Global Average Surface Air Temperature Research Articles

Urbanization Heat Flux Modeling Confirms It Is a Likely Cause of Significant Global Warming: Urbanization Mitigation Requirements

Recent ground-based measurements find the magnitude of the urbanization effect on the global average annual mean surface air temperature corresponds to an urbanization contribution of 12.7%. It is important to provide modeling to help understand these results as there are conflicting concerns. This study models the global warming contribution that urbanization heat fluxes (UHF) can make due to anthropogenic heat release (AHR), and solar heating of impermeable surface areas (ISAs), with additional secondary effects. Results help explain and support ground-based observations. Climate models typically omit anthropogenic heat release (AHR) as warming estimates are below 1%. In agreement, the baseline assessment in this paper has similar findings. However, in this study, the methods of climate amplification estimates (MCAE) with data-aided physics-based amplification models are used. When the MCAE are applied at the global and microclimate levels that consider greenhouse gases (GHGs), feedback, and other secondary effects; the results show that AHR fluxes can amplify, increasing to have an estimated global warming (GW) influence of 6.5% from 1950 to 2022 yielding a 0.9% decade−1 increase. This increasing rate due to energy consumption is found as anticipated to be reasonably correlated to the increasing population growth rate over this time. Furthermore, using the MCAEs, this paper studies heat fluxes assessment due to solar heating of unshaded impermeable surfaces including likely secondary amplification effects. Impermeable surface areas (ISAs) such as asphalt roads, roofs, and building sides have been reported with high land surface contact temperatures (LSCTs) relative to non-ISAs and significantly found to contribute to urbanization warming. Results indicate that high-temperature unshaded impermeable surfaces (including building sides) are estimated to average around 10–11 °C above the earth’s ambient temperature of 14.5 °C (showing albedo ISA estimates between 0.133 and 0.115 respectively); the ISA heat fluxes with secondary effects are estimated to have about a GW influence of 6.5%. This is broken down with average contributions of 4.0% from urban ISAs and 2.5% from rural ISA heat fluxes. Asphalt road ISA heat fluxes are estimated to have about a 1.1% global warming influence. Then the total UHF effect from ISAs and AHR with secondary effects is assessed in modeling to yield a combined average GW influence of 13% helping to confirm ground-based measurement results. Several key adjustment values were used for shading, cloud coverage, and rural-to-urban ISA ratios. Microclimate GHGs and related water vapor feedback (WVF) were assessed to increase urban warming by about 50%. As well an assessment of water vapor and radiation increases from UHF is provided. This study also shows the need to incorporate urbanization heat fluxes with secondary effects into climate models and indicates the necessity for Paris Agreement urban heat flux mitigation goals. Results also found that given average climate conditions, it is possible to mitigate much of the UHI effect with an albedo increase of 0.1 that is anticipated to lower the average impermeable surface temperatures by about 9 °C. Studies show this can be accomplished with cost-effective cool roads and roofs. Although roads are only estimated to occupy 14% of ISAs, changing roads from asphalt to concrete-type surfaces would improve reflectivity by about a factor of 5 and is estimated to mitigate about 5.5% of global warming. Unfortunately, the current overuse of black asphalt on pavements and roofs is highly dangerous to our environment causing UHI increases in heatwaves, excessive temperatures, and global warming issues and should be banned. Asphalt usage also reduces opportunities for solar geoengineering of urbanization.

The longtime global climatic consequences modeling of the Chicxulub asteroid impact event

Studies indicate the mass death of a significant number of biological groups on Earth, in particular - dinosaurs, at the end of the Cretaceous period 66 million years ago. Currently, there are two main theories: large-scale volcanic eruptions and the asteroid impact that formed the Chicxulub crater (Mexico). The production of sulfur-containing gases from the Earth’s surface layers vapors during impact is considered a main source of climatic effects, as they form stratospheric sulfate aerosols that block sunlight and thus cool the Earth’s atmosphere and interfere with photosynthesis. It is presented an application of the 3-D coupled global hydrodynamic climate model of intermediate complexity, including ocean model, sea ice evolution model and energy - moisture balance atmosphere model to study this asteroid impact effects on the Earth’s climate. The model continents and ocean depths distribution corresponds to Cretaceous period. A series of calculations with different residence times and deposition times of the stratosphere aerosol have been carried out. It was found that, depending on the stratosphere aerosol time parameters, the global annual average surface air temperature decreased by 18°C - 27°C, remained below zero for 4 - 30 years, and a recovery time of more than 30 years was observed.

