Searcharxiv⌕ Search
Home/Archive/arXiv

arXiv · 1402.0131

The controversial early brightening in the first half of 20th century: a contribution from pyrheliometer measurements in Madrid (Spain)

M. Antón·J. M. Vaquero·A. J. P. Aparicio
View original source ↗Read source document ↗Export metadata ↓

Abstract

A long-term decrease in downward surface solar radiation from the 1950s to the 1980s ("global dimming") followed by a multi-decadal increase up to the present ("brightening") have been detected in many regions worldwide. In addition, some researchers have suggested the existence of an "early brightening" period in the first half of 20th century. However, this latter phenomenon is an open issue due to the opposite results found in literature and the scarcity of solar radiation data during this period. This paper contributes to this relevant discussion analyzing, for the first time in Southern Europe, the atmospheric column transparency derived from pyrheliometer measurements in Madrid (Spain) for the period 1911-1928. This time series is one of the three longest dataset during the first quarter of the 20th century in Europe. The results showed the great effects of the Katmai eruption (June 1912, Alaska) on transparency values during 1912-1913 with maximum relative anomalies around 8%. Outside the period affected by this volcano, the atmospheric transparency exhibited a stable behavior with a slight negative trend without any statistical significance on an annual and seasonal basis. Overall, there is no evidence of a possible early brightening period in direct solar radiation in Madrid. This phenomenon is currently an open issue and further research is needed using the few sites with available experimental records during the first half of the 20th century.

Explore related subjects

physics.ao-ph

Keep this discovery

BibTeXRIS

M. Antón, J. M. Vaquero, A. J. P. Aparicio. 2014-02-01. The controversial early brightening in the first half of 20th century: a contribution from pyrheliometer measurements in Madrid (Spain). https://doi.org/10.1016/j.gloplacha.2014.01.013

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph↗
arXiv2026

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph↗