Evidence of air quality data misreporting in China: An impulse indicator saturation model comparison of local government-reported and U.S. embassy-reported PM2.5 concentrations (2015-2017).

This paper analyzes hourly PM2.5 measurements from government-controlled and U.S. embassy-controlled monitoring stations in five Chinese cities between January 2015 and June 2017. We compare the two datasets with an impulse indicator saturation technique that identifies hours when the relation between Chinese and U.S. reported data diverges in a statistically significant fashion. These temporary divergences, or impulses, are 1) More frequent than expected by random chance; 2) More positive than expected by random chance; and 3) More likely to occur during hours when air pollution concentrations are high. In other words, relative to U.S.-controlled monitoring stations, government-controlled stations systematically under-report pollution levels when local air quality is poor. These results contrast with the findings of other recent studies, which argue that Chinese air quality data misreporting ended after a series of policy reforms beginning in 2012. Our findings provide evidence that local government misreporting did not end after 2012, but instead continued in a different manner. These results suggest that Chinese air quality data, while still useful, should not be taken entirely at face value.

Spatial heterogeneity of climate change as an experiential basis for skepticism.

We postulate that skepticism about climate change is partially caused by the spatial heterogeneity of climate change, which exposes experiential learners to climate heuristics that differ from the global average. This hypothesis is tested by formalizing an index that measures local changes in climate using station data and comparing this index with survey-based model estimates of county-level opinion about whether global warming is happening. Results indicate that more stations exhibit cooling and warming than predicted by random chance and that spatial variations in these changes can account for spatial variations in the percentage of the population that believes that "global warming is happening." This effect is diminished in areas that have experienced more record low temperatures than record highs since 2005. Together, these results suggest that skepticism about climate change is driven partially by personal experiences; an accurate heuristic for local changes in climate identifies obstacles to communicating ongoing changes in climate to the public and how these communications might be improved.

Hyperspectral remote sensing of foliar nitrogen content.

A strong positive correlation between vegetation canopy bidirectional reflectance factor (BRF) in the near infrared (NIR) spectral region and foliar mass-based nitrogen concentration (%N) has been reported in some temperate and boreal forests. This relationship, if true, would indicate an additional role for nitrogen in the climate system via its influence on surface albedo and may offer a simple approach for monitoring foliar nitrogen using satellite data. We report, however, that the previously reported correlation is an artifact--it is a consequence of variations in canopy structure, rather than of %N. The data underlying this relationship were collected at sites with varying proportions of foliar nitrogen-poor needleleaf and nitrogen-rich broadleaf species, whose canopy structure differs considerably. When the BRF data are corrected for canopy-structure effects, the residual reflectance variations are negatively related to %N at all wavelengths in the interval 423-855 nm. This suggests that the observed positive correlation between BRF and %N conveys no information about %N. We find that to infer leaf biochemical constituents, e.g., N content, from remotely sensed data, BRF spectra in the interval 710-790 nm provide critical information for correction of structural influences. Our analysis also suggests that surface characteristics of leaves impact remote sensing of its internal constituents. This further decreases the ability to remotely sense canopy foliar nitrogen. Finally, the analysis presented here is generic to the problem of remote sensing of leaf-tissue constituents and is therefore not a specific critique of articles espousing remote sensing of foliar %N.

Effects of warming temperatures on winning times in the Boston marathon.

It is not known whether global warming will affect winning times in endurance events, and counterbalance improvements in race performances that have occurred over the past century. We examined a time series (1933-2004) from the Boston Marathon to test for an effect of warming on winning times by men and women. We found that warmer temperatures and headwinds on the day of the race slow winning times. However, 1.6°C warming in annual temperatures in Boston between 1933 and 2004 did not consistently slow winning times because of high variability in temperatures on race day. Starting times for the race changed to earlier in the day beginning in 2006, making it difficult to anticipate effects of future warming on winning times. However, our models indicate that if race starting times had not changed and average race day temperatures had warmed by 0.058°C/yr, a high-end estimate, we would have had a 95% chance of detecting a consistent slowing of winning marathon times by 2100. If average race day temperatures had warmed by 0.028°C/yr, a mid-range estimate, we would have had a 64% chance of detecting a consistent slowing of winning times by 2100.

Reconciling anthropogenic climate change with observed temperature 1998-2008.

Given the widely noted increase in the warming effects of rising greenhouse gas concentrations, it has been unclear why global surface temperatures did not rise between 1998 and 2008. We find that this hiatus in warming coincides with a period of little increase in the sum of anthropogenic and natural forcings. Declining solar insolation as part of a normal eleven-year cycle, and a cyclical change from an El Nino to a La Nina dominate our measure of anthropogenic effects because rapid growth in short-lived sulfur emissions partially offsets rising greenhouse gas concentrations. As such, we find that recent global temperature records are consistent with the existing understanding of the relationship among global surface temperature, internal variability, and radiative forcing, which includes anthropogenic factors with well known warming and cooling effects.

Evidence for a significant urbanization effect on climate in China.

China has experienced rapid urbanization and dramatic economic growth since its reform process started in late 1978. In this article, we present evidence for a significant urbanization effect on climate based on analysis of impacts of land-use changes on surface temperature in southeast China, where rapid urbanization has occurred. Our estimated warming of mean surface temperature of 0.05 degrees C per decade attributable to urbanization is much larger than previous estimates for other periods and locations. The spatial pattern and magnitude of our estimate are consistent with those of urbanization characterized by changes in the percentage of urban population and in satellite-measured greenness.