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Keywords:

  • ocean salinity;
  • sea surface salinity;
  • passive microwave;
  • microwave radiometers

Abstract

  1. Top of page
  2. Abstract
  3. 1. Salinity Science Goals
  4. 2. Radiometric Measurement of Ocean Salinity
  5. 3. Aquarius Measurement Approach
  6. References
  7. Supporting Information

[1] Aquarius is a NASA/Earth System Science Pathfinder (ESSP) mission that proposes to make the first-ever global measurements of sea surface salinity. These measurements will enable improved understanding of oceanic thermohaline circulation and of the changes in oceanic circulation that are related to seasonal to interannual climate variability. Aquarius science goals also address tropical ocean-climate feedbacks and freshwater budget components of the coupled ocean-atmosphere system. These oceanographic science requirements for Aquarius dictate measurements of global sea surface salinity that are accurate to 0.2–0.3 psu, as averaged monthly and over 100–200 km areas. Key aspects of the Aquarius salinity mission design include the instrument with its high-stability L-band radiometers, the precise calibration of the measurements, and the salinity retrieval algorithm. The Aquarius mission will meet the science needs by providing complete global coverage of ocean surface salinity, with an 8 day cycle of observations using a three beam, L-band radiometer/scatterometer flying in a 6 am/6 pm polar orbit. This conceptual design has been verified using observations from aircraft flight instruments. The radiometer design for the instrument and the needed precise calibration is based on proven, temperature-stabilized radiometer designs with internal references, plus vicarious calibration approaches developed in the course of previous space missions.

1. Salinity Science Goals

  1. Top of page
  2. Abstract
  3. 1. Salinity Science Goals
  4. 2. Radiometric Measurement of Ocean Salinity
  5. 3. Aquarius Measurement Approach
  6. References
  7. Supporting Information

[2] The salinity of the ocean surface (Figure 1) is variable, reflecting the input of fresh water from precipitation, the melting of ice, river runoff, the loss of water through evaporation, and the mixing and circulation of ocean surface water with deep water below. Globally, the sea surface salinity (SSS) is at a minimum near the equator (where there is considerable precipitation) and in polar regions (due to the melting of ice), and is at a maximum in midlatitudes (where there is reduced precipitation and enhanced evaporation). SSS ranges from about 32 to 38 psu, where the practical salinity unit (psu) is approximately equal to the mole fraction of sea salt in water, given in parts per thousand.

image

Figure 1. The estimated annual mean SSS field as derived from the World Ocean Database [Levitus et al., 1998]. The data are gridded on a 1° × 1° area with gray areas representing no data. From 70°S–70°N, about 25% of the oceanic salinity has never been measured.

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[3] The sampling of global sea surface salinity (Figure 1) has been sparse, and is largely limited to shipping lanes and the summer season. A review of historical data [Levitus et al., 1998] indicates that in the ice-free areas of the ocean, about 25% of the 1° latitude-longitude squares have never been sampled, and >73% have fewer than 10 observations. The salinity measurements that do exist, therefore resolve only large, basin-scale salinity patterns; the present knowledge of seasonal-to-interannual variability of sea surface salinity is weak at best.

[4] A more exacting understanding of oceanic salinity is important to explanation of the relationship between ocean circulation and climate. This is because the ocean circulation is largely driven by buoyant forces that are roughly equal functions of seawater temperature and salinity. Additional forcing of the thermohaline ocean circulation is a result of wind stress at the sea surface and internal forces such as Coriolis and frictional forces and internal waves. Presently, the sea surface temperature, winds and sea surface topography are adequately measured on a global scale. The Aquarius global salinity measurements will provide the critical additional measurements needed to understand and predict the buoyant forcing of oceanic circulation. Improved understanding of the oceanic buoyancy field will improve our understanding and prediction of seasonal to interannual changes in oceanic circulation and the feedback between oceanic circulation and climate.

[5] The Aquarius mission has been proposed to the NASA Earth System Science Pathfinder Program. The science goals of Aquarius are to: (1) provide the first, global mapping of the complete oceanic SSS field, (2) to better describe the global thermohaline circulation, (3) to improve understanding of the tropical ocean-climate feedback such as el Niño, and (4) to facilitate investigations of the freshwater budget component of coupled ocean-atmosphere models.

