Trends in U.S. Total Cloud Cover from a Homogeneity-Adjusted Dataset

Abstract

Cloud cover data from ground-based weather observers can be an important source of climate information, but the record of such observations in the United States is disrupted by the introduction of automated observing systems and other artificial shifts that interfere with our ability to assess changes in cloudiness at climate time scales. A new dataset using 54 National Weather Service (NWS) and 101 military stations that continued to make human-augmented cloud observations after the 1990s has been adjusted using statistical changepoint detection and visual scrutiny. The adjustments substantially reduce the trends in U.S. mean total cloud cover while increasing the agreement between the cloud cover time series and those of physically related climate variables. For 1949–2009, the adjusted time series give a trend in U.S. mean total cloud of 0.11% ± 0.22% decade−1 for the military data, 0.55% ± 0.24% decade−1 for the NWS data, and 0.31% ± 0.22% decade−1 for the combined dataset. These trends are less than one-half of those in the original data. For 1976–2004, the original data give a significant increase but the adjusted data show an insignificant trend from −0.17% decade−1 (military stations) to 0.66% decade−1 (NWS stations). Trends have notable regional variability, with the northwest United States showing declining total cloud cover for all time periods examined, while trends for most other regions are positive. Differences between trends in the adjusted datasets from military stations and NWS stations may be rooted in the difference in data source and reflect the uncertainties in the homogeneity adjustment process.