Retrieval of Daily Mean VIIRS SST Products in China Seas

Sea surface temperature (SST) is one of the most important factors in regulating air-sea heat flux and, thus, climate change. Most of current global daily SST products are derived from one or two transient measurements of polar-orbiting satellites, which are not the same to daily mean SST values. In this study, high-temporal-resolution SST measurements (32–40 snapshots per day) from a geostationary satellite, FengYun-4A (FY–4A), are used to analyze the diurnal variation of SST in China seas. The results present a sinusoidal pattern of the diurnal variability in SST, with the maximum value at 13:00–15:00 CST and the minimum at 06:00–08:00 CST. Based on the diurnal variation of SST, a retrieval method for daily mean SST products from polar-orbiting satellites is established and applied to 7716 visible infrared imaging radiometer (VIIRS) data in China seas. The results suggest that it is feasible and practical for the retrieval of daily mean SST with an average RMSE of 0.133 °C. This retrieval method can also be utilized to other polar-orbiting satellites and obtain more daily mean satellite SST products, which will contribute to more accurate estimation and prediction between atmosphere and ocean in the future.

Impact of the Agulhas Current on southern Africa precipitation: a modelling study

The Agulhas Current (AC) creates a sharp temperature gradient with the surrounding ocean, leading to a large turbulent flux of moisture from ocean to atmosphere. We use two simulations of the Weather Research and Forecasting (WRF) model to show the seasonal impact of the warm core of the AC on southern Africa precipitation. In one simulation the sea surface temperature (SST) of the AC is similar to satellite observations, while the second uses satellite SST observations spatially smoothed to reduce the temperature of the core of the AC by ~1.5°C. We show that decreasing the SST of the AC reduces the precipitation of the wettest seasons (austral summer and autumn) inland. Over the ocean, reducing the SST reduces precipitation, low-level wind convergence, SST and SLP Laplacian above the AC in all seasons, consistent with the pressure adjustment mechanism. Moreover, winter precipitation above the Current may be also related to increased latent flux. In summer and autumn, the AC SST reduction is also associated with decreased precipitation further inland (more than 1.5 mm/day), caused by an atmospheric circulation that decreases the horizontal moisture flux from the AC to South Africa. The reduction is also associated with higher geopotential height extending from the surface east and over the AC to the mid-troposphere over southeastern Africa. The westward tilted geopotential height is consistent with the linear response to shallow diabatic heating in midlatitudes. An identical mechanism occurs in spring but is weaker. Winter rainfall response is confined above the AC.

A Completeness and Complementarity Analysis of the Data Sources in the NOAA In Situ Sea Surface Temperature Quality Monitor (iQuam) System

In situ sea surface temperatures (SST) are the key component of the calibration and validation (Cal/Val) of satellite SST retrievals and data assimilation (DA). The NOAA in situ SST Quality Monitor (iQuam) aims to collect, from various sources, all available in situ SST data, and integrate them into a maximally complete, uniform, and accurate dataset to support these applications. For each in situ data type, iQuam strives to ingest data from several independent sources, to ensure most complete coverage, at the cost of some redundancy in data feeds. The relative completeness of various inputs and their consistency and mutual complementarity are often unknown and are the focus of this study. For four platform types customarily employed in satellite Cal/Val and DA (drifting buoys, tropical moorings, ships, and Argo floats), five widely known data sets are analyzed: (1) International Comprehensive Ocean-Atmosphere Data Set (ICOADS), (2) Fleet Numerical Meteorology and Oceanography Center (FNMOC), (3) Atlantic Oceanographic and Meteorological Laboratory (AOML), (4) Copernicus Marine Environment Monitoring Service (CMEMS), and (5) Argo Global Data Assembly Centers (GDACs). Each data set reports SSTs from one or more platform types. It is found that drifting buoys are more fully represented in FNMOC and CMEMS. Ships are reported in FNMOC and ICOADS, which are best used in conjunction with each other, but not in CMEMS. Tropical moorings are well represented in ICOADS, FNMOC, and CMEMS. Some CMEMS mooring reports are sampled every 10 min (compared to the standard 1 h sampling in all other datasets). The CMEMS Argo profiling data set is, as expected, nearly identical with those from the two Argo GDACs.