[6] To meet these science goals, the Aquarius satellite will provide salinity measurements over the range from 32 to 38 psu, and with an accuracy of 0.2–0.3 psu. This required measurement accuracy results from the analysis of the underlying variability of salinity measurements at single locations, the observations of salinity anomalies [e.g., Dickson et al., 1988; Belkin et al., 1998], studies of the effects of rainfall and runoff [e.g., Cronin and McPhaden, 1999] and from studies of seasonal to interannual salinity variability [e.g., Dessier and Donguy, 1994; Donguy and Meyers, 1996; Large and Nurser, 2001; Delcroix, 1998; Delcroix and McPhaden, 2002]. The measurement domain will include the open ocean more than 150 km from coastal and sea ice boundaries. These global SSS measurements will be made with ∼100 km resolution, every 8 days and will characterize salinity variability over the two year mission lifetime. These 100 km, 8 day cycle measurements will be averaged to produce a final monthly salinity product that has the spatial and temporal coverage and measurement accuracy that is needed to meet the Aquarius science goals. The Aquarius measurement accuracy and the spatial and temporal sampling seek to meet the needs of the GODAE requirements [Koblinsky and Smith, 2001]; even less accurate measurements would provide a major improvement in the current knowledge of SSS.

2. Radiometric Measurement of Ocean Salinity

  1. Top of page
  2. Abstract
  3. 1. Salinity Science Goals
  4. 2. Radiometric Measurement of Ocean Salinity
  5. 3. Aquarius Measurement Approach
  6. References
  7. Supporting Information

[7] Ocean surface salinity can be assessed using satellites that measure the microwave brightness temperature of seawater, Tb, which varies with SSS and sea surface temperature, SST [e.g., Blume et al., 1978; Swift and McIntosh, 1983]. At microwave frequencies, Tb is related to SSS and SST by the relation Tb = e × SST, where e is the emissivity of the sea surface, itself a function of SSS and SST. Over the typical range of oceanic SST values (0–32°C), the sensitivity of e to SSS increases as the frequency decreases from 1.5 to 0.4 GHz; however, since the sensitivity of the measurement to errors in SST increases over this range, a frequency in the range from about 800 to 1.5 GHz is optimal [Swift and McIntosh, 1983]. The protected frequency band at 1.413 GHz (L-band) has therefore been selected for measurement of salinity by Aquarius.

[8] For typical ranges of SSS and SST over the open oceans, the Tb at L-band has a range of about 4–6 K. The sensitivity of Tb to changes in SSS and SST is greatest in warm water (∼0.7 K/psu at SST = 30°C) and least in cold water (∼0.3 K/psu at SST = 0°C). Figure 2 shows TbV versus salinity for SST = 0, 15 and 30°C and for an incidence angle of 34°. The variation of Tb with incidence angle and polarization (the magnitude of TbV is ∼40 K greater than TbH) is accounted for in the microwave emission models [e.g., Klein and Swift, 1977] that are used in the Aquarius salinity algorithm.

image

Figure 2. Sensitivity of sea surface brightness temperature TbV to SST and salinity for an incidence angle of 34°.

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[9] Microwave measurements of salinity are complicated by several factors, the largest of which is the effect of sea surface roughness on microwave emissions. Since changes in sea surface roughness can produce a ΔTb of several K for very a rough sea surface, a very accurate means of measuring the sea surface roughness is required. In addition, due to the very short timescale of sea surface wind variability, the sea surface backscatter measurements must be accomplished simultaneously with the Tb measurements. For Aquarius, the sea surface roughness measurement will be made with 1.26 GHz scatterometers that have beams that are matched to each of the radiometer beams. Field measurements made in preparation for Aquarius using the JPL PALS instrument [Wilson et al., 2001a, 2001b] have empirically evaluated the changes in Tb as a function of surface roughness and wind speed, and the ability to make the needed corrections. The estimated error contribution due to surface roughness is given in Table 1 [Yueh et al., 2001]. A full sea surface state model developed as a part of the Aquarius program will further facilitate correction for roughness through calculation of sea surface emission as a function of microwave backscatter cross section.

Table 1. Aquarius Error Analysis for Sea Surface Salinity Retrieval Algorithm Using TbVa
Geophysical ParameterImpact on TbVSupplementary Data Set for CorrectionResidual Error in TbV, KSalinity Error at Midlatitudes
  • a

    The error analysis for TbH is similar, and the values are representative over the range of Aquarius incidence angles. Additional error reductions will result from use of both TbV and TbH in the salinity algorithm.

