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The article discusses a research about the use of tree rings in providing information about the amount of snow or rainfall. It references a study by Kerstin Treydte and colleagues published within the issue. They concluded that the latter part of the twentieth century was by far the wettest period, suggesting that humans may play a role in the climate of the world.

Tropical glaciers are extremely sensitive to a warming climate. In this paper, the evolution of the remaining tropical glaciers in Australasia (Irian Jaya, Indonesia) during the period 1988-2015 was quantified. Landsat series images, a digital elevation model from SRTM, and previously published data were used. Estimated total glacier area in 1988, 1993, 1997 and 2004 was 3.85 km2±0.13 km2, 3.01 km2±0.08 km2, 2.49 km2±0.07 km2 and 1.725 km2 ±0.042 km2, respectively. Only 0.58 km2±0.016 km2 glacierized area remained in 2015 in Puncak Jaya, which is about 84.9% loss in just 27 years. If this rate continued, the remaining tropical glaciers in Australasia would disappear in the 2020s. Timeseries analysis of climate variables showed significant positive trends in air temperature (0.009°C per year) and relative humidity (0.43% per year) but no considerable tendency was observed for precipitation. Warming climate together with mining activities would accelerate loss of glacier coverage in this region. [ABSTRACT FROM AUTHOR]

Meteorological and oceanographic data from ships of opportunity are the largest contributor to the world’s ocean surface database and thus are extensively used to estimate the change in climatic properties over the world’s oceans during the previous 150 years. The importance of these data for climate change studies underscores the need to fully understand the error associated with averages of these data. The sampling error problem is especially acute for ship data due to the fact that ships are moving platforms and, thus, report observations from constantly varying locations with time. This paper develops a theoretical framework for assessing the averaged sampling error associated with monthly, 1°×1° latitude-longitude box averaged ship data. It should be noted that the time-space distribution of ships within the averaging domain strongly affects the sampling error. This is shown in our derivation. The framework developed here can be used to improve upon existing methods for estimating the sampling error associated with three-dimensional box averages of meteorological and oceanographic data obtained from ship records. The framework is complimentary to existing methods of assessing biases and random error due to instrumentation, recording, etc. It is demonstrated mathematically that the uncertainty due to incomplete sampling is primarily a trade off between of the number of observations and their relative locations within the box as well as the inherent time-space correlation structure of the variable of interest. This work differs from other studies in that the three-dimensional interdependence of data is taken into account in deriving an expression for the sampling error. [ABSTRACT FROM AUTHOR]

This paper discusses the effects of vegetation cover and soil parameters on the climate change projections of a regional climate model over the Arctic domain. Different setups of the land surface model of the regional climate model HIRHAM were realized to analyze differences in the atmospheric circulation caused by (1) the incorporation of freezing/thawing of soil moisture, (2) the consideration of top organic soil horizons typical for the Arctic and (3) a vegetation shift due to a changing climate. The largest direct thermal effect in 2 m air temperature was found for the vegetation shift, which ranged between −1.5 K and 3 K. The inclusion of a freeze/thaw scheme for soil moisture shows equally large sensitivities in spring over cool areas with high soil moisture content. Although the sensitivity signal in 2 m air temperature for the experiments differs in amplitude, all experiments show changes in mean sea level pressure (mslp) and geopotential height (z) throughout the troposphere of similar magnitude (mslp: −2 hPa to 1.5 hPa, z: −15 gpm to 5 gpm). This points to the importance of dynamical feedbacks within the atmosphere-land system. Land and soil processes have a distinct remote influence on large scale atmospheric circulation patterns in addition to their direct, regional effects. The assessment of induced uncertainties due to the changed implementations of land surface processes discussed in this study demonstrates the need to take all those processes for future Arctic climate projections into account, and demonstrates a clear need to include similar implementations in regional and global climate models. [ABSTRACT FROM AUTHOR]

In this paper, we have provided an overview of cosmic ray effects on terrestrial processes such as electrical properties, global electric circuit, lightning, cloud formation, cloud coverage, atmospheric temperature, space weather phenomena, climate, etc. It is suggested that cosmic rays control short-term and long-term variations in climate. There are many basic phenomena which need further study and require new and long-term data set. Some of these have been pointed out. [ABSTRACT FROM AUTHOR]

