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J. Boutin and J. Etcheto

Abstract

The authors compare wind speed retrieved from the Geosat altimeter, from two Special Sensor Microwave/Imager (SSM/I) microwave radiometers. The SSM/I F08 and SSM/I F10, and from the European Space Agency ERS-1 scatterometer. As ground truth, ship reports were used that provide a continuous time series of consistent measurements at large scale during the whole period covered by the three satellites, and TOGA TAO data in the tropical Pacific Ocean that are more accurate though more limited in geographical extent than ship wind speeds.

It is evidenced that the Geosat wind speed retrieved using the Witter and Chelton algorithm is underestimated at high wind speed. The authors find that the SSM/I wind speeds retrieved by the Wentz algorithm are underestimated by more than 1 m s−1 with respect to the ship wind speeds in large regions at high latitudes, this effect being larger with SSM/I F10 than with SSM/I F08. The authors compare the ERS-1 wind speeds retrieved from the Cersat preliminary algorithm and from the ESA CMOD4 algorithm; while the former gives wind speeds consistent with the ship measurements, the latter is shown to overestimate low wind speed and to highly underestimate high wind speed. A comparison of the ERS-1 and SSM/I F10 gridded data shows a 0.5–1 m s−1 overestimate of the SSM/I wind speed in the western tropical Pacific and in the intertropical convergence zone and south tropical convergence zone strengthening that the SSM/I wind speeds are disturbed in regions of high atmospheric water content.

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G. Reverdin, J. Boutin, A. Lourenco, P. Blouch, J. Rolland, P. P. Niiler, W. Scuba, and A. F. Rios

Abstract

Sea surface salinity (SSS) data were collected in the Bay of Biscay between April and November 2005. The major source of data is 15 surface drifters deployed during the COSMOS experiment in early April and early May 2005 [12 from the Scripps Instution of Oceanography (SIO) and 3 from METOCEAN]. This is complemented by thermosalinograph (TSG) data from four French research vessels and four merchant vessels, from salinity profiles collected by Argo profiling floats and CTD casts, and from surface samples during two cruises. Time during the two cruises was dedicated to direct inspection of the drifters, recovering some, and providing validation data. This dataset provides a unique opportunity to estimate the accuracy of the SSS data and to evaluate the long-term performance of the drifter salinities. Some of the TSG SSS data were noisy, presumably from bubbles. The TSG data from the research vessels needed to be corrected from biases, which are very commonly larger than 0.1 pss-78 (practical salinity scale), and which in some instances evolved quickly from day to day. These corrections are only available when samples were collected or ancillary data are available (e.g., from CTD profiles). The resulting accuracy of the corrected TSG dataset, which varies strongly in time, is discussed. The surface drifter SSS data presented anomalous daytime values during days with strong surface warming. These data had to be excluded from the dataset. The drifter SSS presented initial biases in the range 0.009 to −0.026 pss-78. The (usually) negative bias increased by an average of −0.007 pss-78 during the average 65-day period before the COSMOS-2 cruise on 22–27 June. High chlorophyll derived from satellite ocean color, and therefore high density of phytoplanktonic cells, is observed in Medium Resolution Imaging Spectrometer (MERIS)/Moderate Resolution Imaging Spectroradiometer (MODIS) composites during part of the period, in particular in late April or early May. No correlation was found between the change in bias and the estimated surface chlorophyll. Evolution during the following summer months is harder to ascertain. For three buoys, there is little change in bias, but for two others, there could have been an increase in bias by up to 0.03 or 0.04 pss-78 during July–August. Seven drifters were recovered in the autumn, which provide recovery or postrecovery estimates of the biases, suggesting in three cases (out of seven) a large (0.02–0.03 pss-78) increase in bias during the autumn months, but no significant increase for the other four drifters.

