and 0.9 for monthly ones. For all types of data the coefficient of proportionality consists of ~0.3 m s−1 on 1 °C.

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