A unified approach to orbital, solar, and lunar forcing based on the Earth's latitudinal insolation/temperature gradient

Widespread empirical evidence suggests that extraterrestrial forcing influences the Earth's climate, but how this could occur remains unclear. Here we describe a new approach to this problem that unifies orbital, solar and lunar forcing based on their common control of the Earth's latitudinal insolation gradient (LIG). The LIG influences the climate system through differential solar heating between the tropics and the poles that gives rise to the latitudinal temperature gradient (LTG), which drives the Earth's atmospheric: and (wind driven) ocean circulation. We use spectral analysis of recent changes in the Earth's LTG to support earlier work on orbital timescales (Davis and Brewer, 2009) that suggests the climate system may be unusually sensitive to changes in the LIG. Identification of LIG forcing of the LTG is possible because the LIG varies according to seasonally specific periodicities based on obliquity in summer (41 kyr orbital and 18.6 yr lunar cycle), and precession (21 kyr orbital cycle) and total solar irradiance (11 yr solar cycle) in winter. We analyse changes in the Northern Hemisphere LTG over the last 120 years and find significant (99%) peaks in spectral frequencies corresponding to 11 years in winter and 18.6 years in summer, consistent with LIG forcing. The cross-seasonal and multi-frequency nature of the LIG signal, and the diffuse effect of the LTG driver on the climate system may account for the complexity of the response to extraterrestrial forcing as seen throughout the climatic record. This hypersensitivity of the LTG to the LIG appears poorly reproduced in climate models, but would be consistent with the controversial theory that the LTG is finely balanced to maximise entropy. (C) 2011 Elsevier Ltd. All rights reserved.

Orbital forcing and the role of the Latitudinal Temperature/Isolation Gradient

Basil Andrew Stansfield Davis

Orbital forcing of the climate system is clearly shown in the Earths record of glacial–interglacial cycles, but the mechanism underlying this forcing is poorly understood. Traditional Milankovitch theory suggests that these cycles are driven by changes in high latitude summer insolation, yet this forcing is dominated by precession, and cannot account for the importance of obliquity in the Ice Age record. Here, we investigate an alternative forcing based on the latitudinal insolation gradient (LIG), which is dominated by both obliquity (in summer) and precession (in winter). The insolation gradient acts on the climate system through differential solar heating, which creates the Earths latitudinal temperature gradient (LTG) that drives the atmospheric and ocean circulation. A new pollen-based reconstruction of the LTG during the Holocene is used to demonstrate that the LTG may be much more sensitive to changes in the LIG than previously thought. From this, it is shown how LIG forcing of the LTG may help explain the propagation of orbital signatures throughout the climate system, including the Monsoon, Arctic Oscillation and ocean circulation. These relationships are validated over the last (Eemian) Interglacial, which occurred under a different orbital configuration to the Holocene. We conclude that LIG forcing of the LTG explains many criticisms of classic Milankovitch theory, while being poorly represented in climate models.

Springer-Verlag2009

The climate of Europe during the Holocene: a gridded pollen-based reconstruction and its multi-proxy evaluation

Pamela Collins, Basil Andrew Stansfield Davis, Jed Oliver Kaplan

We present a new gridded climate reconstruction for Europe for the last 12,000 years based on pollen data. The reconstruction is an update of Davis et al. (2003) using the same methodology, but with a greatly expanded fossil and surface-sample dataset and more rigorous quality-control. The modern pollen dataset has been increased by more than 80%, and the fossil pollen dataset by more than 50%, representing almost 60,000 individual pollen samples. The climate parameters reconstructed include summer/winter and annual temperatures and precipitation, as well as a measure of moisture balance, and growing degree-days above 5 degrees C. Confidence limits were established for the reconstruction based on transfer function and interpolation uncertainties. The reconstruction takes account of post-glacial isostatic readjustment which resulted in a potential warming bias of up to +1-2 degrees C for parts of Fennoscandia in the early Holocene, as well as changes in palaeogeography resulting from decaying ice sheets and rising post-glacial sea-levels. This new dataset has been evaluated against previously published independent quantitative climate reconstructions from a variety of archives on a site-by-site basis across Europe. The results of this comparison are generally very good; only chironomid-based reconstructions showed substantial differences with our values. Our reconstruction is available for download as gridded maps throughout the Holocene on a 1000-year time-step. The gridded format makes our reconstructions suitable for comparison with climate model output and for other applications such as vegetation and land-use modelling. Our new climate reconstruction suggests that warming in Europe during the mid-Holocene was greater in winter than in summer, an apparent paradox that is not consistent with current climate model simulations and traditional interpretations of Milankovitch theory. (C) 2015 Elsevier Ltd. All rights reserved.

