scholarly journals Total organic carbon sensitivity to climate change from Lake Qinghai sediments at different time scales

2019 ◽  
Vol 31 (5) ◽  
pp. 1468-1478
Author(s):  
ZHANG Yao ◽  
◽  
WU Duo ◽  
ZHANG Huan ◽  
ZHOU Aifeng ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Total Organic Carbon ◽  
Time Scales ◽  
Lake Qinghai ◽  
Different Time Scales

Time-scale dependence of climate-carbon cycle feedbacks for weak perturbations in CMIP5 models

2021 ◽  
Author(s):  
Guilherme Torres Mendonça ◽  
Julia Pongratz ◽  
Christian Reick
Keyword(s):  
Climate Change ◽  
Carbon Cycle ◽  
Time Scales ◽  
Radiative Forcing ◽  
Global Carbon Cycle ◽  
Atmospheric Co2 ◽  
Ice Age ◽  
Cmip5 Models ◽  
Global Carbon ◽  
Different Time Scales

<p>The increase in atmospheric CO2 driven by anthropogenic emissions is the main radiative forcing causing climate change. But this increase is not only a result from emissions, but also from changes in the global carbon cycle. These changes arise from feedbacks between climate and the carbon cycle that drive CO2 into or out of the atmosphere in addition to the emissions, thereby either accelerating or buffering climate change. Therefore, understanding the contribution of these feedbacks to the global response of the carbon cycle is crucial in advancing climate research. Currently, this contribution is quantified by the α-β-γ framework (Friedlingstein et al., 2003). But this quantification is only valid for a particular perturbation scenario and time period. In contrast, a recently proposed generalization (Rubino et al., 2016) of this framework for weak perturbations quantifies this contribution for all scenarios and at different time scales. </p><p>Thereby, this generalization provides a systematic framework to investigate the response of the global carbon cycle in terms of the climate-carbon cycle feedbacks. In the present work we employ this framework to study these feedbacks and the airborne fraction in different CMIP5 models. We demonstrate (1) that this generalization of the α-β-γ framework consistently describes the linear dynamics of the carbon cycle in the MPI-ESM; and (2) how by this framework the climate-carbon cycle feedbacks and airborne fraction are quantified at different time scales in CMIP5 models. Our analysis shows that, independently of the perturbation scenario, (1) the net climate-carbon cycle feedback is negative at all time scales; (2) the airborne fraction generally decreases for increasing time scales; and (3) the land biogeochemical feedback dominates the model spread in the airborne fraction at all time scales. This last result therefore emphasizes the need to improve our understanding of this particular feedback.</p><p><strong>References:</strong></p><p>P. Friedlingstein, J.-L. Dufresne, P. Cox, and P. Rayner. How positive is the feedback between climate change and the carbon cycle? Tellus B, 55(2):692–700, 2003.</p><p>M. Rubino, D. Etheridge, C. Trudinger, C. Allison, P. Rayner, I. Enting, R. Mulvaney, L. Steele, R. Langenfelds, W. Sturges, et al. Low atmospheric CO2 levels during the Little Ice Age due to cooling-induced terrestrial uptake. Nature Geoscience, 9(9):691–694, 2016.</p>

scholarly journals Seamless climate change projections and seasonal predictions for bushfires in Australia

2020 ◽  
Vol 70 (1) ◽  
pp. 120
Author(s):  
Andrew J. Dowdy
Keyword(s):  
Climate Change ◽  
Long Range ◽  
Time Scales ◽  
Weather Conditions ◽  
Weather Data ◽  
Future Climate Change ◽  
Data Sets ◽  
Fire Weather ◽  
Climate Change Projections ◽  
Different Time Scales

Spatio-temporal variations in fire weather conditions are presented based on various data sets, with consistent approaches applied to help enable seamless services over different time scales. Recent research on this is shown here, covering climate change projections for future years throughout this century, predictions at multi-week to seasonal lead times and historical climate records based on observations. Climate projections are presented based on extreme metrics with results shown for individual seasons. A seasonal prediction system for fire weather conditions is demonstrated here as a new capability development for Australia. To produce a more seamless set of predictions, the data sets are calibrated based on quantile-quantile matching for consistency with observations-based data sets, including to help provide details around extreme values for the model predictions (demonstrating the quantile matching for extremes method). Factors influencing the predictability of conditions are discussed, including pre-existing fuel moisture, large-scale modes of variability, sudden stratospheric warmings and climate trends. The extreme 2019–2020 summer fire season is discussed, with examples provided on how this suite of calibrated fire weather data sets was used, including long-range predictions several months ahead provided to fire agencies. These fire weather data sets are now available in a consistent form covering historical records back to 1950, long-range predictions out to several months ahead and future climate change projections throughout this century. A seamless service across different time scales is intended to enhance long-range planning capabilities and climate adaptation efforts, leading to enhanced resilience and disaster risk reduction in relation to natural hazards.