Future projection of greenhouse gas emissions due to permafrost degradation using a simple numerical scheme with a global land surface model

The Yedoma layer, a permafrost layer containing a massive amount of underground ice in the Arctic regions, is reported to be rapidly thawing. In this study, we develop the Permafrost Degradation and Greenhouse gasses Emission Model (PDGEM), which describes the thawing of the Arctic permafrost including the Yedoma layer due to climate change and the greenhouse gas (GHG) emissions. The PDGEM includes the processes by which high-concentration GHGs (CO2 and CH4) contained in the pores of the Yedoma layer are released directly by dynamic degradation, as well as the processes by which GHGs are released by the decomposition of organic matter in the Yedoma layer and other permafrost. Our model simulations show that the total GHG emissions from permafrost degradation in the RCP8.5 scenario was estimated to be 31-63 PgC for CO2 and 1261-2821 TgCH4 for CH4 (68th percentile of the perturbed model simulations, corresponding to a global average surface air temperature change of 0.05–0.11 °C), and 14-28 PgC for CO2 and 618-1341 TgCH4 for CH4 (0.03–0.07 °C) in the RCP2.6 scenario. GHG emissions resulting from the dynamic degradation of the Yedoma layer were estimated to be less than 1% of the total emissions from the permafrost in both scenarios, possibly because of the small area ratio of the Yedoma layer. An advantage of PDGEM is that geographical distributions of GHG emissions can be estimated by combining a state-of-the-art land surface model featuring detailed physical processes with a GHG release model using a simple scheme, enabling us to consider a broad range of uncertainty regarding model parameters. In regions with large GHG emissions due to permafrost thawing, it may be possible to help reduce GHG emissions by taking measures such as restraining land development.

Climate networks suggest Rossby-waves–related CO2 concentrations to surface air temperature

The role of carbon dioxide (CO2) on global warming gained wide attention. Previous researches mainly focus on relationship between global average CO2 concentrations and surface air temperature (SAT). Carbon satellites have proven that CO2 concentrations have non-uniform spatio-temporal distributions. The relation between CO2 concentrations from satellite observations and SAT is seldom reported. Climate network approaches have been successful to uncover topology structure and dynamics in the climate system. Here, we construct CO2 concentrations network and SAT network based on the climate network approaches. By comparing the similarity of the properties between CO2 concentrations network and SAT network, their relation has been investigated. We show that negative and positive links in CO2 network have a strong correlation with that in the SAT network. These statistical structures yield a clear association with the pattern of Rossby waves. It is shown that the peaks of phase speeds associated with significant positive and negative weight links are similar, and are arranged in the group velocities of Rossby waves. Further analysis shows their strong correlations and similarity spatial patterns if the equator regions are excluded. In addition, their teleconnections follow similar climate processes, where Rossby waves exhibit dominance in the Southern Hemisphere. The results demonstrate the similar network properties between CO2 and SAT can be partly related to the function of Rossby waves. Our work provides a new perspective with which to understand the relation between CO2 concentrations and SAT, as well as climate system.

The Role of Industrial Carbon Capture and Storage (Ccs) in Emission Mitigation

Carbon capture and storage (CCS) technology is an important option in the portfolio of emission mitigation technologies in scenarios that lead to deep reductions in greenhouse gas (GHG) emissions consistent with limiting increases in global average surface air temperature to 2 degrees Celsius (2C). Industrial CCS applications are more challenging to analyze than CCS in the power sector -- mainly due to the vast heterogeneity in industrial and fuel processes. Our study focuses on the cement industry and provides the estimated costs associated with several CCS options: coal-fired post-combustion capture (PCC), natural gas-fired PCC, and Cryogenic Carbon Capture (CCC). We explore regional cost estimates with variations in costs of capital and fuels to provide a basis for regional and global projections of industrial CCS deployment. We offer a methodology for incorporating the CCS cost information into energy-economic and integrated assessment models. Our methodology can be applied to other applications of CCS in the industrial sector. We illustrate our method by introducing the industrial CCS options into the MIT EPPA model, a global energy-economic model that provides a basis for the analysis of long-term energy deployment, and we discuss different scenarios for industrial CCS deployment in different parts of the world. We tested in the EPPA model the potential for industrial CCS under the assumptions that CCS is the only mitigation option for deep GHG emission reduction in industry and that negative emission options are not available for other sectors of the economy. Overall, industrial CCS enables the continued use of energy-intensive goods with large reductions in global and sectoral emissions. We find that in scenarios with stringent climate policy, CCS in the industry sector is a key mitigation option, and our approach provides a path to projecting the deployment of industrial CCS across industries and regions.