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G. Reverdin, S. Morisset, J. Boutin, N. Martin, M. Sena-Martins, F. Gaillard, P. Blouch, J. Rolland, J. Font, J. Salvador, P. Fernández, and D. Stammer

Abstract

Salinity measurements from 119 surface drifters in 2007–12 were assessed; 80% [Surface Velocity Program with a barometer with a salinity sensor (SVP-BS)] and 75% [SVP with salinity (SVP-S)] of the salinity data were found to be usable, after editing out some spikes. Sudden salinity jumps are found in drifter salinity records that are not always associated with temperature jumps, in particular in the wet tropics. A method is proposed to decide whether and how to correct those jumps, and the uncertainty in the correction applied. Northeast of South America, in a region influenced by the Amazon plume and fresh coastal water, drifter salinity is very variable, but a comparison with data from the Soil Moisture and Ocean Salinity satellite suggests that this variability is usually reasonable. The drifter salinity accuracy is then explored based on comparisons with data from Argo floats and from thermosalinographs (TSGs) of ships of opportunity. SVP-S/SVP-BS drifter records do not usually present significant biases within the first 6 months, but afterward biases sometimes need to be corrected (altogether, 16% of the SVP-BS records). Biases start earlier after 3 months for drifters not protected by antifouling paint. For the few drifters for which large corrections were applied to portions of the record, the accuracy cannot be proven to be better than 0.1 psu, and it cannot be proven to be better than 0.5 psu for data in the largest variability area off northeast South America. Elsewhere, after excluding portions of the records with suspicious salinity jumps or when large corrections were applied, the comparisons rule out average biases in individual drifter salinity record larger than 0.02 psu (midlatitudes) and 0.05 psu (tropics).

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G. Reverdin, J. Boutin, N. Martin, A. Lourenco, P. Bouruet-Aubertot, A. Lavin, J. Mader, P. Blouch, J. Rolland, F. Gaillard, and P. Lazure

Abstract

The accuracy of temperature measurements from drifters is first examined for 16 drifters (manufactured either by Metocean Data Systems or by Pacific Gyre) deployed with two temperature sensors in the tropical or North Atlantic Ocean. One of these sensors is the SST thermistor commonly used on Surface Velocity Program (SVP) drifters since the late 1980s; whereas the other sensor is a platinum temperature probe associated with a Seabird conductivity cell. The authors find (for 19 separate deployments) an average positive offset of the SST thermistor measurements in 17 out of 19 cases, exceeding 0.1°C in five instances. Among the five drifters that were at sea for a year or more, two present a large trend in this offset (0.10° and −0.10°C yr−1); and in two other cases, there is a clear annual cycle of the offset, suggesting a dependency on temperature. Offsets in 9 out of 12 drifters with sea time longer than 4 months present a negative trend, but the average trend is not significantly different from zero. The study also examined 29 drifters from four manufacturers equipped only with the usual SST thermistor, but for which either a precise initial temperature measurement was available or a float was attached to provide accurate temperature measurements (for a duration on the order of a month). These comparisons often identify SST biases at or soon after deployment. This initial bias is null (or slightly negative) for the set of Clearwater Instrumentation’s drifters, it is very small for two out of three sets of Technocean drifters, and positive for the third one, as well as for the set of Pacific Gyre drifters (on the order of 0.05°C).

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G. Reverdin, S. Morisset, H. Bellenger, J. Boutin, N. Martin, P. Blouch, J. Rolland, F. Gaillard, P. Bouruet-Aubertot, and B. Ward

Abstract

This study describes how the hull temperature (Ttop) measurements from multisensor surface velocity program (SVP) drifters can be combined with other measurements to provide quantitative information on near-surface vertical temperature stratification during large daily cycles. First, Ttop is compared to the temperature measured at 17 -cm depth from a float tethered to the SVP drifter. These 2007–12 SVP drifters present a larger daily cycle by 1%–3% for 1°–2°C daily cycle amplitudes, with a maximum difference close to the local noon. The difference could result from flow around the SVP drifter in the presence of temperature stratification in the top 20 cm of the water column but also from a small influence of internal drifter temperature on Ttop. The largest differences were found for small drifters (Technocean) for very large daily cycles, as expected from their shallower measurements. The vertical stratification is estimated by comparing these hull data with the deeper T or conductivity C measurements from Sea-Bird sensors 25 (Pacific Gyre) to 45 cm (MetOcean) below the top temperature sensor. The largest stratification is usually found near local noon and early afternoon. For a daily cycle amplitude of 1°C, these differences with the upper level are in the range of 3%–5% of the daily cycle for the Pacific Gyre drifters and 6%–10% for MetOcean drifters with the largest values occurring when the midday sun elevation is lowest. The relative differences increase for larger daily cycles, and the vertical profiles become less linear. These estimated stratifications are well above the uncertainty on Ttop.

