A5030822850- Climate variability and models
- Atmospheric and Environmental Gas Dynamics
- Meteorological Phenomena and Simulations
- Cryospheric studies and observations
- Tropical and Extratropical Cyclones Research
- demographic modeling and climate adaptation
- Ocean Waves and Remote Sensing
- Climate change impacts on agriculture
- Computational Physics and Python Applications
- Geophysics and Gravity Measurements
- Climate Change and Health Impacts
- Sustainability and Climate Change Governance
- Ionosphere and magnetosphere dynamics
- Urban Heat Island Mitigation
- Experimental and Theoretical Physics Studies
- Climate Change Communication and Perception
- Data Analysis with R
- Atmospheric chemistry and aerosols
- Simulation Techniques and Applications
- Advanced Computational Techniques and Applications
- Plant Water Relations and Carbon Dynamics
- Climate change and permafrost
- Precipitation Measurement and Analysis
- Hydrology and Watershed Management Studies
- Environmental Monitoring and Data Management
Climate Analytics
2021-2024
ETH Zurich
2020-2024
NOAA Oceanic and Atmospheric Research
2024
University of Oxford
2024
Board of the Swiss Federal Institutes of Technology
2021
Abstract. The degree of trust placed in climate model projections is commensurate with how well their uncertainty can be quantified, particularly at timescales relevant to policy makers. On inter-annual decadal timescales, projection due natural variability dominates the local level and imperative describing near-term seasonal events but difficult quantify owing computational constraints producing large ensembles. To this extent, emulators are valuable tools for approximating runs, allowing...
Abstract. Tropical cyclones are among the most damaging extreme weather events. An increase in Atlantic tropical cyclone activity has been observed, but attribution to global warming remains challenging due large inter-annual variability and modeling challenges. Here we show that since 1980s can be robustly ascribed variations atmospheric circulation as well sea surface temperature (SST) increase. Based on a novel weather-pattern-based statistical model, find forced trend SSTs over 1982–2020...
Abstract Global warming is expected to exacerbate heat stress. Additionally, biogeophysical effects of land cover and management changes (LCLMC) could substantially alter temperature relative humidity locally non‐locally. Thereby, LCLMC affect the occupational capacity safely perform physical work under hot environments (labor capacity). However, these have never been quantified globally using a multi‐model setup. Building on results from stylized sensitivity experiments (a) cropland...
The Ensemble Prediction System (EPS) provided by global weather forecast centres generates vast amounts of data that is crucial for early warnings extreme and climate. However, regional national meteorological services often face challenges in processing this efficiently, particularly during downscaling post-processing. Conventional methods downloading storing GRIB-format have become increasingly inefficient unsustainable. Strengthening Early Warning Systems Anticipatory Actions (SEWAA)...
We test methods of postprocessing rainfall forecasts out to 7 days over East Africa.Using the physical forecast models, IFS from ECMWF and GFS NCEP, we apply several combinations post-processing techniques empirically correct predicted towards IMERG blended satellite data. The include a generative adversarial neural network (GAN) model (Harris et al. 2022), isotonic distributional regression (EasyUQ, Walz 2024), EMOS (Gneiting 2005), linear regression, kernel density estimate. Other...
Abstract An ever-growing body of evidence suggests that climate change is already impacting human and natural systems around the world. Global environmental assessments assessing this evidence, for example by Intergovernmental Panel on Climate Change (IPCC) 1 , face increasing challenges to appraise an exponentially growing literature 2 diverse approaches attribution. Here we use language representation model BERT identify classify studies observed impacts, producing a...
Attribution of extreme climate events to global change as a result anthropogenic greenhouse gas emissions has become increasingly important. Extreme arise at the intersection natural variability and forced response Earth system emissions, which may alter frequency severity such events. Accounting for effects both is thus central attribution. Here, we investigate reproducibility probabilistic event attribution results under more explicit representations variability. We employ well-established...
Abstract. The degree of trust placed in climate model projections is commensurate to how well their uncertainty can be quantified, particularly at timescales relevant policy makers. On interannual decadal timescales, due internal variability dominates and imperative understanding near-term seasonal events, but hard quantify owing the computational constraints on producing large ensembles. To this extent, emulators are valuable tools for approximating runs, allowing exploration space...
