Soon 8 candles for SMOS!! (4/8)

Category : CATDS, Cal/Val, Data, L2, Non classé, ground measurements

Today let’s have a look back on what was done over land… but remember: it is only a quick summary of part of the findings!!

blogyhk1

Of course all the emphasis at the beginning was on the soil moisture retrievals over what as called « nominal surfaces », which meant land surface with moderate vegetation cover (fallow, crop land, savannah etc..) with all the cal val efforts related to it. For this in particular, several sites were dedicated to Cal Val (VAS in Spain, UDB in Germany, AACES/COSMOS/NAFE in Australia, and later HOBE in Denmark, with also sites in France, Poland, Finland, Tibet, etc…). We also relied heavily on the USDA so called « Watershed sites » and various sparse networks. Actually it is for SMOS that ESA and NASA decided to start the International Soil moisture Network.

lewis-faugaAACES 6MELBEX-II EMIRAD Installation 004LEWIS_3IMG_9674ELBARA-Sodankyla

Various pictures SMOSREX, AACES, VAS, Crolles, Mysore, Sodankylä …

Surprisingly enough we obtained good results almost immediately. But this was only the beginning as, in parallel, both level 1 and level 2 made significant progresses, leading to always improved retrievals. Actually with such fast progresses, it has always been a bit of a frustration to see people use not up to date products, as publications looking at SMOS data tended – for obvious reasons – to be a couple of version old (but generally failed to stipulate which version they were looking at!).

The most striking features of these always improved retrievals was, to me, the fact that the range of validity tended to regularly increase. Low to medium topography did not seem to a be a limitation, we managed to make sense in case of flooded areas (see for instance Mississipi floods) and we could get information in case of dense vegetation. The Tor Vergata University for instance related very quickly the vegetation depth to tree height and performed soil moisture retrievals under rainforest. No so accurate of course, but the tendencies are well depicted.

blogyhk2

SMOS opacity vs tree height from ICESat for two season (Rahmoune et al)

The only trouble we had was that the vegetation optical depth was not as satisfactory as we would have expected. It remained noisy in spite of significant overall progresses. To address this problem and also to keep on improving our retrievals (parametrisations) INRA and CESBIO worked on a different approach, the so called SMOS-IC and, lo and behold, first results are rather amazing! We believe we have again struck gold. More about this in the near future!

To finish with the surface soil moisture and vegetation opacity retrievals, we were faced with the fact that the retrieval algorithm is not so fast and thus tests or re-processings are a lengthy and tedious. This was another motivation for SMOS-IC but we also wanted to go a step further and, as soon as enough data was acquired, we developed a global neural network retrieval scheme. It has since been implemented in ECMWF and delivers Soil moisture fields less than 3 hours of sensing, paving the way to many applications…. to be summarised soon: stay tuned!

Further reading

Fernandez-Moran, R.; Al-Yaari, A.; Mialon, A.; Mahmoodi, A.; Al Bitar, A.; De Lannoy, G.; Rodriguez-Fernandez, N.; Lopez-Baeza, E.; Kerr, Y.; Wigneron, J.-P. SMOS-IC: An Alternative SMOS Soil Moisture and Vegetation Optical Depth Product. Remote Sens. 2017, 9, 457.

Kerr, Y. H., et al. (2012), The SMOS Soil Moisture Retrieval Algorithm, IEEE Transactions on Geoscience and Remote Sensing, 50(5), 1384-1403, doi:10.1109/tgrs.2012.2184548.

Rahmoune, R., Ferrazzoli, P., Singh, Y., Kerr, Y., Richaume, P., Al Bitar,  A. SMOS Retrieval Results Over Forests: Comparisons With Independent Measurements. J-STARS ,2014

Rodriguez-Fernandez, N.J., Aires, F., Richaume, P., Kerr, Y.H., Prigent, C., Kolassa, J., Cabot, F., Jimenez, C., Mahmoodi, A., & Drusch, M. (2015). Soil Moisture Retrieval Using Neural Networks: Application to SMOS. Ieee Transactions on Geoscience and Remote Sensing, 53, 5991-6007

Vittucci, C., Ferrazzoli, P., Kerr, Y., Richaume, P., Guerriero, L., Rahmoune, R., & Laurin, G.V. (2016). SMOS retrieval over forests: Exploitation of optical depth and tests of soil moisture estimates. Remote Sensing of Environment, 180, 115-127

Postdoctoral Associate Position in WRF Land Data Assimilation at U-Albany

Category : position opening

Postdoctoral Associate Position in WRF Land Data Assimilation at U-Albany


The SUNY University at Albany Atmospheric Sciences Research Center (ASRC) is conducting a search for a postdoctoral associate to work for 2-years in support of a NASA-funded project on assimilation of NASA Soil Moisture Active Passive (SMAP)   satellite-based soil moisture data into short-term NASA Unified Weather Research and Forecasting (NU-WRF) model forecasts. The planned weather- and climate-relevant research will involve extensive numerical weather forecast model evaluation and code modification. The specific objective is to improve short-term (9-30 h) weather (incl. wind) predictability over the central U.S.

To apply, go to:
https://rfhr.interviewexchange.com/jobofferdetails.jsp;jsessionid=DE3CB6CECC39BD78B87966E519AF3EFA?JOBID=90729

The position will remain open until filled. There is a preferred start date of February 2018 or sooner.

Any questions may be directed to Dr. Craig R. Ferguson (crferguson@albany.edu).

See Africa Breathing!

Category : CATDS, Data, L3

Simon Gascoin from CESBIO just sent me this animation he made using CATDS SMOS L3 SM over Africa

SMOS_AFRICA_SM

SMOS MONTHLY SM Fields over Africa (click to activate)

It is fascinating to see not only the pulsating effect of ITCZ over Africa, but also its counterpart in South Africa, the Euphrates  or the rainy seasons over the Maghreb, the internal Niger delta or the Okavango and many more … Enjoy

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.

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