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J. Boutin, Y. Chao, W. E. Asher, T. Delcroix, R. Drucker, K. Drushka, N. Kolodziejczyk, T. Lee, N. Reul, G. Reverdin, J. Schanze, A. Soloviev, L. Yu, J. Anderson, L. Brucker, E. Dinnat, A. Santos-Garcia, W. L. Jones, C. Maes, T. Meissner, W. Tang, N. Vinogradova, and B. Ward

Abstract

Remote sensing of salinity using satellite-mounted microwave radiometers provides new perspectives for studying ocean dynamics and the global hydrological cycle. Calibration and validation of these measurements is challenging because satellite and in situ methods measure salinity differently. Microwave radiometers measure the salinity in the top few centimeters of the ocean, whereas most in situ observations are reported below a depth of a few meters. Additionally, satellites measure salinity as a spatial average over an area of about 100 × 100 km2. In contrast, in situ sensors provide pointwise measurements at the location of the sensor. Thus, the presence of vertical gradients in, and horizontal variability of, sea surface salinity complicates comparison of satellite and in situ measurements. This paper synthesizes present knowledge of the magnitude and the processes that contribute to the formation and evolution of vertical and horizontal variability in near-surface salinity. Rainfall, freshwater plumes, and evaporation can generate vertical gradients of salinity, and in some cases these gradients can be large enough to affect validation of satellite measurements. Similarly, mesoscale to submesoscale processes can lead to horizontal variability that can also affect comparisons of satellite data to in situ data. Comparisons between satellite and in situ salinity measurements must take into account both vertical stratification and horizontal variability.

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Thomas Popp, Michaela I. Hegglin, Rainer Hollmann, Fabrice Ardhuin, Annett Bartsch, Ana Bastos, Victoria Bennett, Jacqueline Boutin, Carsten Brockmann, Michael Buchwitz, Emilio Chuvieco, Philippe Ciais, Wouter Dorigo, Darren Ghent, Richard Jones, Thomas Lavergne, Christopher J. Merchant, Benoit Meyssignac, Frank Paul, Shaun Quegan, Shubha Sathyendranath, Tracy Scanlon, Marc Schröder, Stefan G. H. Simis, and Ulrika Willén

Abstract

Climate data records (CDRs) of essential climate variables (ECVs) as defined by the Global Climate Observing System (GCOS) derived from satellite instruments help to characterize the main components of the Earth system, to identify the state and evolution of its processes, and to constrain the budgets of key cycles of water, carbon, and energy. The Climate Change Initiative (CCI) of the European Space Agency (ESA) coordinates the derivation of CDRs for 21 GCOS ECVs. The combined use of multiple ECVs for Earth system science applications requires consistency between and across their respective CDRs. As a comprehensive definition for multi-ECV consistency is missing so far, this study proposes defining consistency on three levels: 1) consistency in format and metadata to facilitate their synergetic use (technical level); 2) consistency in assumptions and auxiliary datasets to minimize incompatibilities among datasets (retrieval level); and 3) consistency between combined or multiple CDRs within their estimated uncertainties or physical constraints (scientific level). Analyzing consistency between CDRs of multiple quantities is a challenging task and requires coordination between different observational communities, which is facilitated by the CCI program. The interdependencies of the satellite-based CDRs derived within the CCI program are analyzed to identify where consistency considerations are most important. The study also summarizes measures taken in CCI to ensure consistency on the technical level, and develops a concept for assessing consistency on the retrieval and scientific levels in the light of underlying physical knowledge. Finally, this study presents the current status of consistency between the CCI CDRs and future efforts needed to further improve it.

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