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Special Issue "Evaluation of Reanalysis Data in Meteorological and Climatological Applications: Spatial and Temporal Considerations"
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".
Deadline for manuscript submissions: closed (10 June 2022) | Viewed by 15893
Special Issue Editor
Interests: agricultural climatology; crop–climate relationships; crop simulation models; reanalysis datasets; drought indices; statistical climatology; climate change scenarios; statistical downscaling
Special Issues, Collections and Topics in MDPI journals
Special Issue in Hydrology: Trends and Variations in Hydroclimatic Variables
Special Issue Information
Reanalysis datasets are among the most used gridded data in the study of weather and climate. Due to their homogenous nature and high spatial and temporal resolution (compared to raw observations), they are used for evaluating climate models, irrigation management decisions, soil water balance evolution, flooding predictions, as well as for many other purposes.
With multiple reanalysis datasets now available, researchers must consider the strengths and weaknesses of each product by evaluating its quality in reproducing the variation of mean and variability, on spatial and temporal basis, captured in observations. Although efforts to improve reanalysis products have led to significant progress at a global level, reanalysis products at a regional level could not always reproduce characteristic climatological features. Estimates of the basic dynamic fields in modern reanalysis are increasingly similar, especially in the vicinity of abundant observations. While this is true for temperature, physics fields (e.g., precipitation and longwave radiation) are more uncertain, due to shortcomings in the assimilating model and its parameterizations. The challenges become even more formidable when reanalysis data are used to assess climate change and extremes at high resolutions in time and in space.
In this context, this Special Issue welcomes articles dedicated not only to the evaluation of reanalysis products against observations but also to exploring the effects of uncertainties using reanalysis data in model output. Such models include but are not limited to hydrological, weather forecasting, crop models, and any other models used for meteorological and climatological purposes by taking into account spatial and temporal considerations.
Dr. Mavromatis Theodoros
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. Water 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 2200 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.
- reanalysis datasets
- uncertainty assessment in model output
- numerical weather prediction models
- climate model evaluation
- hydrological models
- soil water balance evolution
- crop models
- drought indices
- crop–climate relationships
- climate change scenarios