scholarly journals The Current Configuration of the OSTIA System for Operational Production of Foundation Sea Surface Temperature and Ice Concentration Analyses

2020 ◽  
Vol 12 (4) ◽  
pp. 720 ◽  
Author(s):  
Simon Good ◽  
Emma Fiedler ◽  
Chongyuan Mao ◽  
Matthew J. Martin ◽  
Adam Maycock ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Current System ◽  
Weather Prediction ◽  
Technical Note ◽  
Sea Surface ◽  
Full Description ◽  
Current Configuration ◽  
Ice Concentration ◽  
Marine Environment Monitoring

The Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) system generates global, daily, gap-filled foundation sea surface temperature (SST) fields from satellite data and in situ observations. The SSTs have uncertainty information provided with them and an ice concentration (IC) analysis is also produced. Additionally, a global, hourly diurnal skin SST product is output each day. The system is run in near real time to produce data for use in applications such as numerical weather prediction. Data production is monitored routinely and outputs are available from the Copernicus Marine Environment Monitoring Service (CMEMS; marine.copernicus.eu). As an operational product, the OSTIA system is continuously under development. For example, since the original descriptor paper was published, the underlying data assimilation scheme that is used to generate the foundation SST analyses has been updated. Various publications have described these changes but a full description is not available in a single place. This technical note focuses on the production of the foundation SST and IC analyses by OSTIA and aims to provide a comprehensive description of the current system configuration.

scholarly journals Assessing bias corrections of oceanic surface conditions for atmospheric models

2019 ◽  
Vol 12 (1) ◽  
pp. 321-342 ◽  
Author(s):  
Julien Beaumet ◽  
Gerhard Krinner ◽  
Michel Déqué ◽  
Rein Haarsma ◽  
Laurent Li
Keyword(s):  
Sea Ice ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
General Circulation ◽  
General Circulation Models ◽  
Substantial Improvement ◽  
Sea Surface ◽  
Sea Ice Concentration ◽  
Ice Concentration ◽  
Analogue Method

Abstract. Future sea surface temperature and sea-ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcings for the downscaling of future climate experiments. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly method and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea-ice concentration (SIC) are presented. For SIC, we also propose a new analogue method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiments and some real-case applications using observations. We find that with respect to other previously existing methods, the analogue method is a substantial improvement for the bias correction of future SIC. Consistency between the constructed SST and SIC fields is an important constraint to consider, as is consistency between the prescribed sea-ice concentration and thickness; we show that the latter can be ensured by using a simple parameterisation of sea-ice thickness as a function of instantaneous and annual minimum SIC.

scholarly journals Can we use sea surface temperature and productivity proxy records to reconstruct Ekman upwelling?

2019 ◽  
Vol 15 (6) ◽  
pp. 1985-1998
Author(s):  
Anson Cheung ◽  
Baylor Fox-Kemper ◽  
Timothy Herbert
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Large Scale ◽  
Current System ◽  
California Current ◽  
Sea Surface ◽  
California Current System ◽  
Proxy Records ◽  
Multiple Variables ◽  
Ekman Upwelling

Abstract. Marine sediments have greatly improved our understanding of the climate system, but their interpretation often assumes that certain climate mechanisms operate consistently over all timescales of interest and that variability at one or a few sample sites is representative of an oceanographic province. In this study, we test these assumptions using modern observations in an idealized manner mimicking paleo-reconstruction to investigate whether sea surface temperature and productivity proxy records in the Southern California Current System can be used to reconstruct Ekman upwelling. The method uses extended empirical orthogonal function (EEOF) analysis of the covariation of alongshore wind stress, chlorophyll, and sea surface temperature as measured by satellites from 2002 to 2009. We find that EEOF1 does not reflect an Ekman upwelling pattern but instead much broader California Current processes. EEOF2 and 3 reflect upwelling patterns, but these patterns are timescale dependent and regional. Thus, the skill of using one site to reconstruct the large-scale dominant patterns is spatially dependent. Lastly, we show that using multiple sites and/or multiple variables generally improves field reconstruction. These results together suggest that caution is needed when attempting to extrapolate mechanisms that may be important on seasonal timescales (e.g., Ekman upwelling) to deeper time but also the advantage of having multiple proxy records.

scholarly journals Sea Surface Temperature and Wind Stress Curl Variability near a Cape

2012 ◽  
Vol 42 (11) ◽  
pp. 2073-2087 ◽  
Author(s):  
Renato M. Castelao
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Wind Stress ◽  
Current System ◽  
Empirical Orthogonal Functions ◽  
Sea Surface ◽  
Western Boundary ◽  
Surface Cooling ◽  
Wind Stress Curl ◽  
California Current System

