High-resolution summer temperature reconstruction from Lake Silvaplana based on in-situ reflectance spectroscopy

Annually laminated (varved) sediments of proglacial Lake Silvaplana (46 ̊27’N, 9 ̊48’E, 1791 m a.s.l., Engadine, eastern Swiss Alps) provide an excellent archive for quantitative high-resolution (seasonal – annual) reconstruction of high- and lowfrequency climate signals back to AD 1580. The chronology of the core is based on varve counting, Cs-137, Pb-210 and event stratigraphy. In this study we present a reconstruction based on in-situ reflectance spectroscopy. In situ reflectance spectroscopy is known as a cost- and time-effective non destructtive method for semi-quantitative analysis of pigments (e.g., chlorines and carotenoids) and of lithoclastic sediment fractions. Reflectance-dependent absorption (RDA) was measured with a Gretac Macbeth spectrolino at 2 mm resolution. The spectral coverage ranges from 380 nm to 730 nm at 10 nm band resolution. In proglacial Lake Silvaplana, 99% of the sediment is lithoclastic prior to AD 1950. Therefore, we concentrate on absorption features that are characteristic for lithoclastic sediment fractions. In Lake Silvaplana, two significant correlations that are stable in time were found between RDA typical for lithoclastics and meteorological data: (1) the time series R 570 /R 630 (ratio between RDA at 570 nm and 630 nm) of varves in Lake Silvaplana and May to October temperatures at nearby station of Sils correlate highly significantly (calibration period AD 1864 – 1951, r = 0.74, p < 0.01 for 5ptsmoothed series; RMSE is 0.28 ̊C, RE = 0.41 and CE = 0.38), and (2) the minimum reflectance within the 690nm band (min690) data correlate with May to October (calibration period AD 1864 – 1951, r = 0.68, p < 0.01 for 5pt-smoothed series; RMSE = 0.22 ̊C, RE = 0.5, CE = 0.31). Both proxy series (min690nm and R 570 /R 630 values) are internally highly consistent (r = 0.8, p < 0.001). In proglacial Lake Silvaplana the largest amount of sediment is transported by glacial meltwater. The melting season spans approximately from May to October, which gives us a good understanding of the geophysical processes explaining the correlations between lithoclastic proxies and the meteorological data. The reconstructions were extended back to AD 1580 and show a broad corresponddence with fully independent reconstructions from tree rings and documentary data.

Late Holocene summer temperatures in the central Andes reconstructed from the sediments of high-elevatin Laguna Chepical, Chile (32° S)

High-resolution reconstructions of climate variability that cover the past millennia are necessary to improve the understanding of natural and anthropogenic climate change across the globe. Although numerous records are available for the mid- and high-latitudes of the Northern Hemisphere, global assessments are still compromised by the scarcity of data from the Southern Hemisphere. This is particularly the case for the tropical and subtropical areas. In addition, high elevation sites in the South American Andes may provide insight into the vertical structure of climate change in the mid-troposphere. This study presents a 3000 yr-long austral summer (November to February) temperature reconstruction derived from the 210Pb- and 14C-dated organic sediments of Laguna Chepical (32°16' S, 70°30' W, 3050 m a.s.l.), a high-elevation glacial lake in the subtropical Andes of central Chile. Scanning reflectance spectroscopy in the visible light range provided the spectral index R570/R630, which reflects the clay mineral content in lake sediments. For the calibration period (AD 1901–2006), the R570/R630 data were regressed against monthly meteorological reanalysis data, showing that this proxy was strongly and significantly correlated with mean summer (NDJF) temperatures (R3 yr = −0.63, padj = 0.01). This calibration model was used to make a quantitative temperature reconstruction back to 1000 BC. The reconstruction (with a model error RMSEPboot of 0.33 °C) shows that the warmest decades of the past 3000 yr occurred during the calibration period. The 19th century (end of the Little Ice Age (LIA)) was cool. The prominent warmth reconstructed for the 18th century, which was also observed in other records from this area, seems systematic for subtropical and southern South America but remains difficult to explain. Except for this warm period, the LIA was generally characterized by cool summers. Back to AD 1400, the results from this study compare remarkably well to low altitude records from the Chilean Central Valley and southern South America. However, the reconstruction from Laguna Chepical does not show a warm Medieval Climate Anomaly during the 12–13th century, which is consistent with records from tropical South America. The Chepical record also indicates substantial cooling prior to 800 BC. This coincides with well-known regional as well as global glacier advances which have been attributed to a grand solar minimum. This study thus provides insight into the climatic drivers and temperature patterns in a region for which currently very few data are available. It also shows that since ca. AD 1400, long-term temperature patterns were generally similar at low and high altitudes in central Chile.

A Closed-Form, Consistent and Robust Solution to Uncalibrated Photometric Stereo Via Local Diffuse Reflectance Maxima

Images of an object under different illumination are known to provide strong cues about the object surface. A mathematical formalization of how to recover the normal map of such a surface leads to the so-called uncalibrated photometric stereo problem. In the simplest instance, this problem can be reduced to the task of identifying only three parameters: the so-called generalized bas-relief (GBR) ambiguity. The challenge is to find additional general assumptions about the object, that identify these parameters uniquely. Current approaches are not consistent, i.e., they provide different solutions when run multiple times on the same data. To address this limitation, we propose exploiting local diffuse reflectance (LDR) maxima, i.e., points in the scene where the normal vector is parallel to the illumination direction (see Fig. 1). We demonstrate several noteworthy properties of these maxima: a closed-form solution, computational efficiency and GBR consistency. An LDR maximum yields a simple closed-form solution corresponding to a semi-circle in the GBR parameters space (see Fig. 2); because as few as two diffuse maxima in different images identify a unique solution, the identification of the GBR parameters can be achieved very efficiently; finally, the algorithm is consistent as it always returns the same solution given the same data. Our algorithm is also remarkably robust: It can obtain an accurate estimate of the GBR parameters even with extremely high levels of outliers in the detected maxima (up to 80 % of the observations). The method is validated on real data and achieves state-of-the-art results.