Surface roughness<5 Kscatterometer with ±3% (0.15 dB) stability0.150.27
SST±0.14 K per Δ1°C SSToperational SST products (±0.5°C)0.070.00
Dry air2.4–2.8 Koperational air pressure (±5 hPa) and temperature (±2°C) 0.070.13
Cloud liquid water<0.1 Koperational integrated columnar water vapor (±0.15 mm water)0.040.07
Rain cells<0.1 Kareas with heavy rain will be flagged0.020.04
Solar reflection<0.1 Kdiffuse scattering away from sun with solar emission known to 5%0.0050.01
Faraday rotation<5 Kpolarametric radiometer measurements provide <±0.2 K error0.020.04
Galactic<2 K + 3 K backgroundsky survey with 1% accuracy0.020.04
RSS of total geophysical error per observation0.200.33
Radiometer calibration stability per observation0.150.27
Radiometer NEΔT per observation0.060.10
RSS of total error per observation0.260.44
Average number of monthly Aquarius observations per 100 km grid cell9
Aquarius monthly average accuracy (psu), assuming 1√n improvement 0.15

[10] The retrieval of SSS consists, first, of satellite measurement of Tb and the sea surface roughness. The satellite-measured Tb value includes the actual emission Tb at the sea surface (due to SSS, SST, and surface roughness), plus galactic emissions that are reflected off the ocean surface and emissions from the atmosphere, rain, water vapor, and cloud liquid water. Additionally, atmospheric constituents absorb and scatter upwelling radiation, and the polarization of the radiation is altered as it passes through the ionosphere. The effects of each of these processes must be removed from the Tb that is measured at the satellite.

[11] Radiation from the galactic background [LeVine and Abraham, 2001] includes cosmic microwave background radiation which is constant in space and time at 2.7 K, plus hydrogen line emission and continuum radiation from extraterrestrial sources. Both are variable across the sky and can affect the measured Tb values by up to ∼2–3 K. This galactic radiation reflects off the sea surface and into the radiometer, but can be corrected for using data from the L-band sky surveys [LeVine and Abraham, 2001] plus a sea surface roughness/emission model that quantifies the reflection off the sea surface. The JPL PALS instrument [Wilson et al., 2001a, 2001b] has been used to verify that this approach is repeatedly accurate to better than 0.05 K.

[12] The atmosphere emits and absorbs at L-band due to molecular oxygen absorption of radiation [Blume et al., 1978]. The net atmospheric emission of 2.4 to 2.8 K that is measured by the satellite is proportional to atmospheric pressure [Yueh et al., 2001] and can be corrected for with a net residual error of 0.07 K (Table 1). The effects of water vapor are small and can effectively be ignored, and the Tb contribution due to cloud liquid water and the effects of heavy rain cells are small [Blume et al., 1978; Swift and MacIntosh, 1983; Ulaby et al., 1981]. These effects can be reduced using operational data [Yueh et al., 2001].

[13] The Faraday rotation (the change in direction of polarization of microwave emissions as the radiation passes through the ionosphere) can be corrected for using polarametric measurements [Yueh, 2000; Yueh et al., 2001; LeVine and Abraham, 2002]. Aquarius measurements of polarization signals will provide the third Stokes parameter, U, which can be used to correct for Faraday rotation with a residual error of <0.02 K. Aquarius data analysis will also include TbV + TbH, which is insensitive to Faraday rotation, to produce an alternative, lower sensitivity measurement of SSS that still meets measurement requirements.

[14] Reflected solar radiation will be avoided by pointing the Aquarius radiometers away from the sun toward the shaded side of Earth. During the summer solstice in the northernmost portion of the orbit, the footprint will be in sunlight, however, the induced error will be <0.01 K.

[15] Following the corrections for all the contributions to the Tb as measured at the satellite altitude, the Tb at the sea surface is calculated. Thereafter, the sea surface salinity is calculated from the sea surface Tb, SST, and the sea surface roughness, using empirical models of the sea surface roughness-emission relationship and of the dielectric constant of seawater [Klein and Swift, 1977].

