Atmospheric Corrections for Altimetry Studies over Inland Water
Abstract
:1. Introduction
2. Tropospheric Corrections
2.1. Dry Tropospheric Correction
2.1.1. DTC Estimation
2.1.2. Analysis of DTC Errors Present on Altimetric Products
- (1)
- For ERA Interim and NCEP, for all altimetric missions, the SLP is first interpolated in space and time from the available model grids and then reduced to surface height using Equation (6), while setting hs = 0. The surface height has been extracted from the DTU10 topographic data set, except for the Caspian Sea, where a constant value of −27 m was adopted. DTU10 are upgrades of the corresponding DNSC08 models [47]. The DTU10 topographic data set contains topographic information as follows: over land and most inland water regions, it contains the surface height above the geoid as modeled by a digital elevation model (DEM), while over oceans and over the Caspian Sea, it possesses bathymetric information.
- (2)
- For the ECMWF operational model, the DTC values are those extracted from the GDR products of each altimeter mission, without any modification, except for CryoSat-2, for which the correction has been computed from the model grids using the same procedure as in (1). For Geosat and GFO, only the DTC from ERA Interim and NCEP models are available. For T/P, J1 and J2, the AVISO GDRs have been used.
- (1)
- The DTC has been computed from SLP grids, with an expression similar to Equation (3) with no further reduction to the water surface level. For each location, this error is mainly a bias, which, for inland water at high altitudes, such as the Lake Titicaca (~3800 m), can reach 80 cm. Apart from a constant part, this error also has a seasonal component, since, according to Equation (6), an accurate height dependence of surface pressure can only be modeled by accounting for the seasonal variations of atmospheric pressure with temperature [43].
- (2)
- The DTC is estimated from surface pressure grids at the level of the model orography. This will induce interpolation errors, due to the fact that the model orography might depart significantly from the actual surface height. In regions of large variations in terrain height, such as a river in a deep valley or a lake surrounded by high mountains, even if the model orography correctly fits the terrain heights, there may be a large difference between the DTC at the points over the mountains and the DTC at the center of lake or river. This may cause along-track interpolation errors at the decimeter level, with a linear decrease/increase in the DTC as the points approach the center of the lake, reported as “V shape” errors by, e.g., [5], and illustrated in Figures 3 and 4 for Lake Tanganyika.
- (3)
- The DTC has been computed from SLP grids, with an expression, such as Equation (3), with further reduction to the surface water level, for each along-track altimeter location, using an appropriate height reduction. Studies by [43] show that, for heights up to 1000 m, Equation (6) provides the DTC with an accuracy of a few millimeters if an accurate DEM is adopted and the GPT climatological model is used to model the seasonal dependence of atmospheric pressure on temperature. Further research is required to find out how these results can be extended to larger heights, up to 4000 or 5000 m, since a few continental water regions of interest exist at these altitudes. Preliminary results indicate that for these altitudes, errors due to the inaccurate modeling of both the height and the temperature dependence of surface pressure are expected.
- (1)
- For each atmospheric model SLP grid node, compute the correction at sea level using Equation (3) and setting hs = 0.
- (2)
- Interpolate for each altimeter measurement location.
- (3)
- Apply height reduction using Equation (6) and a model topography, such as DTU10 (apart from the Caspian Sea, where a mean sea height must be adopted). Users may also use a local and more precise DEM where available. For studies over lakes or reservoirs, for example, it will be preferable to use the mean lake height instead. In the implementation of Equation (6), the surface temperature can be obtained from the values of the temperature at mean sea level given by the GPT climatologic model and considering a mean normal lapse rate of temperature with height of −0.0065 K/m.
