Improving a tree-ring reconstruction from west-central Scandinavia: 900?years of warm-season temperatures

Dendroclimatological sampling of Scots pine (Pinus sylvestris L.) has been made in the province of J?mtland, in the west-central Scandinavian mountains, since the 1970s. The tree-ring width (TRW) chronology spans several thousand years and has been used to reconstruct June?CAugust temperatures back to 1632 bc. A maximum latewood density (MXD) dataset, covering the period ad 1107?C1827 (with gap 1292?C1315) was presented in the 1980s by Fritz Schweingruber. Here we combine these historical MXD data with recently collected MXD data covering ad 1292?C2006 into a single reconstruction of April?CSeptember temperatures for the period ad 1107?C2006. Regional curve standardization (RCS) provides more low-frequency variability than ??non-RCS?? and stronger correlation with local seasonal temperatures (51% variance explained). The MXD chronology shows a stronger relationship with temperatures than the TRW data, but the two chronologies show similar multi-decadal variations back to ad 1500. According to the MXD chronology, the period since ad 1930 and around ad 1150?C1200 were the warmest during the last 900?years. Due to large uncertainties in the early part of the combined MXD chronology, it is not possible to conclude which period was the warmest. More sampling of trees growing near the tree-line is needed to further improve the MXD chronology.     

COSMO-CLM2: a new version of the COSMO-CLM model coupled to the Community Land Model

This study presents an evaluation of a new biosphere-atmosphere Regional Climate Model. COSMO-CLM² results from the coupling between the non-hydrostatic atmospheric model COSMO-CLM version 4.0 and the Community Land Model version 3.5 (CLM3.5). In this coupling, CLM3.5 replaces a simpler land surface parameterization (TERRA_ML) used in the standard COSMO-CLM. Compared to TERRA_ML, CLM3.5 comprises a more complete representation of land surface processes including hydrology, biogeophysics, biogeochemistry and vegetation dynamics. Historical climate simulations over Europe with COSMO-CLM and with the new COSMO-CLM² are evaluated against various data products. The simulated climate is found to be substantially affected by the coupling with CLM3.5, particularly in summer. Radiation fluxes as well as turbulent fluxes at the surface are found to be more realistically represented in COSMO-CLM². This subsequently leads to improvements of several aspects of the simulated climate (cloud cover, surface temperature and precipitation). We show that a better partitioning of turbulent fluxes is the central factor allowing for the better performances of COSMO-CLM² over COSMO-CLM. Despite these improvements, some model deficiencies still remain, most notably a substantial underestimation of surface net shortwave radiation. Overall, these results highlight the importance of land surface processes in shaping the European climate and the benefit of using an advanced land surface model for regional climate simulations.     

Analysis of extreme precipitation characteristics in low mountain areas based on three-dimensional copulas—taking Kuandian County as an example

Rainfall in New South Wales (NSW), located in the southeast of the Australian continent, is known to be influenced by four major climate drivers: the El Niño/Southern Oscillation (ENSO), the Interdecadal Pacific Oscillation (IPO), the Southern Annular Mode (SAM) and the Indian Ocean Dipole (IOD). Many studies have shown the influences of ENSO, IPO modulation, SAM and IOD on rainfall in Australia and on southeast Australia in particular. However, only limited work has been undertaken using a multiple regression framework to examine the extent of the combined effect of these climate drivers on rainfall. This paper analysed the role of these combined climate drivers and their interaction on the rainfall in NSW using Bayesian Model Averaging (BMA) to account for model uncertainty by considering each of the linear models across the whole model space which is equal to the set of all possible combinations of predictors to find the model posterior probabilities and their expected predictor coefficients. Using BMA for linear regression models, we are able to corroborate and confirm the results from many previous studies. In addition, the method gives the ranking order of importance and the probability of the association of each of the climate drivers and their interaction on the rainfall at a site. The ability to quantify the relative contribution of the climate drivers offers the key to understand the complex interaction of drivers on rainfall, or lack of rainfall in a region, such as the three big droughts in southeastern Australia which have been the subject of discussion and debate recently on their causes.     