3. Aquarius Measurement Approach

  1. Top of page
  2. Abstract
  3. 1. Salinity Science Goals
  4. 2. Radiometric Measurement of Ocean Salinity
  5. 3. Aquarius Measurement Approach
  6. References
  7. Supporting Information

[16] Observations of oceanic salinity using the L-band radiometer on Skylab first suggested the potential for monitoring salinity from space [Lerner and Hollinger, 1977]. Early design studies of a microwave sensor dedicated to the measurement of salinity [e.g., Blume et al., 1978; Swift and McIntosh, 1983] detailed the conceptual approach and the physics, including the required microwave emission model [Klein and Swift, 1977]. Since then, aircraft instruments and flight programs have addressed the technology of the L-band radiometer required to measure SSS from space (Figure 3) [LeVine et al., 1998, 2001; Wilson et al., 2001a, 2001b]. Based on these developments and on advancements in the development of RF hardware at L-band, the state of technology is now sufficient to produce an accurate L-band radiometer-scatterometer system that can be coupled with a planned global array of in situ salinity observations to provide the needed level of measurement accuracy.

image

Figure 3. Comparison of L-band radiometer and ship salinity measurements [LeVine et al., 1998].

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[17] The Aquarius mission design (Figure 4) includes V- and H-polarized, 1.413 GHz radiometers and a 1.26 GHz scatterometer. A 3 m offset parabaloid reflector will be illuminated by three separate feeds to produce three beams, each with a 5.5° beam width and a beam efficiency of 95%. The three beams will have incidence angles of 23.3°, 33.7°, and 41.7° and will sample the sea surface using the V- and H-polarization radiometers, plus the H-polarization scatterometer. The resultant three-beam swath-width of 250 km will give complete global coverage in 8 days, providing enough samples each month to meet the accuracy requirement through averaging (see Table 1 and Yueh et al. [2001]). The orbit will be a 6am/6pm orbit, with the beams directed toward the dark side of the earth in order to avoid reflected solar radiation. Data from both ascending and descending passes will be included for analysis, but may be processed differently, as the effects of diurnal variations in SST and Faraday rotation are accommodated.

image

Figure 4. Aquarius design concept showing the three feeds, the main reflector and the solar array.

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[18] As a part of the Aquarius project, all aspects of the data analysis algorithm are being reviewed and updated. These investigations include aircraft test programs [LeVine et al., 1998, 2001; Wilson et al., 2001a, 2001b] that used L-band aircraft radiometer systems plus validating surface measurements to demonstrate microwave radiometric measurements of salinity. Additional components of the Aquarius salinity algorithm development include laboratory re-evaluation of the seawater dielectric constant model, numerical simulations of individual components of the algorithm [e.g., LeVine and Abraham, 2001, 2002; Yueh et al., 2001], plus a full end-to-end simulation of the data algorithm system using ocean and atmospheric models plus field experiment data.

[19] The on-orbit calibration of the Aquarius instrument will include regular deep space calibration maneuvers, plus detailed vicarious calibration corrections that will address calibration drifts using a variety of vicarious data analysis approaches. Highly accurate in-situ measurements of SSS, SST, and surface winds are available from present and planned moored and drifting buoys, the automated Argo profiling buoy array, and volunteer observing ships. These data sources will provide ∼500 coincident observations per 8 day Aquarius repeat cycle. Vicarious calibrations approaches [e.g., Wentz et al., 2000; Ruf, 2000] have detailed the effects of spatial variability on comparisons between buoy and satellite radiometer measurements. These vicarious calibration approaches have been successfully applied to TRMM/TMI and TOPEX/POSEIDON TMR data that successfully reached the same Tb accuracy that is required for Aquarius.

[20] The Aquarius instrument design meets the oceanographic science needs within the constraints of measurement accuracy, spatial and temporal sampling requirements, and the need for global ocean coverage. The design is based on a heritage of proven technology that reduces the project risk and cost. This radiometer/scatterometer design heritage is based on the lessons from integration of similar systems on the PALS systems [Wilson et al., 2001a, 2001b], and on the Advanced Water Vapor Radiometer (AWVR; Randa et al. [2000]) which has demonstrated radiometer stability of ∼0.05 K over 30 day timescales; more than a factor of two better than required for Aquarius.

