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The SARAL/AltiKa mission: A step forward to the future of altimetry

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The SARAL/AltiKa mission: A step forward to the future of altimetry

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The CNES/ISRO altimetric satellite SARAL/AltiKa was launched in February 2013 and since then has provided useful data for various scientific and operational applications in oceanography, hydrology, cryospheric sciences and geodesy. However, a Reaction Wheel problem forced relaxation of the repeatability constraint on the satellite’s orbit, which has been drifting slowly since July 2016. Beyond the expected contributions of this mission and its very good integration into the objectives of the constellation of altimetric satellites, it has become more and more apparent that specific contributions and innovations related to the main specification of SARAL/AltiKa, that is to say the use of the Ka-band, have clearly emerged. The advantages of the Ka-band are in short the reduction of ionosphere effects, the smaller footprint, the better horizontal resolution and the higher vertical resolution. A drawback of the Ka-band is the attenuation due to water/water vapor in case of rain and the resulting loss of data. The main objective of this paper is to highlight the specific advances of the Ka-band in different scientific and technical fields and to show why they are promising for the future and open the way to several missions or mission projects. Although unplanned initially, the fine coverage of the Drifting Phase brings some interesting openings especially for geodesy and hydrology applications.
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The SARAL/AltiKa mission: A step forward to the future of altimetry
Jacques Verron
a,
, Pascal Bonnefond
b
, Ole Andersen
c
, Fabrice Ardhuin
d
Muriel Berge
´-Nguyen
e
, Suchandra Bhowmick
f
, Denis Blumstein
e,g
, Franc¸ois Boy
g
Laurent Brodeau
h
, Jean-Franc¸ois Cre
´taux
e,g
, Mei Ling Dabat
e
,Ge
´rald Dibarboure
g
Sara Fleury
e
, Florent Garnier
e
, Lionel Gourdeau
e
, Karen Marks
i
, Nade
`ge Queruel
g
,
David Sandwell
j
, Walter H.F. Smith
i
, E.D. Zaron
k
a
Institut des Ge
´osciences de l’Environnement, CNRS, CS 40700, 38 058 Grenoble Cedex 9, France
b
Observatoire de Paris, SYRTE, 77 avenue Denfert Rochereau, 75014 Paris, France
c
DTU SPACE, National Space Institute, Technical University of Denmark, Elektrovej, 2800 Kgs. Lyngby, Denmark
d
LOPS, IFREMER, CS 10070, 29280 Plouzane
´, France
e
LEGOS, 14 Avenue Edouard Belin, 31400 Toulouse, France
f
ISRO, Oceanic Sciences Division, Space Applications Centre, Ambawadi Vistar P.O., Ahmedabad 380015, India
g
CNES, 18 Avenue Edouard Belin, 31400 Toulouse, France
h
OCEAN NEXT, 90 chemin du Moulin, 38660 La Terrasse, France
i
Laboratory for Satellite Altimetry, NOAA, 5830 University Research Court, College Park, MD 20740, USA
j
Scripps Inst. of Oceanography, 8622 Kennel Way, La Jolla, CA 92037, USA
k
Department of Civil and Environmental Engineering, Portland State University, P.O. Box 751, Portland, OR 97207-0751, USA
Received 28 June 2019; received in revised form 20 January 2020; accepted 23 January 2020
Abstract
The CNES/ISRO altimetric satellite SARAL/AltiKa was launched in February 2013 and since then has provided useful data for var-
ious scientific and operational applications in oceanography, hydrology, cryospheric sciences and geodesy. However, a Reaction Wheel
problem forced relaxation of the repeatability constraint on the satellite’s orbit, which has been drifting slowly since July 2016. Beyond
the expected contributions of this mission and its very good integration into the objectives of the constellation of altimetric satellites, it
has become more and more apparent that specific contributions and innovations related to the main specification of SARAL/AltiKa,
that is to say the use of the Ka-band, have clearly emerged. The advantages of the Ka-band are in short the reduction of ionosphere
effects, the smaller footprint, the better horizontal resolution and the higher vertical resolution. A drawback of the Ka-band is the atten-
uation due to water/water vapor in case of rain and the resulting loss of data. The main objective of this paper is to highlight the specific
advances of the Ka-band in different scientific and technical fields and to show why they are promising for the future and open the way to
several missions or mission projects. Although unplanned initially, the fine coverage of the Drifting Phase brings some interesting open-
ings especially for geodesy and hydrology applications.
Ó2020 Published by Elsevier Ltd on behalf of COSPAR.
Keywords: Satellite; Altimetry; Ka-band
1. Introduction
The SARAL (‘‘Satellite with ARgos and ALtiKaalso
meaning ‘‘Easyin Sanskrit) mission is jointly conducted
https://doi.org/10.1016/j.asr.2020.01.030
0273-1177/Ó2020 Published by Elsevier Ltd on behalf of COSPAR.
Corresponding author.
www.elsevier.com/locate/asr
Available online at www.sciencedirect.com
ScienceDirect
Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
by the Indian Space Agency (ISRO) and the French Space
Agency (CNES). SARAL was launched on February 25,
2013. Calibration and validation investigations have shown
that the quality of the data meets the expectations and ini-
tial mission requirements as discussed for example in
Bonnefond et al. (2018). Data have been delivered to users
in a very rapid manner. They are available on EUMET-
SAT, CMEMS and CNES servers. The quality of all prod-
ucts was in line with mission requirements. Many scientific
investigations have been undertaken and a large part of the
scientific community has quickly seized the opportunity
offered by these data.
In 2015, SARAL/AltiKa exhibited an increasing need to
reduce the stress on its Reaction Wheels in order to extend
the mission beyond the nominal lifetime of the satellite.
ISRO and CNES eventually decided that the best strategy
was to stop all orbit control maneuvers and to let the alti-
tude decay naturally. SARAL/AltiKa left its repetitive
orbit to begin a new phase named ‘‘Drifting Phase(DP)
starting July 4, 2016 (Dibarboure et al., 2018). Data pro-
cessing and data latency were unchanged. From this date,
SARAL satellite has flown free of station keeping maneu-
vers. The repetitive ground track is no longer maintained
and with the natural decay of the orbit, the ground track
is slowly drifting. In short, this new orbit configuration
has required some adjustment for users, particularly in
hydrology, given the need to adapt the algorithms. On
the contrary, some other uses profit from this new orbital
configuration.
The SARAL/AltiKa’s main scientific objectives were to
provide data to oceanographers to improve knowledge and
understanding of the ocean mesoscale variability. These
scientific objectives regarding mesoscale ocean dynamics
come under different aspects: observations, theoretical
analyses, modeling and data assimilation. Climate studies
are also concerned by SARAL/AltiKa not only through
the improved access to the sea-level measurements but also
by contributing to understand the role of mesoscale fea-
tures on the climate variability. Coastal oceanography
was also directly interested by the SARAL/AltiKa data
as well as many downstream applications including opera-
tional oceanography. SARAL/AltiKa’s other objectives
include inland waters (lakes, rivers, enclosed seas), moni-
toring of sea-level changes, polar oceans, wave and wind
fields, continental and sea ice, etc. Since the beginning of
the mission, the SARAL/AltiKa Ka-band altimetric mis-
sion has taken a full position in the altimetric satellite con-
stellation that has been built over years providing a major
push to oceanographic sciences. The scientific results are
exemplified by the special issue dedicated to SARAL/
AltiKa (Verron and Picot, 2015) and many other papers.
The purpose of the present paper is to go further in these
directions by highlighting how the specific features of
SARAL/AltiKa has allowed new openings both in terms
of data, science and applications and to discuss how a
Ka-band satellite such as SARAL/AltiKa opens the way
to future satellite projects. The paper is written by first
quickly recalling two aspects of the SARAL/AltiKa mis-
sion: the technological continuity and its gapfiller role.
Indeed, SARAL/AltiKa has been designed in a technolog-
ical continuity with other altimetry satellites, building on a
true maturity of altimetry technology: it is a remarkable
dimension of this mission whose main aspects are quickly
recalled in Section 2. But SARAL/AltiKa also aimed at
being a gapfiller between Envisat and Sentinel-3A: we
briefly recall how SARAL/AltiKa fulfilled this objective
in Section 3.
But the essential purpose of this paper is to discuss how
SARAL/AltiKa has been a real driver of innovation. In
Section 4, we discuss on the case of the resolution of the
oceanic mesoscales and the openings towards the Surface
Water Ocean Topography Mission (SWOT) (e.g. Durand
et al., 2010; Biancamaria et al., 2016) and of the capability
of SARAL/AltiKa to access to the snow depth and then to
the openings towards the CRISTAL mission project. In
Section 5, the role of SARAL/AltiKa as a demonstrator
for the SKIM and for the SMASH mission projects is
evoked. Section 6discusses more specifically of the Drifting
Phase and the openings that are offered in geodesy and for
lakes observations. Conclusions are provided in Section 7.
2. Technological continuity
It is useful to remember that SARAL/AltiKa relies on a
great maturity of the altimetry technology and a long his-
tory Vincent et al. (2006). The SARAL satellite is com-
posed of a spacecraft bus developed by the Indian Space
Agency (ISRO), and a payload developed by the French
Space Agency (CNES). As its full name indicates, two mis-
sions are onboard the SARAL satellite: The AltiKa altime-
ter component – of interest here – and ARGOS-3. The
altimeter payload includes first the AltiKa Altimeter-
Radiometer in Ka-band, a DORIS system for precise orbit
determination (POD), and a Laser Retro-reflector Array
instrument used for precise calibration of other POD
instruments (Steunou et al., 2015). The altimeter shares
the antenna with a bi-frequency radiometer required to
correct the altimeter range for the wet troposphere path
delay. AltiKa is a nadir-looking altimeter in line with
Poseidon-3 on-board Jason-3 and other existing altimeters,
but operates in a single frequency band, the Ka-band.
Ka-band offers a number of advantages and has some
possible drawbacks. Ka-band is much less affected by the
ionosphere than Ku-band (Steunou et al., 2015). It is this
reduced ionosphere effects in Ka-band that makes it possi-
ble to use a mono-frequency altimeter and implicitly
removes the noise of the ionosphere derived from dual-
frequency for other missions. The Ka-band high frequency
(35.75 GHz, to be compared to 13.5 GHz on Jason-2/3)
leads to a smaller footprint (8 km diameter, to be compared
to 20 km on Jason-2/3 and to 15 km for Envisat) and to a
better horizontal resolution. Ka-band allows to use a larger
bandwidth (480 MHz to be compared to 320 MHz on
Jason-2/3). This 480 MHz bandwidth provides a high
2J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
vertical resolution (0.3 m) which is better with respect to
other altimeters. The higher Pulse Repetition Frequency
(4 kHz to be compared to 2 kHz on Jason-2/3) permits a
decorrelation time of sea echoes at Ka-band shorter than
at Ku-band, then allowing a better along-track sampling
(40 Hz vs. 20 Hz). This makes possible to increase signifi-
cantly the number of independent echoes per second com-
pared with Ku-band altimeters. This low ionospheric
attenuation can even be considered as negligible, except
for some exceptional ionospheric situations. It discards
the need for a dual-frequency altimeter. Ka-band provides
a better estimation of sea surface roughness than at
Ku-band (see e.g. Bhowmick et al., 2015; Abdalla, 2015).
