Lukas Hörtnagl
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lukasdata.bsky.social
Lukas Hörtnagl
@lukasdata.bsky.social
690 followers 900 following 2 posts
Data scientist working on ecosystem fluxes @Grassland Sciences group, ETH Zurich, Switzerland. Helping with Swiss FluxNet, ICOS and open science.
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Reposted by Lukas Hörtnagl
copernicusecmwf.bsky.social
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June 11, 2025 at 7:07 AM
Reposted by Lukas Hörtnagl
copernicusecmwf.bsky.social
climate.copernicus.eu/role-data-vi...
May 12, 2025 at 10:30 AM
Reposted by Lukas Hörtnagl
rpallanuk.bsky.social
I found better versions of the figures in the accepted version for now
Figure 1. (a, left) Deseasonalised global-mean Earth energy imbalance. Piece-wise linear trend fits are based on combined DEEP-C and CERES data (green, with break point of July 2010) and CERES only (red, with break point at August 2010). (b, right) Earth energy accumulation (integrated EEI) from combined DEEP-C and CERES. Merchant et al. (2025) ERL http://doi.org/10.1088/1748-9326/adaa8a Figure 2. (a) Deseasonalised monthly mean sea surface temperature between 60°N and 60°S (GMSST). Blue line: observed timeseries from the European Space Agency Climate Change Initiative (ESA CCI). Orange line: fit to observed timeseries using Earth Energy Accumulation (EEA), El-Niño Southern Oscillation (ENSO) index, volcanic stratospheric aerosol and top-of-atmosphere total solar irradiance as predictors. (b) The components of the fit, i.e. the scaled predictors that (with an offset parameter not shown) sum to give the fitted curve in panel (a). Merchant et al. (2025) ERL http://doi.org/10.1088/1748-9326/adaa8a Figure 3. EEI from 2000 to 2024 and three scenarios for the evolution of trends in EEI, used to derive scenarios for future EEA. Merchant et al. (2025) ERL http://doi.org/10.1088/1748-9326/adaa8a Figure 4. GMSST observations and data-driven future scenarios. The shaded band encompasses 99% of expected ENSO variability around the outer EEI-based scenarios. Merchant et al. (2025) ERL http://doi.org/10.1088/1748-9326/adaa8a
January 28, 2025 at 12:34 PM