2.2. Wet Tropospheric Correction
2.2.1. WTC Estimation
2.2.2. Analysis of WTC Errors Present on Altimetric Products
2.3. Examples of Case Studies
3. Ionospheric Correction
3.1. Estimation of the Ionospheric Correction
3.2. Analysis of Issues Regarding the Computation of the Ionospheric Correction over Inland Waters
4. Discussion and Conclusions
Acknowledgements
Conflict of Interest
- Author ContributionsAll authors contributed to the conception of the paper, data processing, analysis and discussion, writing of the manuscript and its overall editing and revision.
References and Notes
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Models | RADS | Envisat GDR | Jason GDR |
---|---|---|---|
Description | Multi-satellite altimeter database. Though originally developed for ocean data, currently contains 1-Hz data over all terrains, including some focus on inland data. | Geophysical Data Records. Applicable primarily to oceans. Include dedicated inland algorithms. | Geophysical Data Records. No specific land processing at all. |
Version | RADS version 3; version 4 is under development. Data updated twice daily with new data and frequently when better models become available or bugs are found. | GDR v2.1. Require additional external instrumental corrections. May be updated in a few years. | Jason-1: version GDR-C; Jason-2: version GDR-D, version GDR-E under development; will be released in a year. |
Data rate | 1-Hz, multi-Hz option in RADS v4. | 20-Hz range, SWH, backscatter. All corrections at 1-Hz | |
Retrackers | Ocean only. | Ocean, sea ice, ice1, ice2 | Ocean only. MLE4 (J2: also MLE3) |
Dry tropospheric correction | Three corrections are provided: (1) based on ECMWF analysis (same as GDRs); (2) based on sea-level pressure (SLP) fields from NCEP analysis; (3) based on SLP from ERA Interim reanalysis. Both (2) and (3) are corrected for elevation as described in Section 2.1.1, and air tides are taken into account. For long-term stability, ERA Interim is recommended. | Based on surface pressure fields from ECMWF operational analysis. The limited resolution of the background topography model and the development of the model in the frequency domain led to the errors discussed in Section 2.2. Only the most recent GDRs (Jason GDR-D standards) take air tides into account. | |
Model wet tropospheric correction | Three corrections are provided: (1) based on ECMWF analysis (same as GDRs); (2) based on total column water vapor and near-surface temperature from NCEP, as described in Section 2.2.1; (3) same as in (2) from ERA Interim reanalysis. For long-term stability, ERA Interim is recommended. | Based on multi-layer water vapor fields and temperature from ECMWF operational analysis. Integrated vertically to obtain six-hourly wet tropospheric correction fields used in the multi-mission environment. | |
Radiometer wet tropospheric correction | Based on brightness temperatures in GDR products, corrected for drift and gain loss, applying appropriate algorithm per satellite. | Based on radiometer brightness temperatures and neural network (Envisat) or parametric (Jason) algorithms. Drift correction already applied in GDR. Same as RADS. | |
Dual-frequency ionospheric correction | Dual-frequency altimeters only: based on difference in the Ku-band and S- or C-band range. Recomputed taking into account range biases in secondary channel. An along-track smoothed version is also provided. | Based on difference in the Ku-band and S- or C-band range. Does not take range biases into account. Not available on Envisat since the failure of the S-band on 27 January 2008. | |