The 8 mm wavelength in Ka-band is better suited to
describing the detailed slopes of the sea surface and gives
a more accurate measurement of the backscatter coefficient
over calm or moderate seas, thus leading to a noise reduc-
tion of a factor of two compared to Jason-class altimeters
for wave heights greater than 1 m. With Ka-band, there is a
lower radar penetration of snow and ice: penetration of
snowpack is less than 3 cm for snow on sea ice and 1 m
for continental ice, around ten times less than for
Ku-band. The altimetric observation and height restitution
thus correspond to a thin subsurface layer.
A possible drawback of Ka-band was that the attenua-
tion due to water or water vapor in the troposphere might
affect Ka-band pulses in case of rain and increase signifi-
cantly the rate of missing data for strong rain rates. In fact,
this was not found to be true, thanks in particular to a fine
tuning of the data processing (more especially the flagging
algorithm as discussed in particular by Tournadre et al.,
2015), and rain had little influence on data availability
and quality.
3. A gapfiller between Envisat and Sentinel-3A
The SARAL/AltiKa orbit is almost polar (98.55°of
inclination), sunsynchronous and with a 35-day repeat
cycle. These orbit characteristics of SARAL/AltiKa were
chosen to be the same as Envisat. The practical objectives
were to continue the time series and to benefit from the
existing mean sea surface thanks to long term mean sea
profiles from ERS-1/2 and Envisat. As a consequence,
the SARAL/AltiKa mission was considered as a ‘‘gap
fillerbetween Envisat (lost in April 2012) and Sentinel-
3A (launched in February 2016). This gap filler objective
is almost fully fulfilled: because of the late launch of
SARAL/AltiKa compared to the loss of Envisat there is
however a gap of 8 months.
In particular, we can notice the key contributions of
SARAL/AltiKa to the Data Unification and Altimeter
Combination System (DUACS) products on the corre-
sponding period. The DUACS production system is used
for the operational production of sea level products for
the Marine (CMEMS) and Climate (C3S) services of the
EU Copernicus program, for the processing of the
Sentinel-3 products on behalf of EUMETSAT and for
the production of demonstration and pre-operational
products on behalf of CNES. As discussed in Dibarboure
et al. (2018) and Verron et al. (2018) for example,
SARAL/AltiKa contributed to around 45% of the input
data to DUACS during the period ranging from Spring
2013 to Nov. 2016. Even in the recent period since Nov.
2016, including after the launch of Sentinel-3, SARAL/
AltiKa contributes to something between 25 and 30% of
the altimeter data flow.
4. Some innovations from SARAL/AltiKa and openings for
ocean, snow and ice observations
The main objective of this paper is to discuss how much
SARAL/AltiKa was and is innovative and what routes are
opening for the future thanks the pioneer role of SARAL/
AltiKa. Two emblematic examples are discussed below, the
case of the oceans and the one of snow and ice.
4.1. An improved access to the fine scales of the ocean and a
playground for the SWOT mission
The first and most obvious of these routes is that opened
by the good horizontal resolution and low noise of the
SARAL/AltiKa measurement of the Sea Surface Height
(SSH) for oceanography. This allows better access to ocea-
nic mesoscales and their variability. And it is no coinci-
dence that the SWOT mission will be launched in 2021
using the Ka-band for its KaRin main radar instrument.
Let us comment a little more about access to the mesos-
cales. This is also a SARAL/AltiKa’s main scientific objec-
tive to improve our knowledge of the ocean mesoscale
variability, mainly associated to eddies, meandering cur-
rents, fronts, filaments and squirts. The mesoscale variabil-
ity refers to ocean signals with space scales of 50–500 km
and time scales from a few days to a few months.
Technological advances in all of the recent satellite
altimeter missions have improved their signal-to-noise
ratio, allowing us to observe finer-scale ocean processes
with along-track altimeter data. Using 1 Hz data,
Vergara et al. (2019) revisited global SSH wavenumber
spectra from recent altimetric missions. With specific edit-
ing for SARAL/AltiKa, they show the dramatic improve-
ment in SSH error levels achieved by Sentinel-3A, which
is around 40% better than SARAL/AltiKa error level (itself
30% better than Jason-2), whatever distinct seasonal and
geographical variations related to local oceanic/atmo-
spheric conditions such as Significant Wave Height
(SWH), rain cells, wind streaks and ocean slicks. Their
results confirm the globally-averaged SSH wavenumber
spectra from the different missions described in Verron
et al. (2018) (their Fig. 1) when analyzing high resolution
data (20/40 Hz). For the Jason-SARAL/AltiKa class
altimeters, this statistical estimate of the altimetric noise
and the observable scales are largely constraint by a
spectral hump in the 10–40 km wavelength range due to
the inhomogeneities in the ocean surface, as well as
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 3
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
atmospheric events that does not exist for a SAR altimeter
such as Sentinel-3A. Dibarboure et al. (2014) shows that
oceanography users interested in small-scale SSH signals
can mitigate the hump corruption by using better editing
and post-processing algorithms. They test two simple edit-
ing procedures on the 20 Hz Jason data: a running stan-
dard deviation threshold and a nonlinear iterative editing
filter. Both methods exhibit a substantial mitigation of
the hump. The shape of SSH spectra for the shorter wave-
length change drastically, especially for the SARAL mis-
sion with an error level below the Sentinel-3A error level
as shown by the globally-averaged SSH wavenumber spec-
tra from the different missions described in Bonnefond
et al. (2018) (their Fig. 12). The data-editing step is an
important phase of altimeter data processing because it
determines the quantity and quality of the measurements
ultimately available that directly impact the estimation of
SSH wavenumber spectra. Using 1 Hz SARAL/AltiKa
data, Gourdeau et al. (2017) propose two new editing pro-
cedures: a specific median filter applied on the SSH data set
(MAD filter), and a clustering editing procedure based on a
subset of GDR parameters that improve the data-editing
step especially in coastal areas.
Here we show that a careful data editing on 1 Hz data to
filter out outliers modifies the shape of the SSH spectra.
Such editing criteria are tested in open-ocean by the use
of a MAD filter. Spectra are representative of a 1500
1500 km square box chosen south of New Caledonia in
an area of strong mesoscale variability (Fig. 1). The
difference in the editing procedure by comparison with
Fig. 1. Wavenumber spectra of SSH anomalies (in m
2
/cpkm) from the 1 Hz along-track data representative of a 1500 km 1500 km box located southeast
of New Caledonia (34°–20°S; 168°–180°E) for three different missions: Jason-2 (J2 in green); Sentinel-3A (S3A in red); and SARAL/AltiKa (SRL in blue)
when using the standard editing procedure recommended in the User Handbook. SARAL/AltiKa is particularly sensitive to the editing criteria, and
applying an additional MAD filter on the along track data modifies greatly the shape of the SARAL/AltiKa spectrum for wavelengths shorter than 90 km
(SRL in black). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
4J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
the standard procedure recommended in the User Hand-
book does not change the spectral characteristic for the
Jason-2/3 and Sentinel-3A mission. But the effect is partic-
ularly significant for wavelength finer than 90 km when
using SARAL/AltiKa data even if the MAD filter rejects
only 4% of the data. One explanation is the reduced foot-
print and the sensitivity of the Ka-band to the atmospheric
conditions compared to the Ku-band. If the estimation of
the mesoscale spectral slope is similar whatever the satellite
missions with a k3:5slope characteristic of a SQG dynam-
ics, the error level (estimated by fitting a straight line to the
Sea Level Anomaly (SLA) spectra for wavelengths smaller
than 30 km) is drastically reduced to 1.3 cm for the
SARAL/AltiKa mission when using the MAD filter. The
noise level of SARAL/AltiKa is lower compared to
Jason-2 and Sentinel-3A as already illustrated at global
scale by Bonnefond et al. (2018) with the effect to observe
20% (10%) smaller features than Jason-2 (Sentinel-3).
SARAL/AltiKa can observe wavelengths of 70 km,
whereas Jason-2 only allow to observe wavelengths of
90 km, and 80 km for Sentinel-3A.
Then, at this stage, the benefit of the Ka-band is clearly
illustrated when looking at the finest scales. If working on
the raw 40 Hz data is the best way to reduce the hump
effect that affects wavelength up to 100 km (Dibarboure
et al., 2014), a more easier editing procedure based on
1 Hz data provide similar results based on a spectral
approach. In general, we find that the latest generation
altimetry satellites are consistent among themselves with
respect to the spectral behavior at the largest scales. For
the smaller scales, the level of error and effective resolution
appears to be better with SARAL/AltiKa.
The mesoscale resolution capability of present genera-
tion altimeters is improving our understanding of the con-
tribution of mesoscale processes on the ocean circulation.
As such, SARAL/AltiKa observations are particularly well
suited to assess the ability of high-resolution ocean models
to resolve these mesoscale processes (see for example Le
Sommer et al., 2018 on the status of current ocean models).
Meanwhile, it is the same numerical models that are pre-
sently used to prepare the SWOT mission, both when it
comes to simulating the submesoscale altimetric signal that
SWOT will actually ‘‘seeand to generate synthetic data to
prepare post-processing. SARAL/AltiKa therefore plays
an important, indirect, yet critical, role in the preparation
of upcoming high-resolution altimetry missions like
SWOT.
Here we illustrate how SARAL data are used to perform
a spectral comparison of the simulated ocean surface state
from a submesoscale-permitting twin-experiment per-
formed with eNATL60 to observations. eNATL60 is a
basin-scale North Atlantic configuration of the NEMO
model (https://www.nemo-ocean.eu/) at unprecedented
horizontal and vertical resolutions (1/60°and 300 levels
respectively) (Fig. 2). Technically, the horizontal grid reso-
lution of eNATL60 varies from 0.8 up to 1.6 km and the
effective resolution has been shown to be about 10 km.
These simulations were supported through an allocation
from the EU PRACE program (www.prace-ri.eu/).
SARAL/AltiKa data is used for spectral evaluations of
the SSH generated by these simulations and in particular
for assessing the energy contribution of the internal tide
to the SSH signal. As shown in Fig. 3, the model behavior
is close to SARAL/AltiKa for large scales down to
80 km. The inclusion of tidal forces leads to a significant
energy increase of the SSH signal at smaller scales. The
energy level is much more pronounced in Summer, because
of the strong stratification, more conducive to the genera-
tion and spread of the internal tide. At these fine scales,
the cascade of energy approaches a slope in k2, peculiar
to a flow regime dominated by wave turbulence. Still at
these fine scales, the altimetry signal measured by
SARAL/AltiKa (and other current satellites) is obscured
by the noise and therefore does not allow a direct con-
frontation with the model. At scales larger than typically
100 km, on the other hand, the flow is balanced, and in
agreement with the QG theory, the cascade of energy fol-
lows a slope in k5, in excellent agreement with SARAL/
AltiKa.
Combining the knowledge of a realistic virtual surface
state of the ocean at the kilometer scale resulting from
these simulations to the knowledge of an observed surface
state from SARAL/AltiKa data, will allow to start unrav-
elling some aspects of the mesoscale dynamics with regard
to the tidal effects and internal waves, the seasonality effect,
regional aspects, etc ...All this for the purpose of improv-
ing the knowledge of ocean surface dynamics that will
allow better use and interpretation of future SWOT data.
