Subdivision on Precipitation & climate
Chair: Andreas Langousis
The Precipitation and Climate subdivision covers all research of hydrological relevance into measuring and understanding precipitation and its variability in space and time, as well as research at the interface between hydrology and climate science.
Precipitation is the input to hydrological systems. Quantifying it properly is therefore crucial to our ability to model these systems. Proper quantification means the use of appropriate measurement devices or of reliable models where observations are not available, together with estimates of the uncertainty involved. Our subdivision focusses upon the different methods (raingauges, disdrometers, radars, microwave links, satellites) for estimating observed precipitation at a range of scales (from the fine scales of urban hydrology to the mesoscale range), and the different approaches to modelling or downscaling the precipitation signal in time and in space.
The climate interacts with the hydrological cycle in a number of ways. The study of how changes in the climate impact this cycle, and conversely, how different processes within the cycle influence the climate, is within the remit of this subdivision. But our interest in climate is also broader: it covers research into the impact of the climate-water interaction upon health and upon society.
- Techniques for measuring precipitation at hydrologically relevant space and time scales, including the scales relevant to urban hydrology.
- Approaches to modelling and downscaling the space-time variability of precipitation, from physics-based models, via scaling and fractal approaches to stochastic and statistical models.
- Assessment and representation of different sources of uncertainty versus natural variability of precipitation.
- Physical processes leading to the small-scale rainfall variability
- Applications of measured precipitation fields in urban hydrological models to understand and characterise urban hydrological variability and predict hydrological response.
- Novel measurement devices, combinations of devices (both in situ and remote sensors).
- Uncertainty and variability in spatially and temporally heterogeneous multi-source precipitation products.
- Precipitation data assimilation.
- Precipitation drop (or particle) size distribution and its small scale variability.
- Impact of using uncertain hydrological and/or climate change predictions for planning.
- Understanding the informational needs of planners and the impact of information availability and presentation on the planning process.
- Relationship of climate with the hydrological cycle and water resources availability for hydro-engineering works.
- Evaluation of traditional techniques of water-related planning and management in the light of a changing climate.
- Coupling stochastic approaches with deterministic hydro-meteorological predictions, in order to better represent predictive uncertainty;
- Variability at climatic scales and its interplay with the ergodicity of space-time probabilities;
- Linking underlying physics and scaling stochastics of hydrometeorological extremes;
- Predictive methods used to model hydroclimatic extremes.
- Changes and trends in hydroclimatic variables e.g., storms, cyclones and tornadoes, river floods, flash floods, extreme temperatures, heat and cold waves, droughts, etc.
- Role of insurance in managing extreme events and the challenge of climate change.
- Use of hydro-climatological data to improve our understanding of the physical processes associated with climate, calibrate models, improve forecasts and estimate uncertainties.
- Use of hydro-climatological data to investigate societal concerns about hydrological and climate changes
- Complex inter-linkages of hydrological conditions and population health.
- Assessment of the impact of climate change and climate variability on hydrological conditions and water resources and their associated human and ecological health impacts.
- Modelling tools for organizing integrated solutions to climate-water-health problems.
- Characterizing and modelling disease spread patterns and their relationships with climatic, weather, and hydrological conditions.