Pergamon-Elsevier Science Ltd2015

Exploring the coupled ocean and atmosphere system with a data science approach applied to observations from the Antarctic Circumnavigation Expedition

Andrea Baccarini, Irina Gorodetskaya, Christel Sybille Hassler, Sebastian Johannes Heinz-Josef Landwehr, Katherine Colby Leonard, Robin Lewis Modini, Fernando Perez Cruz, Julia Schmale, Jenny Thomas

The Southern Ocean is a critical component of Earth's climate system, but its remoteness makes it challenging to develop a holistic understanding of its processes from the small scale to the large scale. As a result, our knowledge of this vast region remains largely incomplete. The Antarctic Circumnavigation Expedition (ACE, austral summer 2016/2017) surveyed a large number of variables describing the state of the ocean and the atmosphere, the freshwater cycle, atmospheric chemistry, and ocean biogeochemistry and microbiology. This circumpolar cruise included visits to 12 remote islands, the marginal ice zone, and the Antarctic coast. Here, we use 111 of the observed variables to study the latitudinal gradients, seasonality, shorter-term variations, geographic setting of environmental processes, and interactions between them over the duration of 90 d. To reduce the dimensionality and complexity of the dataset and make the relations between variables interpretable we applied an unsupervised machine learning method, the sparse principal component analysis (sPCA), which describes environmental processes through 14 latent variables. To derive a robust statistical perspective on these processes and to estimate the uncertainty in the sPCA decomposition, we have developed a bootstrap approach. Our results provide a proof of concept that sPCA with uncertainty analysis is able to identify temporal patterns from diurnal to seasonal cycles, as well as geographical gradients and “hotspots” of interaction between environmental compartments. While confirming many well known processes, our analysis provides novel insights into the Southern Ocean water cycle (freshwater fluxes), trace gases (interplay between seasonality, sources, and sinks), and microbial communities (nutrient limitation and island mass effects at the largest scale ever reported). More specifically, we identify the important role of the oceanic circulations, frontal zones, and islands in shaping the nutrient availability that controls biological community composition and productivity; the fact that sea ice controls sea water salinity, dampens the wave field, and is associated with increased phytoplankton growth and net community productivity possibly due to iron fertilisation and reduced light limitation; and the clear regional patterns of aerosol characteristics that have emerged, stressing the role of the sea state, atmospheric chemical processing, and source processes near hotspots for the availability of cloud condensation nuclei and hence cloud formation. A set of key variables and their combinations, such as the difference between the air and sea surface temperature, atmospheric pressure, sea surface height, geostrophic currents, upper-ocean layer light intensity, surface wind speed and relative humidity played an important role in our analysis, highlighting the necessity for Earth system models to represent them adequately. In conclusion, our study highlights the use of sPCA to identify key ocean–atmosphere interactions across physical, chemical, and biological processes and their associated spatio-temporal scales. It thereby fills an important gap between simple correlation analyses and complex Earth system models. The sPCA processing code is available as open-access from the following link: https://renkulab.io/gitlab/ACE-ASAID/spca-decomposition (last access: 29 March 2021). As we show here, it can be used for an exploration of environmental data that is less prone to cognitive biases (and confirmation biases in particular) compared to traditional regression analysis that might be affected by the underlying research question.