Post-doctoral position Water extent mapping from data fusion of L-Band radiometry and radar

Category : CATDS, Data, L3, L4, position opening

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Post-doctoral position

Water extent mapping from data fusion of L-Band radiometry and radar

Location: Centre d’Etudes Spatiale de la Biosphère (CESBIO), Toulouse, France

Duration: 18 months start before November 2018

Description:

Interested in creating state of the art remote sensing products in hydrology for existing and future satellite mission, then join us ! In the framework of the future Surface Water and Ocean Topography (SWOT), a joint mission from French (CNES), American (NASA), Canadian (CSA), and British (UKSA) space agencies, CNES is developing a down-stream application service that will also integrate products from contemporary satellites. In 2008 the CNES had already developed a downstream centre (CATDS www.catds.fr) for the Soil Moisture Ocean Salinity (SMOS) mission which is providing today high level products for the mission. You will join the Microwave-SMOS group in the Observation Systems team at CESBIO. You will be under the supervision of Ahmad Al bitar (Ph.D.) who si in charge of high end (L4) products for CATDS and member of the Science Team of SWOT. You will contribute to existing collaborations with other institutions: LEGOS, GET, ECOLAB, Univ. Purpan.  You will be in charge of developing operationally ready products for the monitoring of inland water surfaces (wetlands, floodplains…) by extending the domain of application of existing algorithms and improving their resolution. These areas represent a great challenge and raise important scientific questions related to the water cycle, biodiversity and carbon cycle. Recent studies at CESBIO demonstrated the advantage of the use of L-Band for the monitoring of water surfaces under dense tropical forests. The final objective is to enrich the existing databases at global scale (CCI Water bodies, GSWO, GIEMS) and to make available a validation dataset for the future SWOT mission.

Actions:

> Adapting the retrieval algorithms for global application using L-Band brightness temperatures.
> Writing scientific papers, presenting results at conferences and project key-points.

Required Skills:

> Advanced knowledge of one programming language Matlab, Python using geospatial datasets.
> Proven writing and communication skills.
> Motivated, innovative and team-player.

Links:

https://www.researchgate.net/publication/317012733_Mapping_Dynamic_Water_Fraction_under_the_Tropical_Rain_Forests_of_the_Amazonian_Basin_from_SMOS_Brightness_Temperatures

Contact:

e-mail to : ahmad.albitar@cesbio.cnes.fr & santiago.penaluque@cnes.fr

SMOS retrieves salinity closer to the coast line

Category : L2, L3, Ocean

From J Boutin, and colleagues from LOCEAN

Salinity observing satellites have the potential to monitor river fresh-water plumes mesoscale spatio-temporal variations better than any other observing system. In the case of the SMOS mission, this capacity was hampered due to the contamination of SMOS data processing by strong land-sea emissivity contrasts.

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With the new systematic error mitigation, SMOS SSS becomes more consistent with the independent SMAP SSS close to land, for instance capturing consistent spatio-temporal variations of low salinity waters in the Bay of Bengal and Gulf of Mexico (see Figure 1 below). The standard deviation of the differences between SMOS and SMAP weekly SSS is less than 0.3 pss in most of the open ocean. The standard deviation of the differences between 18-day SMOS SSS and 100-km averaged ship SSS is 0.20 pss (0.24 pss before correction) in the open ocean (see Figure 2 below). Even if this standard deviation of the differences increases closer to land, the larger SSS variability yields a more favorable signal-to-noise ratio, with r2 between SMOS and SMAP SSS larger than 0.8. The correction also reduces systematic biases associated with man-made Radio Frequency Interferences (RFI), although SMOS remains more impacted by RFI than SMAP. This newly-processed dataset will allow the analysis of SSS variability over a larger than 8 years period in regions previously heavily influenced by land-sea contamination, such as the Bay of Bengal or the Gulf of Mexico.

The new SMOS SSS products are available at CATDS (’CEC LOCEAN debias v2′ produced by LOCEAN/ACRI expertise center and ‘CPDC L3Q’ produced by the near real time CATDS chain). The paper is available here (the link is freely active during 2 months).

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Figure 1: SMOS SSS corrected according to (a,d) Kolodziejczyk et al. (2016) methodology, (b, e) the method described in this paper (CEC); (c, f) SMAP SSS, in two areas : (a, b, c) : Bay of Bengal - August 21st 2015; (d, e, f) : Gulf of Mexico – August18th 2015.SMOS and SMAP SSS is averaged over a SMOS repetitive orbit sub-cycle (18 days) and two SMAP repetitive orbit cycles (16 days) respectively. Striking fresh SSS features in better agreement with SMOS (new version) and SMAP are indicated with white arrows.

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Figure 2: Statistics of ship comparisons (May 2010-August 2016) binned as a function of the distance from the nearest coast: top) mean difference; bottom) standard deviation of the differences; the black line indicates the standard deviation of ship SSS in each class. Ship and SMOS SSS are integrated over 100 km. Orange: monthly SMOS L3P SSS (without error mitigation) ; pink : monthly SMOS L3Q (with error mitigation; near real time processing); light blue : 18-day SMOS CEC (with error mitigation; LOCEAN/ACRI expertise center processing); green : ISAS (Argo optimal interpolation).