Note that in the frame of the Copernicus extension
beyond 2030, it is envisaged to replace nadir altimeters
for Sentinel-3 by wide-swath altimeters. A study named
WiSA (Wide-Swath Altimetry) is currently in phase A in
collaboration between CNES and ESA, and SARAL/
AltiKa technology and data are also strongly contributing
to the design of such mission.
Finally it is found that the transition to the SARAL-DP
has no significant drawback on the mesoscale sampling
capability. Dibarboure et al. (2012) demonstrated that it
could be possible to find geodetic orbits that were compat-
ible with mesoscale monitoring: this was achieved by
including so-called ‘‘orbit sub-cyclesthat maximize the
ocean mesoscale sampling over a period of 15–20 days.
But this study was carried out in the context of a well-
maintained altitude, and the mesoscale sampling properties
of altitude-decaying orbits had not been studied so far. DP
demonstrated that it is possible for altimeter missions to
keep a good mesoscale sampling for years even if their alti-
tude is not actively maintained and even if it decays due to
the atmospheric drag. Indeed, Dibarboure et al. (2018)
report that the orbit sub-cycles evolve in slow and contin-
uous way over a few kilometers of altitude. Because the
SARAL orbit is affected by a moderate atmospheric drag
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 5
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
(altitude loss of approximately 20 cm/day), the satellite will
remain in an altitude range with mesoscale-compatible
orbit sub-cycles for many years. Fig. 4 from Dibarboure
et al. (2018) explains why the SARAL-DP was initiated
approximately 1 km above the ERS/Envisat orbit. Indeed,
even accounting for the altitude loss, the sampling pattern
of DP remains controlled by 13, 16 and 19-day sub-cycles,
i.e. a good combination for mesoscale for 6 years or more.
The quality of mesoscale observation is measured using the
decorrelation between adjoining SARAL/AltiKa tracks.
When the altimeter tracks are very close from one another
(e.g. distance shorter than the decorrelation scales of ocean
mesoscale), they provide duplicate mesoscale content. In
turn, other regions of the ocean are poorly sampled which
results in an overall degraded observation capability (see
Dibarboure et al., 2012).
4.2. A unique tool for sea ice and snow cover observation and
a key step for the CRISTAL mission
The observations of sea ice and snow is a primary
importance for the climate. Whereas the global warming
can be characterized by many parameters, one of the most
demonstrative is the reduction of the Arctic Sea Ice area in
Summer that has lost about 13% of its surface with regard
to the previous decade. This phenomenon is mainly
explained by the differences of albedos between the sea
ice, its snow cover and the surrounding ocean, which are
respectively of about 0.5, 0.9 and 0.1: under the influence
of the global warming, the ice tends to melt, offering a lar-
ger surface of ice-free ocean that absorbs 2–9 times more of
the solar energy than ice. In its turn this extra heat acceler-
ates the ice melting. This positive feedback explains the
Arctic amplification of the global warming. The Arctic
sea ice is both a key witness and an actor of the global cli-
mate, although clearly there are strong regional effects.
Arctic and Austral sea ice has been mainly survey with
optical, thermic and radiometric satellite images. They
have allowed monitoring of the sea ice extent and concen-
tration daily since the late Seventies. These observations
have largely contributed to improve sea ice models and
are now frequently used to constraint such models for
short-term forecasts of the sea ice extent (e.g. Screen and
Simmonds, 2010). Nevertheless numerous publications
have recently demonstrated that these forecasts can be lar-
gely improved when assimilating sea ice thickness (SIT)
observation (e.g. Xie et al., 2018]) or more precisely, the
sea ice freeboard, which is a proxy of the SIT. This can
be intuitively understood as the thinnest is the ice the more
Fig. 2. Geographical domain eNATL60, instantaneous speed of the current in the simulation with explicit resolution of the tide.
Fig. 3. SSH Power Spectrum during Summer 2016 (July, August,
September, JAS) and Winter 2017 (January, February, March, JFM)
over a region of the North Atlantic centered southwest of the Azores (37–
24°W and 23–40°N) (i) as observed by SARAL/AltiKa, and (ii) based on
the hourly SSH of eNATL60 (with and without explicit resolution of the
tide) interpolated in space and time on SARAL/AltiKa’s ground track.
6J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
fragile it is to thermo-mechanical stresses (heat, waves, cur-
rents, ...).
The first attempts to measure sea ice freeboard have
used ERS-2’s altimeter but with large uncertainties
(Peacock and Laxon, 2004). The method consists of mea-
suring the height differences between the ice and the sur-
rounding water in the cracks of the ice (see Fig. 5). This
approach has been deeply improved thanks to the first
SAR altimeter on board CryoSat, which produced several
sea ice freeboard products (Guerreiro et al., 2017). Using
such product, Blockley and Peterson (2018) have demon-
strated the ability to extend the sea ice forecast range from
a few weeks to a few months.
But snow is still a missing parameter. The conversion of
the sea ice freeboard (hi) into SIT basically consists in
applying the hydrostatic equilibrium equation:
SIT ¼hiqw
qwqi
ð1Þ
qiand qware respectively the density of ice and water. But
this equation must be corrected to account for the presence
of snow on the ice pack for two reasons: (i) the load
induced by snow, and (ii) the decrease in the speed of prop-
agation of the Ku-band radar wave in snow (see Fig. 5).
Then Eq. (1) must be re-written as follows:
SIT ¼hiqwþð1þaÞhsqs
qwqi
ð2Þ
where hsis the snow depth, qsthe snow density and athe
decrease of speed propagation in snow. The snow density
is about 30% of the water density and the speed reduction
ais between 20% and 25%. While the average snow depth is
probably slightly higher than the freeboard in the Arctic,
their ratio is much more significant in Antarctica. It implies
that the term related to the ice and the term related to the
snow in the numerator of Eq. (2) are of the same order of
magnitude. In other words, the snow depth is nearly as
important as the freeboard to retrieve SIT.
Nevertheless, while the measurement of freeboard has
made great progress, the same cannot be said for the mea-
surement of snow depth that still remains largely unknown.
For now all the SIT products derived from altimetry use
the Warren 99 climatology that has been established from
1954 to 1991 Arctic expeditions, i.e. before the sensible
effects of global warming. The only adaptation of this cli-
matology consists in dividing by two the snow depth over
the first year ice in order to take into account its reduced
lifespan. This solution is known as the ‘‘modified Warren
climatology(W99m).
SARAL/AltiKa is the first satellite to give some access
to snow depth observations. With regard to the Ku-band,
the Ka-band frequency does not penetrate so much the
snow. Several studies have explored this potential to
retrieve the snow depth (Armitage and Ridout, 2015;
Guerreiro et al., 2017). While the first study concludes that
50% of the Ka-band penetrates the snow, the correction of
the surface roughness in the second study has resulted in
remarkable correlations between Ka/Ku satellite altimeters
and Operation Ice Bridge snow radar airborne measure-
ments (see Fig. 6).
From the difference of the freeboards, computed respec-
tively with SARAL/AltiKa and CryoSat (using the pLRM
mode), snow depth maps were established for the seven
colder months of the Arctic (October-April) and the six
colder months of the Antarctic (May-October) over the
period 2013–2017 and up to 81.5°N/S.
This opens the way toward improved SIT observations.
New SIT monthly maps have been computed from this
Altimetric Snow Depth (ASD) product, and the freeboard
obtained with CryoSat (using the SAR and SARIN mode).
In order to estimate the impact of the snow depth solution,
we have substituted this snow solution with W99m’s and
CNRM’s snow solutions. The results presented Fig. 7
confirm the hypothesis deduced from Eq. (2). The SIT
products over the Arctic and the Antarctic, using the
ASD, will be soon available (http://ctoh.legos.obs-mip.fr/
Fig. 4. Overview of the dominant sub-cycles for a 6-km altitude range
near the historical ERS orbit. The quality of mesoscale observation is
controlled by some sub-cycles (15–19 days is better) so some altitude
ranges are better than others (colored ellipses and right-hand-side color
bar). From Dibarboure Barzaghi et al. (2018). (For interpretation of the
references to colour in this figure legend, the reader is referred to the web
version of this article.)
Fig. 5. These diagrams illustrate the principle of measuring the sea ice
thickness by altimetry, without snow on the left, and with snow on the
right. The snow sinks the ice on the water and slows down the radar speed
propagation. These two effects reduce the perceptible freeboard of the ice
and must be taken into account to retrieve the real sea ice thickness.
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 7
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
). Whereas the sea ice extent encountered a drastic reduc-
tion, the only radar altimeter that covers the Arctic Ocean,
and more generally the Polar Regions, is CryoSat that is
already 9 years old.
All these works and first of all, the SARAL/AltiKa find-
ings, justify the consideration of a new mission project,
CRISTAL, using Ku- and Ka- band together. CRISTAL
is one of the 6 High Priority Candidate Missions (HPCM)
of the Copernicus Sentinel Expansion program. The first
priorities of this polar mission is to survey the sea ice, its
snow cover and the land ice, and its main objectives are
to support the maritime operations in the polar oceans
and to better understand the climate processes. This mis-
sion will be equipped with the first Ka/Ku SAR/SARin
altimeter, and with an increased band-width (500 MHz)
to improve the vertical resolution. The Ku-band insures
the continuity of the long series of Ku altimetric survey
of the solid and liquid water over the planet, and the Ka-
band brings a clear innovation to measure the snow depth.
Contrarily to the results presented above, the Ka and the
Ku measurements will be synchronous and from a same
reference platform, allowing simultaneous measurements
of the heights of ice, of snow and of waters, with unprece-
dented precisions. So the CRISTAL mission, with the qual-
ity of the SAR/SARin technology, will be able to extend
the measurements of seas, lakes, rivers, permafrost, glaciers
and ice caps heights up to 88°N/S in near-real time, and
also the snow depth on the sea ice and probably on frozen
land. Although it is already known, through SARAL/
CryoSat-2 comparisons, that the Ka/Ku difference pro-
vides a good proxy for snow depth, further studies are
needed to validate and determine possible corrections to
this approach based on the characteristics of the snow
(depth, density, grain sizes, salinity, number of layers,
etc.) and its support (ice, sea ice, land). For that purpose,
SARAL/AltiKa remains an essential and unique tool to
accomplish the preparation of CRISTAL. Its extension
should allow further analyses of the penetration of Ka
and Ku bands in snow, in particular through comparisons
with the new Ka/Ku radars on board the CryoVex aircraft,
with the IceSat-2 lidar and with in situ measurements.
5. SARAL/AltiKa: a demonstrator for future Ka-band
missions
5.1. A demonstrator for the SKIM mission
SKIM is one of the two candidate satellite missions
under development for ESA Earth Explorer 9 (Ardhuin
et al., 2019). The Sea surface KInematics Multiscale
Fig. 6. Snow depth measurements using Operation Ice Bridge airborne snow radar (left map), compared with, left to right scatter plots, the Warren 99
snow depth modified climatology, the Altimetry Snow Depth (ASD) solution, and the CNRM-CMIP5 model forced by ERA-Interim reanalysis. We can
observe that W99m remains too high, despite the heuristic correction over the first year ice. The low CNRM values are due to too low ERA-Interim
precipitation, which highlights the lack of observation over this region.
