Time-dependent response of a zonally averaged ocean–atmosphere–sea ice model to Milankovitch forcing

Author Posting. © The Author(s), 2010. This is the author's version of the work. It is posted here by permission of Springer-Verlag for personal use, not for redistribution. The definitive version was published in Climate Dynamics 6 (2010): 763-779, doi:10.1007/s00382-010-0790-6.An ocean-atmosphere-sea ice model is developed to explore the time-dependent response of climate to Milankovitch forcing for the time interval 5-3 Myr BP. The ocean component is a zonally averaged model of the circulation in five basins (Arctic, Atlantic, Indian, Pacific, and Southern Oceans). The atmospheric component is a one-dimensional (latitudinal) energy balance model, and the sea-ice component is a thermodynamic model. Two numerical experiments are conducted. The first experiment does not include sea ice and the Arctic Ocean; the second experiment does. Results from the two experiments are used to investigate (i) the response of annual mean surface air and ocean temperatures to Milankovitch forcing, and (ii) the role of sea ice in this response. In both experiments, the response of air temperature is dominated by obliquity cycles at most latitudes. On the other hand, the response of ocean temperature varies with latitude and depth. Deep water formed between 45°N-65°N in the Atlantic Ocean mainly responds to precession. In contrast, deep water formed south of 60°S responds to obliquity when sea ice is not included. Sea ice acts as a time-integrator of summer insolation changes such that annual mean sea-ice conditions mainly respond to obliquity. Thus, in the presence of sea ice, air temperature changes over the sea ice are amplified, and temperature changes in deep water of southern origin are suppressed since water below sea ice is kept near the freezing point.This work was supported by an NSERC Discovery Grant awarded to L.A.M. We also thank GEC3 for a Network Grant

Internet of Things for Sustainable Human Health

The sustainable health IoT has the strong potential to bring tremendous improvements in human health and well-being through sensing, and monitoring of health impacts across the whole spectrum of climate change. The sustainable health IoT enables development of a systems approach in the area of human health and ecosystem. It allows integration of broader health sub-areas in a bigger archetype for improving sustainability in health in the realm of social, economic, and environmental sectors. This integration provides a powerful health IoT framework for sustainable health and community goals in the wake of changing climate. In this chapter, a detailed description of climate-related health impacts on human health is provided. The sensing, communications, and monitoring technologies are discussed. The impact of key environmental and human health factors on the development of new IoT technologies also analyzed

Performance of a frost hollow as a hemispherical thermal radiometer

Radiant sky hemispheric temperature, snow-surface temperature, and thermal profiles within the snowpack were measured at night in a frost hollow in southeastern Michigan, U.S.A. Snow-surface temperatures remained 3° to 5°C colder than air temperatures at 3 m above the snow surface and 6° to 7°C colder than air temperatures at 18 m, the height of the hollow's rim above its floor. Due to suppression of turbulent heat transfer, the energy balance at the surface was dominated by net longwave radiation; energy involved in sensible heat transfer through the snow was equal to only about 10% of the incoming longwave radiation. Incoming longwave radiation can be expressed as a linear function of surface temperature by means of a regression equation, which yields a coefficient of determination of 0.75. Die Strahlungstemperatur der Himmelshemisphäre, die Schneeoberflächentemperatur und thermische Profile in der Schneedecke wurden in einer klaren Nacht in einer Frostmulde im Südosten von Michigan, U.S.A., gemessen. Die Schneeoberflächentemperatur blieb 3 bis 5°C kälter als die Lufttemperatur in 3 m über der Schneeoberfläche und um 6 bis 7°C kälter als die Lufttemperatur in 18 m Höhe, das ist die Höhe des oberen Randes der Mulde über ihrem Boden. Bei Bestimmung der turbulenten Wärmeübertragung war der Energiehaushalt an der Oberfläche von der langwelligen Strahlungsbilanz beherrscht. Die mit der Transport fühlbarer Wärme durch den Schnee verbundene Energie betrug nur ungefähr 10% der langwelligen Einstrahlung. Die langwellige Einstrahlung kann durch eine lineare Funktion der Oberflächentemperatur mittels einer Regressionsgleichung ausgedrückt werden, die einen Regressionskoeffizienten von 0,75 ergibt.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41662/1/703_2005_Article_BF02273978.pd

Early Diagnosis of Vegetation Health From High-Resolution Hyperspectral and Thermal Imagery: Lessons Learned From Empirical Relationships and Radiative Transfer Modelling

[Purpose of Review] We provide a comprehensive review of the empirical and modelling approaches used to quantify the radiation–vegetation interactions related to vegetation temperature, leaf optical properties linked to pigment absorption and chlorophyll fluorescence emission, and of their capability to monitor vegetation health. Part 1 provides an overview of the main physiological indicators (PIs) applied in remote sensing to detect alterations in plant functioning linked to vegetation diseases and decline processes. Part 2 reviews the recent advances in the development of quantitative methods to assess PI through hyperspectral and thermal images.[Recent Findings] In recent years, the availability of high-resolution hyperspectral and thermal images has increased due to the extraordinary progress made in sensor technology, including the miniaturization of advanced cameras designed for unmanned aerial vehicle (UAV) systems and lightweight aircrafts. This technological revolution has contributed to the wider use of hyperspectral imaging sensors by the scientific community and industry; it has led to better modelling and understanding of the sensitivity of different ranges of the electromagnetic spectrum to detect biophysical alterations used as early warning indicators of vegetation health.[Summary] The review deals with the capability of PIs such as vegetation temperature, chlorophyll fluorescence, photosynthetic energy downregulation and photosynthetic pigments detected through remote sensing to monitor the early responses of plants to different stressors. Various methods for the detection of PI alterations have recently been proposed and validated to monitor vegetation health. The greatest challenges for the remote sensing community today are (i) the availability of high spatial, spectral and temporal resolution image data; (ii) the empirical validation of radiation–vegetation interactions; (iii) the upscaling of physiological alterations from the leaf to the canopy, mainly in complex heterogeneous vegetation landscapes; and (iv) the temporal dynamics of the PIs and the interaction between physiological changes.The authors received funding provided by the FluorFLIGHT (GGR801) Marie Curie Fellowship, the QUERCUSAT and ESPECTRAMED projects (Spanish Ministry of Economy and Competitiveness), the Academy of Finland (grants 266152, 317387) and the European Research Council Synergy grant ERC-2013-SyG-610028 IMBALANCE-P.Peer reviewe

Beyond equilibrium climate sensitivity

ISSN:1752-0908ISSN:1752-089