Review and assessment of latent and sensible heat flux accuracy over the global oceans

For over a decade, several research groups have been developing air-sea heat flux information over the global ocean, including latent (LHF) and sensible (SHF) heat fluxes over the global ocean. This paper aims to provide new insight into the quality and error characteristics of turbulent heat flux estimates at various spatial and temporal scales (from daily upwards). The study is performed within the European Space Agency (ESA) Ocean Heat Flux (OHF) project. One of the main objectives of the OHF project is to meet the recommendations and requirements expressed by various international programs such as the World Research Climate Program (WCRP) and Climate and Ocean Variability, Predictability, and Change (CLIVAR), recognizing the need for better characterization of existing flux errors with respect to the input bulk variables (e.g. surface wind, air and sea surface temperatures, air and surface specific humidities), and to the atmospheric and oceanic conditions (e.g. wind conditions and sea state). The analysis is based on the use of daily averaged LHF and SHF and the asso- ciated bulk variables derived from major satellite-based and atmospheric reanalysis products. Inter-comparisons of heat flux products indicate that all of them exhibit similar space and time patterns. However, they also reveal significant differences in magnitude in some specific regions such as the western ocean boundaries during the Northern Hemisphere winter season, and the high southern latitudes. The differences tend to be closely related to large differences in surface wind speed and/or specific air humidity (for LHF) and to air and sea temperature differences (for SHF). Further quality investigations are performed through comprehensive comparisons with daily-averaged LHF and SHF estimated from moorings. The resulting statistics are used to assess the error of each OHF product. Consideration of error correlation between products and observations (e.g., by their assimilation) is also given. This reveals generally high noise variance in all products and a weak signal in common with in situ observations, with some products only slightly better than others. The OHF LHF and SHF products, and their associated error characteristics, are used to compute daily OHF multiproduct-ensemble (OHF/MPE) estimates of LHF and SHF over the ice-free global ocean on a 0.25° × 0.25° grid. The accuracy of this heat multiproduct, determined from comparisons with mooring data, is greater than for any individual product. It is used as a reference for the anomaly characterization of each individual OHF product

Extended triple collocation: estimating errors and correlation coefficients with respect to an unknown target

Calibration and validation of geophysical measurement systems typically require knowledge of the true value of the target variable. However, the data considered to represent the true values often include their own measurement errors, biasing calibration, and validation results. Triple collocation (TC) can be used to estimate the root-mean-square-error (RMSE), using observations from three mutually independent, error-prone measurement systems. Here, we introduce Extended Triple Collocation (ETC): using exactly the same assumptions as TC, we derive an additional performance metric, the correlation coefficient of the measurement system with respect to the unknown target, rho(t,Xi). We demonstrate that rho(2)(t,Xi) is the scaled, unbiased signal-to-noise ratio and provides a complementary perspective compared to the RMSE. We apply it to three collocated wind data sets. Since ETC is as easy to implement as TC, requires no additional assumptions, and provides an extra performance metric, it may be of interest in a wide range of geophysical disciplines.Peer ReviewedPostprint (published version

Improved BEC SMOS Arctic Sea Surface Salinity product v3.1

17 pages, 13 figures, 1 table.-- Data availability: The product (Martínez et al., 2019) is freely distributed on the BEC (Barcelona Expert Center) web page (http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019) and on the Digital CSIC server: https://digital.csic.es/handle/10261/219679 (last access: 25 January 2022). Data can be downloaded from the FTP service: http://bec.icm.csic.es/bec-ftp-service/ (last access: 25 January 2022). The maps are distributed in the standard grid EASE-Grid 2.0, which has a spatial resolution of 25 km. In addition to the product validated in this work (L3 with temporal resolution of 9 d), L3 products having a temporal resolution of 3 and 18 d and the L2 product are available. These Arctic SSS products cover the period from 2011 to 2019.-- This work represents a contribution to the CSIC Thematic Interdisciplinary Platform PTI Teledetect and PolarCSIC. Argo data were collected and made freely available by the International Argo program and the national programs that contribute to it (https://argo.ucsd.edu, https://www.ocean-ops.org, last access: 25 January 2022). The Argo program is part of the Global Ocean Observing SystemMeasuring salinity from space is challenging since the sensitivity of the brightness temperature (TB) to sea surface salinity (SSS) is low (about 0.5 K psu−1), while the SSS range in the open ocean is narrow (about 5 psu, if river discharge areas are not considered). This translates into a high accuracy requirement of the radiometer (about 2–3 K). Moreover, the sensitivity of the TB to SSS at cold waters is even lower (0.3 K psu−1), making the retrieval of the SSS in the cold waters even more challenging. Due to this limitation, the ESA launched a specific initiative in 2019, the Arctic+Salinity project (AO/1-9158/18/I-BG), to produce an enhanced Arctic SSS product with better quality and resolution than the available products. This paper presents the methodologies used to produce the new enhanced Arctic SMOS SSS product (Martínez et al., 2019) . The product consists of 9 d averaged maps in an EASE 2.0 grid of 25 km. The product is freely distributed from the Barcelona Expert Center (BEC, http://bec.icm.csic.es/, last access: 25 January 2022) with the DOI number https://doi.org/10.20350/digitalCSIC/12620 (Martínez et al., 2019). The major change in this new product is its improvement of the effective spatial resolution that permits better monitoring of the mesoscale structures (larger than 50 km), which benefits the river discharge monitoringThis work has been carried out as part of the ESA Arctic+Salinity project (AO/1-9158/18/I-BG), which permitted the production of the database, and the Ministry of Economy and Competitiveness, Spain, through the National R&D Plan under L-BAND project ESP2017-89463-C3-1-R. [...] With the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)Peer reviewe