Did Smoke From City Fires in World War II Cause Global Cooling?

AbstractBetween 3 February and 9 August 1945, an area of 461 km2 in 69 Japanese cities, including Hiroshima and Nagasaki, was burned during the U.S. B‐29 Superfortress air raids. In the previous 5 years, 205 km2 in German cities were destroyed, so the smoke that was generated was spread out over a much longer period of time than that from Japan in 1945. Observations of solar irradiance show reductions consistent with the hypothesis that smoke was injected into the stratosphere by the city fires. Historical simulations from the Coupled Model Intercomparison Project 5, with no smoke in their forcing, showed no postwar cooling. Global average surface air temperature observations during and following World War II are problematic, because of issues with measuring sea surface temperatures, but there were no large volcanic eruptions, El Niño, or La Niña during this period to confuse the record. Nevertheless, 1945 and 1946 global average land surface air temperatures were not significantly lower than the average for 1940–1944. Estimates of the amount of smoke generated by the fires are somewhat uncertain. Although the climate record is consistent with an expected 0.1–0.2 K cooling, because of multiple uncertainties in smoke injected to the stratosphere, solar radiation observations, and surface temperature observations, it is not possible to formally detect a cooling signal from World War II smoke.

Recently amplified arctic warming has contributed to a continual global warming trend

The existence and magnitude of the recently suggested global warming hiatus, or slowdown, have been strongly debated1–3. Although various physical processes4–8 have been examined to elucidate this phenomenon, the accuracy and completeness of observational data that comprise global average surface air temperature (SAT) datasets is a concern9,10. In particular, these datasets lack either complete geographic coverage or in situ observations over the Arctic, owing to the sparse observational network in this area 9 . As a consequence, the contribution of Arctic warming to global SAT changes may have been underestimated, leading to an uncertainty in the hiatus debate. Here, we constructed a new Arctic SAT dataset using the most recently updated global SATs 2 and a drifting buoys based Arctic SAT dataset 11 through employing the ‘data interpolating empirical orthogonal functions’ method 12 . Our estimate of global SAT rate of increase is around 0.112 °C per decade, instead of 0.05 °C per decade from IPCC AR5 1 , for 1998–2012. Analysis of this dataset shows that the amplified Arctic warming over the past decade has significantly contributed to a continual global warming trend, rather than a hiatus or slowdown.

Population and trends in the global mean temperature

The Fisher ideal index, developed to measure price inflation, is applied to define a population-weighted temperature trend. This method has the advantages that the trend is representative for the population distribution throughout the sample but without conflating the trend in the population distribution and the trend in the temperature. I show that the trend in the global area-weighted average surface air temperature is different in key details from the population-weighted trend. I extend the index to include urbanization and the urban heat island effect. This substantially changes the trend again. I further extend the index to include international migration, but this has a minor impact on the trend.

Comparisons of Time Series of Annual Mean Surface Air Temperature for China since the 1900s: Observations, Model Simulations, and Extended Reanalysis

Abstract Time series of global or regional average surface air temperature (SAT) are fundamental to climate change studies. A number of studies have developed several national and regional SAT series for China, but because of the diversity of the meteorological observational sites, the different quality control routines for processing the data, and the inconsistency of the statistical methods used, they differ in their long-term trends. This paper assesses the similarities and differences of the existing time series of the annual average SAT for China that are based upon historical meteorological observations since the 1900s. The results indicate that the China average is similar to the series for the Northern Hemisphere (NH) landmass, except that the initial warming of the NH series derived from the CRUTEM3/4 datasets, which represent global historical land surface air temperatures and near-surface air temperature anomalies over land, respectively, ends earlier (before the early 1940s) than in China’s series. A major difference among the existing China average time series is the 1940s warmth, a period when there were very few observations across the country because of World War II. The SAT anomalies for China during the 1930s to 1940s have been reduced by improved homogeneity assessment compared to previous estimates. The new improved time series is in better agreement with both the historical twentieth-century reanalysis data and the historical climate simulation of phase 5 of the Coupled Model Intercomparison Project (CMIP5) models. The new time series also shows the slowdown of the warming trend during the past 18 yr (1998–2015). The best estimate of a linear trend for increases in temperature with a 95% uncertainty range is 0.121° ± 0.009°C decade–1 for 1900–2015, indicating that the improved homogeneity assessment for China leads to a slightly greater trend than that based on raw data (0.107° ± 0.009°C decade–1).

