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.

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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.

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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.

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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

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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.

Soon 8 candles for SMOS!!!!! (5/8)

Category : CATDS, L2, L3, Model, Ocean

Another post from Jacqueline…and Jérôme

Water cycle in the Bay of Bengal

J. Vialard , S. Marchand et al. (LOCEAN)

The Bay of Bengal receives large amounts of freshwater from the Ganges-Brahmaputra river and monsoonal rainfall. The associated very low surface salinities induce a very stable stratification that inhibits vertical mixing of heat and nutrients. This has strong consequences for the climatological rainfall, intensification of tropical cyclones and ocean productivity in this region.

Available climatologies based on in situ data (e.g. World Ocean Atlas, top row) do not resolve the very strong horizontal gradients in this region. SMOS data (middle row) reveal that the narrow, coastal-trapped East-Indian Coastal Current transport the freshwater plume of Ganges-Brahmaputra along the Indian coast from October to December, resulting in large horizontal gradients (typically ~5 pss between coastal and offshore waters). The 8 years-long time series reveals a strong inter-annual variability of the freshwater plume southward extent, which can be related to Indian Ocean climate variability.


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Caption: World ocean atlas (derived from in situ data, top row) and SMOS (middle row) (SSS climatology (altimeter-derived surface current climatology are overlaid on both panels). (Bottom row) Latitude-time section of SMOS SSS along the east coast of India. The southward extent of the freshwater plume varies depending on Indian Ocean climate variability associated with the Indian Ocean Dipole (Akhil et al. in prep.). (SMOS CATDS CPDC L3Q SSS)

To know more about associated work:

Akhil, V.P., F. Durand, M. Lengaigne, J. Vialard, M.G. Keerthi, V.V. Gopalakrishna, C. Deltel, F. Papa and C. de Boyer Montégut, 2014: A modeling study of the processes of surface salinity seasonal cycle in the Bay of Bengal, J. Geophys. Res. Oceans, 119, doi:10.1002/2013JC009632.

Akhil, V. P., M. Lengaigne, J. Vialard, F. Durand, M. G. Keerthi, A. V. S. Chaitanya, F. Papa, V. V. Gopalakrishna, and C. de Boyer Montégut, 2016a: A modeling study of processes controlling the Bay of Bengal sea surface salinity interannual variability, J. Geophys. Res. Oceans, 121, 8471–8495, doi:10.1002/2016JC011662.

Akhil, V.P., M. Lengaigne, F. Durand, J. Vialard, V.V. Gopalakrishna, C. de Boyer Montégut and J. Boutin, 2016b: Validation of SMOS and Aquarius remotely-sensed surface salinity in the Bay of Bengal, IJRS, 37,  doi: 10.1080/01431161.2016.1145362

Boutin, J., J.L. Vergely, S. Marchand, F. D’Amico, A. Hasson, N. Kolodziejczyk, N. Reul, G. Reverdin (2017), Revised mitigation of systematic errors in SMOS sea surface salinity: a Bayesian approach, Remote Sensing of Environment, in revision.

Chaittanya, A.V.S., M. Lengaigne, J. Vialard, V.V. Gopalakrishna, F. Durand, Ch. Krantikumar, V. Suneel, F. Papa and M. Ravichandran, 2014: Fishermen-operated salinity measurements reveal a “river in the sea” flowing along the east coast of India, Bull. Am. Met. Soc., 95, 1897-1908.

Fournier, S., J. Vialard, M. Lengaigne, T. Lee, M.M. Gierach, A.V.S. Chaitanya, Unprecedented satellite synoptic views of the Bay of Bengal “river in the sea”, 2017: J. Geophys. Res., in (minor) revision.

Postdoctoral Researcher: Satellite-Based Data Assimilation for Soil Moisture Estimation

Category : Model, position opening

We are searching for an enthusiastic postdoctoral researcher with experience in land surface modeling and/or data assimilation to implement advanced modules into an existing global land surface data assimilation system. You will be part of the Department of Earth and Environmental Sciences, Division Soil and Water Management, at the KU Leuven (Belgium), working under the supervision of prof. Gabrielle De Lannoy.

Soil moisture is a key variable in the water, energy and carbon cycle over land. The objective of this project is to merge large-scale land surface simulations with satellite-based microwave observations, using an advanced data assimilation scheme which corrects for both the random and persistent errors in soil moisture estimates. The improved soil moisture time series will help enhancing subsequent predictions of flooding, landslides, soil and vegetation carbon, deeper groundwater and the atmospheric boundary layer.

Our team

Responsibilities
==========
- Perform and disseminate highly qualitative research related to land surface modeling, observation and data assimilation
- Possibly supervise PhD or master thesis students

Profile
==========
- PhD degree in Hydrology, Civil or Environmental Engineering, Meteorology, Remotely Sensed Earth Observation, Physics, Mathematics, Computer Sciences, or equivalent
- Experience with data-processing applications such as Matlab/Python, IDL,GrADS, R, or other
- Experience in programming and scientific computing
- Excellent motivation and grades
- Creative, critical, analytical and innovative mindset
- Ability to work independently
- Excellent written and oral communication skills in English, proven in publications

Offer
==========
- 2-year position with a competitive salary; support in career development
- Multi-disciplinary and international professional environment
- Leuven is a charming historical university town, located in the heart of Western Europe

Interested?
==========
Only persons matching the above profile should apply. Please submit your resume, along with a motivation letter and two names for references on-line. The start date is 1 June 2017, but earlier or later start dates can be negotiated. For more information please contact prof. Gabrielle De Lannoy, tel.: +32 16 37 67 13, mail: gabrielle.delannoy@kuleuven.be.

Apply for this job no later than 15 May, 2017 via the online application tool. The position will remain open until filled by an excellent candidate.

Next Living Planet Symposium!

Category : Cal/Val, Data, Model, Satellite, ground measurements

…. from the LPS16 Organising Committee team

Dear colleague,

We would like to kindly remind you that the deadline for submitting abstracts to ESA’s Living Planet Symposium 2016 is 16 October 2015.

On the Symposium website (http://lps16.esa.int/), you will find more information about the event that will be held in Prague (Czech Republic) 9-13 May 2016 including the link to submit your abstracts
https://www.conftool.pro/lps16/index.php?page=index

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