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We re-analyze historical daily atmospheric temperature time series for investigating long-range correlation. Such a problem is attracting much attention due to the deep importance of assessing statistical dependence of atmospheric phenomena on climatic scales in the context of Climate modeling. In particular, we adopt Detrended Fluctuation Analysis (DFA), which is one of the most used techniques for detecting scale invariance in stationary signals contaminated by external non-stationary disturbances. A very standard application of this methodology seems to evidence persistence power-law exponents close to 0.65 on time scales greater than the meteorological one (>15 days). Nevertheless, more careful investigations put into evidence the local character of this exponent whose value decays progressively with scale. Our results show that the simple detection of approximately straight lines in a log–log plot cannot be considered as a signature of scale invariance and local scale features have to be explicitly investigated.

The role of vegetation cover within the processes that link land and atmosphere is of stringent interest for the correct modeling of Climate dynamics. Temporal and spatial correlation of the terrestrial coverage varies according to Climate and acts as a major forcing on it through changes in surface energy and water balance as well as in the carbon cycle. Recent studies have enhanced the actual and potential impact of this forcing on the radiative balance thus evidencing effects that are at least comparable to that due to all the anthropogenic greenhouse gases together. At now, observational studies on land cover dynamics are strongly in progress thanks to satellite data. The availability of continuous observations of the land surface can allow us to understand the correlation structure, both in time and in space, that characterizes the land cover activity. Satellites provide time series of photosynthetic activity measures that can be regarded as a succession of observations of a two-dimensional scalar field. We exploited the paradigm of fluctuating surfaces as a mechanic analogue for our problem. To capture vegetation cover characteristic time-scales, persistence properties were evaluated by analysing annual maps of NDVI-AVHRR time series and persistence probability was estimated by using the sing-time distribution methodology. The analysis performed for ecoregions of Italian and Greek territories evidenced signatures of short range persistence with characteristic time scales that depend on land cover, climate, and anthropic activities. Our results confirm that such an approach can provide a useful parameterisation for including vegetation into climate models as a dynamical component.

In this journal, Gerhard Gerlich and Ralf D. Tscheuschner claim to have falsified the existence of an atmospheric greenhouse effect.¹ Here, we show that their methods, logic, and conclusions are in error. Their most significant errors include trying to apply the Clausius statement of the Second Law of Thermodynamics to only one side of a heat transfer process rather than the entire process, and systematically ignoring most non-radiative heat flows applicable to the Earth's surface and atmosphere. They claim that radiative heat transfer from a colder atmosphere to a warmer surface is forbidden, ignoring the larger transfer in the other direction which makes the complete process allowed. Further, by ignoring heat capacity and non-radiative heat flows, they claim that radiative balance requires that the surface cool by 100 K or more at night, an obvious absurdity induced by an unphysical assumption. This comment concentrates on these two major points, while also taking note of some of Gerlich and Tscheuschner's other errors and misunderstandings.

In this work we propose a method that exploits the feedback between empirical and theoretical knowledge of a complex macroscopic system in order to build a nonlinear model. We apply the method to the monthly earth's mean surface temperature time series. The problems of contamination and stationarity are considered noting the importance of observation and modeling scales. We construct a dynamical system of ordinary differential equations where the vector field relating the relevant degrees of freedom and their variations in time is expressed in terms of a polynomial base orthonormal to the measure associated to the time series under study. The optimal size of the model and the values of its parameters are estimated with the principle of minimum description length and the Adams–Molton predictor–corrector method. This procedure is self-consistent because it does not use any external parameter or assumption. We then present a first approach to find the closest chaotic dynamical system corresponding to the earth's mean surface temperature and compare it with scale consistent theoretical or phenomenological models of the lower atmosphere. This comparison allows us to obtain an explicit functional form of the heat capacity of the earth's surface as a function of the earth's mean surface temperature.

Detrended fluctuation analysis (DFA) is used to investigate correlations between the monthly average of the maximum daily temperatures for different locations in the continental United States and the different climates these locations have. When we plot the scaling exponents obtained from the DFA versus the standard deviation of the temperature fluctuations, we observe crowding of data points belonging to the same climates. Thus, we conclude that by observing the long-time trends in the fluctuations of temperature it would be possible to distinguish between different climates.

In the current era, entire global economies are transitioning to sustainable development because of global warming and climate change. Due to turbulence in environmental issues such as weather shocks, climate change and basic infrastructure and industrial planning, many countries are changing their approach and taking green steps. This paper assesses sustainable finance in India and the ways in which India can mitigate climate changing risk toward zero carbon policy and supporting SDGs 2030. It talks about the physical and transitional climate risks in India like surface temperature, heat wave concourse, etc., and provides a comprehensive analysis of how the corporate sector is imparting its role in sustainable nature through corporate social responsibility (CSR). India is an emerging economy where energy is an essential component. This study analyzes about supply of energy and how India is shifting from traditional energy sources to renewal energy sources.

Thus, the objective of this study is to focus on the initiatives taken by the Indian government for sustainable finance through green bond policy at national and international platforms using the Panchamrit framework adopted by India thereby focusing on India’s sustainable policy support for SDGs 2030. Also, this research proposes numerous recommendations for future sustainable finance research in the context to India, which includes developing and diffusing innovative sustainable financing instruments, magnifying, and managing the profitability and returns of sustainable financing, making sustainable finance more sustainable, and leveraging the power of new-age technologies for sustainable finance.

Although the dramatic increase in computational power, a complete description of the Earth's climate by means of solutions of the equations of motion is far from being achieved. Most of the problems arise because the solutions depend on the second order effects of the dynamic and thermodynamic instability processes that plague the system. These instabilities are such that the observed behavior strongly departs from the response of the atmosphere to the forcing associated with the energy input. In illustrating the nature of the problem, we shall discuss the Atmospheric General Circulation, i.e. the circulation obtained by averaging the atmospheric motion along the longitude. We will show, by considering both the observed motion and some theoretical models, that the solution requires the parameterization of the momentum and heat fluxes associated with the baroclinic instability of the full three dimensional field. We will discuss how the parameterizations strongly depend on the detailed nature of the external parameters. As a conclusion, some speculations on the nature of the closure needed for this problem will be offered.

Cycles of glaciation with an average period of ~100 kyr are mediated by impacts of cometary bolides. Ice-age conditions are dry and dusty with low rates of precipitation. Comets in the mass range 10¹⁵–10¹⁶ g impacting the oceans could release enough water vapour into the atmosphere to enhance a depleted greenhouse effect. The energy deposited in the oceans would also warm the surface layers, thus starting up an evaporation-precipitation cycle which ushers in warmer interglacial interludes. The latter have neutral stability and are necessarily short-lived, eventually drifting back to glacial conditions on timescales of ~10 kyr.