What do historical temperature records tell us about natural variability in global temperature?

Global average surface air temperature can change when it is either ‘forced’ to change by factors such as increasing greenhouse gasses, or it can change on its own through ‘unforced’ natural cycles like El-Niño/La-Niña. In this paper we estimated the magnitude of unforced temperature variability using historical datasets rather than the more commonly used computer climate models. We used data recorded by thermometers back to the year 1880 as well as data from “nature’s thermometers” – things like tree rings, corals, and lake sediments – that give us clues of how temperature varied naturally from the year 1000 to 1850. We found that unforced natural temperature variability is large enough to have been responsible for the decade-to-decade changes in the rate of global warming seen over the 20th century. However, the total warming over the 20th century cannot be explained by unforced variability alone and it would not have been possible without the human-caused increase in greenhouse gasses. We also found that unforced temperature variability may be the driver behind the reduced rate of global warming experienced at the beginning of the 21st century.

Recent intensification of wind-driven circulation in the Pacific and the ongoing warming hiatus

The slowdown in global average surface warming has recently been linked to sea surface cooling in the eastern Pacific Ocean. This work shows that strengthening trade winds caused a reduction in the 2012 global average surface air temperature of 0.1–0.2 °C. This may account for much of the warming hiatus and is a result of increased subsurface ocean heat uptake.

Isoprene emission variability through the twentieth century

AbstractA biochemical model of isoprene emission embedded within a global chemistry‐climate simulation framework is applied to investigate the transient response to environmental change over the past century. In the model, the isoprene production is directly coupled to photosynthesis and depends on intercellular carbon dioxide concentration (CO2), atmospheric CO2, and canopy temperature. Sensitivity runs are performed to isolate the relative roles of individual global change drivers: CO2, physical climate, and anthropogenic land cover change (ALCC). Between 1880 and 2000, atmospheric CO2 increased by ~30% from 291 to 370 ppmv, global average surface air temperature increased by 0.7°C, and the crop cover fraction of vegetated land area more than doubled from 15 to 37%. Over the past century, isoprene emission has decreased globally by 20% from 534 to 449 Tg C/yr, while gross primary productivity has increased by 15% from 107 to 124 Pg C/yr mostly due to CO2 fertilization. In terms of individual drivers, the global isoprene source increased by 7% due to the atmospheric CO2 concentration rise (including the opposing effects of CO2 fertilization and CO2 inhibition), decreased by 22% due to ALCC, and increased by only 3% due to physical climate change. Thus, ALCC is the dominant driver of isoprene emission change. Modeled global isoprene emissions were higher in the preindustrial than in the present day. In the industrial era, isoprene emission change represents a human‐induced climate forcing, analogous to land use‐driven CO2 emission, not a climate feedback because temperature‐driven increase was a relatively weak driver of isoprene emission change from 1880 to 2000.