Fig. 7. Average altimetric Sea Ice Thickness for the winters 2013/14 and 2014/15 over the Beaufort Sea (left plots) and over the Arctic Basin (right plots)
up to 81.5°N. The Beaufort Sea is the region where the altimetric freeboard and snow depth have been validated with OIB (see Fig. 6). The different color
curves correspond to different snow depth estimations. The extreme curves were respectively obtained with the Warren climatology (green dotted lines) and
a solution ignoring the snow (yellow line). The reality is probably in-between the solution using the Modified Warren climatology (green lines), that
provides over estimated SD, and the solution using the CNRM-CMIP5 model (red lines), that provides under estimated SD, i.e., a discrepancy of 0.5 m for
a mean SIT of 1.5 m. The solution using Alti Snow Depth is in blue. (For interpretation of the references to colour in this figure legend, the reader is
referred to the web version of this article.)
8J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
monitoring (SKIM) satellite mission is designed to explore
ocean surface currents and waves. This includes tropical
currents, notably the poorly known patterns of divergence
and their impact on the ocean heat budget, and monitoring
of the emerging Arctic up to 82.5°N. SKIM will also make
unprecedented direct measurements of strong currents,
from boundary currents to the Antarctic circumpolar cur-
rent, and their interaction with ocean waves with expected
impacts on air-sea fluxes and extreme waves. Horizontal
velocity components will be obtained with an accuracy bet-
ter than 7 cm/s for horizontal wavelengths larger than
80 km and time resolutions larger than 15 days, with a
mean revisit time of 4 days for of 99% of the global oceans.
This will provide unique and innovative measurements that
will further our understanding of the transports in the
upper ocean layer, permanently distributing heat, carbon,
plankton, and plastics. SKIM will also benefit from co-
located measurements of water vapor, rain rate, sea ice
concentration, and wind vectors provided by the European
operational satellite MetOp-SG(B), allowing many joint
analyses.
For the first time, SKIM will directly measure the ocean
surface current vector from space. The main instrument on
SKIM is a Ka-band conically scanning, multi-beam Dop-
pler radar. The main innovation is the combination of
rotating beams similar to SWIM on CFOSAT (Hauser
et al., 2017), here with incidence angles i = 0°(nadir), 6°
and 12°, with a Doppler capability that will measure the
surface velocity vector and ocean wave spectra across a
320 km swath. The well-proven Doppler pulse-pair tech-
nique will give a surface drift velocity representative of
the top meter of the ocean, after subtracting a large
wave-induced contribution. The velocity is given by the
phase difference of consecutive pulses (pulse-pairs) trans-
mitted at a frequency of 32 kHz. This high pulse repetition
frequency guarantees a high coherence between consecutive
pulses. Ka-band was chosen for its high precision
compared to Ku-band (pulse-pair technique precision is
three time higher in Ka-band). On the other hand, one of
the major concerns of using Ka-band is its sensitivity to
atmospheric conditions. Same concerns were shared during
the development of the SARAL/AltiKa mission, but now,
future Ka-band missions can be built using SARAL/
AltiKa measurements and experience. Lessons learned
show the data loss over ocean is lower than anticipated
(<0.1%) and the signal-to-noise ratio is higher than the pre-
flight expected value thanks to margins taken in the altime-
ter link budget (Steunou et al., 2015). Despite the very low
number of lost data, the presence of atmospheric liquid
water impacts the altimeter waveform shape. In a same
way, SKIM radar measurements will be polluted.
SARAL/AltiKa measurements has been used to evaluate
the global impact. Fig. 8 shows the percentage of
SARAL/AltiKa measurements impacted by rain events
thanks to the use of the matching pursuit algorithm
(Tournadre et al., 2009). Flagging strategy and algorithms
have been designed on SKIM based on this experience.
In addition, accurate SKIM measurements of the geo-
physical surface velocity require a very accurate knowledge
of the platform pointing error. Besides this, an apparent
skew-pointing of the radar beam can also be caused by a
non-homogeneous distribution, within the observed ocean
scene, of the normalized radar cross section (NRCS) r0.
This error is directly proportional to the azimuthal r0gra-
dients within the footprint. SARAL/AltiKa measurements
is used to evaluate the amplitude of this error, at global
scales. r0map at 12°incidence (SKIM, Fig. 9b) has been
extrapolated from SARAL/AltiKa r0map (Fig. 9a) using
equations from (Nouguier et al., 2016). Then, r0gradients
has been computed (Fig. 9a) and the error was estimated
and the analysis confirmed the agreement with perfor-
mances expectations.
In case of selection in the Earth Explorer 9 ESA pro-
gram, SKIM or its avatars will keep on learning from
Fig. 8. Percentage of measurements impacted by rain events on SARAL/AltiKa.
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 9
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
SARAL/AltiKa experience to consolidate the mission per-
formances, data processing and instrument design.
5.2. A demonstrator for the SMASH mission
SMASH (SMall Altimetry Satellites for Hydrology) is a
satellite altimetry constellation aimed at providing daily
water levels of rivers, lakes and other inland water bodies
with an end-to-end accuracy of 10 cm for which a feasibil-
ity investigation is presently supported by CNES
(Blumstein et al., 2019).
Indeed, the monitoring of water resources at the global
scale is already a major challenge whose importance will
increase in the next years. Continental waters are essential
components of the water, energy and carbon cycles.
The rivers and lakes water levels are identified as essential
Fig. 9. (a) SARAL/AltiKa r0map (dB), (b) SKIM r0map (dB, at 12°incidence, extrapolated from SARAL/AltiKa), (c) SKIM r0gradients (dB/km).
10 J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
climate variables by the Global Climate Observing System
(GCOS) which recommends daily measurements of these
variables. Traditionally, this information was provided by
gauge data. However, the availability of these in situ mea-
surements is very heterogeneous and is declining (Global
Runoff Data Centre, GDRC). For the last twenty years,
numerous research teams have demonstrated that measure-
ments from space altimeters could be used to mitigate this
lack of in situ measurements even if these instruments
where mainly designed for measurements over the oceans
(Birkett, 1995, 1998; Cre
´taux and Birkett, 2006; Frappart
et al., 2015; Hossain et al., 2014; Cre
´taux et al., 2015).
However, all the historic and current altimetry missions,
based on repeat track orbits with cycle durations of 10 days
(TOPEX/Poseidon Jason-2/3), 27 days (Sentinel-3), 35 days
(ERS-2, Envisat, SARAL/AltiKa) and more (CryoSat)
cannot provide these measurements daily (Tourian et al.,
2016; Boergens et al., 2017). As the performance of altime-
try missions applied to inland water surfaces improves con-
stantly, the next frontier is to increase the frequency of
temporal revisit.
The SMASH mission is a proposal to reach this goal. It
is very complementary to the Wide Swath altimetry mis-
sions like SWOT and WiSA which provide almost com-
plete spatial coverage at a lower temporal frequency. The
mission is based on a constellation of small satellites each
carrying a Ka-band altimeter.
The optimization of the payload definition was based on
the precious experience gained from the analysis of in-flight
measurements provided by the AltiKa altimeter: both the
standard 40 Hz data and the so-called individual echoes
(IE). These IE are the raw outputs of the altimeter and
96 of them are incoherently summed on-board to provide
a 40 Hz echo (or waveform). In order to save downlink
bandwidth, only the 40 Hz echoes are nominally transmit-
ted to the ground. However, occasionally, a sequence of
one second of successive IE is transmitted, this is similar
to the Envisat bursts (Roca et al., 2007). A first analysis
of IE data was described in Quartly and Passaro (2018)
for the ocean. Here, we report an analysis using a method
adapted to inland waters radar returns which are very dif-
ferent from the returns observed over the oceans. Specifi-
cally, the returns over inland waters are very peaky and
can often be accurately modeled (e.g. Abileah et al.,
2017) as the Point Target Response (PTR) of the instru-
ment which is, in theory, a squared cardinal sine (sinc2)
for SARAL/AltiKa.
We analyzed one pass of SARAL/AltiKa data over the
Salar de Uyuni. The Salar de Uyuni on the Altiplano of
southwestern Bolivia is a 9.600 km
2
salt lake, the largest
salt flat in the world. Its surface is expansive, flat, smooth,
and is a specular reflector, making it an ideal satellite
altimeter target. Contrary to these previous studies we
choosed a period when it was fully inundated on the 28th
of January 2019, making its surface even more flat and
smooth (very much like an almost perfect mirror). Indeed
we were much more interested in the intrinsic noise of
the instrument rather than on its absolute calibration.
Fig. 10, resulting from this Sala de Uyuni investigation,
is highly instructive. First, the noise of the height retrieved
from the IE at 4 kHz is in this case very low (around 6 mm
RMSE). This means that we get a very precise evaluation
at a spatial sampling of around 2 m. Furthermore, the
curve of heights retrieved from the 40 Hz waveform is very
close from it. Second, we have here a clear demonstration
that, on this kind of peaky waveforms, the ice1 retracking
algorithm can be outperformed by algorithms using physi-
cal models of the waveform, here a simple PTR model, and
that the accuracy improvement can be significant (ice1
RMSE 5 cm, sinc2retracking 5 mm). The acquisition of
this type of measurements over a wide diversity of inland
waterbodies (rivers, lakes, floodplains all of various sizes
and shapes) sampled over the world is ongoing. The results
of the analysis of this dataset will be an important factor to
guide the design choices in order to reduce the costs while
maintaining the performances of the mission. We believe
this will be a key factor in the demonstration of the feasi-
bility of the SMASH payload.
6. Ka-band and the drifting phase
The main consequence of the DP was that the SARAL
subsatellite track rapidly drifted away from the historical
ground track formerly used by the ERS and the Envisat
satellites since the Nineties. Sandwell et al. (2014) have
shown that using a drifting ground track could be extre-
mely useful for the marine geodesy community: the
unprecedented precision of SARAL/AltiKa could help
resolve uncharted sea mounts and sea floor topography.
Indeed, improving marine geodesy products requires a
so-called ‘‘geodetic altimeter sampling, i.e., a sampling
Fig. 10. Retrieved height (WGS84) of the inundated Salar de Uyuni water
surface in meters: computed from the SARAL/AltiKa IE (blue),
computed from the 40 Hz echoes in the SGDR with ice1 retracking
(green).The absolute value and the bias between the two curves is not
significant and has been adjusted to make the figure clear. (For
interpretation of the references to colour in this figure legend, the reader
is referred to the web version of this article.)
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 11
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pattern where the subsatellite tracks over a long period
(e.g., one year) create a very dense grid with a resolution
of 8 km or less. In general, this is achieved by keeping pre-
cisely the satellite on a so-called ‘‘geodetic orbit, i.e., an
orbit with a very long exact repeat cycle (e.g. Jason-1
Geodetic-Mission, or Jason-2 Long Repeat Orbit (LRO)
phase). In contrast, for SARAL-DP, there is not an exact
repeat because the orbit altitude decays continuously. Yet
the geodetic sampling of SARAL-DP is still naturally
dense, albeit somewhat random. An efficient metric to
characterize the quality of the geodetic grid is to look at
the histogram of the distance between adjoining equator
crossings for ascending or descending altimeter tracks. To
illustrate, Jason-2 LRO is currently sampling a 4 km reso-
lution grid over a period of 2 years (mid-2017 to mid-2019).