Validating the dynamic downscaling ability of WRF for East Asian summer climate

This work aims, as a first step, to analyze rainfall variability in Northern Algeria, in particular extreme events, during the period from 1940 to 2010. Analysis of annual rainfall shows that stations in the northwest record a significant decrease in rainfall since the 1970s. Frequencies of rainy days for each percentile (5th, 10th, 25th, 50th, 75th, 90th, 95th, and 99th) and each rainfall interval class (1–5, 5–10, 10–20, 20–50, and ≥50 mm) do not show a significant change in the evolution of daily rainfall. The Tenes station is the only one to show a significant decrease in the frequency of rainy days up to the 75th percentile and for the 10–20-mm interval class. There is no significant change in the temporal evolution of extreme events in the 90th, 95th, and 99th percentiles. The relationships between rainfall variability and general atmospheric circulation indices for interannual and extreme event variability are moderately influenced by the El Niño-Southern Oscillation and Mediterranean Oscillation. Significant correlations are observed between the Southern Oscillation Index and annual rainfall in the northwestern part of the study area, which is likely linked with the decrease in rainfall in this region. Seasonal rainfall in Northern Algeria is affected by the Mediterranean Oscillation and North Atlantic Oscillation in the west. The ENSEMBLES regional climate models (RCMs) are assessed using the bias method to test their ability to reproduce rainfall variability at different time scales. The Centre National de Recherches Météorologiques (CNRM), Czech Hydrometeorological Institute (CHMI), Eidgenössische Technische Hochschule Zürich (ETHZ), and Forschungszentrum Geesthacht (GKSS) models yield the least biased results.     

Summer temperature variability across four urban neighborhoods in Knoxville,Tennessee, USA

The urban heat island (UHI) is a well-documented effect of urbanization on local climate, identified by higher temperatures compared to surrounding areas, especially at night and during the warm season. The details of a UHI are city-specific, and microclimates may even exist within a given city. Thus, investigating the spatiotemporal variability of a city’s UHI is an ongoing and critical research need. We deploy ten weather stations across Knoxville, Tennessee, to analyze the city’s UHI and its differential impacts across urban neighborhoods: two each in four neighborhoods, one in more dense tree cover and one in less dense tree cover, and one each in downtown Knoxville and Ijams Nature Center that serve as control locations. Three months of temperature data (beginning 2 July 2014) are analyzed using paired-sample t tests and a three-way analysis of variance. Major findings include the following: (1) Within a given neighborhood, tree cover helps negate daytime heat (resulting in up to 1.19 ^°C lower maximum temperature), but does not have as large of an influence on minimum temperature; (2) largest temperature differences between neighborhoods occur during the day (0.38–1.16 ^°C difference), but larger differences between neighborhoods and the downtown control occur at night (1.04–1.88 ^°C difference); (3) presiding weather (i.e., air mass type) has a significant, consistent impact on the temperature in a given city, and lacks the differential impacts found at a larger-scale in previous studies; (4) distance from city center does not impact temperature as much as land use factors. This is a preliminary step towards informing local planning with a scientific understanding of how mitigation strategies may help minimize the UHI and reduce the effects of extreme weather on public health and well-being.     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Past connections and present similarities in slave ownership and fossil fuel usage

