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The understanding of airborne pollen transportation is crucial for the reconstruction of the paleoenvironment. Under favorable conditions, a considerable amount of long-distance-transported pollen can be deposited far from its place of origin. In extreme arid regions, in most cases, such situations occur and increase the difficulty to interpret fossil pollen records. In this study, three sets of Cour airborne pollen trap were installed on the northern slope of Tianshan Mountains to collect airborne Picea schrenkiana (spruce) pollen grains from July 2001 to July 2006. The results indicate that Picea pollen disperses extensively and transports widely in the lower atmosphere far away from spruce forest. The airborne Picea pollen dispersal period is mainly concentrated between mid-May and July. In desert area, weekly Picea pollen began to increase and peaked suddenly in concentration. Also, annual pollen indices do not decline even when the distance increased was probably related to the strong wind may pick up the deposited pollen grains from the topsoil into the air stream, leading to an increase of pollen concentration in the air that is irrelevant to the normal and natural course of pollen transport and deposition. This, in turn, may lead to erroneous interpretations of the pollen data in the arid region. This study provided insight into the shift in the Picea pollen season regarding climate change in arid areas. It is recorded that the pollen pollination period starts earlier and the duration became longer. The results also showed that the temperature of May and June was positively correlated with the Picea pollen production. Furthermore, the transport of airborne Picea pollen data is useful for interpreting fossil pollen records from extreme arid regions. peerReviewed

This paper assesses the long-term combined effects of land use (LU) and climate change on river hydrology and water scarcity of two rivers of the Western Ghats of India. The historical LU changes were studied for four decades (1988–2016) using the maximum likelihood algorithm and the long-term LU (2016–2075) was estimated using the Dyna-CLUE prediction model. Five General Circulation Models (GCMs) were utilized to assess the effects of climate change (CC) and the Soil and Water Assessment Tool (SWAT) model was used for hydrological modeling of the two river catchments. To characterize granular effects of LU and CC on regional hydrology, a scenario approach was adopted and three scenarios depicting near-future (2006–2040), mid-future (2041–2070), and far-future (2071–2100) based on climate were established. The present rate of LU change indicated a reduction in forest cover by 20% and an increase in urbanized areas by 9.5% between 1988 and 2016. It was estimated that forest cover in the catchments may be expected to halve compared to the present-day LU (55% in 2016 to 23% in 2075), along with large-scale conversion to agricultural lands (13.5% in 2016 to 49.5% in 2075). As a result of changes to LU and forecasted climate, it was found that rivers in the Western Ghats of India might face scarcity of fresh water in the next two decades until the year 2040. However, because of large-scale LU conversion toward the year 2050, streamflow in rivers might increase as high as 70.94% at certain times of the year. Although an increase in streamflow is perceived favorable, the streamflow changes during summer and winter may be expected to affect the cropping calendar and crop yield. The changes to streamflow were also linked to a 4.2% increase in ecologically sensitive wetlands of the Aghanashini river catchment.

Copyright © The Author(s) 2021. Increasing resilience to natural hazards and climate change is critical for achieving many Sustainable Development Goals (SDGs). In recent decades, China has experienced rapid economic development and became the second-largest economy in the world. This rapid economic expansion has led to large-scale changes in terrestrial (e.g., land use and land cover changes), aquatic (e.g., construction of reservoirs and artificial wetlands) and marine (e.g., land reclamation) environments across the country. Together with climate change, these changes may significantly influence flood risk and, in turn, compromise SDG achievements. The Luanhe River Basin (LRB) is one of the most afforested basins in North China and has undergone significant urbanisation and land use change since the 1950s. However, basin-wide flood risk assessment under different development scenarios has not been considered, although this is critically important to inform policy-making to manage the synergies and trade-offs between the SDGs and support long-term sustainable development. Using mainly open data, this paper introduces a new framework for systematically assessing flood risk under different social and economic development scenarios. A series of model simulations are performed to investigate the flood risk under different land use change scenarios projected to 2030 to reflect different development strategies. The results are systematically analysed and compared with the baseline simulation based on the current land use and climate conditions. Further investigations are also provided to consider the impact of climate change and the construction of dams and reservoirs. The results potentially provide important guidance to inform future development strategies to maximise the synergies and minimise the trade-offs between various SDGs in LRB. Natural Environment Research Council (NERC) of the UK Research and Innovation (UKRI) through the Towards a Sustainable Earth (TaSE) programme (NE/S012427/1).

