LUMI in a fight against climate change

Our climate is changing, and not for the better. We have seen unprecedented heat waves and wildfires whose effects have been far-reaching. The year 2023 is confirmed as the warmest calendar year in global temperature data records dating back to 1850; July and August were the warmest two months on record. Heat waves across Asia, North America, and Europe; wildfires, amplified by heat and dryness, have raged in Canada and the Mediterranean – all signs that the Earth is warming at an unprecedented rate. Climate change will severely impact nature and human life; the regional and local effects are shrouded in uncertainty. Thus, we need new solutions to help us better understand the climate change adaptation efforts and how to assess the risks of possible failures from mitigation actions.

Climate Digital Twin (Climate DT) is a new type of climate information system that can produce climate simulations with a finer spatial resolution than before to assess climate change impacts and evaluate different adaptation strategies at local and regional levels over multiple decades. It is one of the first thematic digital twin projects started in the Destination Earth initiative, which aims to build a digital twin of the Earth by 2030 and is implemented on behalf of the ECMWF.

The Climate DT harnesses two Earth-system models (ESMs), ICON and IFS-FESOM/NEMO, which are optimized to run on the LUMI supercomputer. The Climate DT introduces the idea of a generic state vector (GSV) by streaming climate model output directly into the impact models. This novel approach enables the ESMs to work at an unprecedented scale and thus improves the fidelity of the climate information and its relevance for the users.

The project’s first phase examines climate change’s impact through five different themed applications or use cases to assess climate change impacts on various topics based on the streamed climate simulation data. This information can be used in decision-making when planning measures to adapt and mitigate climate change. Next, we’ll go through the five use cases being developed in the Climate DT project to provide actionable information and decision support to its users.

Wildfire

Many terrestrial ecosystems from the tropics to the Arctic are disturbed by wildfires that adversely affect human life and nature. Wildfire weather has also become more widespread, longer lasting, and intense in some regions and is projected to increase with higher global warming levels in many areas of the world.

The project aims to develop three wildfire applications that will run on Climate DT based on approaches such as the Fire Weather Index (FWI) for the European domain, the Fire Spread Model PROMETHEUS simulations in selected regions, and the mechanistic fire model SPITFIRE simulating climate change’s impact on fire risk in Finland.

The goal is to test the fire risk in different land use scenarios, e.g., forest management with different carbon capture, biodiversity, and bioenergy policies. Using Climate DT’s high-resolution capabilities of fire spread models and land use data allows us to assess the vulnerability and risk of selected sites’ propensity to wildfires, such as critical infrastructure and residential areas.

HydroRiver

The 6th Assessment Report from IPCC (The Intergovernmental Panel on Climate Change) emphasized water-related disasters and their impact on various sectors and regions. Earth’s energy balance determines global precipitation and evaporation changes. The limitations of energy budgets at global scales and moisture budgets at regional scales cause key water cycle characteristics such as precipitation intensity, duration, and frequency to change as the climate warms.  Given these future water availability issues, hydrological data is crucial for assessing vulnerability and developing adaptation strategies.

In this HydroRiver use case, we seek to provide estimates of the climate impacts on critical hydrological processes, both at the global and local scale, over past, present, and future conditions. The aim is also to evaluate future drought and flood duration, frequency, intensity, severity, peak, and geographic extent to control impacts and devise mitigation efforts.

Utilizing the Mesoscale hydrological model (mHM) developed by the Helmholtz Center for Environmental Research and coupled with high-resolution global simulations on LUMI, we aim to determine the key variables essential to assess the state of freshwater (streamflow, soil moisture, and groundwater storage) globally.

In this use case, we strive to reduce the uncertainty of the derived hydrological impacts by bridging the gap between the resolutions of global climate simulations and the hydrological impact model. We will also be able to understand and share details about smaller river segments and explore more sections along the river paths than ever before in order to make informed decisions about water resource management and conservation efforts.

Hydrometeorology

We often experience the impact of climate change through extreme events. Recent years have shown the importance of mitigation efforts toward extreme rainfall events; identifying these rainfall event characteristics and trends plays a significant role in tailoring a well-suited adaptation strategy. The Climate DT will provide statistics for extreme rain events and an event-based catalog to identify changes and future trends. To achieve this, we will utilize two different codes developed by the German Meteorological Service Deutsche Wetterdienst (DWD).

Through this use case, we will create beyond state-of-the-art statistics and information on simulated rainfall extremes, such as flash floods and extreme precipitation, using adapted software to extract the relevant information from the high-resolution Climate DT data. The data, in turn, can be used to develop more accurate adaptation strategies and better risk management processes.

Energy

Mitigating climate change requires considerable investments in wind energy production, particularly for offshore wind farms. High-resolution climate data is needed to accurately provide information on the harvesting capability of renewable energy and environmental design parameters for infrastructure. The overall goal of the energy use case is to produce estimates of the changes in wind resources under future climate conditions. Within this energy use case, two applications are developed in parallel, Energy Onshore and Energy Offshore, with the implementation of several energy-related indicators, including wind speed anomalies, wind power density (WPD), capacity factors (CF), annual energy production (AEP), and the interannual variability of these metrics.

The intent is to evaluate wind energy supply and aspects influencing energy demand as well as develop a method to estimate ocean, sea ice, and atmosphere extremes for offshore windfarm’s (OWF) design.
We hope to develop an application based on a set of wind energy indicators for onshore and offshore using models and data from high-resolution data the Climate DT project produces.

The energy use case will be a trailblazer by providing energy indicators and relevant statistics at spatial resolutions crucial for better understanding the power grid vulnerability and future energy market management.

Urban

According to the World Meteorological Organization, climate projections indicate a severe increase in the intensity, duration, and frequency of heat waves. Urban environments are particularly vulnerable to heat waves due to the urban heat island (UHI) effect. UHI occurs when cities replace natural land cover, such as vegetation, with dense concentrations of pavement, buildings, and other surfaces that absorb and retain heat. This effect increases energy costs (e.g., for air conditioning), air pollution levels from exhaust heat, and heat-related illness and mortality.

The Urban use case studies the overarching variability of heat waves in urban environments through extreme temperature climate indicators, such as Heat Wave Magnitude Index (HWMI) and Excess Heat Factor (EHF). Given that heat waves strongly impact human health, several human thermal comfort indicators have also been developed and implemented. Earth System Models (ESMs) with km-scale grids and sub-hourly output frequency provide us the ability to study heat waves at global, regional, or even local levels, together with an enhanced representation of the large circulation systems or the worldwide system of winds that give rise to heat waves.

The long-term goal of our work is to provide useful knowledge and data to urban planners, which can be used in designing more resilient cities that are better adapted to the impacts of heat waves.