Explanatory analysis of the relationship between atmospheric circulation and occurrence of flood-generating events in a coastal city

Abstract

The aim of this study is to enhance the understanding of the occurrence of flood‐generating events in urban areas by analysing the relationship between large‐scale atmospheric circulation and extreme precipitation events, extreme sea water level events and their simultaneous occurrence, respectively. To describe the atmospheric circulation, we used the Lamb circulation type (LCT) classification and re‐grouped it into Lamb circulation classes (LCC). The daily LCCs/LCTs were connected with rare precipitation and water‐level events in Aarhus, a Danish coastal city. Westerly and cyclonic LCCs (W, C, SW and NW) showed a significantly high occurrence of extreme precipitation. Similarly, for extreme water‐level events westerly LCCs (W and SW) showed a significantly high occurrence. Significantly low occurrence of extreme precipitation and water‐level events was obtained in easterly LCCs (NE, E and SE). For concurrent events, significantly high occurrence was obtained in LCC W. We assessed the change in LCC occurrence frequency in the future based on two regional climate models (RCMs). The projections indicate that the westerly directions in LCCs are expected to increase in the future. Consequently, simultaneous occurrence of extreme water level and precipitation events is expected to increase in the future as a result of change in LCC frequencies. The RCM projections for LCC frequencies are uncertain because the representation of current LCCs is poor; a large number of days cannot be classified and the frequencies of the days that can be classified differ from the observed time series. Copyright © 2015 John Wiley & Sons, Ltd.

Spatial and temporal characteristics of extreme rainfall: Added benefits with sub‐kilometre‐resolution climate model simulations?

“…Soil moisture and other initial values for the soil scheme are taken from ERA5 to HCLIM5km and from this simulation to HCLIM750m, making these as realistic and balanced as practically possible. Note that heavily convective precipitation events are not expected to occur in April (Åström et al ., 2016) and we only aim to spin up the atmosphere, since the soil initialisation is expected to have only small effects on the climate in such a small domain. Note also, that most weather systems move into the domain from the sea, which also reduces the importance of soil initialisation.…”

“…The analysed datasets consist of five years of data from April to October, stretching over the period where most heavy convective precipitation events in Denmark occur. While heavy convective precipitation events do not normally occur in April (Åström et al ., 2016), and also include spin‐up for the 5‐km and the 750‐m simulations, we included it in the analysis anyway due to the limited simulation length. The available data from April to October are hereafter referred to as the heavy convective precipitation seasons.…”

Uncovering the shortcomings of a weather typing method

“…Application of this scaling rate to precipitation intensities is valid assuming that extreme precipitation amounts are controlled by the local moisture availability and are not influenced by the large-scale atmospheric circulation patterns. In reality, however, physical processes interact and higher scaling rates are also found (Barbero et al, 2018;Blenkinsop et al, 2018;Manola et al, 2018;Lenderink et al, 2017;Zhang et al, 2017). The CC relationship is determined by the annual timescale.…”

A Robust Method to Update Local River Inundation Maps Using Global Climate Model Output and Weather Typing Based Statistical Downscaling

“…Projections of synoptic weather types under climate change can be obtained almost immediately from the output of GCMs, which are expected to correctly reproduce large scale atmospheric features (Räisänen 2007;Hargreaves 2010;Hargreaves and Annan 2014). A few works have indeed analyzed the ability of GCMs in reproducing circulation patterns, and explored changes in synoptic variability in the twenty-first century (Demuzere et al 2009;Lorenzo et al 2011;Åström et al 2016;Otero et al 2018).…”