Soil is the largest terrestrial carbon pool, making it crucial for climate change mitigation. Soil organic carbon (SOC) is suggested to depend on biodiversity components, but much evidence comes from diversity-function experiments. To disentangle the relationships of plant guild diversity with SOC storage (kg m−2) at broad spatial scales, we applied diversity-interaction models to a regional grassland database (n = 96) including wide environmental conditions and management regimes. The questions were: (1) Are the effects of plant guilds on SOC stocks in natural grasslands consistent with those found in experimental systems? (2) Are plant guild effects on SOC stocks independent of each other or do they show interactive—synergistic or antagonistic—effects? (3) Do environmental variables, including abiotic and management, modify guild effects on SOC stocks? Among our most novel results we found, legume effects on grassland SOC vary depending on legume proportion consistently across broad spatial scales. SOC increased with legume proportion up to 7–17%, then decreased. Additionally, these effects were strengthened when grasses and forbs were codominant. Grazing intensity modulated grass proportion effects on SOC, being maximum at relatively high intensities. Interpreting our results in terms of existing contrasted ecological theories, we confirmed at broad spatial scales and under wide-ranging environmental conditions the positive effects of plant guild diversity on SOC, and we showed how legumes exert a keystone effect on SOC in natural grasslands, probably related to their ability to fix inorganic N. Niche complementarity effects were illustrated when codominance of forbs and grasses at optimum legume proportions boosted SOC storage, whereas grass dominance increased SOC stocks at medium–high grazing intensities. These findings can facilitate the preparation of regional and local strategies to ameliorate the soil capacity to absorb carbon. Research in this paper is based on the PASTUS database, compiled from different funding sources over time, the most relevant being: the EU Interreg III- A Programme (I3A- 4- 147- E) and the POCTEFA Programme/Interreg IV- A (FLUXPYR, EFA 34/08); the Spanish Science Foundation FECYT- MICINN (CARBOPAS: REN2002- 04300- C02- 01; CARBOAGROPAS: CGL2006- 13555- C03- 03 and CAPAS: CGL2010- 22378- C03- 01); the Foundation Catalunya- La Pedrera; and the Spanish Institute of Agronomical Research INIA (CARBOCLUS: SUM2006- 00029- C02- 0). This work was funded by the Spanish Science Foundation FECYT- MINECO (BIOGEI: CGL2013-49142-C2-1-R and IMAGINE: CGL2017-85490-R) and the University of Lleida (PhD Fellowship to AR). This research article has received a grant for its linguistic revision from the Language Institute of the University of Lleida (2021 call).

Forest structural properties largely govern surface fluxes of moisture, energy, and momentum that strongly affect regional climate and hydrology. Forest structural properties are greatly shaped by forest management activities, especially in the Fennoscandia (Norway, Sweden, and Finland). Insight into transient developments in forest structure in response to management intervention is therefore essential to understanding the role of forest management in mitigating regional climate change. The aim of this study is to present a simple grid-based framework – the Fennoscandic Forest State Simulator (F2S2) -- for predicting time-dependent forest structural trajectories in a manner compatible with land models employed in offline or asynchronously coupled climate and hydrological research. F2S2 enables the prescription of future regional forest structure as a function of: i) exogenously defined scenarios of forest harvest intensity; ii) forest management intensity; iii) climate forcing. We demonstrate its application when applied as a stand-alone tool for forecasting three alternative future forest states in Norway that differ with respect to background climate forcing, forest harvest intensity (linked to two Shared Socio-economic Pathways (SSPs)), and forest management intensity. F2S2 captures impacts of climate forcing and forest management on general trends in forest structural development over time, and while climate is the main driver of longer-term forest structural dynamics, the role of harvests and other management-driven effects cannot be overlooked. To our knowledge this is the first paper presenting a method to map forest structure in space and time in a way that is compatible with land surface or hydrological models employing sub-grid tiling.