Evaluation of the in situ Sea Surface Temperature Quality Control in the NOAA in situ SST Quality Monitor (iQuam) System

In situ sea surface temperature (SST) measurements play a critical role in the calibration/validation (Cal/Val) of satellite SST retrievals and ocean data assimilation. However, their quality is not always optimal, and proper quality control (QC) is required before they can be used with confidence. The in situ SST Quality Monitor (iQuam) system was established at the National Oceanic and Atmospheric Administration (NOAA) in 2009, initially to support the Cal/Val of NOAA satellite SST products. It collects in situ SST data from multiple sources, performs uniform QC, monitors the QC’ed data online, and distributes it to users. In this study, the iQuam QC is compared with other QC methods available in some of the in situ data ingested in iQuam. Overall, the iQuam QC performs well on daily-to-monthly time scales over most global oceans and under a wide variety of environmental conditions. However, it may be less accurate in the daytime a when pronounced diurnal cycle is present, and in dynamic regions, due to the strong reliance on the “reference SST check”, which employs daily low-resolution level 4 (L4) analyses with no diurnal cycle resolved. The iQuam “performance history check”, applied to all in situ platforms, is an effective alternative to the customary “black/gray” lists, available only for some platforms (e.g., drifters and Argo floats). In the future, iQuam QC will be upgraded (e.g., using improved reference field(s), with enhanced temporal and spatial resolutions). More comparisons with external QC methods will be performed to learn and employ the best QC practices.

Characterizing an anticyclone in Western Mediterranean Sea using altimetric data and an eddy tracker

<p>In April 2019, a large anticyclonic Eddy has formed in Western Mediterranean Sea between Sardinia and Balearic Islands. This anticyclone was observable with Sentinel-3 SST satellite data for 7 months and its diameter was estimated to 150 km. Although mesoscale anticyclones are quite common in this part of the Mediterranean Sea, such large and long-live eddies remain exceptional and repercussions for ocean-atmospheric exchanges and for biodiversity might be consequent. However, due to the increase of temperatures during summer, the satellite SST track of the eddy has been lost during a few weeks in August and September. Indeed, the SST signature of the eddy was not distinguishable from surrounding waters anymore. In order to track the eddy during its entire life and have a better understanding of its characteristics, sea level anomaly derived from altimetric data will be analysed in this study with the Py Eddy Tracker toolbox to investigate the variation of its position, its altimetry and its size. The distribution of other remarkable eddies in this zone and period will also be considered. Moreover, a high-resolution SST field will be reconstructed with DINEOF method so the comparison between eddy’s SST and altimetric characteristics will be assured.</p>

Using Satellite Altimeter and SST Observations of the 1997-1998 El Nino to Check the Key Ocean Processes Involved in a Strong El Nino.

<p>A recent high-resolution ocean model study of the strong El Ninos of 1982-1983 and 1997-1998 highlighted a previously neglected ocean mechanism which was active during their growth.   The mechanism involved a weakening of both the Equatorial Current and the tropical instability eddies in mid-ocean.  It also involved an increase in the strength of the North Equatorial Counter Current due to the passage of the annual Rossby wave.</p><p>      This presentation reports how satellite altimeter and satellite SST data was used to validate the model results the key areas, confirming the changes in the current and eddy fields and the resulting eastward extension of the region of highest SST values.  The SST changes were sufficient to trigger new regions deep-atmospheric convection and so had the potential to have a significant impact on the development of the El Nino and the resulting changes in the large scale atmospheric circulation.</p>

Implementation and Validating of the Regional Ocean Model System (ROMS) for the Sunda Strait connecting the Java Sea to the Indian Ocean