The LRO grid is also built from two 8-km interleaved grids
of one year each. The Jason-2 LRO grid is currently incom-
plete after only 1.5 years, which results in the histogram of
Fig. 11b. This histogram has 2 peaks: one at 4 km where
the final grid has been sampled, and one at 8-km grid for
equator nodes that will be acquired in the coming months.
Using the same metric for SARAL after 2.5 years of drift-
ing phase yields Fig. 11a. Because of the random nature of
the DP orbit, the histogram is different from Fig. 11b:
instead of 2 very narrow peaks associated with a controlled
geodetic orbit, the histogram of SARAL-DP is continuous
with an average of 3.2 km, with many grid nodes less than
2 km from one another, but many other with 5 km or more
(this number would be 0 if the orbit was controlled like
Jason-2 LRO). In December 2018, approximately 75% of
the 4-km geodetic grid has been effectively sampled. This
is less than the 100% that would have been collected with
a controlled orbit, but that is still a very large and precious
geodetic dataset. A possible Jason-2 mission extension up
to 2021 would allow to almost fill a 2 km grid but only
for latitude below 66°while SARAL/AltiKa will provide
complementary information for high latitudes.
6.1. Comparisons of SWH ans SLA measurements and
predicting cyclones in both SARAL/AltiKa phases
As said earlier, SARAL/AltiKa went for a DP operation
from July 2016. Thus to begin applications it was wise to
find out how the observation of SARAL changed in such
new mode. Thus individual 3 months (October–December
2016) of data from SARAL/AltiKa in DP was analysed
and compared to 3 months (July–September 2013) of
SARAL/AltiKa data in the nominal exact repeat orbit
mode (ERM).
Fig. 12 shows the 3 monthly average of SWH data from
these two modes. One thing was noteworthy from this exer-
cise is on a monthly scale the availability of data in DP is
much more than the ERM mode. To test the quality of
the data, a global validation was carried out using NDBC
buoy data particularly for two geophysical products i.e.
wind and wave. It was seen that both the wind and waves
are of very high quality in DP. In the similar way the
Jason-2 SLA has been inter-compared with the SARAL
SLA in two phases.
The left panel in Fig. 13 shows the comparison of the
SWH with global buoy data in October 2016 when SARAL
was in DP and October 2013 when SARAL was in ERM
mode respectively. The right panel on the other hand shows
the comparison of SLA for same months using the Jason-2
SLA from AVISO.
Albeit one can say that statistically SWH in DP looks
like a mild improvement upon ERM mode. But this is
not the case since the number of observation increases in
Fig. 11. Histogram of the distance between the adjoining equator crossings (ascending tracls) of the geodetic grids of SARAL-DP (panel a) and Jason-2
LRO (panel b) in January 2019.
12 J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
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DP as compared to ERM mode resulting to a better statis-
tic. But one can safely conclude that DP data is equally
good and high quality observations from SARAL as
ERM mode is. The real impact of the change to DP is
evident in the OGDR of the SLA which shows a mildly
lowered correlation and mild increase in RMSE and Bias.
Thus the DP SWH and Wind are equally high quality
and useable as ERM mode data. However, the SSHA
may need little bit of correction in successive levels (IGDR
and GDR).
Thus to look into the suitability of application of the DP
model data in oceanography we randomly select two
cyclones which occurred during SARAL being in ERM
and DP respectively. These are Phailin (October 4, 2013–
October 14, 2013) and Vardah (December 9, 2016–Decem-
ber 19, 2016). The former is a Category-5 cyclone with
3 min sustainable wind speed of 230 km/h and the other
one is Category-1 cyclone with the same as 150 km/h,
but both look heavy toll on Indian subcontinent in terms
of fatality. SARAL/AltiKa happened to monitor both clo-
sely. Fig. 14 shows the SARAL/AltiKa observing waves
during Phailin and Vardah on 11th October 2013 and
11th December 2016 respectively. Very clearly SARAL/
AltiKa in both the cases were able to peak up the intense
impact of cyclone over the ocean. The east Indian Coastal
Current (EICC) was found to become intense during the
cyclone cases for example in case of Vardah the EICC on
1st December 2016 prior to occurrence of the cyclone
and on 11th December 2016 when it was at its best status
has been shown in left and right panels of Fig. 15. Even
in its drifting phase, SARAL/AltiKa was able to provide
valuable information that have led to accurate capture of
the change of EICC during cyclone Vardah.
Fig. 12. The 3 monthly average of SWH data from ERM and GM modes.
Fig. 13. (Left panel) The Validation of SWH for October of 2013 and 2016 using global buoy observations. (Right Panel) The inter comparison of SLA
from Jason-2 and SARAL for the same period as SWH.
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 13
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6.2. Tides and the SARAL/AltiKa drifting phase
SLA data acquired during the SARAL/AltiKa drifting
orbit mission phase have been useful for evaluating
newly-developed ocean tide models. An early example of
this is the evaluation of a baroclinic tide model in Ray
and Zaron (2016). Tide models such as FES (Lyard
et al., 2006), DTU (Cheng and Andersen, 2011), and
GOT (Ray, 2013) incorporate nearly all available altimeter
data from missions in the so-called reference orbits origi-
nally occupied by the TOPEX/Poseidon and ERS-1/2 mis-
sions. Thus, the measurements from the drifting orbit
occupied by SARAL/AltiKa are extremely valuable
because they are from locations not routinely sampled,
and the precision of these measurements is advantageous
in distinguishing the small differences among tide models
(e.g., Stammer et al., 2014). For example, comparisons of
the variance reduction of the latest FES2014 tide model
(Carrere et al., 2014), compared with the older FES2004
model (Lyard et al., 2006), validate the newer model and
Fig. 14. SARAL/AltiKa observing wave height and SSHA during Phailin and Vardah on 11th October 2013 and 11th December 2016 respectively. In
these dates the Cyclones were at its peak intensity.
Fig. 15. East Indian Coastal Current before (left) and during (right) Vardah.
14 J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
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exhibit its improvements at small scales near the coastline
(Fig. 16). Note that the spacing of the reference mission
ground tracks is generally quite large compared to the
scales of the tides near the coast, and the existing tide gauge
network is otherwise not able to globally validate the
improvements in tide models near the coast (Andersen
et al., 2006).
6.3. SARAL/AltiKa for a refined observation of lakes
Lake water level can be measured over long period of
time using constellation of radar altimeters. It has been
used in a considerable number of studies (e.g.Cre
´taux
et al., 2016). However, in contrast to large lakes or rivers,
onboard altimeters also may have difficulties to track the
real surface of the water body when it is narrow or located
in region with rough topography, or in case where several
water bodies at different altitudes are located close to each
others. It is particularly the case in boreal regions like the
northern Canada, Alaska or Siberia, but also in moun-
taineous areas. In such situation, the tracker simply does
not always acquire the measurements due to bad a priori
information on the definition and adjustment of the track-
ing window of the instruments. To solve this question,
recently, a new tracking mode has been implemented
onboard the two missions, Jason-3 and Sentinel-3A. It is
based on a priori onboard database with near real time
information on the position of the satellite (thanks to the
DORIS/Diode navigator (Jayles et al., 2010) and a data-
base including a pseudo Digital Elevation Model (DEM)
with a priori height of the water bodies (lakes and rivers).
The two tracking mode are called respectively Close Loop
(CL) and Open Loop (OL). The target’s predicted distance
is calculated directly by the altimeter, combining altitude
data from DORIS/Diode with the altitude from the
DEM recorded in the altimeter’s onboard memory. Recent
results have proved that OL mode has allowed tracking
continuously more than 90% of potential lakes compared
to only 50% when the tracking mode is the CL with
Jason-3. However the number of potential lakes is much
larger for the current missions like Sentinel-3A and
Sentinel-3B.
Hopefully in 2021, SWOT will be able to measure water
height of about 8 millions of lakes worldwide with a revisit
of 21 days and an expected accuracy of 10 cm for lakes lar-
ger than 1 km
2
. In order to perform an optimal use of the
interferometer, it is also necessary to use a priori lake data-
base with several information: reference contour and height
of each lake (Rodriguez, 2015). For SWOT which measures
differences of phases, a priori DEM is necessary in order to
solve for ambiguity, which is at the range of 5–10 m in the
near range and more like 60 m in the far range. Since the
accuracy of a priori height for onboard DEM (for nadir
altimeter and for SWOT) is on the order of magnitude of
5 to 10 m, the main issue is to obtain satellite data from
various instruments in order to cover the maximum of
lakes worldwide. This is evident that over the 8 millions
of lakes that will be surveyed using SWOT it is practically
impossible to obtain a priori height from current nadir
altimeters for the totality of them, but geodetic missions
are well designed to measure reference height of a very high
number of targets. Jason-2 and SARAL/AltiKa are current
missions both candidates for this purpose. However, Jason-
2 does not cover high latitude region while SARAL/AltiKa
does. Since the beginning of the SARAL-DP about 3 years
of data have been acquired. It therefore now allows over-
passing a very high number of lakes, in particular in the
boreal region where the majority of lakes are located.
For a region located on the east bank of the Hudson
Bay, we have done a simulation of the potential of
Fig. 16. Evaluating tide models with SARAL/AltiKa data from the drifting orbit phase (July 2016–June 2019). SARAL/AltiKa provides an important
source of precise SLA at locations off the reference mission ground tracks. It permits the validation of tide models in coastal regions where the scales of the
tide are comparable to, or smaller than the resolution of the reference missions. Regions in red, generally near the coast, show where the newer tide model
(FES2014) explains more SLA variance than the old tide model (FES2004). (For interpretation of the references to colour in this figure legend, the reader
is referred to the web version of this article.)
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 15
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
SARAL/AltiKa to provide reference height of the lakes
present in this region. A single pass is presumably enough
to reach this objective.
Fig. 17 shows the coverage of SARAL/AltiKa over the
nominal mission (from cycle 1 to 35) and over the DP until
now. The largest lakes are also represented. They are
released in the Global Lakes and Wetlands Database
(GLWD, https://www.worldwildlife.org/pages/global-
lakes-and-wetlands-database) in the form of polygons of
the lake’s contours. Over this region we have computed
the number of lakes present in the GLWD, the number that
are overpassed by the nominal orbit and the number that
are overpassed during the DP. To fill Table 1 we have
counted the number of lakes for which at least one valid
measurement (without error’s flag in the GDRs) is
acquired within the polygons defining the lake contour.
For lakes within the GLWD, it was simply done using
the existing lake polygons, while for smaller lakes, we have
done manual inspection for the final counting. With the DP
orbit all of the lakes included within the GLWD are now
covered using the DP orbit since it was only 77% with
the nominal orbit. If now we look at all lakes bigger than
1km
2
, that therefore are for most of them not included into
GLWD, then the gain is much higher. The total number of
lakes included in the zone, which has served as example,
increased from 28 % of the totality using nominal orbit
to 75% using the DP orbit. This result suggests therefore
that a longer period of DP orbit with SARAL/AltiKa of
few months will likely be enough to cover almost 100%
of lakes bigger than 1 km
2
. This represents approximately
300,000 to 400,000 lakes worldwide according to
Verpooter et al. (2014) for which a least a reference height
could be estimated using only SARAL/AltiKa. In order to
consolidate the computation, the use of data from other
missions has already started. In particular we have calcu-
lated reference height of about 6000 lakes and reservoirs
worldwide using only Cryosat mission. It will serve for
cross validation with the SARAL/AltiKa data over the
same lake dataset. Results are summarized in Table 1.