This paper investigates the role of intervening transport processes on lake sediment records of the atmospherically deposited radionuclides 210Pb and 137Cs. Brotherswater is of particular interest to this issue in that its large catchment/lake area ratio and short water residence time are likely to amplify the influence of these processes, both from the catchment and through the water column. Brotherswater is also unique in being the site of two earlier multicore studies that, together with the present study, span a period of 4 decades. Measurements of fallout radionuclides were made on soil cores, suspended sediments and sediment cores, and the results combined with those from earlier studies to construct mass balances for 210Pb and 137Cs in Brotherswater. The results showed that catchment inputs accounted for 63% of 210Pb entering the lake. Further, just 47% of 210Pb entering the water column was delivered to the sediment record. For comparison, in an earlier study at nearby Blelham Tarn with a relatively smaller catchment but longer water residence time it was shown that 47% of 210Pb inputs were delivered via the catchment, 75% of which were delivered to the sediment record. Results from both sites suggest that 210Pb is predominantly transported on fine particulates with a mean particle size of 3–4 μm. Their relatively slow removal from the water column allows them to be transported relatively uniformly throughout the lake and may help account for the fact that simple 210Pb dating models are relatively reliable in spite of the complexities of the transport processes. Mass balance calculations for 137Cs are more complicated because of the variable fallout record. Measurements of 137Cs in the input stream and water column showed that catchment inputs are still significant 30 years after the last significant fallout (Chernobyl). Modelled results showed that catchment inputs delayed the date of peak inputs of weapons test fallout to the lake though by no more than 2 years. Although the results presented here are primarily concerned with fallout radionuclides and their reliability for dating, they also have implications for the use of sediment archives in reconstructing historical records of other atmospherically deposited substances such as trace metals or persistent organic pollutants.

The overall global-scale consequences of climate change are dependent on the distribution of impacts across regions, and there are multiple dimensions to these impacts. This paper presents a global assessment of the potential impacts of climate change across several sectors, using a harmonised set of impacts models forced by the same climate and socio-economic scenarios. Indicators of impact cover the water resources, river and coastal flooding, agriculture, natural environment and built environment sectors. Impacts are assessed under four SRES socio-economic and emissions scenarios, and the effects of uncertainty in the projected pattern of climate change are incorporated by constructing climate scenarios from 21 global climate models. There is considerable uncertainty in projected regional impacts across the climate model scenarios, and coherent assessments of impacts across sectors and regions therefore must be based on each model pattern separately; using ensemble means, for example, reduces variability between sectors and indicators. An example narrative assessment is presented in the paper. Under this narrative approximately 1 billion people would be exposed to increased water resources stress, around 450 million people exposed to increased river flooding, and 1.3 million extra people would be flooded in coastal floods each year. Crop productivity would fall in most regions, and residential energy demands would be reduced in most regions because reduced heating demands would offset higher cooling demands. Most of the global impacts on water stress and flooding would be in Asia, but the proportional impacts in the Middle East North Africa region would be larger. By 2050 there are emerging differences in impact between different emissions and socio-economic scenarios even though the changes in temperature and sea level are similar, and these differences are greater in 2080. However, for all the indicators, the range in projected impacts between different climate models is considerably greater than the range between emissions and socio-economic scenarios.

Combining bioenergy and carbon dioxide (CO2) capture and storage (CCS) technologies (BECCS) has the potential to remove CO2 from the atmosphere while producing useful energy. BECCS has played a central role in scenarios that reduce climate forcing to low levels such as 2.6 Wm−2. In this paper we consider whether BECCS is essential to limiting radiative forcing (RF) to 2.6 Wm−2 by 2100 using the Global Change Assessment Model, a closely coupled model of biogeophysical and human Earth systems. We show that BECCS can potentially reduce the cost of limiting RF to 2.6 Wm−2 by 2100 but that a variety of technology combinations that do not include BECCS can also achieve this goal, under appropriate emissions mitigation policies. We note that with appropriate supporting land-use policies terrestrial sequestration could deliver carbon storage ranging from 200 to 700 PgCO2-equiavalent over the 21st century. We explore substantial delays in participation by some geopolitical regions. We find that the value of BECCS is substantially higher under delay and that delay results in higher transient RF and climate change. However, when major regions postponed mitigation indefinitely, it was impossible to return RF to 2.6 Wm−2 by 2100. Neither finite land resources nor finite potential geologic storage capacity represented a meaningful technical limit on the ability of BECCS to contribute to emissions mitigation in the numerical experiments reported in this paper.

