Satellite Data Assimilation for Land Surface Modelling

Dear Colleagues,

The recent advancements in remote sensing techniques have gained a lot of attention as it becomes more important to improve our understanding of the Earth’s system. Traditionally, various types of models, such as hydrologic and atmospheric models, have been used for modelling/simulating and predicting hydro‐meteorological processes at regional and global scales. Nevertheless, due to various sources of uncertainties such as imperfect modelling, data limitations on both temporal and spatial resolutions, their errors, as well as limited knowledge about empirical model parameters, the accuracy of model simulations can be degraded.

Assimilation of satellite data has been shown to be effective for improving the models’ performance and their forecasting skills. This allows us to better study, for example, water resources and their distribution, mass variations and balance, extreme events such as droughts and floods, and ice transfer, and also helps us adapt to long-term environmental challenges posed by climate changes on a continental scale. Data assimilation (DA) facilitates this data integration by constraining the models’ simulations based on observations and errors associated with them. The method has become more popular with the advent of the space era, since scientific observational methods are no longer limited to terrestrial only, and offer high spatiotemporal resolution data with global coverage.

Therefore, satellite DA has great potential in hydro-climate studies. The main goal of this Special Issue is to publish both innovative and practical solutions to the complex DA problems when integrating satellite data products with land surface models. High-quality and original submissions are also encouraged to discuss the current satellite DA challenges in this issue.

Dr. Mehdi Khaki
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Remote Sensing is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• Data assimilation
• Satellite remote sensing
• Hydro-climate modelling
• State-parameter estimation
• Model calibration
• Uncertainty analysis
• Numerical forecasts