Abstract The coupling between sea surface temperature (SST), SST gradients, and wind stress curl variability near a cape off Brazil is investigated using satellite observations and several different SST high-resolution analyses. The cape is characterized by strong SST fronts year-round, associated with upwelling and advection of warm water offshore in a western boundary current. Observations reveal a strong coupling between crosswind SST gradients and wind stress curl variability, with the predominantly negative crosswind gradients leading to negative, upwelling favorable wind stress curl anomalies. The spatial correlation between empirical orthogonal functions (EOF) of those variables is ~0.6, while the correlation between the EOF amplitude time series of the wind stress curl and crosswind SST gradients is larger than 0.7. The coupling occurs during summer and winter and is strongly modulated by variations in the wind stress directional steadiness. The intensity of the coupling is weaker than around capes on the California Current system, presumably because of higher variability in wind direction off Brazil. During periods of high wind stress directional steadiness off Cape Frio, the coupling is intensified by up to 40%–75%. Wind stress curl is also correlated with SST itself, especially in the vicinity of the cape, although not as strongly as with crosswind SST gradients. The analyses suggest that the observed wind stress curl anomalies can lead to surface cooling of as much as 1°C. If the enhanced upwelling leads to further strengthening of the upwelling front, negative wind stress curl anomalies may be intensified in a positive feedback mechanism.

scholarly journals Effects of El-Niño, Indian Ocean Dipole and Madden-Julian Oscillation on Sea Surface Temperature and Rainfall Anomalies in Southeast Asia. Case Study: Biomass Burning Episode of 2015

2018 ◽  
Author(s):  
Amirul Islam ◽  
Andy Chan ◽  
Matthew Ashfold ◽  
Chel Gee Ooi ◽  
Majid Azari
Keyword(s):  
Indian Ocean ◽  
Southeast Asia ◽  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Biomass Burning ◽  
Indian Ocean Dipole ◽  
Weather Prediction ◽  
Sea Surface ◽  
Madden Julian Oscillation ◽  
Rainfall Anomalies

Maritime Continent (MC) positions in between Asian and Australian summer monsoons zone. Its complex topography and shallow seas around it is a major challenge for the climate researchers to model and understand it. Monsoon in this area is affected by inter-scale ocean-atmospheric interactions like El-Niño Southern Oscillation (ENSO), Indian Ocean Dipole (IOD) and Madden-Julian Oscillation. Monsoon rainfall in MC (especially in Indonesia and Malaysia) profoundly exhibits its variability dependency on ocean-atmospheric phenomena in this region. This monsoon shift often introduces to dreadful events like biomass burning (BB) in Southeast Asia (SEA) which sometimes leads to severe trans-boundary haze pollution. In this study, the episode of BB in 2015 of SEA is highlighted and discussed. Observational satellite datasets are tested by performing simulations with numerical weather prediction (NWP) model using WRF-ARW (Advanced research WRF). Observed and model datasets are compared to study the sea surface temperature (SST) and precipitation (rainfall) anomalies influenced by ENSO, IOD and MJO. Correlations have been recognised which explains the delayed rainfall of regular monsoon in MC due to the influence of ENSO, IOD and MJO during 2015 BB episode, eventually leading to intensification of fire and severe haze.

scholarly journals Using Saildrones to Validate Satellite-Derived Sea Surface Salinity and Sea Surface Temperature along the California/Baja Coast

2019 ◽  
Vol 11 (17) ◽  
pp. 1964 ◽  
Author(s):  
Jorge Vazquez-Cuervo ◽  
Jose Gomez-Valdes ◽  
Marouan Bouali ◽  
Luis Miranda ◽  
Tom Van der Stocken ◽  
...  
Keyword(s):  
Surface Temperature ◽  
Sea Surface Temperature ◽  
Current System ◽  
California Current ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Surface Salinity ◽  
California Current System ◽  
The Impact ◽  
Buoy Measurements

Traditional ways of validating satellite-derived sea surface temperature (SST) and sea surface salinity (SSS) products by comparing with buoy measurements, do not allow for evaluating the impact of mesoscale-to-submesoscale variability. We present the validation of remotely sensed SST and SSS data against the unmanned surface vehicle (USV)—called Saildrone—measurements from the 60 day 2018 Baja California campaign. More specifically, biases and root mean square differences (RMSDs) were calculated between USV-derived SST and SSS values, and six satellite-derived SST (MUR, OSTIA, CMC, K10, REMSS, and DMI) and three SSS (JPLSMAP, RSS40, RSS70) products. Biases between the USV SST and OSTIA/CMC/DMI were approximately zero, while MUR showed a bias of 0.3 °C. The OSTIA showed the smallest RMSD of 0.39 °C, while DMI had the largest RMSD of 0.5 °C. An RMSD of 0.4 °C between Saildrone SST and the satellite-derived products could be explained by the diurnal and sub-daily variability in USV SST, which currently cannot be resolved by remote sensing measurements. SSS showed fresh biases of 0.1 PSU for JPLSMAP and 0.2 PSU and 0.3 PSU for RMSS40 and RSS70 respectively. SST and SSS showed peaks in coherence at 100 km, most likely associated with the variability of the California Current System.

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