Modelling rain heterogeneities in urban areas

Urbanisation modifies the local climate and results in the so-called urban climate. Within the urban boundary layer, the average wind speed is reduced, while gustiness is increased. Buildings induce vertical winds. Heterogeneities in the rain pattern around buildings are the consequence. Human discomfort in street canyons may be one result. In addition, sealed urban surfaces lead to large rainwater run-off, which is a cause for flash floods in urban areas.

Increased computational power allows high-resolution modelling in urban areas with a horizontal resolution well below 10 m. The consideration of more meteorological processes like cloud and rain microphysics is possible. This allows us to estimate the impact of rain events, especially heavy rain events and flash floods, to urban neighbourhoods. Nevertheless, the domain size with these high-resolution models is restricted and the cloud and rain development passes the domain without full development of rain. To overcome this challenge, high-resolution information about rain events in urban areas are necessary.

In the area of Hamburg, Germany, measurements of a X-band weather radar at a 100-metre-scale and a vertically pointing micro rain radar are available for several years. These high-resolution measurement data are used to develop a forcing method for the microscale, obstacle resolving transport and stream model MITRAS (Salim et al. 2019). The forcing method samples 2D and 3D information about the rain rate to the model domain. The nudging approach adds the information about the rain rate to the top and the lateral boundaries of the model domain. Model simulations with different synoptic situations evaluate the forcing methodology.

In this contribution, the forcing method will be presented and results from different test cases in a test area in Hamburg will be shown.

Salim M.H, Schlünzen K.H., Grawe D., Boettcher M., Gierisch A.M.U., Fock B.H. (2018): The microscale obstacle-resolving meteorological model MITRAS v2.0: model theory. Geosci. Model Dev., 11, 3427–3445, https://doi.org/10.5194/gmd-11-3427-2018.