Abstract

In order to better understand how urban areas modify the regional atmospheric boundary layer (ABL) and to improve and evaluate weather and climate models for urban applications and services, detailed ABL observations are needed. With new instrument technologies and advanced automatic algorithms for detection of aerosols, mixed-layer height (MLH) and boundary-layer clouds, ground-based remote sensing instruments are increasingly used in urban observational networks.During a one-year measurement campaign in Berlin, Germany (urbisphere-Berlin, Autumn 2021 – Autumn 2022), a variety of ground-based ABL observations were carried out in the greater Berlin region. Berlin as an isolated continental city with approximately 3.8 million inhabitants provides a fairly homogeneous rural background. The urbisphere network included five inner-city, six outer-city and 14 rural sites equipped with continuously-operated Automatic Lidar and Ceilometers (ALC). The measurement network was designed and set up in a systematic and rigorous manner in order to capture intra-urban, urban-rural, and upwind-city-downwind effects of MLH, cloud-base height (CBH), and cloud cover fraction (CCF) along several transects as air masses move over the city. Based on the ALC observations, MLH, CBH and CCF were automatically derived. ALC observations are complemented by measurements of wind and temperature profiles over the city using Doppler-Wind Lidars and radiosondes concurrently released in urban and rural locations during selected days. Surface heat fluxes are continuously measured with six eddy-covariance flux towers and seven path-averaging scintillometers in urban and rural settings.This contribution highlights the scientific considerations of the systematic measurement network design and the corresponding data analysis. We are proposing a scheme of attributing measurements to rings around the city centre representing the inner city (radius of 6 km), the outer city (radius of 18 km) and rural areas (radius of 90 km), further separated into upwind, downwind and other sectors. A detailed statistical analysis of the year-long dataset finds differences in MLH, CBH and CCF during different seasons and under different weather forcings. Selected case-study days are analysed in more detail to understand the processes controlling the interactions between surface fluxes and mixed-layer dynamics. These days are further used to evaluate the forecasting skill of hectometric dynamical-modelling runs with regard to ABL dynamics, quantifying also the sensitivity of ABL dynamics in the model to surface representation (e.g. soil moisture, heat flux partitioning).

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