TY - JOUR

T1 - Steric sea-level fluctuations from remote sensing, oceanic reanalyses and objective analyses in the North Atlantic

AU - Koldunov, Aleksey

AU - Fedorov, Aleksandr

AU - Bashmachnikov, Igor

AU - Belonenko, Tatyana

N1 - Funding Information: support of the Russian Science Foundation (RSF, project No. 18-17-00027). Publisher Copyright: © Copyright 2020 by the Geophysical Center RAS. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.

PY - 2020/5

Y1 - 2020/5

N2 - Five data sets were used to estimate steric level fluctuations in the North Atlantic for 2003-2015. We compare estimates made by a combination of altimetry and GRACE gravity data (ALT-GRV) with assessments obtained from vertical density profiles derived from SODA reanalysis, ARMOR, and EN4 objective analyses. We analyze the datasets without linear trends, and the seasonal signals are also removed. The resulting signals demonstrate the steric sea-level anomalies not related to the linear trends and the seasonal cycles and can be connected with short-period intra-annual variability as well as vortex dynamics of the region since mesoscale eddies can transfer heat and salt and influence thereby the thermohaline water structure from the sea surface to the depth. The deep convection, as well as meandering of the currents also influences the variability of residual time series. The steric sea-level fluctuations, obtained from the ARMOR dataset, which incorporates results of satellite observations, shows the best fit for those, derived from ALT-GRV data. The correlation coefficient between ARMOR and ALT-GRV varies between 0.6 and 0.8 over the study region (0.7 on average). Steric sea-level variations derived from SODA or EN4 show good matches with ALT-GRV only for the steric sea-level fluctuations spatially averaged over central regions of the North Atlantic. The discrepancies between the data sets increase northwards and towards the coast. Of the considered data sets, ARMOR is the most suitable for climate studies and research of the sea-level change effects; however, it should be used with caution in the study of the spatial distribution of the steric level.

AB - Five data sets were used to estimate steric level fluctuations in the North Atlantic for 2003-2015. We compare estimates made by a combination of altimetry and GRACE gravity data (ALT-GRV) with assessments obtained from vertical density profiles derived from SODA reanalysis, ARMOR, and EN4 objective analyses. We analyze the datasets without linear trends, and the seasonal signals are also removed. The resulting signals demonstrate the steric sea-level anomalies not related to the linear trends and the seasonal cycles and can be connected with short-period intra-annual variability as well as vortex dynamics of the region since mesoscale eddies can transfer heat and salt and influence thereby the thermohaline water structure from the sea surface to the depth. The deep convection, as well as meandering of the currents also influences the variability of residual time series. The steric sea-level fluctuations, obtained from the ARMOR dataset, which incorporates results of satellite observations, shows the best fit for those, derived from ALT-GRV data. The correlation coefficient between ARMOR and ALT-GRV varies between 0.6 and 0.8 over the study region (0.7 on average). Steric sea-level variations derived from SODA or EN4 show good matches with ALT-GRV only for the steric sea-level fluctuations spatially averaged over central regions of the North Atlantic. The discrepancies between the data sets increase northwards and towards the coast. Of the considered data sets, ARMOR is the most suitable for climate studies and research of the sea-level change effects; however, it should be used with caution in the study of the spatial distribution of the steric level.

KW - North Atlantic

KW - Remote sensing

KW - Sea-level

KW - SATELLITE ALTIMETRY

KW - CIRCULATION

KW - PERFORMANCE

KW - CONVECTION

KW - remote sensing

KW - TRENDS

KW - VARIABILITY

KW - TEMPERATURE

KW - GRACE

KW - SALINITY

KW - LABRADOR

UR - http://www.scopus.com/inward/record.url?scp=85092271710&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/6f82071b-2efb-374e-aa30-b4cf14d4cf32/

U2 - 10.2205/2020ES000702

DO - 10.2205/2020ES000702

M3 - Article

AN - SCOPUS:85092271710

VL - 20

JO - Russian Journal of Earth Sciences

JF - Russian Journal of Earth Sciences

SN - 1681-1178

IS - 3

M1 - ES3003

ER -