Semi-arid river basins often rely on reservoirs for water supply. Small reservoirs may impact on large-scale water availability both by enhancing availability in a distributed sense and by subtracting water for large downstream user communities, e.g. served by large reservoirs. Both of these impacts of small reservoirs are subject to climate change. Using a case-study on North-East Brazil, this paper shows that climate change impacts on water availability may be severe, and impacts on distributed water availability from small reservoirs may exceed impacts on centralised water availability from large reservoirs. Next, the paper shows that the effect of small reservoirs on water availability from large reservoirs may be significant, and increase both in relative and absolute sense under unfavourable climate change.

Just over 40 years ago, I wrote a paper entitled “Climate change: Are we on the brink of a pronounced global warming?” In it, I attempted to explain why despite a rise in the atmosphere’s CO2 content there had been no significant warming. I predicted that a natural cooling was about to give way to a warming, and that industrial emissions of CO2 would amplify this warming. The paper published in Science in 1975. Warming did follow in 1976–1977. However, a retrospective look shows that my analysis was flawed. What is more—and to my chagrin—based on the words “global warming” in my Science paper, I was given the title “Father of Global Warming.” Not only did I not like this title, I had done little to merit it.

The projected climate change signals of a five-member high resolution ensemble, based on two global climate models (GCMs: ECHAM5 and CCCma3) and two regional climate models (RCMs: CLM and WRF) are analysed in this paper (Part II of a two part paper). In Part I the performance of the models for the control period are presented. The RCMs use a two nest procedure over Europe and Germany with a final spatial resolution of 7 km to downscale the GCM simulations for the present (1971–2000) and future A1B scenario (2021–2050) time periods. The ensemble was extended by earlier simulations with the RCM REMO (driven by ECHAM5, two realisations) at a slightly coarser resolution. The climate change signals are evaluated and tested for significance for mean values and the seasonal cycles of temperature and precipitation, as well as for the intensity distribution of precipitation and the numbers of dry days and dry periods. All GCMs project a significant warming over Europe on seasonal and annual scales and the projected warming of the GCMs is retained in both nests of the RCMs, however, with added small variations. The mean warming over Germany of all ensemble members for the fine nest is in the range of 0.8 and 1.3 K with an average of 1.1 K. For mean annual precipitation the climate change signal varies in the range of −2 to 9 % over Germany within the ensemble. Changes in the number of wet days are projected in the range of ±4 % on the annual scale for the future time period. For the probability distribution of precipitation intensity, a decrease of lower intensities and an increase of moderate and higher intensities is projected by most ensemble members. For the mean values, the results indicate that the projected temperature change signal is caused mainly by the GCM and its initial condition (realisation), with little impact from the RCM. For precipitation, in addition, the RCM affects the climate change signal significantly.

Producing food, transportation, and energy for seven billion people has led to large and widespread increases in the use of synthetic nitrogen (N) fertilizers and fossil fuel combustion, resulting in a leakage of N into the environment as various forms of air and water pollution. The global N cycle is more severely altered by human activity than the global carbon (C) cycle, and reactive N dynamics affect all aspects of climate change considerations, including mitigation, adaptation, and impacts. In this special issue of Biogeochemistry, we present a review of the climate–nitrogen interactions based on a technical report for the United States National Climate Assessment presented as individual papers for terrestrial and aquatic ecosystems, agriculture and human health within the US. We provide a brief overview of each of the paper’s main points and conclusions is presented in this foreword summary.

Background The default international accounting rules estimate the carbon emissions from forest products by assuming all harvest is immediately emitted to the atmosphere. This makes it difficult to assess the greenhouse gas (GHG) consequences of different forest management or manufacturing activities that maintain the storage of carbon. The Intergovernmental Panel on Climate Change (IPCC) addresses this issue by allowing other accounting methods. The objective of this paper is to provide a new model for estimating annual stock changes of carbon in harvested wood products (HWP). Results The model, British Columbia Harvested Wood Products version 1 (BC-HWPv1), estimates carbon stocks and fluxes for wood harvested in BC from 1965 to 2065, based on new parameters on local manufacturing, updated and new information for North America on consumption and disposal of wood and paper products, and updated parameters on methane management at landfills in the USA. Based on model results, reporting on emissions as they occur would substantially lower BC’s greenhouse gas inventory in 2010 from 48 Mt CO2 to 26 Mt CO2 because of the long-term forest carbon storage in-use and in the non-degradable material in landfills. In addition, if offset projects created under BC’s protocol reported 100 year cumulative emissions using the BC-HWPv1 the emissions would be lower by about 11%. Conclusions This research showed that the IPCC default methods overestimate the emissions North America wood products. Future IPCC GHG accounting methods could include a lower emissions factor (e.g. 0.52) multiplied by the annual harvest, rather than the current multiplier of 1.0. The simulations demonstrated that the primary opportunities for climate change mitigation are in shifting from burning mill waste to using the wood for longer-lived products.