Accuracy of wind observations from open-ocean buoys: Correction for flow distortion

The comparison of equivalent neutral winds obtained from (a) four WHOI buoys in the subtropics and (b) scatterometer estimates at those locations reveals a root-mean-square (RMS) difference of 0.56-0.76 m/s. To investigate this RMS difference, different buoy wind error sources were examined. These buoys are particularly well suited to examine two important sources of buoy wind errors because: (1) redundant anemometers and a comparison with numerical flow simulations allow us to quantitatively assess flow distortion errors, and (2) one-minute sampling at the buoys allows us to examine the sensitivity of buoy temporal sampling/averaging in the buoy-scatterometer comparisons. The inter-anemometer difference varies as a function of wind direction relative to the buoy wind vane and is consistent with the effects of flow distortion expected based on numerical flow simulations. Comparison between the anemometers and scatterometer winds supports the interpretation that the inter-anemometer disagreement, which can be up to 5% of the wind speed, is due to flow distortion. These insights motivate an empirical correction to the individual anemometer records and subsequent comparison with scatterometer estimates show good agreement

Validation practices for satellite based earth observation data across communities

Assessing the inherent uncertainties in satellite data products is a challenging task. Different technical approaches have been developed in the Earth Observation (EO) communities to address the validation problem which results in a large variety of methods as well as terminology. This paper reviews state-of-the-art methods of satellite validation and documents their similarities and differences. First the overall validation objectives and terminologies are specified, followed by a generic mathematical formulation of the validation problem. Metrics currently used as well as more advanced EO validation approaches are introduced thereafter. An outlook on the applicability and requirements of current EO validation approaches and targets is given

Accuracy of wind observations from open-ocean buoys: Correction for flow distortion

The comparison of equivalent neutral winds obtained from (a) four WHOI buoys in the subtropics and (b) scatterometer estimates at those locations reveals a root-mean-square (RMS) difference of 0.56-0.76 m/s. To investigate this RMS difference, different buoy wind error sources were examined. These buoys are particularly well suited to examine two important sources of buoy wind errors because: (1) redundant anemometers and a comparison with numerical flow simulations allow us to quantitatively assess flow distortion errors, and (2) one-minute sampling at the buoys allows us to examine the sensitivity of buoy temporal sampling/averaging in the buoy-scatterometer comparisons. The inter-anemometer difference varies as a function of wind direction relative to the buoy wind vane and is consistent with the effects of flow distortion expected based on numerical flow simulations. Comparison between the anemometers and scatterometer winds supports the interpretation that the inter-anemometer disagreement, which can be up to 5% of the wind speed, is due to flow distortion. These insights motivate an empirical correction to the individual anemometer records and subsequent comparison with scatterometer estimates show good agreement

Spaceborne Microwave Radiometry: Calibration, Intercalibration, and Science Applications.