The statement on the SARAL/AltiKa potential to pro-
vide height’s reference for lakes larger than 1 km
2
is valid
in favorable environment conditions. It has been shown
for example in Arsen et al. (2015) that a realistic threshold
of approximately 10 km
2
is more likely valid in mountain-
ous conditions, and with the aim to perform highly accu-
rate time series of water height variations. For the
objective of performing height reference with precision of
about 4–5 m (which is needed for SWOT a priori database)
we assessed in Table 1 that this is achievable in flat regions
like the Canadian plains where the biggest world density of
small lakes is observed. In mountainous region, this is
likely a too optimistic assessment and potentially, only
Table 1
Coverage of worldwide lakes by SARAL/AltiKa during the nominal orbit
phase and the SARAL-Drifting Phase by reference to the present Global
Lakes and Wetlands Database.
Total Nominal orbit Drifting phase
(Number/percentage) (Number/percentage)
GLWD 130 100/77% 130/100%
All lakes 6000 1725/28% 4500/75%
Fig. 17. Projection of the SARAL/AltiKa tracks over the region located on the East of the Hudson bay in Canada (with a zoom for a better view of the
detailed tracking coverage). Red line represents the nominal orbit, green light the Drifting Phase from cycle 100 to cycle 126. The contour of lakes are
inferred from the GLWD database. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this
article.)
16 J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
lakes bigger than 10 km
2
would be observable by SARAL/
AltiKa.
6.4. SARAL/AltiKa for a refined description of the geoid and
of the MSS
The value of satellite altimetry for geodesy lies in the
combination of uniform mapping at high spatial density
and the range precision of the individual sea surface height
observations, and SARAL/AltiKa is an excellent altimeter
for resolving short-wavelength features in the geoid/gravity
and mean sea surface (MSS).
The investigations by Smith (2015) showed that the
range precision of SARAL/AltiKa is roughly 2 times more
precise than Envisat due to its more beam-limited wave-
form shape and its higher pulse repetition frequency of
4 kHz (vs. 2 kHz for Envisat). The range precision is 2.5
times more precise than older geodetic mission data from
Geosat and ERS-1. Compared with other altimeters cur-
rently flying (Jason-2 and Cryosat), the range precision is
roughly twice as precise as Jason-2 and even 50% better
than the Cryosat SAR altimetry. Zhang and Sandwell
(2017) even demonstrated that SARAL/AltiKa benefits
from the 2-pass retracking.
Since July 2016 then, the SARAL-DP leads to a ground
track pattern will be more uneven (e.g. Fig. 18 over the
Hawaii area). Other geodetic missions are maintained in
controlled geodetic missions with typical 8 km ground
track spacing. The uneven drifting ground track pattern
of SARAL/AltiKa is in principle a ‘‘downsideas it limits
the spatial resolution of the recovered gravity and MSS to
twice the largest ground track spacing (up to 20 km as of
2019). However, by merging the SARAL/AltiKa data with
the regular sampled geodetic mission of Jason-1/2 or Cryo-
sat, this is counter-acted such that the full potential and full
usage of the high range precision can be gained in a system-
atic way.
Detection of seamount and bathymetry mapping are
and will be a key usage of the SARAL-DP data. Earlier
generation of altimeter technology could map all sea-
mounts 2 km and taller than 2 km, but there might be as
many as 50,000 seamounts between 1–2 km tall that were
not yet found. Smith (2015) used single cycles of
SARAL/AltiKa 40 Hz sea surface height data to identify
seamounts as small as 1.35 km tall from the initial exact
repeat mission (consequently limited by the roughly
70 km cross track spacing). A further development of this
was presented by Marks and Smith (2016). Here stacked
repeat cycles of 32 repeat (nearly 3 years) of 40 Hz
SARAL/AltiKa data profiles over selected areas improved
the resolution of small seamount signals and lowered the
noise. The noise variance decreases with an increase in
the number of cycles stacked and was below 2 cm when
12 or more repeat cycles were stacked. Seamounts smaller
than 720 m tall could easily be identified in the stacked
profiles, and a seamounts 500 m tall was perceptible.
Coherence analyses between geoid height and topography
shows that full wavelengths down to 10 km are being
resolved with SARAL/AltiKa. Marks and Smith (2018)
applied a seamount detection filter to stacked SARAL/
AltiKa sea surface profiles globally, revealing over 75,000
possible seamounts (Fig. 19).
It was possible to assign proxy heights to 4824 of the
possible seamounts that were located over multibeam sur-
veys, by subtracting regional SRTM30 depths from the
multibeam depths. These proxy heights followed a Poisson
statistical distribution similar to that which fit acoustic
bathymetry profiles over seamounts (Fig. 20). This model
suggests at least 84% of the possible seamounts are less
than 2 km tall. Employing the stacking method on repeat
cycle data from other modern satellites may further aug-
ment the global seamount census, particularly for sea-
mount heights less than 2 km tall.
Another important virtue of SARAL/AltiKa for geo-
desy is the smaller footprint illuminated on the sea surface.
The smaller footprint is particularly important for geodetic
purposes in coastal- and sea ice-contaminated regions, as
fewer sea surface height observations are corrupted by
the presence of land or ice inside the footprint The Ka-
band altimeter has a slightly smaller footprint than other
conventional altimeters operating at Ku-band when wave
heights are small (see Fig. 9 and Eqs. 10 & 11 in Smith
(2015)). Within the Geomed-2 project (Barzaghi et al.,
2018) to derive an improved geoid of the Mediterranean
Fig. 18. 77 months of Cryosat sea surface slopes around Hawaii (left) and 13 months of SARAL/AltiKa sea surface slopes (right). The varying ground
track density is clearly shown.
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 17
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
Sea we investigated the importance of geodetic mission
data from different geodetic missions in complex coastal
regions.
The histogram of geoid residuals to EGM2008 from one
year of Jason-1 (Fig. 21 left picture) and from 3 years of
SARAL/AltiKa (Fig. 21 right picture) clearly demonstrate
the superior data coverage with SARAL/AltiKa in coastal
regions due to the smaller footprint. This is particularly
important for recovering the marine gravity field and
MSS in coastal and Arctic regions. In Arctic regions sea-
ice effects are similar to coastal effects in disturbing the
waveform inside the footprint.
7. Conclusion
In this paper, the specificities of Ka-band altimetry
and of SARAL/AltiKa which is the first satellite using it,
have been reminded. We have tried to show from this
Fig. 19. Locations of possible seamounts detected in AltiKa repeat cycles (from Fig. 4 in (Marks & Smith 2018)).
Fig. 20. Cumulative number of possible seamounts located over multi-
beam surveys versus estimated seamount height (from Fig. 5, (Marks &
Smith 2018)).
Fig. 21. Residual geoid heights in meters from Jason-1 (left) and SARAL/AltiKa (right) close to Crete (Eastern Mediterranean Sea). The histogram of
residuals (in meters) is shown as well. SARAL/AltiKa clearly shows superior data-coverage and a narrower histogram compared with Jason-1 being very
valuable to coastal geodesy.
18 J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
– by developing each of the main aspects – how it is possible
to project into the future towards new planned or proposed
satellite missions (e.g. SWOT, CRISTAL, SKIM and
SMASH, which are all in Ka-band).
For the oceans, SARAL/AltiKa provides an improved
resolution and a better accuracy of the SSH signal espe-
cially at the mesoscales. Assuming appropriate editing,
the along-track SSH spatial resolution SARAL/AltiKa
provides resolution better than Jason-2/3 missions and
even than Sentinel-3A. Note that coastal oceanography
directly benefits of the better discrimination in transition
zones as well as this improved resolution of the measure-
ments. These refined measurements in the regional and
coastal areas is of major relevance to societal applications.
Until the first high resolution altimetry observations from
the SWOT mission are available, SARAL/AltiKa is the
satellite capable of providing altimetry observations at
the best resolution. In this context, SARAL/AltiKa data
has the potential to play a key and forerunner role in the
preparation, interpretation and understanding of future
SWOT data.
For inland waters, SARAL/AltiKa definitely improves
the quality of hydrology products derived from satellite
altimetry. Especially for water level time series over lakes
and rivers, SARAL/AltiKa dramatically improved the
measurements due to its smaller footprint and its higher
pulse repetition frequency. SARAL/AltiKa allows the
access to smaller rivers and lakes that are not accessible
with standard altimeters. During the Drifting Phase,
SARAL/AltiKa appears to open the way for better observ-
ing lakes on various size in various regions such as Canada
or Siberia. All of this provide a strong technological and
scientific foundation for the SMASH proposal for inland
waters observations, but also for better designing the
SWOT mission (e.g. the DEM).
For high latitudes, ice-covered regions, the lesser radar
penetration of snow by SARAL/AltiKa is beneficial for
various types of measurements and especially for a better
discrimination between snow, ice and water. The difference
between Ka and Ku-band height provides a good proxy of
snow depth above sea ice that is a limitation to estimate ice
thickness. Sea ice and ice sheet measurements are a major
issue for climate monitoring. As for inland waters applica-
tions, ice applications gave evidence of the key importance
of continuous observations along the same repeat orbit, as
was possible with ERS-2, Envisat and SARAL/AltiKa
(during the nominal phase). This is used to develop the
CRISTAL project using a dual Ku-Ka band system.
Ka-band clearly brings some opportunities to under-
stand Ku-band better. This is an evidence in the previously
mentioned case of ice and snow measurements. But this is
probably true also for other domains (e.g. wave-currents
interaction studies).
For geodesy, it appears that AltiKa is an excellent
altimeter for resolving short-wavelength geoid anomalies.
In the Drifting Phase, the resulting dataset will be a
boon to marine geophysics, bathymetric estimation, and
seamount mapping. Seamount size-frequency distribution
models suggest that there may be as many as 10
5
sea-
mounts between 1 and 2 km in height that are uncharted
and were not detected by previous Ku-band altimeters.
After the full completion of the Drifting Phase, SARAL/
AltiKa will surely find some of these and brings a major
improvement in the Mean Sea Surface definition very use-
ful for all altimetric missions.
Clearly, SARAL/AltiKa is an altimetric satellite mission
that opens more than previously the doors of interdisci-
plinarity. Indeed, the extended capabilities that are offered
by the Ka-band allow to open even more widely some new
frontiers of altimetry such as coastal oceanography, cryo-
spheric sciences, hydrology, beyond the traditional scope
of the open ocean investigations. It is therefore very signif-
icant to note that an initially oceanography-dedicated
satellite like SARAL/AltiKa opens the way – thanks to
the Ka-band – to satellite projects not only in oceanogra-
phy like SWOT and SKIM but also in glaciology (CRIS-
TAL), in hydrology (SWOT, SMASH) or even in
geodetic directions.
The use of the Ka-band had initially been seen as prob-
lematic because of the important limitations hypothesized
in rain situations. The SARAL/AltiKa mission was
launched despite this constraint, taking a certain risk in this
respect but also preventing as much as possible the difficul-
ties by appropriate technological adjustments. Reality
shows that these limitations were largely overestimated.
