Inference of Sea Surface Temperature, Near Surface Wind, and Atmospheric Water by Fourier Analysis of Scanning Multichannel Microwave Radiometer Data

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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A Comparative Assessment of Surface Wind Speed and Sea Surface Temperature over the Indian Ocean by TMI, MSMR, and ERA-40

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech2021.1 ◽

2007 ◽

Vol 24 (6) ◽

pp. 1131-1142 ◽

Cited By ~ 23

Author(s):

Anant Parekh ◽

Rashmi Sharma ◽

Abhijit Sarkar

Keyword(s):

Wind Speed ◽

Indian Ocean ◽

Surface Temperature ◽

Sea Surface Temperature ◽

Microwave Radiometer ◽

Surface Wind ◽

Surface Wind Speed ◽

Sea Surface ◽

Wind Speeds ◽

Low Wind Speeds

A 2-yr (June 1999–June 2001) observation of ocean surface wind speed (SWS) and sea surface temperature (SST) derived from microwave radiometer measurements made by a multifrequency scanning microwave radiometer (MSMR) and the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) is compared with direct measurements by Indian Ocean buoys. Also, for the first time SWS and SST values of the same period obtained from 40-yr ECMWF Re-Analysis (ERA-40) have been evaluated with these buoy observations. The SWS and SST are shown to have standard deviations of 1.77 m s−1 and 0.60 K for TMI, 2.30 m s−1 and 2.0 K for MSMR, and 2.59 m s−1 and 0.68 K for ERA-40, respectively. Despite the fact that MSMR has a lower-frequency channel, larger values of bias and standard deviation (STD) are found compared to those of TMI. The performance of SST retrieval during the daytime is found to be better than that at nighttime. The analysis carried out for different seasons has raised an important question as to why one spaceborne instrument (TMI) yields retrievals with similar biases during both pre- and postmonsoon periods and the other (MSMR) yields drastically different results. The large bias at low wind speeds is believed to be due to the poorer sensitivity of microwave emissivity variations at low wind speeds. The extreme SWS case study (cyclonic condition) showed that satellite-retrieved SWS captured the trend and absolute magnitudes as reflected by in situ observations, while the model (ERA-40) failed to do so. This result has direct implications on the real-time application of satellite winds in monitoring extreme weather events.

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On the changes in the sea surface temperature in the benguela upwelling region. Part 2: the long-term tendencies

Исследования Земли из космоса ◽

10.31857/s0205-96142019429-39 ◽

2019 ◽

pp. 29-39 ◽

Cited By ~ 2

Author(s):

A. B. Polonsky ◽

A. N. Serebrennikov

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Wind Field ◽

Surface Wind ◽

Field Structure ◽

Sea Surface ◽

Near Surface ◽

Tangential Wind ◽

Benguela Upwelling

The paper examines the issue on the long-term trends in the sea surface temperature (SST) in the Benguela upwelling zone and their causes using the daily SST satellite data for 1985–2017’s and the daily near-surface wind for 1988–2017”s. It is shown that in the Benguela upwelling region, there is a significant intensification of driving winds in the last 20 yrs. This is accompanied by a decrease of the thermal upwelling index (taking into account the sign of the index or an increase of its absolute values) in the southern part of the Benguela upwelling, but practically does not influence this indicator in its northern part. The likely reason for this difference is the change in the wind field structure, as a result of which there are opposite trends in the magnitude of the vorticity of the tangential wind stress in different parts of the Benguela upwelling. In the southern part of the Benguela upwelling, both the Ekman’s upwelling and the vertical velocities due to the vorticity of the driving wind intensify, while in the northern part the corresponding trends have the opposite signs. This leads to a partial compensation of these two effects in the northern part of the Benguela upwelling. The reason for the change in the wind field structure is the displacement of the center of the Subtropical High to the south-east and the concomitant reversal of the near-surface wind vector in the coastal zone.

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Variability of Diurnal Sea Surface Temperature during Short Term and High SST Event in the Western Equatorial Pacific as Revealed by Satellite Data

Remote Sensing ◽

10.3390/rs12193230 ◽

2020 ◽

Vol 12 (19) ◽

pp. 3230

Author(s):

Anindya Wirasatriya ◽

Kohtaro Hosoda ◽

Joga Dharma Setiawan ◽

R. Dwi Susanto

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Surface Wind ◽

Equatorial Pacific ◽

Western Pacific ◽

Sea Surface ◽

Occurrence Rate ◽

Near Surface ◽

Western Equatorial Pacific ◽

The Western Pacific

Near-surface diurnal warming is an important process in the climate system, driving exchanges of water vapor and heat between the ocean and the atmosphere. The occurrence of the hot event (HE) is associated with the high diurnal sea surface temperature amplitude (δSST), which is defined as the difference between daily maximum and minimum sea surface temperature (SST). However, previous studies still show some inconsistency for the area of HE occurrence and high δSST. The present study produces global δSST data based on the SST, sea surface wind data derived from microwave radiometers, and solar radiation data obtained from visible/infrared radiometers. The value of δSSTs are estimated and validated over tropical oceans and then used for investigating HE in the western equatorial Pacific. A three-way error analysis was conducted using in situ mooring buoy arrays and geostationary SST measurements by the Himawari-8 and Geostationary Operational Environmental Satellite (GOES). The standard deviation error of daily and 10-day validation is around 0.3 °C and 0.14–0.19 °C, respectively. Our case study in the western Pacific (from 110°E to 150°W) shows that the area of HE occurrence coincided well with the area of high δSST. Climatological analysis shows that the collocated area between high occurrence rate of HE and high δSST, which coincides with the western Pacific warm pool region in all seasons. Thus, this study provides more persuasive evidence of the relation between HE occurrence and high δSST.

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Case Studies of Tropical Cyclones and Phytoplankton Blooms over Atlantic and Pacific Regions

Earth Interactions ◽

10.1175/2013ei000517.1 ◽

2013 ◽

Vol 17 (17) ◽

pp. 1-19 ◽

Cited By ~ 8

Author(s):

Ashley M. Merritt-Takeuchi ◽

Sen Chiao

Keyword(s):

Surface Temperature ◽

Sea Surface Temperature ◽

Case Studies ◽

Tropical Cyclones ◽

Surface Wind ◽

Ocean Basin ◽

Sea Surface ◽

Phytoplankton Blooms ◽

Near Surface ◽

Chl A

Abstract This study investigates phytoplankton blooms following the passage of tropical cyclones in the Atlantic and Pacific Ocean basins. The variables of sea surface temperature (SST), chlorophyll (Chl-a), precipitation, and storm surface winds were monitored for two case studies, Typhoon Xangsane (2006) and Hurricane Earl (2010). Strong near-surface wind from tropical cyclones creates internal friction, which causes deep nutrient enriched waters to displace from the bottom of the ocean floor up toward the surface. In return, the abundance of upwelled nutrients near the surface provides an ideal environment for the growth of biological substances such as chlorophyll and phytoplankton. The inverse correlation coefficients of SST and Chl-a for this study are −0.67 and −0.26 for Xangsane and Earl, respectively. This suggests that, regardless of ocean basin, changing sea surface temperature and chlorophyll concentrations can be correlated to various characteristics of tropical cyclones including precipitation and surface wind, which in combination results in an increase of phytoplankton.

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

Annales Geophysicae ◽

10.5194/angeo-29-393-2011 ◽

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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