The impact of climate change on runoff in the southeastern Tibetan Plateau

The Tibetan Plateau (TP) is the “water tower of Asia” and strongly influences both the hydrology and climate of southern and eastern Asia. Exploring the impact of climate change on the runoff of TP rivers is critical to improve water resources management. However, thorough studies on the runoff response to climate change are seldom conducted on large TP river systems. To complement the current body of work, this study uses two rainfall–runoff models (SIMHYD and GR4J) to simulate the monthly and annual runoff across the Yarlung Tsangpo River (YTR) basin in the southeastern TP (i.e., upstream of the Brahmaputra) under historical (1962–2002) and future (up to approximately 2030) climate conditions. The future climate series are obtained by using 20 Global Climate Models (GCMs) outputs from the Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4) to reflect a 1 °C increase in the global average surface air temperature. The two rainfall–runoff models successfully simulate the historical runoff for the eight catchments in the YTR basins with median monthly runoff Nash–Sutcliffe Efficiencies (NSE) of 0.86 for SIMHYD and 0.83 for GR4J. The mean annual future precipitation and runoff across the region are projected to increase by most of the modeling results. The mean annual precipitation changes obtained from the 20 GCMs are −15%, 7% and 16% for the 10th percentile, median and 90th percentile of GCM outputs, respectively, and the corresponding changes in the simulated mean annual runoffs are −24%, 13% and 29% for the SIMHYD model outputs and −22%, 11% and 26% for the GR4J model outputs. The projected increase in the runoff at the median percentile mainly occurs in the middle reaches of the YTR and its two tributaries, the Lhasa River and the Nyangqu River, with a 12% increase in annual runoff that mainly occurs in the wet season from May to September. The present work is the first comprehensive study on the hydrological response to climate change covering the entire upstream area of the Brahmaputra, and the results found in this study are not only helpful for local water resource management but also for the lower reaches of the Brahmaputra.

Southern Ocean Sector Centennial Climate Variability and Recent Decadal Trends

Abstract Evidence is presented for the notion that some contribution to the recent decadal trends observed in the Southern Hemisphere, including the lack of a strong Southern Ocean surface warming, may have originated from longer-term internal centennial variability originating in the Southern Ocean. The existence of such centennial variability is supported by the instrumental sea surface temperatures (SSTs), a multimillennial reconstruction of Tasmanian summer temperatures from tree rings, and a millennial control integration of the Kiel Climate Model (KCM). The model variability was previously shown to be linked to changes in Weddell Sea deep convection. During phases of deep convection the surface Southern Ocean warms, the abyssal Southern Ocean cools, Antarctic sea ice extent retreats, and the low-level atmospheric circulation over the Southern Ocean weakens. After the halt of deep convection the surface Southern Ocean cools, the abyssal Southern Ocean warms, Antarctic sea ice expands, and the low-level atmospheric circulation over the Southern Ocean intensifies, consistent with what has been observed during the recent decades. A strong sensitivity of the time scale to model formulation is noted. In the KCM, the centennial variability is associated with global-average surface air temperature (SAT) changes of the order of a few tenths of a degree per century. The model results thus suggest that internal centennial variability originating in the Southern Ocean should be considered in addition to other internal variability and external forcing when discussing the climate of the twentieth century and projecting that of the twenty-first century.

Which Emissions to Reduce?

Climate Science![Figure][1] CREDIT: © SCUBAZOO/SUPERSTOCK/CORBIS A fierce debate is being waged about the relative merits of controlling the anthropogenic emissions of climate-affecting pollutants with long atmospheric lifetimes, such as carbon dioxide, and those with shorter atmospheric lifetimes, such as methane or black carbon. Both classes of compounds have substantial radiative impacts, and arguments about which is more important to reduce have been made for each. By using a sophisticated global model, Smith and Mizrahi examined the potential climate effects of a strategy to mitigate the short-lived climate-forcing agents methane and black carbon and concluded that the likely benefits of such an approach are much more modest than had been suggested recently. Even assuming the maximally feasible reductions in emissions over the next decades, the rise in global average surface air temperature by the year 2050 would be only about one-half of the previous best estimate. Thus, a policy of focusing on reducing emissions of short-lived climate forcers, attractive to many because of its rapid effect and possibly easier and less costly implementation, may not be the silver bullet some have hoped it might be. Proc. Natl. Acad. Sci. U.S.A. 110 , 10.1073/pnas.1308470110 (2013). [1]: pending:yes

