Ocean Response to Super-Typhoon Haiyan

Water ◽  
2021 ◽  
Vol 13 (20) ◽  
pp. 2841
Author(s):  
Tolulope Emmanuel Oginni ◽  
Shuang Li ◽  
Hailun He ◽  
Hongwei Yang ◽  
Zheng Ling
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Surface Wind ◽  
Vertical Mixing ◽  
Sea Surface ◽  
Ocean Reanalysis ◽  
Argo Float ◽  
Super Typhoon ◽  
Ocean Response ◽  
Daily Sampling

Present paper studies the ocean response to super-typhoon Haiyan based on satellite and Argo float data. First, we show the satellite-based surface wind and sea surface temperature during super-typhoon Haiyan, and evaluate the widely-used atmospheric and oceanic analysis-or-reanalysis datasets. Second, we investigate the signals of Argo float, and find the daily-sampling Argo floats capture the phenomena of both vertical-mixing-induced mixed-layer extension and nonlocal subsurface upwelling. Accordingly, the comparisons between Argo float and ocean reanalysis reveal that, the typhoon-induced upwelling in the ocean reanalysis needs to be further improved, meanwhile, the salinity profiles prior to typhoon arrival are significantly biased.

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.

scholarly journals Controlling atmospheric forcing parameters of global ocean models: sequential assimilation of sea surface Mercator-Ocean reanalysis data

Ocean Science ◽  
2009 ◽  
Vol 5 (4) ◽  
pp. 403-419 ◽  
Author(s):  
C. Skandrani ◽  
J.-M. Brankart ◽  
N. Ferry ◽  
J. Verron ◽  
P. Brasseur ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Reanalysis Data ◽  
Ocean Model ◽  
Sea Surface ◽  
Global Ocean ◽  
Atmospheric Forcing ◽  
Ocean Reanalysis ◽  
Ocean Reanalysis Data

Abstract. In the context of stand alone ocean models, the atmospheric forcing is generally computed using atmospheric parameters that are derived from atmospheric reanalysis data and/or satellite products. With such a forcing, the sea surface temperature that is simulated by the ocean model is usually significantly less accurate than the synoptic maps that can be obtained from the satellite observations. This not only penalizes the realism of the ocean long-term simulations, but also the accuracy of the reanalyses or the usefulness of the short-term operational forecasts (which are key GODAE and MERSEA objectives). In order to improve the situation, partly resulting from inaccuracies in the atmospheric forcing parameters, the purpose of this paper is to investigate a way of further adjusting the state of the atmosphere (within appropriate error bars), so that an explicit ocean model can produce a sea surface temperature that better fits the available observations. This is done by performing idealized assimilation experiments in which Mercator-Ocean reanalysis data are considered as a reference simulation describing the true state of the ocean. Synthetic observation datasets for sea surface temperature and salinity are extracted from the reanalysis to be assimilated in a low resolution global ocean model. The results of these experiments show that it is possible to compute piecewise constant parameter corrections, with predefined amplitude limitations, so that long-term free model simulations become much closer to the reanalysis data, with misfit variance typically divided by a factor 3. These results are obtained by applying a Monte Carlo method to simulate the joint parameter/state prior probability distribution. A truncated Gaussian assumption is used to avoid the most extreme and non-physical parameter corrections. The general lesson of our experiments is indeed that a careful specification of the prior information on the parameters and on their associated uncertainties is a key element in the computation of realistic parameter estimates, especially if the system is affected by other potential sources of model errors.

scholarly journals Observations of Coupling between Surface Wind Stress and Sea Surface Temperature in the Eastern Tropical Pacific

2001 ◽  
Vol 14 (7) ◽  
pp. 1479-1498 ◽  
Author(s):  
Dudley B. Chelton ◽  
Steven K. Esbensen ◽  
Michael G. Schlax ◽  
Nicolai Thum ◽  
Michael H. Freilich ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Stress ◽  
Surface Wind ◽  
Tropical Pacific ◽  
Sea Surface ◽  
Eastern Tropical Pacific ◽  
Surface Wind Stress

scholarly journals Latent Heat Flux Sensitivity to Sea Surface Temperature: Regional Perspectives

2017 ◽  
Vol 30 (1) ◽  
pp. 129-143 ◽  
Author(s):  
B. Praveen Kumar ◽  
Meghan F. Cronin ◽  
Sudheer Joseph ◽  
M. Ravichandran ◽  
N. Sureshkumar
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Global Analysis ◽  
Surface Wind ◽  
Sea Surface ◽  
State Variables ◽  
Monsoon Period

