A closer look at United States and global surface temperature change
Bibliographic record
Abstract
We compare the United States and global surface air temperature changes of the past century using the current Goddard Institute for Space Studies (GISS) analysis and the U.S. Historical Climatology Network (USHCN) record [Karl et al., 1990]. Changes in the GISS analysis subsequent to the documentation by Hansen et al. [1999] are as follows: (1) incorporation of corrections for time‐of‐observation bias and station history adjustments in the United States based on Easterling et al. [1996a], (2) reclassification of rural, small‐town, and urban stations in the United States, southern Canada, and northern Mexico based on satellite measurements of night light intensity [Imhoff et al., 1997], and (3) a more flexible urban adjustment than that employed by Hansen et al. [1999], including reliance on only unlit stations in the United States and rural stations in the rest of the world for determining long‐term trends. We find evidence of local human effects (“urban warming”) even in suburban and small‐town surface air temperature records, but the effect is modest in magnitude and conceivably could be an artifact of inhomogeneities in the station records. We suggest further studies, including more complete satellite night light analyses, which may clarify the potential urban effect. There are inherent uncertainties in the long‐term temperature change at least of the order of 0.1°C for both the U.S. mean and the global mean. Nevertheless, it is clear that the post‐1930s cooling was much larger in the United States than in the global mean. The U.S. mean temperature has now reached a level comparable to that of the 1930s, while the global temperature is now far above the levels earlier in the century. The successive periods of global warming (1900–1940), cooling (1940–1965), and warming (1965–2000) in the 20th century show distinctive patterns of temperature change suggestive of roles for both climate forcings and dynamical variability. The U.S. was warm in 2000 but cooler than the warmest years in the 1930s and 1990s. Global temperature was moderately high in 2000 despite a lingering La Niña in the Pacific Ocean.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".