References

  1. Top of page
  2. Abstract
  3. 1. Salinity Science Goals
  4. 2. Radiometric Measurement of Ocean Salinity
  5. 3. Aquarius Measurement Approach
  6. References
  7. Supporting Information
  • Belkin, I. M., S. Levitus, J. Antonov, and S.-A. Malmberg, Great salinity anomalies in the North Atlantic, Prog. Oceanogr., 41, 168, 1998.
  • Blume, H.-J., B. Kendall, and J. Fedors, Measurement of ocean temperature and salinity via microwave radiometry, Boundary Layer Meteorol., 13, 295308, 1978.
  • Cronin, M. F., and M. J. McPhaden, Diurnal cycle of rainfall and surface salinity in the western Pacific warm pool, Geophys. Res. Lett., 26, 34653468, 1999.
  • Delcroix, T., Observed surface oceanic and atmospheric variability in the tropical Pacific at seasonal and ENSO timescales: A tentative overview, J. Geophys. Rev., 103, 18,61118,633, 1998.
  • Delcroix, T., and M. McPhaden, Interannual sea surface salinity and temperature changes in the western Pacific warm pool during 1992–2000, J. Geophys. Res., 107(C12), 8002, doi:10.1029/2001JC000862, 2002.
  • Dessier, A., and J.-R. Donguy, The SSS in the tropical Atlantic between 10S and 30N-Seasonal and interannual variations (1997–1989), Deep Sea Res., 41, 81100, 1994.
  • Dickson, R. R., J. Meincke, S.-A. Malmberg, and A. J. Lee, The great salinity anomaly in the northern north Atlantic, 1968–1982, Prog. Oceanogr., 20, 103151, 1988.
  • Donguy, J.-R., and G. Meyers, Seasonal variations of sea-surface salinity and temperature in the tropical Indian Ocean, Deep Sea Res., 43, 117138, 1996.
  • Klein, L., and C. Swift, An improved model for the dielectric constant of seawater at microwave frequencies, IEEE Trans. Antennas Propag., AP-25, 104111, 1977.
  • Koblinsky, C. J., and N. R. Smith (Eds.), Observing the Oceans in the 21st Century, 604 pp., Bur. of Meteorol., Melbourne, 2001.
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  • Lerner, R. M., and J. P. Hollinger, Analysis of 1.4 GHz radiometric measurements from Skylab, Remote Sens. Environ., 6, 251269, 1977.
  • LeVine, D. M., and S. Abraham, Galactic noise and passive microwave remote sensing from space at L-band, paper presented at International Geoscience and Remote Sensing Symposium (IGARSS 2001), Sydney, Australia, NASA, 2001.
  • LeVine, D., and S. Abraham, The effect of the ionosphere on remote sensing of sea surface salinity from space: Absorption and emission at L band, IEEE Trans. Geosci. Remote Sens., 40, 771782, 2002.
  • LeVine, D., M. Kao, R. Garvine, and T. Saunders, Remote sensing of ocean salinity: Results from the Delaware costal current experiment, J. Atmos. Ocean. Technol., 15, 14781484, 1998.
  • LeVine, D., C. Koblinsky, F. Pellerano, G. Lagerloef, Y. Chao, S. Yueh, and W. Wilson, The measurement of salinity from space: Sensor concepts, paper presented at International Geoscience and Remote Sensing Symposium (IGARSS 2001), Sydney, Australia, NASA, 2001.
  • Levitus, S., T. P. Boyer, M. E. Conkright, T. O-Brien, J. Antonov, C. Stephens, L. Statoplos, D. Johnson, and R. Gelfeld, NOAA/NESDIS 18, World Ocean Database, http://www.nodc.noaa.gov/OC5/WOD01/pr_wod01.html, Natl. Oceanogr. Data Cent., Silver Spring, Md., 1998.
  • Randa, J., L. Dunleavy, and L. Terrell, Stability measurements on noise sources, IEEE Trans. Instrum. Meas., 50, 368372, 2000.
  • Ruf, C., Detection of calibration drifts in spaceborne microwave radiometers using a vicarious cold reference, IEEE Trans. Geosci. Remote Sens., 38, 4452, 2000.
  • Swift, C., and R. McIntosh, Considerations for microwave remote sensing of ocean surface salinity, IEEE Trans. Geosci. Remote Sens., 21, 480491, 1983.
  • Ulaby, F. T., R. K. Moore, and A. K. Fung, Microwave Remote Sensing, chap. 4–5, Addison-Wesley-Longman, Reading, Mass., 1981.
  • Wentz, F., C. Gentemann, D. Smith, and D. Chelton, Satellite measurement of sea surface temperature through clouds, Science, 288, 847850, 2000.
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Supporting Information

  1. Top of page
  2. Abstract
  3. 1. Salinity Science Goals
  4. 2. Radiometric Measurement of Ocean Salinity
  5. 3. Aquarius Measurement Approach
  6. References
  7. Supporting Information
FilenameFormatSizeDescription
rds4808-sup-0001tab01.txtplain text document1KTab-delimited Table 1.

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