The ACCESS coupled model: description, control climate and evaluation

4OASIS3.2–5 coupling framework. The primary goal of the ACCESS-CM development is to provide the Australian climate community with a new generation fully coupled climate model for climate research, and to participate in phase five of the Coupled Model Inter-comparison Project (CMIP5). This paper describes the ACCESS-CM framework and components, and presents the control climates from two versions of the ACCESS-CM, ACCESS1.0 and ACCESS1.3, together with some fields from the 20 th century historical experiments, as part of model evaluation. While sharing the same ocean sea-ice model (except different setups for a few parameters), ACCESS1.0 and ACCESS1.3 differ from each other in their atmospheric and land surface components: the former is configured with the UK Met Office HadGEM2 (r1.1) atmospheric physics and the Met Office Surface Exchange Scheme land surface model version 2, and the latter with atmospheric physics similar to the UK Met Office Global Atmosphere 1.0 includ ing modifications performed at CAWCR and the CSIRO Community Atmosphere Biosphere Land Exchange land surface model version 1.8. The global average annual mean surface air temperature across the 500-year preindustrial control integrations show a warming drift of 0.35 °C in ACCESS1.0 and 0.04 °C in ACCESS1.3. The overall skills of ACCESS-CM in simulating a set of key climatic fields both globally and over Australia significantly surpass those from the preceding CSIRO Mk3.5 model delivered to the previous coupled model inter-comparison. However, ACCESS-CM, like other CMIP5 models, has deficiencies in various as pects, and these are also discussed.

模拟增温和不同凋落物基质质量对凋落物分解速率的影响

采用凋落物分解袋法,研究了在土壤、水分相当的条件下模拟增温对红松(<em>Pinus koraiensis</em>)、蒙古栎(<em>Quercus mongolica</em>)及其混合凋落物分解的影响,以及在不同温度水平下,不同凋落物质量(两种单一凋落物和混合凋落物)的分解特性。利用碱式吸收法测量了凋落物分解累积释放CO₂动态。将N浓度和C/N率作为凋落物质量参数,用呼吸产生CO₂的积累值和凋落物质量损失率确定凋落物分解率。结果表明温度升高对单一凋落物和混合凋落物分解均有促进作用,在不同温度水平上,不同质量凋落物的分解特性有所差别,25 ℃和29 ℃条件下混合凋落物分解速率>蒙古栎单一凋落物>红松单一凋落物分解速率。然而,在31 ℃条件下混合凋落物与蒙古栎单一凋落物分解速率相差不大,二者均大于红松单一凋落物分解速率。;Litter decomposition is a fundamental process to ecosystem functioning being responsible of carbon and nutrient cycling. The decomposition of dead leaves depends on both biotic and abiotic factors. The combination of climate (e.g. mean annual temperature (MAT), mean annual precipitation (MAP), actual evapotranspiration, etc) and litter quality (N content, C/N ratio and lignin content) appeared to be the primary controllers of little decomposition. This is particularly true for temperature, which is inextricably linked to other environment parameters as a mutually confounding factor in terrestrial systems. Global average surface air temperature is predicted to increase 1.1-6.4 ℃ over this century. Climate warming is expected to cause species movements and extinctions, change the composition of communities and alter ecosystem functioning. As decomposition depends strongly on temperature, it is expected to be particularly sensitive to climate warming. However, it is still unclear how climate changes influence little decomposition. As global climate changes, it will become warmer and somewhat drier in forest ecosystems, in northeastern China. Changes in global warming and drying could affect forest distribution. The areas of tropical forests and subfrigid forests might increase and that of temperate forests and boreal coniferous forests might decrease, which might affect little quality by altering the structure and species of the original forest communities. The primary temperate forest in northeastern China is dominated by Korean pine (<em>Pinus koraiensis</em> Sieb.et Zucc.) mixed with deciduous species. Many studies showed that <em>Quercus mongolica</em> will become a main associated tree species in broadleaved <em>Pinus koraiensis </em>forest, because it is more conducive to survival under the environment change in future. Therefore, the process of litter decomposition will be affected by climate warming and composition of little species change. Given that decomposition of dead plant tissues in forest ecosystems regulates the transfer of carbon and nutrients to soil, and represents an important source of CO₂ to the atmosphere. It is necessary to carry out research about litter decomposition of the two species under climate change in future. This study used litter bag methods, the whole process use an alkali absorption in a closed chamber method to measured cumulative CO₂ production. We recognized N concentration and C/N ratio as the litter quality parameters, and calculated decomposition rates as cumulative CO₂ production and initial mass remaining. Microcosm experiments under controlled laboratory conditions have proven useful for investigating the various factors that influence litter decomposition. Thus, this study was carried out through a microcosm experiment, in order to:(i) determine the effect of imitate increase temperature on <em>Pinus koraiensis</em>,<em>Quercus mongolica</em> pure and their mix litter decomposition rate and (ii)the effect of litter with different physicochemical properties on litter decomposition rate at the same temperature level under constant moisture condition, during a time period of 151 days incubation in laboratory. Our results suggest that increased temperature accelerated leaf little decomposition rates within both mixed-species litterbags and single-species litterbags. However, its response may vary depending on the level of increased temperature. When the temperature in closed chamber was at 25 ℃ and 29 ℃, decomposition rates within litterbags decreased in the order of mixed-species > single-<em>Quercus mongolica</em> > single-<em>Pinus koraiensis</em>. When the temperature in closed chamber increased to 31 ℃, decomposition rates was faster within mixed-species litterbags and single-<em>Quercus mongolica</em> litterbags than single-<em>Pinus koraiensis</em>, but the variation between mixed-species litterbags and single-<em>Quercus mongolica</em> litterbags decomposition rates was not statistically significant. This study has great significance on understanding of forest ecosystem carbon and nutrient cycle.