The first part of the paper demonstrates the connection between the abolition of slavery and the Industrial Revolution: steam power changed the perception of labour; new techniques facilitated diffusion of pro-abolition pamphlets; fewer threats to basic existence resulting from industrial advances fostered sensibilities and moral standards toward abolitionism; and, through industrial development, the North grasped victory in the American Civil War. The second part presents similarities between societies in the past that have used slave labour and those in the present that use fossil fuels. It argues that slaves and fossil-fuelled machines play(ed) similar economic and social roles: both slave societies and developed countries externalise(d) labour and both slaves and modern machines free(d) their owners from daily chores. Consequently, we are as dependent on fossil fuels as slave societies were dependent on bonded labour. It also suggests that, in differing ways, suffering resulting (directly) from slavery and (indirectly) from the excessive burning of fossil fuels are now morally comparable. When we emit carbon dioxide at a rate that exceeds what the ecosystem can absorb, when we deplete non-renewable resources, we indirectly cause suffering to other human beings. Similarly, cheap oil facilitates imports of goods from countries with little social protection and hence help externalise oppression. The conclusion draws on the lessons which may be learned by Climate Change campaigners from the campaigns to abolish slavery: environmental apathy can be opposed effectively if we learn from what worked in the fight against this inhuman institution.     

Physical and economic bias in climate change research: a scientometric study of IPCC Third Assessment Report

This study demonstrates that IPCC Third Assessment Report is strongly dominated by Natural sciences, especially the Earth sciences. The Social sciences are dominated by Economics. The IPCC assessment also results in the separation of the Earth, Biological and Social sciences. The integration that occurs is mainly between closely related scientific fields. The research community consequently imposes a physical and economic bias and a separation of scientific fields that the IPCC reproduces in the policy sphere. It is argued that this physical and economic bias distorts a comprehensive understanding of climate change and that the weak integration of scientific fields hinders climate change from being fully addressed as an integral environmental and social problem. If climate change is to be understood, evaluated and responded to in its fullness, the IPCC must broaden its knowledge base and challenge the anthropocentric worldview that places humans outside of nature.     

Drivers of long-term precipitation and runoff variability in the southeastern USA

The hydroclimatology of the southeastern USA (AL, GA, NC, SC, and TN) is analyzed from a holistic perspective, including multiple climate drivers. Monthly precipitation modeled by the PRISM group and runoff data (1952–2011) from 18 basins are analyzed using a single-field based principal component’s analysis. Results indicate that the Atlantic Multidecadal Oscillation and El Niño-Southern Oscillation are the main atmospheric drivers of hydroclimate variability in the region, sometimes operating at several months’ lag. Their influence is the strongest in the fall through spring, which corresponds with the dry season in the southern parts of the study area thereby increasing pressure on already limited water resources. The Arctic Oscillation, North Atlantic Oscillation, and Pacific-North American patterns vary on shorter-term bases, and also show a significant, but temporally more sporadic influence. Insight is also brought to the ongoing discussion, confirming the disassociation of the Arctic and North Atlantic Oscillation. Findings can be used in water resources forecasting, giving an indication of expected water volumes several months ahead.     

Drought analysis in the Tons River Basin,India during 1969-2008

The primary focus of this study is the analysis of droughts in the Tons River Basin during the period 1969–2008. Precipitation data observed at four gauging stations are used to identify drought over the study area. The event of drought is derived from the standardized precipitation index (SPI) on a 3-month scale. Our results indicated that severe drought occurred in the Allahabad, Rewa, and Satna stations in the years 1973 and 1979. The droughts in this region had occurred mainly due to erratic behavior in monsoons, especially due to long breaks between monsoons. During the drought years, the deficiency of the annual rainfall in the analysis of annual rainfall departure had varied from ?26% in 1976 to ?60% in 1973 at Allahabad station in the basin. The maximum deficiency of annual and seasonal rainfall recorded in the basin is 60%. The maximum seasonal rainfall departure observed in the basin is in the order of ?60% at Allahabad station in 1973, while maximum annual rainfall departure had been recorded as ?60% during 1979 at the Satna station. Extreme dry events (z score <?2) were detected during July, August, and September. Moreover, severe dry events were observed in August, September, and October. The drought conditions in the Tons River Basin are dominantly driven by total rainfall throughout the period between June and November.