Wind speed variability over the Canary Islands, 1948-2014: focusing on trend differences at the land-ocean interface and below-above the trade-wind inversion layer

This study simultaneously examines wind speed trends at the land?ocean interface, and below?above the trade-wind inversion layer in the Canary Islands and the surrounding Eastern North Atlantic Ocean: a key region for quantifying the variability of trade-winds and its response to large-scale atmospheric circulation changes. Two homogenized data sources are used: (1) observed wind speed from nine land-based stations (1981?2014), including one mountain weather station (Izaña) located above the trade-wind inversion layer; and (2) simulated wind speed from two atmospheric hindcasts over ocean (i.e., SeaWind I at 30 km for 1948?2014; and SeaWind II at 15 km for 1989?2014). The results revealed a widespread significant negative trend of trade-winds over ocean for 1948?2014, whereas no significant trends were detected for 1989?2014. For this recent period wind speed over land and ocean displayed the same multi-decadal variability and a distinct seasonal trend pattern with a strengthening (late spring and summer; significant in May and August) and weakening (winter?spring?autumn; significant in April and September) of trade-winds. Above the inversion layer at Izaña, we found a predominance of significant positive trends, indicating a decoupled variability and opposite wind speed trends when compared to those reported in boundary layer. The analysis of the Trade Wind Index (TWI), the North Atlantic Oscillation Index (NAOI) and the Eastern Atlantic Index (EAI) demonstrated significant correlations with the wind speed variability, revealing that the correlation patterns of the three indices showed a spatio-temporal complementarity in shaping wind speed trends across the Eastern North Atlantic.C. A. -M. has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 703733 (STILLING project). This research was also supported by the Research Projects: Swedish BECC, MERGE, VR (2014–5320), PCIN-2015-220, CGL2014-52135-C03-01 and Red de variabilidad y cambio climático RECLIM (CGL2014-517221-REDT). M.M is indebted to the Spanish Government for funding through the “Ramón y Cajal” program and supported by Grant PORTIO (BIA2015-70644-R

Brief Communication Arising: Arctic tropospheric warming amplification?

No abstract availabl

Separating signal and noise in atmospheric temperature changes: The importance of timescale

We compare global-scale changes in satellite estimates of the temperature of the lower troposphere (TLT) with model simulations of forced and unforced TLT changes. While previous work has focused on a single period of record, we select analysis timescales ranging from 10 to 32 years, and then compare all possible observed TLT trends on each timescale with corresponding multi-model distributions of forced and unforced trends. We use observed estimates of the signal component of TLT changes and model estimates of climate noise to calculate timescale-dependent signal-to-noise ratios (S/N). These ratios are small (less than 1) on the 10-year timescale, increasing to more than 3.9 for 32-year trends. This large change in S/N is primarily due to a decrease in the amplitude of internally generated variability with increasing trend length. Because of the pronounced effect of interannual noise on decadal trends, a multi-model ensemble of anthropogenically-forced simulations displays many 10-year periods with little warming. A single decade of observational TLT data is therefore inadequate for identifying a slowly evolving anthropogenic warming signal. Our results show that temperature records of at least 17 years in length are required for identifying human effects on global-mean tropospheric temperature. Copyright 2011 by the American Geophysical Union

Tropospheric temperature trends: history of an ongoing controversy

Changes in atmospheric temperature have a particular importance in climate research because climate models consistently predict a distinctive vertical profile of trends. With increasing greenhouse gas concentrations, the surface and troposphere are consistently projected to warm, with an enhancement of that warming in the tropical upper troposphere. Hence, attempts to detect this distinct ‘fingerprint’ have been a focus for observational studies. The topic acquired heightened importance following the 1990 publication of an analysis of satellite data which challenged the reality of the projected tropospheric warming. This review documents the evolution over the last four decades of understanding of tropospheric temperature trends and their likely causes. Particular focus is given to the difficulty of producing homogenized datasets, with which to derive trends, from both radiosonde and satellite observing systems, because of the many systematic changes over time. The value of multiple independent analyses is demonstrated. Paralleling developments in observational datasets, increased computer power and improved understanding of climate forcing mechanisms have led to refined estimates of temperature trends from a wide range of climate models and a better understanding of internal variability. It is concluded that there is no reasonable evidence of a fundamental disagreement between tropospheric temperature trends from models and observations when uncertainties in both are treated comprehensivel