SMOS: A new tool to monitor the carbon budget of vegetation: first application to the African continent

Category : L3

How do the vegetation carbon stocks change at the continental scale? What are the drivers of these changes? These are central questions for the sciences of Climate and for the application of international agreements on climate. A study coordinated by the University of Copenhagen1 has developed a new approach to investigate this issue. In collaboration with scientific teams2 from CEA, CNES and CNRS, INRA has coordinated the development of the new data set derived from SMOS microwave observations which is used to quantify vegetation carbon stocks. The study demonstrates that over the African continent and during the 2010-2016 period, the net carbon balance is negative (corresponding to a decrease of the quantity of carbon stored in the vegetation biomass) and that most of the carbon losses occurred in dryland savannahs. These results were published on 9th April 2018 in the journal Nature Ecology and Evolution.

Satellite passive microwaves reveal recent climate-induced carbon losses in African drylands, Martin Brandt, et al., Nature Ecology & Evolution, Apr 9, 2018, doi:10.1038/s41559-018-0530-6

Changes in aboveground vegetation carbon stocks in sub-Saharan Africa over 2010–2016. Regions with significant negative (carbon source) or positive (carbon sink) carbon changes are shown, respectively, in red or green.

© M. Brandt – Université de Copenhague

Scientists from INRA and their colleagues have produced a new data set of the vegetation index referred to as L-VOD (L-band vegetation optical depth), retrieved from space-borne observations of the SMOS satellite over 2010-2016. The data have been used to quantify annual aboveground biomass-carbon changes in sub-Saharan Africa stocks over the time period. The L-VOD index computed from SMOS observations allows sensing the whole canopy layer, while remote sensing observations made so far (including VOD indexes from high frequency microwave observations) were limited to sensing the top of the canopy, especially over relatively dense forests. In this study, the L-VOD index brings a temporal dimension to global, but static, maps of the above ground biomass.

An new tool to carry out an innovative monitoring of the dynamics of aboveground vegetation carbon stocks

This new method allows to monitor the seasonal dynamics of vegetation carbon losses and gains and also to link them with the impact of climate. The results demonstrate the key interest of SMOS L-VOD as a complementary data source for the quantification and monitoring of carbon stocks for national reports and large scale efforts in the framework of international initiatives such as the United Nations Framework Convention on Climate Change (UNFCCC) and the Intergovernmental Panel on Climate Change (IPCC). The SMOS L-VOD index is particularly relevant to study relatively dense vegetation ecosystems where the signal measured from other remotely-sensed system saturates. It is also very relevant for semi-arid regions with little inventory data.

First applications of the new L-VOD tool to monitor carbon changes in sub-Saharan Africa

The study demonstrates there is an overall negative net carbon budget for sub-Saharan Africa (−0.10 PgC yr−1) over 2010-2016 and that the majority of the net losses occurred in drylands. In the latter regions, the gross loss per year represents approximately

5% of the dryland total carbon stocks in Africa. Overall, most of the detected decreases in carbon stocks in drylands were related to abnormally low soil moisture and rainfall conditions. The analyses showed there is a high inter-annual variability in the vegetation carbon stocks with gains during very wet years in (2011) and losses during in 2015 and early 2016, following a severe El Niño episode.

This study questions the general understandin

g that drylands may serve as carbon sinks on the long term. Indeed, the authors have found that dry years have partly reversed this trend and that drylands (especially in southern Africa) turned from being a carbon sink into a source over 2010-2016, demonstrating that climate controls short-term variations in carbon stocks at large scales.

So, in the long term we need to reassess whether woody vegetation in African savannahs will continue to be a carbon sink.


1 Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark

2 List of French teams involved:

Unité « Interaction Sol Plante Atmosphère » (Inra, Bordeaux Sciences Agro), centre Inra Nouvelle-Aquitaine

Laboratoire Evolution et Diversité Biologique (CNRS – IRD – UT3 Paul Sabatier – ENFA)

Laboratoire des sciences du climat et de l’environnement (CEA-CNRS-UVSQ)

Centre d’études spatiales de la biosphère (Cnes-CNRS-IRD-UT3 Paul Sabatier)

NEW PRODUCTS on CATDS

Category : CATDS, L2, L3

I am very pleased to announce that the new SMOS-IC soil moisture product is now available as a science product on the CATDS:

The SMOS INRA-CESBIO (SMOS-IC) algorithm was designed by INRA (Institut National de la Recherche Agronomique) and CESBIO (Centre d’Etudes Spatiales de la BIOsphère) to perform global retrievals of SM and L-VOD using some simplifications with respect to the Level 2 ESA algorithm. The SMOS-IC algorithm and dataset is described in Fernandez-Moran et al. (2017). SMOS -IC was designed on the same basis as the level 2 SM algorithm, i.e., L-MEB (Wigneron et al, 2007). However, one of the main goals of the SMOS-IC product is to be as independent as possible from auxiliary data so as to be more robust and less impacted by potential uncertainties in the afore mentioned auxiliary data sets. It also differs from the SMOS Level 2 product in the treatment of retrievals over regions with a heterogeneous land cover (partially forested areas). Specifically, SMOS-IC does not account for corrections associated with the antenna pattern and the complex SMOS viewing angle geometry. It considers pixels as homogeneous.

The current version is 105 and it is provided in the 25km EASEv2 grid, as netcdf format. SMOS IC is a scientific product delivered by the CATDS, i.e. meaning it is not updated on a daily basis as an operational product for the time being.

We re looking forward to receiving your feed back as we intend to make it an operational product soon.

We will soon deploy the companion  SMOS-IC VOD (vegetation Optical Depth) product as well as a corresponding Level 3 for both SM and VOD obtained with SMOS-IC

Also Note that very soon we will deploy another new product (yes), i.e., SMOS brightness temperature in polar projection

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