Political leaders in numerous nations argue for an upper limit of the global average surface temperature of 2 K above the pre-industrial level, in order to attempt to avoid the most serious impacts of climate change. This paper analyzes what this limit implies in terms of radiative forcing, emissions pathways and abatement costs, for a range of assumptions on rate of ocean heat uptake and climate sensitivity. The primary aim is to analyze the importance of ocean heat uptake for radiative forcing pathways that temporarily overshoot the long-run stabilization forcing, yet keep the temperature increase at or below the 2 K limit. In order to generate such pathways, an integrated climate-economy model, MiMiC, is used, in which the emissions pathways generated represent the least-cost solution of stabilizing the global average surface temperature at 2 K above the pre-industrial level. We find that the level of overshoot can be substantial. For example, the level of overshoot in radiative forcing in 2100 ranges from about 0.2 to 1 W/m2, where the value depends strongly and positively on the effective diffusivity of heat in the oceans. Measured in relative terms, the level of radiative forcing overshoot above its longrun equilibrium level in 2100 is 20% to 60% for high values of climate sensitivity (i.e., about 4.5 K) and 8% to 30% for low values of climate sensitivity (i.e., about 2 K). In addition, for cases in which the radiative forcing level can be directly stabilized at the equilibrium level associated with a specific climate sensitivity and the 2 K limit, the net present value abatement cost is roughly cut by half if overshoot pathways are considered instead of stabilization of radiative forcing at the equilibrium level without an overshoot.

The Arctic is subject to growing economic and political interest. Meanwhile, its climate and water systems are in rapid transformation. In this paper, we review and extend a set of studies on climate model results, hydro-climatic change, and hydrological monitoring systems. Results indicate that general circulation model (GCM) projections of drainage basin temperature and precipitation have improved between two model generations. However, some inaccuracies remain for precipitation projections. When considering geographical priorities for monitoring or adaptation efforts, our results indicate that future projections by GCMs and recent observations diverge regarding the basins where temperature and precipitation changes currently are the most pronounced and where they will be so in the future. Regarding late twentieth-century discharge changes in major Arctic rivers, data generally show excess of water relative to precipitation changes. This indicates a possible contribution to sea-level rise of river water that was previously stored in permafrost or groundwater. The river contribution to the increasing Arctic Ocean freshwater inflow is similar in magnitude to the separate contribution from glaciers, which underlines the importance of considering all possible sources of freshwater when assessing sea-level change. We further investigate monitoring systems and find a lack of harmonized water chemistry data, which limits the ability to understand the origin and transport of nutrients, carbon and sediment to the sea. To provide adequate information for research and policy, Arctic hydrological and hydrochemical monitoring needs to be extended, better integrated and made more accessible. Further water-focused data and modeling efforts are required to resolve the source of excess discharge in Arctic rivers. Finally, improvements in climate model parameterizations are needed, in particular for precipitation projections.

Purpose Current estimations of the climate impact from indirect land use change (ILUC) caused by biofuels are heavily influenced by assumptions regarding the biofuel production period. The purpose of this paper is to propose a new method (baseline time accounting) that takes global land use dynamics into account that is consistent with the global warming potential, that is applicable to any phenomenon causing land use change, and that is independent of production period assumptions. Methods We consider ILUC in two forms. The first is called “accelerated expansion” and concerns ILUC in regions with an expanding agricultural area. The second is called “delayed reversion” and concerns ILUC in regions with a decreasing agricultural area. We use recent trends in international land use and projections of future land use change to assess how ILUC from biofuels will alter the development in global agricultural land use dynamics compared to the existing trend (i.e., the baseline development). We then use the definition of the global warming potential to determine the CO2 equivalence of the change in land use dynamics. Results and discussion We apply baseline time accounting to two existing ILUC studies in the literature. With current trends in global agricultural land use, the method significantly reduces the estimated climate impact in the previous ILUC studies (by more than half). Sensitivity analyses show that results are somewhat sensitive to assumptions regarding carbon sequestration and assumptions regarding postreversion ecosystems. Conclusions The global dynamic development in land use has important implications for the time accounting step when estimating the climate impact of ILUC caused by biofuel production or other issues affecting land use. Ignoring this may lead to erroneous conclusions about the actual climate impact of ILUC. Several land use projections indicate that the global agricultural area will keep expanding up to and beyond 2050. We therefore recommend to apply the baseline time accounting concept as an integrated part of future ILUC studies and to update the results on a regular basis.