Abstract. Land cover changes have been proposed to play a significant role, alongside emission reductions, in achieving the temperature goals agreed upon under Paris Agreement. Such carry both global implications, pertaining biogeochemical effects of land change and thus carbon budget, regional or local biogeophysical arising within immediate area change. Biogeophysical are high relevance national policy decision makers, accounting for them is essential effective deployment practices that...
Abstract Due to insufficient climate action over the past decade, it is increasingly likely that 1.5 °C of global warming will be exceeded – at least temporarily in 21 st century. Such a temporary temperature overshoot carries additional risks which are poorly understood. Earth System Model projections only available for very limited number pathways, thereby preventing comprehensive analysis their impacts. Here, we address this issue by presenting novel dataset spatially resolved emulated...
Abstract An ever-growing body of evidence suggests that climate change is already impacting human and natural systems around the world. Global environmental assessments assessing this evidence, for example by Intergovernmental Panel on Climate Change (IPCC) 1 , face increasing challenges to appraise an exponentially growing literature 2 diverse approaches attribution. Here we use language representation model BERT identify classify studies observed impacts, producing a...
Emulators of Earth System Models (ESM) are runtime efficient models that mimic the behavior an ESM using simple statistical methods. Because their low complexity, emulators allow to quickly generate thousands realizations high-resolution data. Thus, they have proven be valuable tools for exploring emission space, quantifying different sources uncertainty, and investigating extreme events. In this contribution, we introduce extension Modular Model Emulator (MESMER) generating monthly...
Heatwaves are becoming more frequent because of climate change, and this trend is exacerbated in cities due to the urban heat island effect. With than half world’s population living cities, it essential quantify future evolution stress develop smart adaptation strategies counter its impacts. This requires capturing fine-grained variations heat-related hazards within fabric. However, coarse resolutions Earth System Models makes difficult model areas explicitly. Moreover,...
Abstract. Emulators of Earth System Models (ESMs) are statistical models that approximate selected outputs ESMs. Owing to their runtime-efficiency, emulators especially useful whenever vast amounts data required, for example, thoroughly exploring the emission space, investigating high-impact low-probability events, or estimating uncertainties and variability. This paper introduces an emulation framework allows emulate spatially explicit monthly mean precipitation fields using temperature as...
<title>Abstract</title> Extreme event attribution assesses how anthropogenic climate change affected an extreme event, but typically focuses on individual events. Here, we systematize this approach, and apply it to 187 historical heatwaves reported over the period 2000-2022. We show that has made all these more likely intense. In particular, 33% of were virtually impossible without influence. Furthermore, influence rises time, both in intensity likelihood: median 24 times 2000-2009, 293...
Abstract. Emulators of Earth system models (ESMs) are statistical that approximate selected outputs ESMs. Owing to their runtime efficiency, emulators especially useful when large amounts data required, for example, in-depth exploration the emission space, investigating high-impact low-probability events, or estimating uncertainties and variability. This paper introduces an emulation framework allows us emulate gridded monthly mean precipitation fields using temperature as forcing. The...
High-impact climate damages are often driven by compounding conditions. For example, elevated heat stress conditions can arise from a combination of high humidity and temperature. To explore future changes in hazards under range scenarios with large ensembles, emulators provide light-weight, data-driven complements to Earth System Models. Yet, only few existing jointly emulate multiple variables. In this study, we present the Multi-resolution EmulatoR for CompoUnd Risk analYsis: MERCURY....
Abstract. Tropical cyclones are among the most damaging and fatal extreme weather events. An increase in Atlantic tropical cyclone activity has been observed, but attribution to global warming remains challenging due large inter-annual variability modelling challenges. Here we show that since 1980s can be robustly ascribed changes atmospheric circulation as well sea surface temperature (SST) increase. Using a novel pattern based statistical model, find forced trend SSTs over 1982–2018 period...
&lt;p&gt;The latest ensemble of climate models (CMIP6) displays greater overall uncertainty than the previous iteration, with a larger spread temperature projections by end 21st century. Given that these model are essential towards policy and decision making, accurately quantifying their biases uncertainties (model benchmarking) is an important process building public trust. Climate emulators able to explore phase space surrounding at fraction computational cost present themselves as...
Attribution of extreme events in developing countries poses a significant challenge. A primary hindrance is the lack historical observations, which not only limits appraisal extent an event, but also restricts benchmarking climate models for region. secondary that tropical climates, characteristic countries, contain large uncertainties due to natural variability, many struggle represent. As it those and world regions where some most severe consequences impacts emerge, addressing these...