Research Engineer in Remote Sensing: Characterising Uncertainties in Satellite Sea Surface Salinity

Category : Ocean, position opening

A research engineer position is open at the Laboratoire d’Océanographie et du Climat – Expérimentation et Approches Numériques (LOCEAN)/ Institut Pierre Simon Laplace (IPSL), PARIS, starting as soon as possible. The position is open for one year, renewable for 2 years depending on the candidate performance.

Context:

The SMOS (Soil Moisture and Ocean Salinity) mission is the first Earth-observing satellite mission carrying an L-band radiometer interferometer. Since its launch at the end of 2009, it has acquired more than 8 years of data that demonstrate the feasibility of the sea surface salinity retrieved by satellite with remarkable spatial resolution compared to other techniques. It has also opened new research perspectives. This unique 8-year salinity time series has permitted unique analyses of salinity variability, linked to oceanic meso-scale and to El Niño type events. Two other satellite missions, Aquarius (2011-2015, CONAE/NASA) and SMAP (2015-, NASA), also based on L-band radiometry, have been providing complementary synoptic salinity measurements leading to an unprecedented spatial coverage. Nevertheless, uncertainties on retrieved salinities differ depending on the radiometer type, the observation geometry, the calibration method, and on the direct and inverse models.

The LOCEAN team is involved since 1999 in the definition of the direct and inverse models applicable to SMOS and in the calibration-validation of the SMOS measurements. It is recognized as SMOS expert support laboratory by the European Spatial Agency (ESA) and by the Centre Aval de Traitement des Données SMOS funded by Centre National d’Etudes Spatiales (CNES). The selected candidate will join the LOCEAN team involved in the physics of the L-band radiometry, in the satellite salinity validation and in the understanding of responsible processes for the observed differences between satellites and in situ measurements, in particular those associated with air-sea interactions, vertical stratification and small-scale variability (www.locean-ipsl.upmc.fr/smos/ and siss.locean-ipsl.upmc.fr).

Work details :

- Characterization of uncertainties of satellite salinity products based on intercomparisons of the various satellite products and comparisons with in situ measurements. This work will be based on existing tools that the selected engineer will adapt to focus on case studies allowing the identification of the uncertainties origin. It will be performed in strong collaboration with researchers and engineers of the LOCEAN SMOS team.

- SMOS data processor development assessment in collaboration with the engineers and researchers in charge of its evolution. Participation to regular progress meetings (teleconferences) of CATDS (2-3 per year).

- Support to users (in French and English)

-Writing of technical papers and participation to scientific papers is possible, depending on the obtained results.

Required Skills:

-       Physics of satellite measurement

-       Data statistical analysis and critical interpretation of the results

-       Autonomy and team collaborative working

-       Python / Matlab ; LINUX

-       Interest in team software development: object-oriented programming, code refactoring & automated testing (e.g. pytest), version control (e.g. Git), code documentation.

Appreciated Skills:

-       Optimization for large dataset processing

-       Interest for environmental science

-       French and English

Level: Research Engineer (PhD thesis or equivalent). Master 2 in remote sensing will also be considered.

Address : LOCEAN, Sorbonne Université, Tour 45-55, 5E, 4, place Jussieu, 75005 PARIS, FRANCE.

Salary : about 1900E monthly net, commensurable with qualification and experience of the candidate (CNRS salary grid)

Candidates should send a statement of interest, CV and coordinates of 2 referees to  Jacqueline Boutin (jb@locean-ipsl.upmc.fr) and Dimitry Khvorostyanov (dimitry.khvorostyanov@locean.upmc.fr ).

Breaking news –> SMOS new LEVEL 2 SM Version in ready!

Category : L2

Dear All

The long awaited SMOS V650 is now ready for release and thus for you to use!

We (ESA and ESLs) have prepared it  tested it, run the reprocessing from beginning to now, and the operational processor is no ready to produce it giving you access to the whole data set!

The main features of the new versions are described in the release note made available with the new distribution. It capitalises as usual on the progresses made at level 1, but the most salient features are

  • the replacement of ECOCLIMAP by IGBP which enables to have i) an up to date land use map and ii) to be aligned with SMAP and Aquarius,
  • the use of CdF matching in mixed forest nominal pixels and much more accurate and
  • relevant DQX and Chi2
  • Finally the way the current files are updated is also improved.