Because of the long-term nature of the climate problem, technological advances are often seen as an important component of any solution. However, when considering the potential for technology to help solve the climate problem, two market failures exist which lead to under investment in climate-friendly R&D: environmental externalities and the public goods nature of new knowledge. As a result, government subsidies to climate-friendly R&D projects are often proposed as part of a policy solution. Using the ENTICE model, I analyze the effectiveness of such subsidies, both with and without other climate policies, such as a carbon tax. While R&D subsidies do lead to significant increases in climate-friendly R&D, this R&D has little impact on the climate itself. Subsidies address the problem of knowledge as a public good, but they do not address the environmental externality, and thus offer no additional incentive to adopt new technologies. Moreover, high opportunity costs to R&D limit the potential role that subsidies can play. While R&D subsidies can improve efficiency, policies that directly affect the environmental externality have a much larger impact on both atmospheric temperature and economic welfare. [ABSTRACT FROM AUTHOR]

In order to investigate Last Glacial Maximum and future climate, we 'precalibrate' the intermediate complexity model GENIE-1 by applying a rejection sampling approach to deterministic emulations of the model. We develop ~1,000 parameter sets which reproduce the main features of modern climate, but not precise observations. This allows a wide range of large-scale feedback response strengths which generally encompass the range of GCM behaviour. We build a deterministic emulator of climate sensitivity and quantify the contributions of atmospheric (±0.93°C, 1 σ) vegetation (±0.32°C), ocean (±0.24°C) and sea-ice (±0.14°C) parameterisations to the total uncertainty. We then perform an LGM-constrained Bayesian calibration, incorporating data-driven priors and formally accounting for structural error. We estimate climate sensitivity as likely (66% confidence) to lie in the range 2.6-4.4°C, with a peak probability at 3.6°C. We estimate LGM cooling likely to lie in the range 5.3-7.5°C, with a peak probability at 6.2°C. In addition to estimates of global temperature change, we apply our ensembles to derive LGM and 2xCO probability distributions for land carbon storage, Atlantic overturning and sea-ice coverage. Notably, under 2xCO we calculate a probability of 37% that equilibrium terrestrial carbon storage is reduced from modern values, so the land sink has become a net source of atmospheric CO. [ABSTRACT FROM AUTHOR]

To characterize observed global and hemispheric temperatures, previous studies have proposed two types of data-generating processes, namely, random walk and trend-stationary, offering contrasting views regarding how the climate system works. Here we present an analysis of the time series properties of global and hemispheric temperatures using modern econometric techniques. Results show that: The temperature series can be better described as trend-stationary processes with a one-time permanent shock which cannot be interpreted as part of the natural variability; climate change has affected the mean of the processes but not their variability; it has manifested in two stages in global and Northern Hemisphere temperatures during the last century, while a second stage is yet possible in the Southern Hemisphere; in terms of Article 2 of the Framework Convention on Climate Change it can be argued that significant (dangerous) anthropogenic interference with the climate system has already occurred. [ABSTRACT FROM AUTHOR]

Anomalies of mean air temperature of 12 consecutive months were detected recently at a number of spatial scales: from local via national and continental, to hemispheric. At all these spatial scales, pre-2007 records were exceeded by considerable margins. The recent rise in the mean temperature of 12 consecutive months at several scales has remained largely unnoticed, because the 12-month means are seldom analyzed. Broad attention is typically focused on monthly, seasonal and annual temperatures. Analysis of shifted 12-month periods helps spot peculiar 12-month episodes with remarkable temperature anomalies that do not coincide with a calendar year. Introducing 12-month running mean temperatures into the global warming debate can prove useful. [ABSTRACT FROM AUTHOR]

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO2 concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. [ABSTRACT FROM AUTHOR]

A number of reconstructions of millennial-scale climate variability have been carried out in order to understand patterns of natural climate variability, on decade to century timescales, and the role of anthropogenic forcing. These reconstructions have mainly used tree-ring data and other data sets of annual to decadal resolution. Lake and ocean sediments have a lower time resolution, but provide climate information at multicentennial timescales that may not be captured by tree-ring data. Here we reconstruct Northern Hemisphere temperatures for the past 2,000 years by combining low-resolution proxies with tree-ring data, using a wavelet transform technique to achieve timescale-dependent processing of the data. Our reconstruction shows larger multicentennial variability than most previous multi-proxy reconstructions, but agrees well with temperatures reconstructed from borehole measurements and with temperatures obtained with a general circulation model. According to our reconstruction, high temperatures-similar to those observed in the twentieth century before 1990-occurred around ad 1000 to 1100, and minimum temperatures that are about 0.7K below the average of 1961-90 occurred around ad 1600. This large natural variability in the past suggests an important role of natural multicentennial variability that is likely to continue. [ABSTRACT FROM AUTHOR]

In this article, the author discusses on how to log local temperatures. He advises that climate community should work with each other for creating a clean and open repository of detailed temperature data. He says that the projects that are working for creating the climate data sets on smaller scales of time and space do not cover the whole world and are operating only in specific regions. The author further believes that community must collect temperature records throughout the world.