Traces of sunlight in carbon biochemistry of shallow subarctic lakes

2020 ◽  
Author(s):  
Marttiina Rantala ◽  
Henriikka Kivilä ◽  
Carsten Meyer-Jacob ◽  
Maxime Wauthy ◽  
Milla Rautio ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Time Scales ◽  
Carbon Pools ◽  
Uv Spectrum ◽  
Subarctic Lakes ◽  
Climate Fluctuations ◽  
Underwater Light ◽  
Long Time ◽  
Experimental Treatments

<p>Sunlight fuels the drawdown and evasion of carbon in shallow northern lakes. Amplified polar warming is altering the sunlit transport and transformation of aquatic carbon at an alarming rate entailing potential for climate feedbacks. We combined experimental and retrospective approaches to explore the synoptic interlinks between underwater light, aquatic carbon biochemistry, landscape carbon cycling and climate change in two shallow subarctic lakes with divergent light and carbon regime (a clear lake low in organic carbon and a dark organic rich lake). In situ enclosures (treatments under full sunlight, sunlight without the ultraviolet [UV] spectrum, no light) were first deployed on the lakes to decipher the effect of photochemical alteration on the spectral, elemental and isotopic properties of lake water organic carbon pools under short term (four weeks) exposure. We then focused on elemental, isotopic and spectral fingerprints archived in the sediments of the lakes to trace coeval variability in aquatic primary production, terrestrial carbon transport, and underwater light under centennial climate fluctuations. We observed distinct differences in carbon biochemistry between the experimental treatments illustrating the importance of sunlight, and particularly the UV spectrum, in shaping the carbon pools of the lakes already over short time scales. Over the past centennia, sediment biogeochemical composition carried signatures of change in carbon origins (algal vs terrestrial) and shifting underwater light regime. The results shed light on how climate change and sunlight shape carbon flows in shallow northern lakes over short and long time scales.</p>

scholarly journals Complexity Analysis of Precipitation and Runoff Series Based on Approximate Entropy and Extreme-Point Symmetric Mode Decomposition

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1388 ◽  
Author(s):  
Dongyong Sun ◽  
Hongbo Zhang ◽  
Zhihui Guo
Keyword(s):  
Climate Change ◽  
Correlation Coefficient ◽  
Extreme Point ◽  
Time Scales ◽  
Approximate Entropy ◽  
Monthly Precipitation ◽  
Symmetric Mode ◽  
Mode Decomposition ◽  
Different Time Scales ◽  
The Imf

Many regional hydrological regime changes are complex under the influences of climate change and human activities, which make it difficult to understand the regional or basin al hydrological status. To investigate the complexity of precipitation and the runoff time series from 1960 to 2012 in the Jing River Basin on different time scales, approximate entropy, a Bayesian approach and extreme-point symmetric mode decomposition were employed. The results show that the complexity of annual precipitation and runoff has decreased since the 1990sand that the change occurred in 1995. The Intrinsic Mode Function (IMF)-6 component decomposed by extreme-point symmetric mode decomposition of monthly precipitation and runoff was consistent with precipitation and runoff. The IMF-6 component of monthly precipitation closely followed the 10-year cycle of change, and it has an obvious correlation with sunspots. The correlation coefficient is 0.6, representing a positive correlation before 1995 and a negative correlation after 1995. However, the IMF-6 component of monthly runoff does not have a significant correlation with sunspots, and the correlation coefficient is only 0.41, which indicates that climate change is not the dominant factor of runoff change. Approximate entropy is an effective analytical method for complexity, and furthermore, it can be decomposed by extreme-point symmetric mode decomposition to obtain the physical process of the sequences at different time scales, which helps us to understand the background of climate change and human activity in the process of precipitation and runoff.

scholarly journals How Might the Ocean Change in the Future?

2021 ◽  
Vol 9 ◽  
Author(s):  
Denise Tyemi Fukai ◽  
Anna Beatriz Jones Oaquim ◽  
Mauro Cirano
Keyword(s):  
Climate Change ◽  
Time Scales ◽  
Ocean Circulation ◽  
Thermohaline Circulation ◽  
Water Density ◽  
Ocean Water ◽  
The World ◽  
Main Components ◽  
Circulation Changes ◽  
Different Time Scales

The ocean is one of the main components of the climate system. It distributes and absorbs heat to regulate climate at different time scales. Temperature and salinity (saltiness) control the density of ocean water. Differences in water density are important for ocean circulation—they are responsible for generating some currents of water that move through the ocean. An important part of ocean circulation is called thermohaline circulation. Thermohaline circulation absorbs, stores, and transfers heat around the world. Changes in the temperature or salinity of ocean waters can affect thermohaline circulation, so climate change may also alter this circulation. Changes in water circulation also impact the ocean’s chemistry and the organisms that live in the ocean. First, we will explain how ocean circulation happens, and then we will look at how climate change can affect it.

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