A global analysis of latent heat flux (LHF) sensitivity to sea surface temperature (SST) is performed, with focus on the tropics and the north Indian Ocean (NIO). Sensitivity of LHF state variables (surface wind speed Ws and vertical humidity gradients Δq) to SST give rise to mutually interacting dynamical (Ws driven) and thermodynamical (Δq driven) coupled feedbacks. Generally, LHF sensitivity to SST is pronounced over tropics where SST increase causes Ws (Δq) changes, resulting in a maximum decrease (increase) of LHF by ~15 W m−2 (°C)−1. But the Bay of Bengal (BoB) and north Arabian Sea (NAS) remain an exception that is opposite to the global feedback relationship. This uniqueness is attributed to strong seasonality in monsoon Ws and Δq variations, which brings in warm (cold) continental air mass into the BoB and NAS during summer (winter), producing a large seasonal cycle in air–sea temperature difference ΔT (and hence in Δq). In other tropical oceans, surface air is mostly of marine origin and blows from colder to warmer waters, resulting in a constant ΔT ~ 1°C throughout the year, and hence a constant Δq. Thus, unlike other basins, when the BoB and NAS are warming, air temperature warms faster than SST. The resultant decrease in ΔT and Δq contributes to decrease the LHF with increased SST, contrary to other basins. This analysis suggests that, in the NIO, LHF variability is largely controlled by thermodynamic processes, which peak during the monsoon period. These observed LHF sensitivities are then used to speculate how the surface energetics and coupled feedbacks may change in a warmer world.

scholarly journals An empirical stochastic model of sea-surface temperature and surface wind over the Southern Ocean

2011 ◽  
Vol 8 (4) ◽  
pp. 1891-1936
Author(s):  
S. Kravtsov ◽  
D. Kondrashov ◽  
I. Kamenkovich ◽  
M. Ghil
Keyword(s):  
Southern Ocean ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Singular Spectrum Analysis ◽  
Surface Wind ◽  
Preliminary Evidence ◽  
Sea Surface ◽  
Satellite Measurements ◽  
Synoptic Variability ◽  
Ocean Region

Abstract. This study employs NASA's recent satellite measurements of sea-surface temperature (SST) and sea-level wind (SLW) with missing data filled-in by Singular Spectrum Analysis (SSA), to construct empirical models that capture both intrinsic and SST-dependent aspects of SLW variability. The model construction methodology uses a number of algorithmic innovations that are essential in providing stable estimates of model's propagator. The best model tested herein is able to faithfully represent the time scales and spatial patterns of anomalies associated with a number of distinct processes. These processes range from the daily synoptic variability to interannual signals presumably associated with oceanic or coupled dynamics. Comparing the simulations of an SLW model forced by the observed SST anomalies with the simulations of an SLW-only model provides preliminary evidence for the climatic behavior characterized by the ocean driving the atmosphere in the Southern Ocean region.

scholarly journals Sea surface temperature changes due to polar lows over the Nordic Seas

2020 ◽  
Vol 65 (4) ◽  
Author(s):  
Pavel A. Golubkin ◽  
◽  
Julia E. Smirnova ◽  
Vsevolod S. Kolyada ◽  
◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Microwave Radiometer ◽  
Surface Wind ◽  
Sea Surface ◽  
Polar Lows ◽  
Wind Speeds ◽  
Sea Surface Wind ◽  
Polar Low ◽  
Upper Mixed Layer

In this study possible changes in sea surface temperature (SST) caused by passage of polar lows and analyzed. Polar lows are extreme atmospheric phenomena inherent to high latitudes. They develop sea surface wind speeds from 15 m/s up to hurricane force values and are characterized by small sizes (on average, 300 km) and lifetimes (less than two days), which complicates their detection and studies. It is assumed that as in case of tropical cyclones, which may considerably lower SST due to intense mixing and entrainment of colder waters to the ocean upper mixed layer, polar lows could similarly influence SST. Moreover, in the high latitude areas, where salt stratification may be present instead of temperature stratification, SST may increase due to mixing with deeper warmer layer. In this study 330 polar lows were analyzed using satellite passive microwave radiometer measurements of SST. In result, 47 cases when average SST values changed in polar low forcing areas were found. Out of these cases, in six cases SST increase of at least 0.5 °С was found, and in fifteen cases SST decrease of at least 0.5 °С was found. This indicates that upper ocean response to polar lows is quite rare phenomenon, which should be further analyzed along with its possible role in the ocean-ice-atmosphere system.

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