The abundance of Ka-band satellite projects today demon-
strates a posteriori the value of some technological risk-
taking for the benefit of scientific and operational
applications.
Beyond the scientific impacts mentioned previously, the
experience of the SARAL/AltiKa Drifting Phase is of
interest for other satellite missions. SARAL/AltiKa has
demonstrated the benefits of this DP strategy: reducing
the number of maneuvers has effectively extended the satel-
lite lifetime as expected, and the DP orbit provides an
enhanced sampling capability of ocean mesoscale, as well
as precious measurements to improve marine geodesy ref-
erences fields (e.g., bathymetry, geoid or mean sea surface).
More generally, the strategy developed for SARAL/AltiKa
can be used for any other altimeter (e.g., Jason-3 or
Sentinel-3), for instance if the satellite maneuvering capa-
bility is limited by onboard aging anomalies (Dibarboure
et al., 2018). This strategy could also be used to minimize
satellite operations, or to reduce the amount of fuel needed
during the mission’s lifetime and then applied to mission/-
constellation for which the maintenance effort is highly lim-
ited (i.e. nanosatellites).
Acknowledgements
The contributions of A. Abulatitijiang, S. Bruinsma, H.
Harper, J. Le Sommer, F. Lyard & R. Morrow are deeply
acknowledged. This work was sponsored by CNES as part
of the TOSCA program. Ocean Next contribution is for a
J. Verron et al. / Advances in Space Research xxx (2020) xxx–xxx 19
Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
part supported by CNES and CMEMS. Thanks to CNES
and ISRO for having adapted their plan of operations in
order to acquire the useful dataset of SARAL/AltiKa over
the Salar de Uyuni. The sea ice thickness and snow depth
studies have also been supported by the Cryo-SeaNice
ESA project and the data base is available at LEGOS/
CTOH.
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Please cite this article as: J. Verron, P. Bonnefond, O. Andersen et al., The SARAL/AltiKa mission: A step forward to the future of altimetry,
Advances in Space Research, https://doi.org/10.1016/j.asr.2020.01.030
... Agriculture, exploiting CLMS [21,48] and C3S [9], others such as CEMS [44] and CAMS [47] for the Management of Natural Disasters. Climate [8], [30], [39], [41], [45], [7], [15], [27], [23], [38]. Coastal and Marine Exploitation and Preservation [43]. ...
... Urban Monitoring [11], [24]. OCEAN Coastal and Marine Exploitation and Preservation [19], [4], [6], [12], [23], [26], (CMEMS) [36], [37], [42], [49], [45]. ...
... Type of users Our study highlights the involvement of different type of users according to their roles in the data value chain and their levels of skills in EO or other scientific fields. For instance, EO-experts' skills are required in research topics about Land and Urban monitoring [24,45]. EO knowledge is used at an intermediate level by GIS users in application areas such as geology, or meteorology [26,11,47,44], where the goal is not to implement the resource but to reach a sector-specific final product. ...
Chapter
The European Programme Copernicus is one of the main sources of free and open Earth Observation (EO) data and information services, aimed at sustaining important social and economic advancements to the European Union with Remote Sensing (RS) practices. To achieve these goals User Uptake initiatives have been undertaken: aimed at increasing Copernicus awareness, dissemination and competences, thus supporting the development of downstream applications. The paper introduces the ongoing activity of the EO-UPTAKE project, funded by Liguria Region, aiming to bridge the skills gap between intermediate and end-users involved in the downstream sectors and promoting the use and integration of Copernicus data and services. It presents an overview of the Copernicus Programme and the European User Uptake initiatives, and provides a survey about the downstream applications based on academic literature, by outlining thematic sectors involved, the developed applications, their users, and data integration practices. Benefits and obstacles are discussed.
... Using a higher frequency allowed the footprint of the altimeter to reduce from 15 km at the Ku band to 4 km, but also the range noise and the impact of the ionosphere [9]. Since 2013, this mission has proven the benefits of measurements at the Ka band to oceanography, even extending the boundaries of altimetry to new scientific fields (coastal oceanography, cryospheric sciences, hydrology) [10,11]. The major counterpart in terms of SSH monitoring is a larger sensitivity to the water in the atmosphere: the altimeter backscattering coefficient atmospheric attenuation is seven times larger at the Ka band than at the Ku band [12]. ...
... One objective is to assess the impact of the atmospheric attenuation on the data availability that remains critical for the future interferometric missions based on Ka band measurements. Indeed, Verron et al. (2021) [11] demonstrated how SARAL/AltiKa and its Ka band can be considered as a demonstrator of the future potential missions based on the same band: the Sea surface KInematics Multiscale (SKIM) mission dedicated to ocean surface currents and wave [24], the CRISTAL mission focusing on the monitoring of the sea ice, its snow cover and the land ice and the SMall Altimetry Satellites for Hydrology (SMASH) dedicated to inland water bodies [25]. The first direct successor of SARAL/AltiKa will be the NASA/CNES Surface Water Ocean Topography Mission (SWOT), to be launched in 2022, providing two-dimensional observations of the sea surface for the first time [26,27]. ...
... One objective is to assess the impact of the atmospheric attenuation on the data availability that remains critical for the future interferometric missions based on Ka band measurements. Indeed, Verron et al. (2021) [11] demonstrated how SARAL/AltiKa and its Ka band can be considered as a demonstrator of the future potential missions based on the same band: the Sea surface KInematics Multiscale (SKIM) mission dedicated to ocean surface currents and wave [24], the CRISTAL mission focusing on the monitoring of the sea ice, its snow cover and the land ice and the SMall Altimetry Satellites for Hydrology (SMASH) dedicated to inland water bodies [25]. The first direct successor of SARAL/AltiKa will be the NASA/CNES Surface Water Ocean Topography Mission (SWOT), to be launched in 2022, providing two-dimensional observations of the sea surface for the first time [26,27]. ...
Article
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The impact of large atmospheric attenuation events on data quality and availability is a critical aspect for future altimetry missions based on Ka-band altimetry. The SARAL/AltiKa mission and its Ka-band nadir altimeter offer a unique opportunity to assess this impact. Previous publications (Tournadre et al., 2009, 2015) already analyzed the impact of rain on the waveforms at Ka-band and proposed a definition of an elaborate rain flag. This notion tends to give a simpler black and white view of the atmospheric attenuation when the effect on the altimeter measurement is intense. However, in practice, there is a continuum of measurements that may be partially distorted or corrupted by rain events. The present study proposes a wider point of view, directly using the timeseries of the Ka-band altimeter backscattering coefficient for the first time, when previous studies relied on microwave radiometer (MWR) observations or model analyses with coarser resolutions. As guidelines for future Ka-band missions concerning the impact of the atmosphere, the Attenuation CElls Characterization ALgorithm (ACECAL) approach not only provides more representative statistics on rain cells (occurrences, amplitude, size), but also describes the internal structure of the cells. The actual atmospheric attenuation retrieved with ACECAL is about four times larger than the attenuation retrieved from the MWR. At a global scale, 1% of the measurements are affected by an attenuation larger than 23 dB and 10% of the atmospheric attenuation events have a size larger than 40 km. At regional scale, some areas of particular interest for oceanography as Gulf Stream, North Pacific and Brazil currents are more systematically affected compared with global statistics, with atmospheric attenuation up to 8 dB and cell size larger than 25 km when rain occurs. This study also opens some perspectives on the benefits that the community could be drawn from the systematic distribution of the rain cells parameters as secondary products of altimetry missions.
... Ka/Ku band) and/or altimeters in tandem/complementary orbits are undergoing preparation (Kern et al., 2020;Guerreiro et al., 2016). To implement this approach, it is crucial to understand the quantitative differences in penetration of radar waves into the snow/ice/ocean medium at Ku/Ka wavelengths, in particular taking the benefit of SARAL/AltiKa (Verron et al., 2021). ...
... .). Most of the scientific benefits of this new technology are listed in Verron et al. (2021). Furthermore, before AltiKa, clouds and rain were considered to be a major concern for Ka-band altimetry. ...
... It will complement the Ku-band for the CRISTAL mission, and it has been proposed for the SKIM Earth Explorer 9 mission (Ardhuin et al., 2018;. In all cases, a sciencedriven mission was designed leveraging the lessons learned from AltiKa which was a technology-driven demonstrator but also aimed at being a gapfiller between Envisat and Sentinel-3A (Verron et al., 2021). ...
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Full-text available
In 2018 we celebrated 25 years of development of radar altimetry, and the progress achieved by this methodology in the fields of global and coastal oceanography, hydrology, geodesy and cryospheric sciences. Many symbolic major events have celebrated these developments, e.g., in Venice, Italy, the 15th (2006) and 20th (2012) years of progress and more recently, in 2018, in Ponta Delgada, Portugal, 25 Years of Progress in Radar Altimetry. On this latter occasion it was decided to collect contributions of scientists, engineers and managers involved in the worldwide altimetry community to depict the state of altimetry and propose recommendations for the altimetry of the future. This paper summarizes contributions and recommendations that were collected and provides guidance for future mission design, research activities, and sustainable operational radar altimetry data exploitation. Recommendations provided are fundamental for optimizing further scientific and operational advances of oceanographic observations by altimetry, including requirements for spatial and temporal resolution of altimetric measurements, their accuracy and continuity. There are also new challenges and new openings mentioned in the paper that are particularly crucial for observations at higher latitudes, for coastal oceanography, for cryospheric studies and for hydrology. The paper starts with a general introduction followed by a section on Earth System Science including Ocean Dynamics, Sea Level, the Coastal Ocean, Hydrology, the Cryosphere and Polar Oceans and the “Green” Ocean, extending the frontier from biogeochemistry to marine ecology. Applications are described in a subsequent section, which covers Operational Oceanography, Weather, Hurricane Wave and Wind Forecasting, Climate projection. Instruments’ development and satellite missions’ evolutions are described in a fourth section. A fifth section covers the key observations that altimeters provide and their potential complements, from other Earth observation measurements to in situ data. Section 6 identifies the data and methods and provides some accuracy and resolution requirements for the wet tropospheric correction, the orbit and other geodetic requirements, the Mean Sea Surface, Geoid and Mean Dynamic Topography, Calibration and Validation, data accuracy, data access and handling (including the DUACS system). Section 7 brings a transversal view on scales, integration, artificial intelligence, and capacity building (education and training). Section 8 reviews the programmatic issues followed by a conclusion.
... The Indo-French SARAL/AltiKa mission in Ka band with twofold range precision compared to conventional Ku band altimeters has provided valuable information on the global oceans (Verron et al. 2020). The SARAL/AltiKa mission, designed as a follow-on to the ENVISAT-RA2 in the same orbit and ground track, provides an excellent opportunity to compare resolution capabilities of the Ka and Ku band altimeters. ...
... A comprehensive analysis of the results as provided in Tables 2 and S1-S3 clearly suggests that for all three sites the short-wavelength resolution of SARAL/ AltiKa (15-18 km) is ~27-33% better than the ENVISAT-RA2 (22-25 km) data (Table 2). Enhancement in the performance of SARAL/AltiKa could be due to its lower noise levels and higher pulse repetition frequencies compared to that of ENVISAT-RA2 (Vincent et al. 2006;Verron et al. 2015Verron et al. , 2020. Further, smaller footprint of SARAL/AltiKa provides more accurate sea surface measurements near to the coast. ...