Spaceborne microwave radiometry is the backbone for assimilation into numerical weather forecasts and provides important information for Earth and environment science. The extensive radiometric data must go through the process of calibration and intercalibration prior to science application. This work deals with the entire process by providing systematic methods and addressing critical challenges. These methods have been applied to NASA and JAXA’s Global Precipitation Measurement (GPM) mission and many other radiometers to make important contributions and to solve long-standing issues with coastal science applications. Specifically, it addresses four important challenges: 1) improving cold calibration with scan dependent characterization; 2) reducing the uncertainty of warm calibration; 3) deriving calibration dependence across the full range of brightness temperatures with both cold and warm calibration; and 4) investigating calibration variability and dependence on geophysical parameters. One critical challenge in science applications of radiometer data is that coastal science products from radiometers have previously been largely unavailable due to land contamination. We therefore develop methods to correct for land contamination and derive coastal science products. This thesis addresses these challenges by developing their solutions and then applying them to the GPM mission and its radiometer constellation.PhDAtmospheric, Oceanic and Space SciencesUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/120728/1/johnxun_1.pd

First SMOS Sea Surface Salinity dedicated products over the Baltic Sea

26 pages, 24 figures, 4 tables.-- Data availability: Access to the data is provided by the Barcelona Expert Center, through its FTP service. The DOI of the L3 product is https://doi.org/10.20350/digitalCSIC/13859 (González-Gambau et al., 2021a). The DOI of the L4 product is https://doi.org/10.20350/digitalCSIC/13860 (González-Gambau et al., 2021b). Seasonal averaged L4 SSS products are also available in the HELCOM catalogue (https://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/9d979033-1136-4dd1-a09b-7ee9e512ad14, BEC team, 2021b), and they can be visualized in the HELCOM Map and Data service (https://maps.helcom.fi/website/mapservice/?datasetID=9d979033-1136-4dd1-a09b-7ee9e512ad14, last access: 9 November 2021).-- This work is a contribution to the CSIC Thematic Interdisciplinary Platform TeledetectThis paper presents the first Soil Moisture and Ocean Salinity (SMOS) Sea Surface Salinity (SSS) dedicated products over the Baltic Sea. The SSS retrieval from L-band brightness temperature (TB) measurements over this basin is really challenging due to important technical issues, such as the land–sea and ice–sea contamination, the high contamination by radio-frequency interference (RFI) sources, the low sensitivity of L-band TB at SSS changes in cold waters, and the poor characterization of dielectric constant models for the low SSS range in the basin. For these reasons, exploratory research in the algorithms used from the level 0 up to level 4 has been required to develop these dedicated products. This work has been performed in the framework of the European Space Agency regional initiative Baltic+ Salinity Dynamics. Two Baltic+ SSS products have been generated for the period 2011–2019 and are freely distributed: the Level 3 (L3) product (daily generated 9 d maps in a 0.25∘ grid; https://doi.org/10.20350/digitalCSIC/13859, González-Gambau et al., 2021a) and the Level 4 (L4) product (daily maps in a 0.05∘ grid; https://doi.org/10.20350/digitalCSIC/13860, González-Gambau et al., 2021b)​​​​​​​, which are computed by applying multifractal fusion to L3 SSS with SST maps. The accuracy of L3 SSS products is typically around 0.7–0.8 psu. The L4 product has an improved spatiotemporal resolution with respect to the L3 and the accuracy is typically around 0.4 psu. Regions with the highest errors and limited coverage are located in Arkona and Bornholm basins and Gulfs of Finland and Riga. The impact assessment of Baltic+ SSS products has shown that they can help in the understanding of salinity dynamics in the basin. They complement the temporally and spatially very sparse in situ measurements, covering data gaps in the region, and they can also be useful for the validation of numerical models, particularly in areas where in situ data are very sparseThis work has been carried out as part of the Baltic+ Salinity Dynamics project (4000126102/18/I-BG), funded by the European Space Agency. It has been also supported in part by the Spanish R&D project INTERACT (PID2020-114623RB-C31), which is funded by MCIN/AEI/10.13039/501100011033. We also received funding from the Spanish government through the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S)Peer reviewe

Quantification of Aquarius, SMAP, SMOS and Argo-Based Gridded Sea Surface Salinity Product Sampling Errors