The paper estimates and compares the level of Reducing Emissions from Deforestation and Degradation (REDD+) payments required to compensate for the opportunity costs (OCs) of stopping the conversion of montane forest and miombo woodlands into cropland in two agro-ecological zones in Morogoro Region in Tanzania. Data collected from 250 households were used for OC estimation. REDD+ payment was estimated as the net present value (NPV) of agricultural rent and forest rent during land clearing, minus net returns from sustainable wood harvest, divided by the corresponding reduction in carbon stock. The median compensation required to protect the current carbon stock in the two vegetation types ranged from USD 1 tCO2e −1 for the montane forest to USD 39 tCO2e −1 for the degraded miombo woodlands, of which up to 70 % and 16 %, respectively, were for compensating OCs from forest rent during land clearing. The figures were significantly higher when the cost of farmers' own labor was not taken into account in NPV calculations. The results also highlight- ed that incentives in the form of sustainable harvests could offset up to 55 % of the total median OC to protect the montane forest and up to 45 % to protect the miombo woodlands, depending on the wage rates. The findings suggest that given the possible factors that can potentially affect estimates of REDD+ payments, avoiding deforestation of the montane forest would be feasible under the REDD+ scheme. However, implementation of the policy in villages around the miombo area would require very high compensation levels.

Long-term changes in the magnetic environment of the Earth are of interest to those studying space weather and climate change, particularly in the upper atmosphere. In this paper we examine long-term changes in daily variation as derived from hourly mean values from 14 geomagnetic observatories around the world. Their time series date back to the beginning of the 20th century. We find that there are similar features in all the records, with peaks in the amplitudes of the daily variation occurring in the 1950s and 1980s, and a small upward trend of 1.3 nT/century corresponding to an increase of over 10%. The extrema coincide with those seen in solar irradiance proxy data, in particular the F10.7 flux density dataset which starts in 1947.

Probabilistic climate data have become available for the first time through the UK Climate Projections 2009, so that the risk of change in tree growth can be quantified. We assessed the drought risk spatially and temporally using drought probabilities calculated from the weather generator data and tree species vulnerabilities using Ecological Site Classification model across Britain. We evaluated the drought impact on the potential yield class of three major tree species (Picea sitchensis, Pinus sylvestris, and Quercus robur), which cover around 59 % (400,700 ha) of state-managed forests, across the lowlands and uplands. We show that drought impacts result mostly in reduced tree growth over the next 80 years when using B1, A1B, and A1FI IPCC emissions scenarios, but varied spatially. We found a maximum reduction of 94 % but also a maximum increase of 56 % in potential stand yield class in the 2080s from the baseline climate (1961–1990). Furthermore, potential production over the state-managed forests for all three species in the 2080s is estimated to decrease due to drought by 42 % in the lowlands and by 32 % in the uplands in comparison to the baseline climate. Our results reveal that potential tree growth and forest production on the state-managed forests in Britain is likely to reduce, and indicate where and when adaptation measures are required. Moreover, this paper demonstrates the value of probabilistic climate projections for an important economic and environmental sector.

Changes in temperature, precipitation, sea level, and coastal storms will likely increase the vulnerability of infrastructure across the United States. Using four models that analyze vulnerability, impacts, and adaptation, this paper estimates impacts to roads, bridges, coastal properties, and urban drainage infrastructure and investigates sensitivity to varying greenhouse gas emission scenarios, climate sensitivities, and global climate models. The results suggest that the impacts of climate change in this sector could be large, especially in the second half of the 21st century as sea-level rises, temperature increases, and precipitation patterns become more extreme and affect the sustainability of long-lived infrastructure. Further, when considering sea-level rise, scenarios which incorporate dynamic ice sheet melting yield impact model results in coastal areas that are roughly 70 to 80 % higher than results that do not incorporate dynamic ice sheet melting. The potential for substantial economic impacts across all infrastructure sectors modeled, however, can be reduced by cost-effective adaptation measures. Mitigation policies also show potential to reduce impacts in the infrastructure sector – a more aggressive mitigation policy reduces impacts by 25 to 35 %, and a somewhat less aggressive policy reduces impacts by 19 to 30 %. The existing suite of models suitable for estimating these damages nonetheless covers only a small portion of expected infrastructure sector effects from climate change, so much work remains to better understand impacts on electric and telecommunications networks, rail, and air transportation systems. In addition, the effects of climate-induced extreme events are likely to be important, but are incompletely understood and remain an emerging area for research.