As  a consequence the new version is « wetter » at high latitudes and around forested areas (with also higher VODs), more retrievals are successful. In terms of metrics with respect to our usual sparse and dense networks, both correlation coefficients and RMSE  are improved but also thereis no bias at all while the SDTE remains the same.

V651-SM

Difference (V650-V620) of averaged soil moisture (4 months per year January; April, July and October) during 7 years.

V650-Tau

Difference (V650-V620) of averaged vegetation opacity (4 months per year January; April, July and October) during 7 years.

Data and documentation available at the usual ESA / Array addresses

Note that the SM NRT are being updated. CATDS L3 will also be updated, but after we have corrected an issue with L3 temporal approach algorithm.

Have fun!

Soon 8 candles for SMOS!!!!!! (6/8)

Category : CATDS, L2, L3, L4, Model

After the illustrations of some striking results over oceans, we can only marvel, especially as many other aspects were not covered.  Eight years ago we did not have any of such applications and science return. Those span from rainfall estimates over oceans to wind speed retrievals for strong winds (tropical storms, hurricanes and the like) where wind scatterometers do saturate for lower wind speeds. SMOS, Aquarius and now SMAP do show that L band measurements bring forward many new science obviously but also many very practical and societal applications which are not fulfilled without them.

IRMA_SMOS_20170907_2

Caption: IRMA (2017 09 07) as seen from SMOS in terms of surface wind speed (N. Reul)

This also applies for land of course where new applications blossomed at an unprecedented rate.

It exemplifies, to me at least, how real measurements can never be replaced by proxies. The first radar for EO flew in 1977 (yes 40 years ago!), the scatterometers with Envisat have been available since 1991 but we have yet to see a real soil moisture map from these. Intrinsically active systems are more sensitive to structure that to content and radar soil moisture are at best validated only over small areas where all is known, and similarly to scatterometers, rely on change detection (yes I know I am partial but I can claim that I started fiddling with radars 40 years ago and was one of the pro SCAT over land (convincing ESA to make the sigma nought triplets available over land which was not originally planned incidentally), but to realise soon that it was no game for absolute retrievals). Which means that they have to be scaled and that the validity at point (xi,yi) and no relationship with the validity at point (xj, yj) etc … but this is another story…To make a long story short a nicely coloured map has never make an accurate map.

With L band radiometry no such issues and if properly done, you have access to the soil moisture per se. As a direct consequence, and in opposition to active systems, a few months only after the release of the data the first applications emerged. We saw the first use in food security (W Crow , USDA), the first drought indices really related to what was happening (A Al Bitar detecting the drought in California in 2011 when the official drought index was to detect it only a couple of years later) or monitoring the Mississippi  floods and levees destruction in 2011, the making of a flood risk forecasting tool demonstrator, the Spanish BEC fire risk analysis tool, etc… etc.. etc…

There isn’t enough room in a blog to document all this so I am giving only three samples.

1) high resolution soil moisture map

One of the main limitations of passive microwave is the spatial resolution. Olivier Merlin and his team developed an approach which -in many cases enables to monitor soil moisture with a 1 km resolution as shown in the example below.

anim-1KM_Morocco

Caption: 1 km soil moisture map from SMOS/ MODIS over Morocco (J. Malbeteau)

It can be successfully applied at 100 m in some cases (irrigation optimisation) as shown Catalonia (MJ Escorihuela). Other approaches rely on the use of active systems as originally planned for SMAP (N. Das) and done with SMOS (S. Tomer) or SMAP with Sentinel 1. Ideally the two approaches should be merged to my feeling.

Uses for such derived high resolution products are obvious, for irrigation and hydrology as already mentioned, but also for pest control (Locusts in Africa) or epidemiology (dengue, zika and malaria to name but a few). Moreover it can be used to derive high resolution root zone soil moisture and other passive L band products.

2) Rainfall estimates over land

It is known that rainfall mission (TRMM to GPM) are very useful tool for estimating rainfall distribution over land. It is also well known that estimating rainfall with one instantaneous measurement every so often is somewhat difficult. Sometimes and in some areas/context, the cumulated errors amount to several folds. The idea is thus to assimilate soil moisture estimates so as to « correct » the GPM rainfall estimates. Pellarin, Brocca and Crow and others demonstrated the efficiency of this approach.

blogyhk3

Caption: Evolution of rainfall estimates after assimilating SMOS data (Pellarin, Brocca, Crow et al.)

