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We thank the authors (hereafter referred to as CCC) for providing us an opportunity to clarify some points of our original paper. CCC list in their abstract three "key points"that we respond to in this Reply. The first comment is the central one and the most developed. It deals mainly with discussion of features of methods of spectral analysis, mainly SSA. We have quoted the sub‐parts of that comment as items 1a to 1k. The replies to comments/key points 2 and 3 are shorter. We disagree with most of the comments by CCC and explain why. We conclude that we have successfully countered CCC's criticism and shown many of their points to be unsubstantiated. The main problem seems to reside in differences concerning the literature on Singular Spectral Analysis and our use of it. Much of our response to the comments can be found in textbooks and review papers on SSA and time series analysis; we quote extensively, both in our original paper and in this response to CCC, Golyandina and Zhigljavsky (2013). Key Points: We find compelling results showing a significant co‐variability between sunspot numbers and global temperature.We do not have a mechanism to explain that forcing: it remains to be found. We do not discuss further the parts of CCC on mechanisms.The trends of temperature and sunspots (first SSA component) are similar; the second component results in an opposite trend in the last 30 years. [ABSTRACT FROM AUTHOR]

The discrepancy between simulated and observed globally averaged monthly atmospheric concentrations of carbon dioxide could be attributed either to deficiencies in the observation network or to inadequacies in the global carbon cycle models. This paper shows that model results could be brought closer to observations by improving model components that describe the seasonal changes in the storage of quickly decaying fractions of litter. [ABSTRACT FROM AUTHOR]

The article focuses on the metrics used for comparing greenhouse gases with focus on the Integrated Temperature Change Potential (IGTP). It states that the IGTP and global warming potentials (GWP) are asymptotically equal is the time horizon reaches infinity. It says that the IGTP is equal to the Sustained Global Temperature change Potential (SGTP) under standard assumptions when calculating GWPs.

The article presents information on a study conducted on a 500 year model simulation of the mid-Pliocene Warm Period (mPWP) by using the Community Climate System Model, version 4 (CCSM4). Results from the CCSM4 mPWP simulation showed a 1.9 Degrees Centigrade increase in global mean annual temperature, along with a polar amplification of nearly three times the global warming.

In recent years, research on climate change and human security has received much attention among policy makers and academia alike. Communities in the Global South that rely on an intact resource base will especially be affected by predicted changes in temperature and precipitation. The objective of this article is to better understand under what conditions local communities can adapt to anticipated impacts of climate change and avoid conflict over the loss of resources. The empirical part of the paper answers the question to what extent local communities in the Chilwa Basin in Malawi have experienced climate change and how they are affected by it. Further, it assesses one of Malawi's adaptation projects designed to build resilience to a warmer and more variable climate, and points to some of its limitations. This research shows that not all adaptation strategies are suited to cope with a warmer and more variable climate. [ABSTRACT FROM AUTHOR]

The article discusses the interpretation and definition of quantities relating to climate sensitivity in the discussions paper "Climate sensitivity in the Anthropocene," by M. Previdi and colleagues. It states that the paper brought several errors and inconsistencies in the discussion of climate sensitivity. It says that definition of temperature which denoted surface temperature was inconsistent.

Iron oxide assemblages are central to many pursuits, ranging from Mars exploration to environmental remediation. Oxides and oxyhydroxides of iron both carry the special properties of color and magnetism. In this paper, we use visible-light spectroscopy and rock magnetic data collected at varying temperatures (~77–973 K) to analyze the concentrations and identities of iron oxides found in natural hematite-dominated samples that were obtained from a scientific drill core of Late Triassic red beds in the American Southwest. Our results suggest that hematite colorization of Earth materials varies from red to blue/purple as crystal size increases. Second-derivative analysis of the collected visible-light spectra allows this variation to be measured through the characteristic wavelength band position. Magnetic coercivity data indicate "hardness" differences that also may suggest smaller grain sizes are associated with redder colors. Yellowish maghemite and goethite have overlapping characteristic wavelength band positions that make it challenging to distinguish their contributions to mixed assemblages from visible-light data alone. Remanent magnetizations acquired at ~77 K and room temperature suggest the presence of hematite and a low-coercivity phase that may be maghemite and/or oxidized magnetite. However, we interpret this phase as maghemite in order to explain the changes in iron oxide concentrations indicated by visible-light intensities near ~425 nm and because the thermal demagnetization data suggest that goethite is absent from the samples. Future research that increases the resolution of hematite, maghemite, and goethite detection in experimental and natural samples will provide opportunities to refine the study of past climates and constrain soil iron availability under future changes in global moisture and temperature. Multimethod datasets improve understanding of environmental conditions that cause iron oxides assemblages to shift in phase dominance, grain size, and crystallinity. [ABSTRACT FROM AUTHOR]

Given the potential for elements of the Earth system to undergo rapid, hard to reverse changes in state, there is a pressing need to establish robust methods to produce early warning signals of such events. Here we present a conceptual ecosystem model in which a diversity of stable states emerge, along with rapid changes, referred to as critical transitions, as a consequence of external driving and non-linear ecological dynamics. We are able to produce robust early warning signals that precede critical transitions. However, we show that there is no correlation between the magnitude of the signal and magnitude or reversibility of any individual critical transition. We discuss these findings in the context of ecosystem management prior to and post critical transitions. We argue that an understanding of the dynamics of the systems is necessary both for management prior and post critical transitions and the effective interpretation of any early warning signal that may be produced for that system. [ABSTRACT FROM AUTHOR]