Estimating the Impact of Projected Climate Change on Runoff across the Tropical Savannas and Semiarid Rangelands of Northern Australia

Abstract The majority of the world’s population growth to 2050 is projected to occur in the tropics. Hence, there is a serious need for robust methods for undertaking water resource assessments to underpin the sustainable management of water in tropical regions. This paper describes the largest and most comprehensive assessment of the future impacts of runoff undertaken in a tropical region using conceptual rainfall–runoff models (RRMs). Five conceptual RRMs were calibrated using data from 115 streamflow gauging stations, and model parameters were regionalized using a combination of spatial proximity and catchment similarity. Future rainfall and evapotranspiration projections (denoted here as GCMES) were transformed to catchment-scale variables by empirically scaling (ES) the historical climate series, informed by 15 global climate models (GCMs), to reflect a 1°C increase in global average surface air temperature. Using the best-performing RRM ensemble, approximately half the GCMES used resulted in a spatially averaged increase in mean annual runoff (by up to 29%) and half resulted in a decrease (by up to 26%). However, ~70% of the GCMES resulted in a difference of within ±5% of the historical rainfall (1930–2007). The range in modeled impact on runoff, as estimated by five RRMs (for individual GCMES), was compared to the range in modeled runoff using 15 GCMES (for individual RRMs). For mid- to high runoff metrics, better predictions will come from improved GCMES projections. A new finding of this study is that in the wet–dry tropics, for extremely large runoff events and low flows, improvements are needed in both GCMES and rainfall–runoff modeling.

Imposed and Neglected Uncertainty in the Global Average Surface Air Temperature Index

The statistical error model commonly applied to monthly surface station temperatures assumes a physically incomplete climatology that forces deterministic temperature trends to be interpreted as measurement errors. Large artefactual uncertainties are thereby imposed onto the global average surface air temperature record. To illustrate this problem, representative monthly and annual uncertainties were calculated using air temperature data sets from globally distributed surface climate stations, yielding ±2.7 C and ±6.3 C, respectively. Further, the magnitude uncertainty in the 1961–1990 global air temperature annual anomaly normal, entirely neglected until now, is found to be ±0.17 C. After combining magnitude uncertainty with the previously reported ±0.46 C lower limit of measurement error, the 1856–2004 global surface air temperature anomaly with its 95% confidence interval is 0.8±0.98 C, Thus, the global average surface air temperature trend is statistically indistinguishable from 0 C. Regulatory policies aimed at influencing global surface air temperature are not empirically justifiable.

Uncertainty in the Global Average Surface Air Temperature Index: A Representative Lower Limit

Sensor measurement uncertainty has never been fully considered in prior appraisals of global average surface air temperature. The estimated average ±0.2 C station error has been incorrectly assessed as random, and the systematic error from uncontrolled variables has been invariably neglected. The systematic errors in measurements from three ideally sited and maintained temperature sensors are calculated herein. Combined with the ±0.2 C average station error, a representative lower-limit uncertainty of ±0.46 C was found for any global annual surface air temperature anomaly. This ±0.46 C reveals that the global surface air temperature anomaly trend from 1880 through 2000 is statistically indistinguishable from 0 C, and represents a lower limit of calibration uncertainty for climate models and for any prospective physically justifiable proxy reconstruction of paleo-temperature. The rate and magnitude of 20th century warming are thus unknowable, and suggestions of an unprecedented trend in 20th century global air temperature are unsustainable.