GIM ionospheric correction | Based on JPL maps of TEC at two-hourly intervals. Corrected for altitude by a constant scale factor. Only available after September, 1998, period for which the it is the recommended ionospheric correction. | Same as RADS, but altitude correction is unclear. | Same as RADS, but not corrected for altitude, thus overestimating ionospheric correction. |
Ionospheric correction based on climatology | Two corrections, based on IRI2007 and NIC09. The latter is a significant improvement over the former, as it is based on GPS data [28]. Prior to September 1998, NIC09 is recommended. | Based on Bent model; antiquated model from the 1970s. Vastly underestimates ionospheric correction during high solar activity [29,30]. | |
Ocean and load tides | FES2004 and GOT4.8 available. Ocean tide does not include loading. | FES2004 and GOT4.8 available. Ocean tide does include loading. | |
Pole tide | Based on [31]. Properly takes into account different Love numbers for ocean, land and lakes. | Same as RADS. Used to have incorrect Love number over inland waters in older GDR versions. |
Models | Mean | Stand. dev. | Min | Max | |
---|---|---|---|---|---|
T/P | MWR-ERA | −1.4 | 2.2 | −11.1 | 5.1 |
MWR-ECMWF | 9.3 | 3.2 | −1.8 | 20.8 | |
MWR-NCEP | −4.6 | 2.7 | −14.5 | 4.7 | |
J1 | MWR-ERA | 0.6 | 2.3 | −19.2 | 8.7 |
MWR-ECMWF | −0.5 | 2.1 | −22.2 | 5.6 | |
MWR-NCEP | −3.2 | 2.8 | −21.7 | 5.7 | |
J2 | MWR-ERA | 0.3 | 2.0 | −9.6 | 6.5 |
MWR-ECMWF | −0.6 | 1.6 | −9.0 | 6.2 | |
MWR-NCEP | −2.8 | 3.0 | −13.8 | 6.1 | |
EN | MWR-ERA | 1.3 | 4.1 | −19.8 | 11.5 |
MWR-ECMWF | 0.1 | 4.0 | −25.9 | 9.8 | |
MWR-NCEP | −1.8 | 4.4 | −27.6 | 9.7 |
Models | Mean | Stand. dev. | Min | Max | |
---|---|---|---|---|---|
T/P | MWR- RA | 0.4 | 1.6 | −18.1 | 8.8 |
MWR-ECMWF | 0.3 | 2.0 | −18.6 | 10.0 | |
MWR-NCEP | −0.8 | 2.9 | −18.5 | 9.0 | |
J1 | MWR-ERA | 0.3 | 1.8 | −17.8 | 8.5 |
MWR-ECMWF | 0.6 | 1.7 | −18.5 | 11.4 | |
MWR-NCEP | −0.5 | 3.4 | −22.8 | 11.0 | |
J2 | MWR-ERA | 0.3 | 1.8 | −17.8 | 9.1 |
MWR-ECMWF | 0.5 | 1.4 | −9.2 | 10.7 | |
MWR-NCEP | −0.4 | 3.2 | −21.2 | 9.3 | |
EN | MWR-ERA | 0.5 | 3.2 | −20.0 | 9.5 |
MWR-ECMWF | 0.8 | 3.1 | −22.9 | 11.1 | |
MWR-NCEP | −0.1 | 4.0 | −28.0 | 9.3 |
Jason-1 | JPL GIM | Dual-Frequency | Smoothed Dual-Frequency |
---|---|---|---|
N-W Atlantic | 88.5 | 89.2 | 85.5 |
Great Lakes | 64.2 | 64.0 | 64.3 |
Envisat | JPL GIM | Dual-Frequency | Smoothed Dual-Frequency |
N-W Atlantic | 129.5 | 129.7 | 129.3 |
Great Lakes | 62.9 | 63.1 | 62.7 |
© 2014 by the authors; licensee MDPI, Basel, Switzerland This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/).
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Fernandes, M.J.; Lázaro, C.; Nunes, A.L.; Scharroo, R. Atmospheric Corrections for Altimetry Studies over Inland Water. Remote Sens. 2014, 6, 4952-4997. https://doi.org/10.3390/rs6064952
Fernandes MJ, Lázaro C, Nunes AL, Scharroo R. Atmospheric Corrections for Altimetry Studies over Inland Water. Remote Sensing. 2014; 6(6):4952-4997. https://doi.org/10.3390/rs6064952
Chicago/Turabian StyleFernandes, M. Joana, Clara Lázaro, Alexandra L. Nunes, and Remko Scharroo. 2014. "Atmospheric Corrections for Altimetry Studies over Inland Water" Remote Sensing 6, no. 6: 4952-4997. https://doi.org/10.3390/rs6064952