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J. Eduardo Vera-Valdes

Publications and source records attributed to J. Eduardo Vera-Valdes.

3 recordsLinked to original sources

Leveraging Multi-Model Land-Use Emissions Reveals a Rising Airborne Fraction of Atmospheric $CO_2$ Over the Past Six Decades

The airborne fraction, the share of anthropogenic $CO_2$ emissions that remains in the atmosphere rather than being taken up by land and ocean, is a compact diagnostic of sink efficiency and a direct input to the remaining carbon budgets behind climate targets. Here we show that it has risen over the observational record, from $0.32$-$0.40$ in $1959$ to $0.47$-$0.50$ by $2024$ (ranges across estimators), above the $0.44$ commonly reported for recent decades. Applied to IPCC AR6 assessments, this rise reduces the remaining carbon budget by $23$-$48$ $GtCO_2$ for a given temperature target, up to roughly one year of current global fossil emissions. The trend has been difficult to detect because two features of the standard analysis obscure it. First, three high-leverage years following the $1991$ Pinatubo eruption dominate the volcanic term of the natural-variability adjustment and attenuate the estimated trend; smoothing those years, or using a volcanically robust $ENSO$ index, removes the artifact. Second, collapsing land-use and land-cover change emissions to a single series discards the disagreement among models that carries the information needed to resolve a small trend. Propagating the dispersion of $69$ land-use series together with the reported fossil-emission uncertainty into delta-method weights, weighted and generalized least squares recover a positive and significant trend, corroborated by a mixed-effects model and robust across a grid of $49$ natural-variability specifications that maps which treatment choices reproduce which published result.

stat.AP↗

Spatial emergence of acceleration in global warming

Whether global warming is accelerating remains contested because internal variability and spatial heterogeneity can obscure changes in warming rates. Here we use a Bayesian hierarchical spatio-temporal model with structured spatial dependence to estimate local warming trajectories and acceleration, and apply the model to progressively truncated observations to infer when acceleration becomes detectable. We find that detectable acceleration emerges unevenly across the climate system, with the earliest high-confidence signals concentrated in selected high-latitude regions. Across retained grid cells, the proportion exceeding a 90% posterior probability of positive acceleration increases from 13.6% for 1970-1990 to 39.7% for 1970-2026, while the proportion exceeding a 50% threshold increases from 46.4% to 70.3%. These results show that spatial aggregation can delay detection by averaging regions where acceleration has already emerged with regions where it remains weak or uncertain. The framework provides a probabilistic diagnostic for identifying where warming is intensifying and when acceleration becomes statistically detectable.

stat.AP↗

Global Warming Has Been Accelerating Since At Least 1990

We investigate acceleration in global temperature, defining acceleration as a supralinear (greater-than-linear) increase over time. We develop a statistical framework to test for supralinear trends using a linearithmic specification. Our results indicate evidence of acceleration in global temperature since at least 1990, with significance strengthening as more recent data are included. In contrast, evidence for acceleration under a quadratic specification is significant only in the longest estimation window. We also show that, if the true temperature trend is supralinear, standard break-point tests will eventually detect changes in the slope of a linear trend model, which may explain reported structural breaks in global temperature trends.

stat.ME↗