Meteorology

Meteorology is the scientific study of the atmosphere, encompassing its physical structure, chemical composition and dynamic processes that govern weather and climate. At its core lie the energy exchanges driven by solar radiation, the transport of heat and moisture through turbulent mixing and large‐scale circulations, and the interplay of air masses that give rise to fronts, cyclones and anticyclones. The hydrological cycle—including evaporation, condensation, cloud formation and precipitation—links the atmosphere to the surface and to the oceans, while radiative transfer through gases, aerosols and clouds regulates Earth’s energy balance. From microscale convection cells to planetary‐scale wave motions such as Rossby waves, meteorology spans a vast range of scales and timescales. Advances in satellite remote sensing, automated ground networks and high‐resolution numerical models have revolutionised observations and forecasting, yet fundamental challenges remain in representing processes such as cloud feedbacks, boundary‐layer turbulence and extreme‐event prediction under a changing climate.

Research from Nature Portfolio

Recent work has highlighted the pivotal role of lowermost stratospheric water vapour in modulating both stratospheric overturning and tropospheric jet positions. Small biases in simulated water-vapour concentrations at the tropical cold-point tropopause have been shown to shift subtropical jets poleward and strengthen the stratospheric circulation by magnitudes comparable to greenhouse-gas forcing. A parallel study has employed statistical-learning methods constrained by satellite observations to narrow uncertainties in the projected increase of stratospheric water vapour under global warming, ruling out the strongest modelled rises and improving consistency across 61 climate models. In the tropics, model experiments reveal that greenhouse-induced contraction of off-equatorial convection delays and reduces tropical-cyclone formation by shortening the seasonal migration of the intertropical convergence zone, providing a mechanistic explanation for the divergent frequency projections of storm genesis in climate simulations.

Meteorology publication trend

The graph below shows the total number of articles in meteorology across all publications each year (not limited to Nature Index journals).

Technical terms

Radiative transfer: The process by which energy in the form of electromagnetic radiation is absorbed, emitted and scattered through atmospheric gases, aerosols and clouds.

Cold-point tropopause: The altitude of minimum temperature at the boundary between the troposphere and stratosphere, crucial for dehydration and stratospheric water-vapour setting.

Intertropical convergence zone (ITCZ): The near-equatorial belt where trade winds converge, driving intense convection and influencing tropical cyclone seasons.

Statistical-learning constraint: An approach that uses observed covariations between climate variables to narrow model projection ranges and improve future estimates.

Tropical-cyclone genesis potential: A diagnostic measure combining environmental factors such as vorticity, vertical motion and wind shear to assess the favourability for tropical storm formation.

Saffir–Simpson wind scale: A five-category system that classifies hurricanes by sustained wind speed, used for public hazard communication.

References

1. Stratospheric water vapor affecting atmospheric circulation. Nature Communications (2023).
2. Response of stratospheric water vapour to warming constrained by satellite observations. Nature Geoscience (2023).
3. Warming-induced contraction of tropical convection delays and reduces tropical cyclone formation. Nature Communications (2023).
4. The growing inadequacy of an open-ended Saffir–Simpson hurricane wind scale in a warming world. Proceedings of the National Academy of Sciences of the United States of America (2024).
5. Upstream surface roughness and terrain are strong drivers of contrast in tornado potential between North and South America. Proceedings of the National Academy of Sciences of the United States of America (2024).
6. ENSO analysis and prediction using deep learning: A review. Neurocomputing (2023).