<p>Regional Ocean Model System (ROMS) has been simulated for the Sunda Strait, the Java Sea, and the Indian Ocean. The simulation was undertaken for thirteen months of data period (August 2013 – August 2014). However, we only used four months period for validation, namely September – December 2013. The input data involved the HYbrid Coordinate Ocean Model (HYCOM) ocean model output by considering atmospheric forcing from the European Centre for Medium-Range Weather Forecasts (ECMWF), without and with tides forcing from TPXO and rivers. The output included vertical profile temperature and salinity, sea surface temperature (SST), seas surface height (SSH), zonal (u), and meridional (v) velocity. We compared the model SST to satellite SST in time series, SSH to tides gauges data in time series, the model u and v component velocity to High Frequency (HF) radial velocity. The vertical profile temperature and salinity were compared to Argo float data and XBT. Besides, we validated the amplitude and phase of the ROMS seas surface height to amplitude and phase of the tides-gauges, including four constituents (M2, S2, K1, O1).</p>

Assimilating in situ and remote sensing observations in a highly variable estuary-shelf model

To improve the forecasting performance in dynamically active coastal waters forced by winds, tides, and river discharges in a coupled estuary-shelf model off Hong Kong, a multivariable data assimilation (DA) system using the ensemble optimal interpolation (EnOI) method has been developed and implemented. The system assimilates the Conductivity-Temperature-Depth (CTD) profilers, time-series buoy measurement, and remote sensing sea surface temperature (SST) data into a high-resolution estuary-shelf ocean model around Hong Kong. We found that the time window selection associated with the local dynamics and the number of observation samples are two key factors in improving assimilation in the unique estuary-shelf system. DA with a varied assimilation time window based on the intra-tidal variation in the local dynamics can reduce the errors in the estimation of the innovation vector caused by the model-observation mismatch at the analysis time, and improve greatly simulation in both the estuary and coastal regions. Statistically, the overall root-mean-square error (RMSE) between the DA forecasts and not-yet-assimilated observations for temperature and salinity have been reduced by 33.0% and 31.9% in the experiment period, respectively. By assimilating higher resolution remote sensing SST data instead of lower resolution satellite SST, the RMSE of SST is improved by ~18%. Besides, by assimilating real-time buoy mooring data, the model bias can be continuously corrected both around the buoy location and beyond. The assimilation of the combined buoy, CTD, and SST data can provide an overall improvement of the simulated three-dimensional solution. A dynamics-oriented assimilation scheme is essential for the improvement of model forecasting in the estuary-shelf system under multiple forcings.

A Regional Operational Model for the North East Atlantic: Model Configuration and Validation

An operational model for an area of the northeast Atlantic that encompasses all of Ireland’s territorial waters has been developed. The model is an implementation of the Regional Ocean Modelling System (ROMS) and uses operationally available atmospheric and boundary forcing, and a global tide solution for tidal forcing. River forcing is provided by climatological daily discharge rates for 29 rivers across Ireland, west Britain, and west France. It is run in an operational framework to produce 7-day hindcasts once a week, and daily 3-day forecasts which are published in a number of formats. We evaluated the model skill by comparing with measured data and calculating statistics such as mean error, root mean square error (RMSE), and correlation coefficient. The observations consist of satellite Sea Surface Temperature (SST), total surface velocity fields from satellite, water level time series from around the Irish coast, and temperature and salinity data from Array for Real-Time Geostrophic Oceanography (ARGO) and Conductivity Temperature Depth (CTD) profiles. The validation period is from 1 January 2016 until 31 December 2019. The correlation coefficient between the model and satellite SST is 0.97 and recorded in March and April 2018. The model error is about 5% of the total M2 amplitude in the Celtic Sea recorded at Dunmore East tide gauge station. The maximum RMSE between the model and the CTD temperature profiles is 0.8 °C while it is 0.17 PSU for salinity. The model correctly defines the shelf water masses around Ireland. In 2019 the Irish Coastal Current (ICC) was very strong and well defined along most of the western Irish coast. The model results have well reproduced the ICC front for the whole simulation period.