Abstract: Traditionally, high-latitude dendroclimatic studies have focused on measurements of total ring width (RW), with the maximum density of the latewood (MXD) serving as a complementary variable. Whilst MXD has typically improved the strength of the growing season climate connection over that of RW, its measurements are costly and time-consuming. Recently, a less costly and more time-efficient technique to extract density measurements has emerged, based on lignin's propensity to absorb blue light. This Blue Intensity (BI) methodology is based on image analyses of finely-sanded core samples, and the relative ease with which density measurements can be extracted allows for significant increases in spatio-temporal sample depth. While some studies have attempted to combine RW and MXD as predictors for summer temperature reconstructions, here we evaluate a systematic comparison of the climate signal for RW and latewood BI (LWBI) separately, using a recently updated and expanded tree ring database for Labrador, Canada. We demonstrate that while RW responds primarily to climatic drivers earlier in the growing season (January-April), LWBI is more responsive to climate conditions during late spring and summer (May-August). Furthermore, RW appears to be driven primarily by large-scale atmospheric dynamics associated with the Pacific North American pattern, whilst LWBI is more closely associated with local climate conditions, themselves linked to the behaviour of the Atlantic Multidecadal Oscillation. Lastly, we demonstrate that anomalously wide or narrow growth rings consistently respond to the same climate drivers as average growth years, whereas the sensitivity of LWBI to extreme climate conditions appears to be enhanced.

Abstract: Astronomical forcing (obliquity and precession) has been thought to modulate Dansgaard-Oeschger (DO) events, yet the detailed quantification of such modulations has not been examined. In this study, we apply the novel Holo-Hilbert Spectral Analysis (HHSA) to five polar ice core records, quantifying astronomical forcing's time-varying amplitude modulation of DO events and identifying the preferred obliquity phases for large amplitude modulations. The unique advantages of HHSA over the widely used windowed Fourier spectral analysis for quantifying astronomical forcing's nonlinear modulations of DO events is first demonstrated with a synthetic data that closely resembles DO events recorded in Greenland ice cores (NGRIP, GRIP, and GISP2 cores on GICC05 modelext timescale). The analysis of paleoclimatic proxies show that statistically significantly more frequent DO events, with larger amplitude modulation in the Greenland region, tend to occur in the decreasing phase of obliquity, especially from its mean value to its minimum value. In the eastern Antarctic, although statistically significantly more DO events tend to occur in the decreasing obliquity phase in general, the preferred phase of obliquity for large amplitude modulation on DO events is a segment of the increasing phase near the maximum obliquity, implying that the physical mechanisms of DO events may be different for the two polar regions. Additionally, by using cross-spectrum and magnitude-squared analyses, Greenland DO mode at a timescale of about 1400 years leads the Antarctic DO mode at the same timescale by about 1000 years. (C) 2018 Elsevier Ltd. All rights reserved.

Abstract: Daily maximum and minimum temperature data from 758 COOP stations in nineteen states are used to create temperature decile maps. All stations used contain records from 1948 through 2004 and could not be missing more than 5 consecutive years of data. Missing data are replaced using a multiple linear regression technique from surrounding stations. For each station, the maximum and minimum temperatures are first sorted in ascending order for every two years (to reduce annual variability) and divided into ten equal parts (or deciles). The first decile represents the coldest temperatures, and the last decile contains the warmest temperatures. Patterns and trends in these deciles can be examined for the 57-year period. A linear least-squares regression method is used to calculate best-fit lines for each decile to determine the long-term trends at each station. Significant warming or cooling is determined using the Student's t-test, and bootstrapping the decile data will further examine the validity of significance. Two stations are closely examined. Apalachicola, Florida shows significant warming in its maximum deciles and significant cooling in its minimum deciles. The maximum deciles seem to be affected by some localized change. The minimum deciles are discontinuous, and the trends are a result of a minor station move. Columbus, Georgia has experienced significant warming in its minimum deciles, and this appears to be the result of an urban heat-island effect. The discontinuities seen in the Apalachicola case study illustrate the need for a quality control method. This method will eliminate stations from the regional analysis that experience large changes in the ten-year standard deviations within their time series. The regional analysis shows that most of the region is dominated by significant cooling in the maximum deciles and significant warming in the minimum deciles, with more variability in the lower deciles. Field significance testing is performed on subregions (based on USGS 2000 land cover data) and supports the findings from the regional analysis; it also isolates regions, such as the Florida peninsula and the Maryland/Delaware region, that appear to be affected by more local forcings.