Trends and uncertainties in U.S. cloud cover from weather stations and satellite data

Wednesday, 17 December 2014
Melissa Purdy Free1, Bomin Sun2 and Hye Lim Yoo1, (1)NOAA, College Park, MD, United States, (2)IMSG, College Park, MD, United States
Cloud cover data from ground-based weather observers can be an important source of climate information, but the record of such observations in the U.S. 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 such as diurnal temperature range and number of precipitation days. For 1949-2009, the adjusted time series give a trend in U.S. mean total cloud of 0.11 ± 0.22 %/decade for the military data, 0.55 ± 0.24 %/decade for the NWS data, and 0.31 ± 0.22 %/decade for the combined dataset. These trends are less than half those in the original data. For 1976-2004, the original data give a significant increase but the adjusted data show an insignificant trend of -0.17 (military stations) to 0.66 %/decade (NWS stations). The differences between the two sets of station data illustrate the uncertainties in the U.S. cloud cover record.

We compare the adjusted station data to cloud cover time series extracted from several satellite datasets: ISCCP (International Satellite Cloud Climatology Project), PATMOS-x (AVHRR Pathfinder Atmospheres Extended) and CLARA-a1 (CM SAF cLoud Albedo and RAdiation), and the recently developed PATMOS-x diurnally corrected dataset. Like the station data, satellite cloud cover time series may contain inhomogeneities due to changes in the observing systems and problems with retrieval algorithms. Overall we find good agreement between interannual variability in most of the satellite data and that in our station data, with the diurnally corrected PATMOS-x product generally showing the best match. For the satellite period 1984-2007, trends in the U.S. mean cloud cover from satellite data vary widely among the datasets, and all are more negative than those in the station data, with PATMOS-x having the trends closest to those in the station data.