Parameterizing the impact of vegetated urban canopies on wind and temperature fields by using a simple nudging method

<p>Nudging is a simple method that aims to dynamically adjust the model toward the observations by including an additional feedback term in the model governing equation. This method is widely applied in data assimilation due to its simple implementation and reasonable model results. The basic concept of nudging is similar to that of urban canopy parameterization, in which additional terms are usually added in the conservation equations of momentum and energy aiming to simulate the canopy effects. However, few studies have investigated the implementation of nudging methods in urban canopy parameterizations. In this study we developed a multi-layer urban canopy parameterization (UCP) by using a nudging approach to represent the impacts of vegetated urban canopies on temperatures and winds in mesoscale models.</p><p>The difficulty of developing UCP by using a nudging method lies in defining appropriate values for the nudging coefficients and the forcing fields (e.g. indoor temperature fields for temperature nudging). To determine nudging coefficients, we use three major urban canopy morphological parameters: building height, frontal area density and building density. The ranges of these parameters are taken from the values for the Local Climate Zones datasets, in our case for the city of Hamburg. The UCP is employed in the three -dimensional atmospheric mesoscale model METRAS. Results show that this UCP can well simulate wind-blocking effects induced from obstacles as buildings and trees and urban heat island phenomenon for cities. Thus, nudging is an efficient and effective method that can be used for urban canopy parameterizations. However, as well known for nudging, it is not conserving energy. Therefore, we investigated the energy loss by tracking the reduced kinetic energy and internal energy. The UCP and model results will be presented.</p>

Evaluation of the soil moisture model with data assimilation by the triple collocation method

This paper deals with a nonlinear soil moisture transport problem, solved with addition of satellite observed soil moisture. The satellite data are assimilated into the model using Newtonian nudging method. Evaluation is done by the triple collocation method, which involves three independent data sources: model results, ground stations and ERA5 climatic data. The results testify that model results are nearly as accurate as the ground station measurements.

Preprint_Walk Your City_Wernbacher

In recent decades, a stagnation or even a decline in pedestrian traffic has been observed in many cities, despite the ambitious efforts of national and international action plans, strategies and initiatives. Our project "Walk Your City" addresses this problem by designing, developing and evaluating an innovative, behavioral-based pedestrian initiative with a focus on the nudging method. The applied nudging framework includes gamification as well as crowdsourcing elements and aims to decisively improve the quality of life in cities by promoting walking as an active and health-enhancing activity.The core of our approach is represented by nudges which are triggered via an app as well as offline campaigns. The story refers to a not so distant dystopian future where the pilot city Graz suffers from pollution, traffic chaos as well as climate change. Via regular walking as well as visiting places such as parks or viewpoints users of the app are rewarded with tokens. Following the idea of crowdsourcing these tokens can be invested into wishes for improvement such as parking benches or zebra crossings. Through this unique combination of technological innovations, playful approaches, behavioral concepts and creative campaigns, participants are motivated to explore and experience the city on foot. Walking should be perceived as a genuine and healthy alternative for short distances and anchored as first choice when covering small distances.The nudging-method will be iteratively optimized in terms of acceptance, functionality and usability using focus groups, internal lab tests and expert workshops. This strategy will a practice-oriented project implementation that is tailored to the needs of different target groups such as students, commuters as well as tourists. The mobility and health data obtained during the pilot test will be used to evaluate the suitability and impact of the nudging method in course of an academic paper. As the empirical data show, a behavioral change in terms of a larger share of walking in the modal split as well a positive impact on the interest and awareness regarding the effects of walking could be observed.

Introduction of the nudging method in penitentiary facilities in Italy in view of food waste reduction: Preliminary data

The aim of this study was to analyze different aspects of food waste in the specific context of prisons by introducing the nudging method, thanks to the collaboration of District House and Prison of Larino (Italy) involving staff and guests of the penitentiary structure, providing them with the knowledge of the topic and encouraging them to propose creative and effective solutions to prevent and reduce food waste. The study involved n. 50 participants out of total of about 200 prisoners. Data were collected using n.3 questionnaires related to the knowledge of food waste food, the second related to the origin of consumed and food waste and the third collected the participants’ proposals how to reduce food waste. The results show that effects of nudging has awakened the prisoners’ conscience about the social, ethical and economic importance of reducing food waste and a proactive attitude in providing proposals for the reduction of food waste. The most wasted food is bread (35%), pasta (27%) and fresh fruit (20%), provided by the administration because they are considered of inferior quality or prepared and cooked badly. The overwhelming majority (96%) of the participants showed sensitivity about the ethical and economic reasons behind the fight against food waste, making themselves available to contribute to its reduction and suggesting some initiatives. The data collected from the questionnaires related to the causes of waste indicate the need to implement actions aimed at the correct conservation of food and the promotion of good hygiene practices.

Feasible Method for the Assimilation of Satellite-Derived SST with an Ocean Circulation Model

The surface restoring condition of satellite-derived sea surface temperatures (SSTs) is validated as a feasible assimilation method with an ocean circulation model that incorporates the strongly nonlinear mixed layer model. The restoring treatment is an empirical method for correcting the heat flux in order to pull the predicted SST toward the observed SST; it is referred to as the nudging method in this study. A one-dimensional experiment is conducted to evaluate the skill of the nudging method. The mixed layer model (MLM) used in the experiment is a second-order turbulence closure model that has a strong nonlinearity. The skill of the nudging method is compared with that of an ensemble Kalman filter, which is a statistically optimal method for nonlinear dynamic models. Although the nudging method is statistically suboptimal, the result of the experiment shows that the skill of this method is comparable when using an appropriate restoring time scale. A three-dimensional experiment using an ocean general circulation model (OGCM), which incorporates the same MLM as that used in the one-dimensional experiment, is also conducted to further examine the skill of the nudging method. By applying the nudging method to the OGCM, the model improves the estimated thermal structure not only near the surface, but also in the subsurface layers.