Weather Research and Forecasting: Current Status and Future Directions

Dear Colleagues,

Weather information is increasingly being required for decision-making at the community scale. Historically, the meteorological observation network is based primarily on in situ instrumentation. This network was designed to provide the data necessary for predicting synoptic-scale weather features. The stations that form the network are spaced about 500 km apart, and soundings are made twice daily.

A more closely spaced grid network of surface stations Is needed to provide information at the spatial and temporal scales that are useful for the prediction of the meso- (smaller weather systems ranging from a horizontal scale of five to several hundred kilometres) and micro-features (short-lived atmospheric phenomena smaller than mesoscale, about 1 kilometre or less; time scale: very short-lived, often minutes or hours) of the atmosphere, which is what is needed at the community scale. However, these data are not adequate to meet the needs of meteorologists, basically because of the lack of information on the vertical structure of the atmosphere. Studies of the costs and other problems associated with a simple enlargement of the existing radiosonde network have shown that such a solution is not viable. Consequently, attention has turned to developing and deploying new technology, such as satellite and ground-based remote sensing systems, among others, to fill this void.

While the status of synoptic-scale forecasting is reasonable in most parts of the world, there is still room for improvement especially in the tropics. Additionally, the future direction is towards getting information at the community scale (meso- and microscale) to enhance decision-making for improved local governance.

The topics of interest for this Special Issue include, but are not limited to, the following:

Data (surface and upper air observations);
Remote sensing (satellite, radar, etc.);
Convection permitting modelling;
Ensemble prediction;
Unified modelling/seamless prediction;
Data assimilation;
Parametrization;
Machine learning (ML) and artificial intelligence (AI);
Evaluation and verification;
Automatic weather stations (AWS) and related forecasting infrastructure.

This Special Issue welcomes submissions about the status and future trends in various aspects of weather research and forecasting relating to the provision of weather information and also its contribution to climate resilience.

Dr. Benjamin Lantei Lamptey
Guest Editor

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