... The present analysis demonstrated the high-resolution capability of SARAL/AltiKa at continental margins as well. The Drifting Phase (DP) of SARAL/AltiKa since 2016 has collected excellent measurements for resolving short-wavelength geoid anomalies (Verron et al. 2020). As a future work, we envisage to generate high-resolution mean sea surface and gravity fields using an optimal combination of SARAL/AltiKa repeat profiles in the ERM phase with the data in DP and other geodetic altimeters. ...
... The Ka-band altimeter has a higher frequency than the conventional altimeter (Ku/C band), with observations less affected by the ionosphere delay. Furthermore, the diameter of the pulse footprint of the Ka-band altimeter is reduced to ~1.4 km under general ocean conditions, and the ranging accuracy is improved to 1-2 cm [33]. With the improvement of ranging accuracy, SARAL altimeter data play an important role in high-accuracy marine gravity field recovery [22,34]. ...
Article
Full-text available
Marine gravity field recovery relies heavily on satellite altimetry. Thanks to the evolution of altimetry missions and the improvements in altimeter data processing methods, the marine gravity field model has been prominently enhanced in accuracy and resolution. However, high-accuracy and high-resolution gravity field recovery from satellite altimeter data remains particularly challenging. We provide an overview of advances in satellite altimetry for marine gravity field recovery, focusing on the impact factors and available models of altimetric gravity field construction. Firstly, the evolution of altimetry missions and the contribution to gravity field recovery are reviewed, from the existing altimetry missions to the future altimetry missions. Secondly, because the methods of altimeter data processing are of great significance when obtaining high-quality sea surface height observations, these improved methods are summarized and analyzed, especially for coastal altimetry. In addition, the problems to be resolved in altimeter data processing are highlighted. Thirdly, the characteristics of gravity recovery methods are analyzed, including the inverse Stokes formula, the inverse Vening Meinesz formula, Laplace’s equation, and least squares collocation. Furthermore, the latest global marine gravity field models are introduced, including the use of altimeter data and processing methods. The performance of the available global gravity field model is also evaluated by shipboard gravity measurements. The root mean square of difference between the available global marine gravity model and shipboard gravity from the National Centers for Environmental Information is approximately 5.10 mGal in the low-middle latitude regions, which is better than the result in high-latitude regions. In coastal areas, the accuracy of models still needs to be further improved, particularly within 40 km from the coastline. Meanwhile, the SDUST2021GRA model derived from the Shandong University of Science and Technology team also exhibited an exciting performance. Finally, the future challenges for marine gravity field recovery from satellite altimetry are discussed.
... In the agricultural sector [23,[105][106][107][108][109] and the forestry sector [27], the health of crops was assessed respectively employing vegetation indices and variation of woodland cover in protected areas. Monitoring of the temporal trend of the forest cover, when affected by intense deforestation, can be depicted by comparing two inter-annual images, as performed by Palas et al. [30], who were able to determine a quantitative measure of the ecological impact of logging activities using S-2 images. ...
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Full-text available
The European Programme Copernicus, one of the principal sources of free and open Earth Observation (EO) data, intends to sustain social and economic advancements to the European Union. To this end, User Uptake initiatives have been undertaken to increase Copernicus awareness, dissemination, and competencies, thus supporting the development of downstream applications. As part of the activities performed in the EO-UPTAKE project, we illustrate a set of application scenario workflows exemplifying usage practices of the data and tools available in the Copernicus ecosystem. Through the know-how gained in the design and development of the application scenarios and the bibliographic analysis on downstream applications, we discuss a series of practical recommendations to promote the use of Copernicus resources towards a wider audience of end-users boosting the development of new EO applications along with some advice to data providers to improve their publication practices.
Article
Satellite altimeters routinely supply sea surface height (SSH) measurements, which are key observations for monitoring ocean dynamics. However, below a wavelength of about 70 km, along-track altimeter measurements are often characterized by a dramatic drop in signal-to-noise ratio (SNR), making it very challenging to fully exploit the available altimeter observations to precisely analyze small mesoscale variations in SSH. Although various approaches have been proposed and applied to identify and filter noise from measurements, no distinct methodology has emerged for systematic application in operational products. To best address this unresolved issue, the Copernicus Marine Environment Monitoring Service (CMEMS) actually provides simple band-pass filtered data to mitigate noise contamination of along-track SSH signals. More innovative and suitable noise filtering methods are thus left to users seeking to unveil small-scale altimeter signals. As demonstrated here, a fully data-driven approach is developed and applied successfully to provide robust estimates of noise-free sea level anomaly (SLA) signals (Quilfen, 2021). The method combines empirical mode decomposition (EMD), used to help analyze non-stationary and non-linear processes, and an adaptive noise filtering technique inspired by discrete wavelet transform (DWT) decompositions. It is found to best resolve the distribution of SLA variability in the 30–120 km mesoscale wavelength band. A practical uncertainty variable is attached to the denoised SLA estimates that accounts for errors related to the local SNR but also for uncertainties in the denoising process, which assumes that the SLA variability results in part from a stochastic process. For the available period, measurements from the Jason-3, Sentinel-3, and SARAL/AltiKa missions are processed and analyzed, and their energy spectral and seasonal distributions are characterized in the small mesoscale domain. In anticipation of the upcoming SWOT (Surface Water and Ocean Topography) mission data, the SASSA (Satellite Altimeter Short-scale Signals Analysis, https://doi.org/10.12770/1126742b-a5da-4fe2-b687-e64d585e138c, Quilfen and Piolle, 2021) data set of denoised SLA measurements for three reference altimeter missions has already been shown to yield valuable opportunities to evaluate global small mesoscale kinetic energy distributions.
Article
AltiKa, first ever high frequency Ka-band altimeter on board SARAL (Satellite with ARgos and ALtiKa) has gone through different phases of operations, viz. Exact Repeat Mission, (ERM, March 2013 - July 2016), Drifting phase, (DP, July 2016 - January 2018) and then to Mispointing phase, (MP, February 2018 - till date). A detailed assessment of Sea level anomaly (SLA), Significant Wave Height (SWH) and Ocean Surface Wind Speed (WS) has been carried out during these different phases with a focus on the North Indian Ocean. Crossover analysis using the Jason series of satellites available during various phases of SARAL suggest high quality of SARAL/AltiKa data during the ERM and DP with root mean square differences of the order of 0.080 m, 0.25m and 1 m/s for SLA, SWH and WS respectively. These differences are more during MP, being 0.095m, 0.45m and 1.72 m/s for SLA, SWH and WS respectively. Wavenumber Power spectrum computed from the along-track AltiKa SLA reveals that slopes in the mesoscale band (70-250 km) in different phases of operations are not very different. Errors in gridded SARAL/AltiKa SLA with respect to standard AVISO product remains unchanged during DP, but degrade by nearly 9.3% in the MP as compared to ERM. To assess the effect of assimilating along track SWH and SLA from different phases, two set of wave and circulation model simulations, with and without SARAL AltiKa data assimilation, were performed. Assimilation of SWH improved the wave height simulation by ∼12.8% during the DP and ∼ 8% during ERM and MP. As regards to circulation modeling, no significant difference of assimilating SLA from different phases was observed in the mesoscale range. These results indicate the usefulness of SLA from SARAL AltiKa during DP and MP for studying the mesoscale dynamics.
Article
This study presents the first spatial calibration of SWAN model physical parameters based on satellite observations for the Black and Azov Seas. Currently, the wind-wave model performance is unknown in several coastal and offshore areas due to the gap in wave buoy measurements. The development and increase of altimetry satellites allow collecting a large number of observations in a reasonable time, and thus to calibrate spatially wave models. Therefore, the present study aims to determine the best physical parameterization of the unstructured SWAN model based on satellite data for coarse domain over Black and Azov Seas and for local domain implementations. For this purpose, the significant wave height (SWH) was simulated using 44 physical settings for both ERA5 and CFSR winds. The spatial calibration is based on observations from seven altimetry satellites (Jason-3, Sentinel-3A, Sentinel-3B, Cryosat-2, SARAL/AltiKa, CFOSAT, and Hai Yang-2B). The spatial calibration and evaluation of the wind-wave model performance show an informative variation in the wave model performance, which can depend on several factors such as coastal morphology and the wind source accuracy and the physical setting of the wind-wave model. It raises several findings concerning the spatial sensitivity of the SWAN model to the used wind field, the wind and whitecapping source terms, whitecapping coefficient (Cds), and the windscaling tunable parameter, and the wind growth formulates using the ST6 package. Thus, this study allows observing the spatial response of the SWAN model as a function of physical parameterizations. The SWAN model calibration improved the simulation accuracy considerably overall Black and Azov Sea areas, using both CFSR and ERA5. The SWAN model using the ERA5 winds has provided a higher correlation and better accuracy in large part of the seas. It is highly recommended for the whole Black and Azov Seas to define the wind input term and whitecapping term based on (Komen et al., 1984), with a Cds coefficient of 0.8E-5. Considering the spatial error statistics, the same finding was obtained when the model results were compared with Utrish wave buoy measurements in the northeastern part of the Black Sea. Therefore, for local nested model implementation, it is also recommended to define the optimal configuration based on the error statistics mapped in the present paper.
Article
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The upcoming Surface Water and Ocean Topography (SWOT) mission provides a promising opportunity for retrieval of high spatiotemporal resolution water surface height (WSH) over inland water bodies. To investigate the accuracy of SWOT derived WSH, the observations over Lake Baikal are simulated and a comprehensive evaluation is conducted in this study. Firstly, compared with Jason‐class altimeter WSH and in situ WSHs, the accuracy of SWOT KaRIn‐derived monthly WSHs and their spatiotemporal characteristics are analyzed. Secondly, a local cross‐calibration method is used to reduce the short wavelength roll error over lakes. The results show that, though SWOT has more observations than Jason‐class altimeter, the accuracy of the SWOT KaRIn‐derived monthly WSHs is difficult to be equivalent with those from Jason‐class altimeter, and varies with the number of duplicated observations, the spatial location and the time interval due to the effect of systematic erros and random errors, but can be significantly improved by local cross‐calibration method, especially at higher spatial resolutions after cross‐calibration associate with external nadir altimeter.
Article
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Global sea surface height wave number spectra are revisited using the most recent, lower-noise satellite altimeter missions from Saral/AltiKa and Sentinel-3 and compared to Jason-2 wave number spectra. Spectral preprocessing is configured to minimize the spectral slope distortion in the mesoscale wavelength range. A geographically variable wavelength range is used to calculate the spectral slopes, taking into account the regional eddy length scales based on the local Rossby radius. This dynamical wavelength range increases the spectral slope by 0.5 in middle to high latitudes, compared to a fixed wavelength range, and by-1.0 to 1.0 in different regions of the intertropical band. Using this dynamical wavelength range, mean sea surface height wave number spectra for these lower-noise missions exhibit low slope values (k-2) in the intertropical band, values of k-11/3 in the midlatitudes, and reaches k-5 in the subpolar regions and the Antarctic circumpolar current. An important seasonality is also revealed, with mesoscale spectral slope amplitudes decreasing in winter by 0.5 to 1.5 compared to summer, for the middle-to high-energy regions. A phase-locked internal tide correction is tested but has only a small impact on the spectral slope estimates when using the dynamical wavelength range.
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