Robust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. Currently, two such levels are discussed in the context of the international climate negotiations as long-term global temperature goals: a below 2 °C and a 1.5 °C limit in global-mean temperature rise above pre-industrial levels. Despite the prominence of these two temperature limits, a comprehensive assessment of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5 °C and 2 °C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between 1.5 °C and 2 °C. For heat-related extremes, the additional 0.5 °C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2 °C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature induced bleaching from 2050 onwards. This fraction is reduced to about 90 % in 2050 and projected to decline to 70 % by 2100 for a 1.5 °C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and several hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9 to 17 % between 1.5 °C and 2 °C, and the projected lengthening of regional dry spells increases from 7 % longer to 11 %. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and Northern South America are projected to face local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50 cm rise by 2100 relative to year 2000-levels under a 2 °C warming, which is about 10 cm lower for a 1.5 °C scenario. Our findings highlight the importance of regional differentiation to assess future climate risks as well as different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a solid foundation for future work on refining our understanding of warming-level dependent climate impacts. [ABSTRACT FROM AUTHOR]

The article discusses a study conducted to compare three types of data sets with the Coupled Model Intercomparison Project (CMIP5) climate model simulations to understand similarities or differences between temperature trends in CMIP5 simulations with those from the radiosonde observations, reanalyses and CMIP3 climate simulations. It is stated that data sets are compared between the stratosphere and troposphere as well as between the tropics, Arctic and Antarctic.

Terrestrial ecosystems of northern Eurasia are greening, yet few studies have provided definitive attribution for the changes. While prior studies point to increasing temperatures as the principle environmental control, influences from moisture and other factors are less clear. We assess how changes in temperature, precipitation, cloudiness and forest fires contribute to the trend in Gross Primary Productivity (GPP) derived from satellite data across northern Eurasia. For the period 1982-2008 we find that GPP, estimated using ensemble satellite NDVI (Normalized Difference Vegetation Index) observations from GIMMS3g and VIP datasets, is most sensitive to temperature, precipitation and cloudiness during summer, the peak of the growing season. For regional median GPP, summer temperature explains 33.3% of the variation in GPP, while the other environmental variables explain from 2.2 to 11.8 %. Warming over the period analyzed, even without a sustained increase in precipitation, led to a significant GPP increase over 67.3% of the region. A significant decrease in GPP was found over 6.2% of the region, primarily the dryer grasslands in the south-western. For this area, precipitation positively correlates with GPP, as does cloudiness. This shows that the south-western part of northern Eurasia is relatively more vulnerable to drought than other areas. Our results further advance the notion that air temperature is the dominant environmental control for the recent GPP increases across northern Eurasia. [ABSTRACT FROM AUTHOR]

Earth's climate exhibits internal modes of variability on various time scales. Here we investigate multi-decadal variability of the Atlantic meridional overturning circulation (AMOC) in the control runs of an ensemble of CMIP5 models. By decomposing global- mean-temperature (GMT) variance into contributions of the AMOC and Northern Hemisphere sea-ice extent using a graph-theoretical statistical approach, we find the AMOC to contribute 8% to GMT variability in the ensemble mean. Our results highlight the importance of AMOC sea-ice feedbacks that explain 5% of the GMT variance, while the contribution solely related to the AMOC is found to be about 3 %. As a consequence of multi-decadal AMOC variability, we report substantial variations in North Atlantic deepocean heat content with trends of up to 0.7×1022 J decade-1 that are of the order of observed changes over the last decade and consistent with the reduced GMT warming trend over this period. Although these temperature anomalies are largely density-compensated by salinity changes, we find a robust negative correlation between the AMOC and North Atlantic deep-ocean density with density lagging the AMOC by 5 to 11 yr in most models. While this would in principle allow for a self-sustained oscillatory behavior of the coupled AMOC-deep-ocean system, our results are inconclusive about the role of this feedback in the model ensemble. [ABSTRACT FROM AUTHOR]

Soil organic matter (SOM) is the largest store of organic carbon (C) in the biosphere, but still the turnover of SOM is incompletely understood and not well described in global C cycle models. Here we use the Community Land Model (CLM) and compare the out- put for soil organic C (SOC) to estimates from a global data set. We also modify the assumptions about SOM turnover in two ways: (1) we assume distinct temperature sensitivities of SOC pools with different turnover time and (2) we assume a priming effect, such that decomposition rate of native SOM increases in response to a supply of fresh organic matter. The standard model predicted the global distribution of SOM reasonably well in most areas, but it failed to predict the very high stocks of SOM at high latitudes. It also predicted somewhat too much SOC in areas with high plant productivity, such as tropical rain forests and some mid-latitude areas. Assuming that the temperature sensitivity of SOC decomposition is dependent on the turnover rate of component pools reduced total SOC at equilibrium by a relatively small amount (<1% globally). Including a priming effect reduced total global SOC more (6.6% globally) and tended to decrease SOC most in areas with high plant input (tropical and temperate forests), which were also the areas where the unmodified model overpredicted SOC (by about 40 %). The model was then run with climate change prediction for the standard and modified versions. Future simulations showed that differences between the standard and modified versions were maintained in a future with climate change (4-6 and 23-47 Pg difference in soil carbon between standard simulation and the modified with temperature sensitivity and priming respectively). [ABSTRACT FROM AUTHOR]