Special Issue "Extreme Weather Detection, Attribution and Adaptation Design"
A special issue of Climate (ISSN 2225-1154).
Deadline for manuscript submissions: 31 January 2024 | Viewed by 3074
Interests: numerical weather and climate modeling/prediction; impact of climate changes on weather extremes; air quality modeling and prediction; satellite and radar data assimilation; machine learning in atmospheric science; radar-based nowcasting; wind and solar energy forecasting; tropical cyclones prediction; WRF models; WRF-Chem and CAMQ model; AOD data assimilation
Special Issues, Collections and Topics in MDPI journals
Interests: regional weather and climate modelling; data assimilation; weather and climate extremes; indian monsoons
Interests: atmospheric remote sensing; satellite remote sensing (GPM,TRMM); polarimetric weather radar; radar meteorology; radar rainfall estimation
Extreme precipitation events can lead to substantial loss of property and life. The timely and accurate predictions of these events can potentially mitigate some of these losses by providing decision support to stakeholders and communities. The skillful prediction of such extreme events through numerical weather prediction (NWP), statistical techniques, or their combination in hybrid dynamical-statistical methods is crucial for managing preparedness, emergency response, and mitigation of impacts. However, the prediction of rainfall extremes remains challenging in NWP due to various causes, including model deficiencies and initial-value problems. Several approaches for assimilating precipitation observations in NWP models have been developed in the last few years to improve the model’s initial states and subsequent short-range forecasts. This Special Issue invites papers on observational and numerical modeling studies of extreme events such as flash floods and cloud bursts to understand their spatiotemporal characteristics. In particular, we also encourage authors to explore extreme events related to past and near-future hazards, which would assist policymakers in building societies which are potentially more resilient. Additionally, this Special Issue is expected to include articles that use observations and modeling techniques to understand the physics of rainfall extremes and further enhance overall model forecast skills.
Dr. Chandrasekar Radhakrishnan
Dr. Attada Raju
Dr. Biswas Sounak
Dr. Kannan Srinivasa Ramanujam
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. Climate is an international peer-reviewed open access monthly 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 1600 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.
- numerical weather forecasting and nowcasting
- applications of machine learning in severe weather prediction
- data assimilation in numerical weather forecasting models
- severe weather warning systems
- spaceborne satellites/radar weather detection
- impact of climate change on weather extremes