3) Yield estimates

Soil moisture is a driven of crop yield in many areas. First shown by B. Hornebuckle with SMOS, Gibon and Pellarin went one step further by identifying which soil moisture (30 cm deep) and which period (grain filling and to a lesser extent reproductive) of vegetation growth where the drivers for millet in Western Africa. They then compared their local estimates with FAO global maps and found excellent correlation. It is interesting to see that departures are linked to local events

blogyhk4

Caption: Soil moisture anomalies during two key stages and FAO Millet yield anomalies (F. Gibon)

Examples like this can be multiplied, I just picked some low hanging fruit. One can say that such applications an science results could be expected  and were delivered in record time. This blog is probably already way too long and I did not cover very interesting and promising results on evapotranspiration for instance, or hydrology, not to mention cryosphere … I keep the latter for tomorrow!

Stay tuned !

Further reading:

Brocca, L., Pellarin, T., Crow, W.T., Ciabatta, L., Massari, C., Ryu, D., Su, C.H., Rudiger, C., & Kerr, Y. (2016). Rainfall estimation by inverting SMOS soil moisture estimates: A comparison of different methods over Australia. Journal of Geophysical Research-Atmospheres, 121, 12062-12079

Molero, B., Merlin, O., Malbeteau, Y., Al Bitar, A., Cabot, F., Stefan, V., Kerr, Y., Bacon, S., Cosh, M.H., Bindlish, R., & Jackson, T.J. (2016). SMOS disaggregated soil moisture product at 1 km resolution: Processor overview and first validation results. Remote Sensing of Environment, 180, 361-376

Reul, N., Chapron, B., Zabolotskikh, E., Donlon, C., Quilfen, Y., Guimbard, S., & Piolle, J.F. (2016). A revised L-band radio-brightness sensitivity to extreme winds under tropical cyclones: The 5 year SMOS-Storm database. Remote Sensing of Environment, 180, 274-291

Roman-Cascon, C., Pellarin, T., Gibon, F., Brocca, L., Cosme, E., Crow, W., Fernandez-Prieto, D., Kerr, Y.H., & Massari, C. (2017). Correcting satellite-based precipitation products through SMOS soil moisture data assimilation in two land-surface models of different complexity: API and SURFEX. Remote Sensing of Environment, 200, 295-310.

SMOS REPROCESSED Level 2 DATA (V6) now available

Category : Data, L1, L2, Ocean

Dear SMOS data user -

We would like to inform you that the reprocessed level 2 soil moisture and sea surface salinity data are now available on the new ESA SMOS Online Dissemination service: https://smos-ds-02.eo.esa.int/oads/access/.

This release aligns the Level 2 soil moisture and sea surface salinity data available operationally already since May 2015 with the reprocessed data archive: SMOS data users now have a complete v6 data set available.

The algorithm evolutions implemented in the v6 data set are described in the respective Algorithm Theoretical Baseline Documents (ATBDs) and in the read-me-first notes: https://earth.esa.int/web/guest/missions/esa-operational-eo-missions/smos/content/-/asset_publisher/t5Py/content/data-types-levels-formats-7631. We would like to encourage all users to familiarise themselves with the read-me-first notes before using the data.

The level 2 reprocessed data products are available on the new ESA SMOS Online Dissemination service accessible here (smos-diss.eo.esa.int). The new service allows to access data by https and ftp/ftps transfer protocols for all registered ESA EO Single Sign-On (EO-SSO) users. The online service facilitates the data access with enhanced functionality for data navigation and selection by data type, acquisition time, geographical area and data format (i.e. ESA Earth Explorer (EEF) or NetCDF format).

SMOS level 1 brightness temperature data and  ECMWF auxiliary products are also available from the new ESA SMOS Online Dissemination service.

For further details on how to access the SMOS data  and how to register as ESA EO_SSO please https://earth.esa.int/web/guest/missions/esa-operational-eo-missions/smos/content/-/asset_publisher/t5Py/content/how-to-obtain-data-7329.

Kind regards

Susanne Mecklenburg

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