Climate change is a global challenge that affects everyone. However, cities are the places where most people live and work, making them the locations where most of the impacts of climate change are felt. It is estimated that cities generate about 80% of global GDP, consume two-thirds of the world’s energy, and produce more than 70% of greenhouse gas emissions. That’s why it is very important that many cities have adopted a pioneering role in climate action needed to keep global warming scenario below 2°C within reach.
To cope with the effects of climate change and to reduce GHG emissions in the atmosphere, weather and environmental data play an important role across production and consumption chains. We have witnessed significant improvement in the field, such as 5-day weather forecasts today being as accurate as a 3-day forecast 10 years ago. However, cities continue to face special challenges because global models are not trained to capture all the characteristics of urban landscapes, such as buildings, parks, rivers, and other features that affect the climate and weather on a local level. These features create microclimates, heat islands, varying wind conditions, and other phenomena that can have significant impacts on the safety, well-being, and economics of people and assets in cities.
To address this gap, Vaisala has developed solutions for measuring, forecasting, and providing decision-making support on a local level within urban environments. These solutions enable cities to access high-quality and reliable data feeds, which can then be used to improve the accuracy and reliability of weather and air quality forecasts, and to take preventive actions to protect and analyze the effects on people and assets. In this blog post, we will illustrate with a few examples how hyperlocal weather and environmental insights serve as tools, enabling cities to drive actions in energy transition and urban resilience—two pivotal strategies in mitigating and adapting to the effects of climate change.
As a significant portion of energy is increasingly consumed in urban environments, cities play a pivotal role in advancing green energy transition. This includes activities such as decarbonizing the grid by replacing fossil-based electricity with renewable sources, electrifying transportation and buildings, and enhancing the energy efficiency of assets. However, it’s worthwhile to highlight that numerous challenges exist that technology alone cannot resolve. Yet, the availability of weather and environmental data holds extensive role within this transition, influencing the generation, transmission, distribution, and consumption of clean energy. For instance, weather fuels renewable energy production, making the accurate prediction of wind and solar assets’ electricity output crucial for both utilities and individual owners of renewable assets.
However, achieving net-zero targets encompasses far more considerations, and widely independent. While various priorities and solutions could be addressed, in this blog post we specifically delve into building energy efficiency. Buildings contribute to approximately 40% of global energy use, with heating, ventilation, and air conditioning (HVAC) accounting for an average of 40% of energy consumption within buildings. A pivotal approach to curbing energy usage involves the installation of smart building automation and energy management systems. These systems analyze, monitor, report, and control energy usage. Particularly in commercial buildings, AI-based HVAC software solutions have been deployed, learning occupancy behaviors and utilizing local weather pattern data to predict energy demand and optimize HVAC power consumption.
The increased use of automated and AI-based solutions enhances the value of the data these systems rely on. Temperature, humidity, and wind are primary factors influencing energy usage in buildings, yet reliable information at the building level isn’t always available. The solution lies in maintaining reliable on-site observations and integrating these observations into forecasts, enabling tailored solution for the building. By integrating real-time data and AI-based local forecasts, smart energy management solutions can make more informed control decisions with greater confidence hours in advance while consuming less energy.
Cities face a significant challenge in coping with the escalating intensity and frequency of severe weather events like heatwaves, heavy precipitation, storms, and fire weather. These events have already proven to pose serious threats to city safety, health, infrastructure, and result in substantial economic and social losses. The level and type of vulnerability varies across geographies, depending on diverse extreme weather and environmental risks, with some areas being better prepared than others. Even within a city, certain areas might be more vulnerable, highlighting the importance of understanding risks and available options to enhance preparedness and resilience.
Regardless of a city's stage in developing or implementing a climate adaptation strategy, local environmental information availability is pivotal for steering in the right direction. Often, challenges arise due to unavailability or unreliability measurements within a city. Deployed sensors might be in place, yet their usefulness for decision-making is compromised due to insufficient maintenance, calibration, or difficulties in transforming data into actionable insights. Missing local data can lead to oversight of weather and environmental impacts locally.
To tackle this challenge, Vaisala has developed modular solutions that gather high-quality observations, enhancing situational awareness and aiding in managing climate-related risks in cities. For instance, the recently launched Vaisala Beam station can be easily deployed in relevant city hotspots to measure various parameters like temperature, humidity, wind, precipitation, pressure, solar radiation, particulate matter, ozone, nitrogen dioxide, and carbon monoxide. These data can then integrate with Vaisala’s weather and air quality forecast models, generating hyperlocal alerts and guidance for private and governmental stakeholders—emergency services, transportation authorities, utility companies, and citizens.
Climate change presents a complex and pressing challenge for cities, where weather and environmental solutions find extensive use across various applications. Common challenge is that currently solutions might not be in place or often fall short in capturing the details of urban landscapes that significantly influence local climate, weather, and air quality. Vaisala provides a modular range of hardware, data, and software solutions to enable cities to access high-quality, reliable data, enhance the accuracy and reliability of local-level forecasting, and support decision-making in energy transition and urban resilience.
Throughout this blog post, we've illustrated how hyperlocal weather and environmental data assist cities in improving resilience against extreme weather and transitioning towards low-carbon, renewable energy systems. However, these represent just a few ways weather and environmental data contribute to cities becoming more sustainable, resilient, and livable.
Vaisala Beam Weather Station BWS500 is a powerful, flexible and compact air quality and road weather station that provides key measurements for timely and accurate decisions. Built to scale for your needs, Beam Station is perfectly suited for Vaisala Beam Weather Station BWS500monitoring air quality.