Evaluating and validating satellite sea surface salinity (SSS) measurements is fundamental. There are two types of errors in satellite SSS: measurement error due to the instrument’s inaccuracy and problems in retrieval, and sampling error due to unrepresentativeness in the way that the sea surface is sampled in time and space by the instrument. In this study, we focus on sampling errors, which impact both satellite and in situ products. We estimate the sampling errors of Level 3 satellite SSS products from Aquarius, SMOS and SMAP, and in situ gridded products. To do that, we use simulated L2 and L3 Aquarius, SMAP and SMOS SSS data, individual Argo observations and gridded Argo products derived from a 12-month high-resolution 1/48? ocean model. The use of the simulated data allows us to quantify the sampling error and eliminate the measurement error. We found that the sampling errors are high in regions of high SSS variability and are globally about 0.02/0.03 psu at weekly time scales and 0.01/0.02 psu at monthly time scales for satellite products. The in situ-based product sampling error is significantly higher than that of the three satellite products at monthly scales (0.085 psu) indicating the need to be cautious when using in situ-based gridded products to validate satellite products. Similar results are found using a Correlated Triple Collocation method that quantifies the standard deviation of products’ errors acquired with different instruments. By improving our understanding and quantifying the effect of sampling errors on satellite-in situ SSS consistency over various spatial and temporal scales, this study will help to improve the validation of SSS, the robustness of scientific applications and the design of future salinity missions

Monitoring Black Sea environmental changes from space: New products for altimetry, ocean colour and salinity. Potentialities and requirements for a dedicated in-situ observing system

21 pages, 13 figures, 2 tables, supplementary material https://www.frontiersin.org/articles/10.3389/fmars.2022.998970/full#supplementary-material.-- Data availability statement: The datasets generated for this study can be found on the web interface (http://www.eo4sibs.uliege.be/) and on Zenodo under data doi: 10.5281/zenodo.6397223 with a full documentation that include Products User Manuals (PUM) and Algorithm Theoretical Basis Document (ATBD). All these products are distributed in netCDF files Grégoire et al. (2022). SMOS SSS and CDM products are also available at https://bec.icm.csic.es/bec-ftp-service/In this paper, satellite products developed during the Earth Observation for Science and Innovation in the Black Sea (EO4SIBS) ESA project are presented. Ocean colour, sea level anomaly and sea surface salinity datasets are produced for the last decade and validated with regional in-situ observations. New data processing is tested to appropriately tackle the Black Sea’s particular configuration and geophysical characteristics. For altimetry, the full rate (20Hz) altimeter measurements from Cryosat-2 and Sentinel-3A are processed to deliver a 5Hz along-track product. This product is combined with existing 1Hz product to produce gridded datasets for the sea level anomaly, mean dynamic topography, geostrophic currents. This new set of altimetry gridded products offers a better definition of the main Black Sea current, a more accurate reconstruction and characterization of eddies structure, in particular, in coastal areas, and improves the observable wavelength by a factor of 1.6. The EO4SIBS sea surface salinity from SMOS is the first satellite product for salinity in the Black Sea. Specific data treatments are applied to remedy the issue of land-sea and radio frequency interference contamination and to adapt the dielectric constant model to the low salinity and cold waters of the Black Sea. The quality of the SMOS products is assessed and shows a significant improvement from Level-2 to Level -3 and Level-4 products. Level-4 products accuracy is 0.4-0.6 psu, a comparable value to that in the Mediterranean Sea. On average SMOS sea surface salinity is lower than salinity measured by Argo floats, with a larger error in the eastern basin. The adequacy of SMOS SSS to reproduce the spatial characteristics of the Black Sea surface salinity and, in particular, plume patterns is analyzed. For ocean colour, chlorophyll-a, turbidity and suspended particulate materials are proposed using regional calibrated algorithms and satellite data provided by OLCI sensor onboard Sentinel-3 mission. The seasonal cycle of ocean colour products is described and a water classification scheme is proposed. The development of these three types of products has suffered from important in-situ data gaps that hinder a sound calibration of the algorithms and a proper assessment of the datasets quality. We propose recommendations for improving the in-situ observing system that will support the development of satellite productsThis work has been carried out as part of the European Space Agency contract Earth Observation data For Science and Innovations in the Black Sea (EO4SIBS, ESA contract n° 4000127237/19/I-EF). MG received fundings from the Copernicus Marine Service (CMEMS), the European Union’s Horizon 2020 BRIDGE-BS project under grant agreement No. 101000240 and by the Project CE2COAST funded by ANR(FR), BELSPO (BE), FCT (PT), IZM (LV), MI (IE), MIUR (IT), Rannis (IS), and RCN (NO) through the 2019 “Joint Transnational Call on Next Generation Climate Science in Europe for Oceans” initiated by JPI Climate and JPI Oceans. The research on SMOS SSS has been also supported in part by the Spanish R&D project INTERACT (PID2020-114623RB-C31), which is funded by MCIN/AEI/10.13039/501100011033, funding from the Spanish government through the “Severo Ochoa Centre of Excellence” accreditation (CEX2019-000928-S) and the CSIC Thematic Interdisciplinary Platform TeledetectPeer reviewe