Root-zone soil water content and temperature at snow covered and snow-free sites in southern boreal Finland

Poster

Lethal effects of waterlogging on Scots pine appear with delay

Poster

Disentangling the Evidence of Milankovitch Forcing From Tree-Ring and Sedimentary Records

Publisher Copyright: Copyright © 2022 Helama, Herva, Arppe, Gunnarson, Frank, Holopainen, Nöjd, Mäkinen, Mielikäinen, Sutinen, Timonen, Uusitalo and Oinonen.Tree-ring records constitute excellent high-resolution data and provide valuable information for climate science and paleoclimatology. Tree-ring reconstructions of past temperature variations agree to show evidence for annual-to-centennial anomalies in past climate and place the industrial-era warming in the context of the late Holocene climate patterns and regimes. Despite their wide use in paleoclimate research, however, tree rings have also been deemed unsuitable as low-frequency indicators of past climate. The arising debate concerns whether the millennia-long tree-ring records show signals of orbital forcing due to the Milankovitch cycles. Here, we produce a summer-temperature reconstruction from tree-ring chronology running through mid- and late-Holocene times (since 5486 BCE) comprising minimum blue channel light intensity (BI). The BI reconstruction correlates with existing and new tree-ring chronologies built from maximum latewood density (MXD) and, unlike the MXD data, shows temperature trends on Milankovitch scales comparable to various types of sedimentary proxy across the circumpolar Arctic. Our results demonstrate an unrevealed potential of novel, unconventional tree-ring variables to contribute to geoscience and climate research by their capability to provide paleoclimate estimates from inter-annual scales up to those relevant to orbital forcing.Peer reviewe

Very High Spatial Resolution Soil Moisture Observation of Heterogeneous Subarctic Catchment Using Nonlocal Averaging and Multitemporal SAR Data

A soil moisture estimation method was developed for Sentinel-1 synthetic aperture radar (SAR) ground range detected high resolution (GRDH) data to analyze moisture conditions in a gently undulating and heterogeneous subarctic area containing forests, wetlands, and open orographic tundra. In order to preserve the original 10-m pixel spacing, PIMSAR (pixel-based multitemporal nonlocal averaging) nonlocal mean filtering was applied. It was guided by multitemporal statistics of SAR images in the area. The gradient boosted trees (GBT) machine learning method was used for the soil moisture algorithm development. Discrete and continuous in situ soil moisture values were used for training and validation of the algorithm. For surface soil moisture, the root mean square error (RMSE) of the method was 6.5% and 8.8% for morning and evening images, respectively. The corresponding maximum errors were 34.1% and 33.8%. The pixelwise sensitivity to the training set and method choice was estimated as the variance of the soil moisture values derived using the algorithms for the three best methods with respect to the criteria: the smallest maximum error, the smallest RMSE value, and the highest coefficient of determination (R-2) value. It was, on average, 6.3% with a standard deviation of 5.7%. Our approach successfully produced instantaneous high-resolution soil moisture estimates on daily basis for the subarctic landscape and can further be applied to various hydrological, biogeochemical, and management purposes.Peer reviewe

Very High Spatial Resolution Soil Moisture Observation of Heterogeneous Subarctic Catchment Using Nonlocal Averaging and Multitemporal SAR Data

A soil moisture estimation method was developed for Sentinel-1 synthetic aperture radar (SAR) ground range detected high resolution (GRDH) data to analyze moisture conditions in a gently undulating and heterogeneous subarctic area containing forests, wetlands, and open orographic tundra. In order to preserve the original 10-m pixel spacing, PIMSAR (pixel-based multitemporal nonlocal averaging) nonlocal mean filtering was applied. It was guided by multitemporal statistics of SAR images in the area. The gradient boosted trees (GBT) machine learning method was used for the soil moisture algorithm development. Discrete and continuous in situ soil moisture values were used for training and validation of the algorithm. For surface soil moisture, the root mean square error (RMSE) of the method was 6.5% and 8.8% for morning and evening images, respectively. The corresponding maximum errors were 34.1% and 33.8%. The pixelwise sensitivity to the training set and method choice was estimated as the variance of the soil moisture values derived using the algorithms for the three best methods with respect to the criteria: the smallest maximum error, the smallest RMSE value, and the highest coefficient of determination (R-2) value. It was, on average, 6.3% with a standard deviation of 5.7%. Our approach successfully produced instantaneous high-resolution soil moisture estimates on daily basis for the subarctic landscape and can further be applied to various hydrological, biogeochemical, and management purposes.Peer reviewe

New computational methods for efficient utilisation of public data

201

Volcanic dust veils from sixth century tree-ring isotopes linked to reduced irradiance, primary production and human health

The large volcanic eruptions of AD 536 and 540 led to climate cooling and contributed to hardships of Late Antiquity societies throughout Eurasia, and triggered a major environmental event in the historical Roman Empire. Our set of stable carbon isotope records from subfossil tree rings demonstrates a strong negative excursion in AD 536 and 541-544. Modern data from these sites show that carbon isotope variations are driven by solar radiation. A model based on sixth century isotopes reconstruct an irradiance anomaly for AD 536 and 541-544 of nearly three standard deviations below the mean value based on modern data. This anomaly can be explained by a volcanic dust veil reducing solar radiation and thus primary production threatening food security over a multitude of years. We offer a hypothesis that persistently low irradiance contributed to remarkably simultaneous outbreaks of famine and Justinianic plague in the eastern Roman Empire with adverse effects on crop production and photosynthesis of the vitamin D in human skin and thus, collectively, human health. Our results provide a hitherto unstudied proxy for exploring the mechanisms of 'volcanic summers' to demonstrate the post-eruption deficiencies in sunlight and to explain the human consequences during such calamity years

Preface to the special issue on integrated research of atmosphere, ecosystems and environment at Pallas

201