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950–2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin. Electronic supplementary material The online version of this article (doi:10.1007/s13280-014-0583-y) contains supplementary material, which is available to authorized users.

Extensive research is being conducted world- wide to find alternative and efficient systems to lessen the impacts of climate change and reduce environmental pol- lution. The genus Phragmites has proven ability to mitigate the environmental pollution of its surroundings. Common reed (Phragmites australis (Cav.) Trin. Ex. Steudel), a graminaceous plant of cosmopolitan nature, has been extensively studied especially for the mitigation of envi- ronmental contamination. The capability of common reed to grow well at extreme environmental conditions such as elevated CO2 and high temperature is conferred by several factors such as change of carbon trapping mechanism (from C3 to C4 and vice versa), microbial association and biochemical adaptations. P. australis has been a most preferred unique plant system, especially in ecological engineering for improving the quality of wastewater. This paper reviews the current state of knowledge regarding the suitability of Phragmites australis for environmental remediation and summarizes recent advancements in our understanding of this grass.

Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.

Food security in India is tightly linked to rainfall variability. Trends in Indian rainfall records have been extensively studied but the subject remains complicated by the high spatiotemporal variability of rainfall arising from complex atmospheric dynamics. For various reasons past studies have often produced inconsistent results. This paper presents an analysis of recent trends in monthly and seasonal cumulative rainfall depth, number of rainy days and maximum daily rainfall, and in the monsoon occurrence (onset, peak and retreat). A modified version of the Mann-Kendall test, accounting for the scaling effect, was applied to 29 variables derived from square-degree-resolution daily gridded rainfall (1951–2007). The mapping of gridded trend slopes and the regional average Kendall test were used concurrently to assess the field significance of regional trends in areas exhibiting spatial homogeneity in trend directions. The statistics we used account for temporal and spatial correlations, and thus reduce the risk of overestimating the significance of local and regional trends. Our results i/ improve available knowledge (e.g. 5 %-field-significant delay of the monsoon onset in Northern India); ii/ provide a solid statistical basis to previous qualitative observations (e.g. 1 %-field-significant increase/decrease in pre-monsoon rainfall depth in northeast/southwest India); and, iii/ when compared to recent studies, show that the field significance level of regional trends (e.g. in rainfall extremes) is test-dependent. General trend patterns were found to align well with the geography of anthropogenic atmospheric disturbances and their effect on rainfall, confirming the paramount role of global warming in recent rainfall changes.

In the present paper, the inter-seasonal Hg variability in snow cover was examined based on multivariate statistical analysis of chemical and meteorological data. Samples of freshly fallen snow cover were collected at the semi-urban site in Poznań (central Poland), during 3-month field measurements in winter 2013. It was showed that concentrations of atmospherically deposited Hg were highly variable in snow cover, from 0.43 to 12.5 ng L−1, with a mean value of 4.62 ng L−1. The highest Hg concentration in snow cover coincided with local intensification of fossil fuel burning, indicating large contribution from various anthropogenic sources such as commercial and domestic heating, power generation plants, and traffic-related pollution. Moreover, the variability of Hg in collected snow samples was associated with long-range transport of pollutants, nocturnal inversion layer, low boundary layer height, and relatively low air temperature. For three snow episodes, Hg concentration in snow cover was attributed to southerly advection, suggesting significant contribution from the highly polluted region of Poland (Upper Silesia) and major European industrial hotspots. However, the peak Hg concentration was measured in samples collected during predominant N to NE advection of polluted air masses and after a relatively longer period without precipitation. Such significant contribution to the higher Hg accumulation in snow cover was associated with intensive emission from anthropogenic sources (coal combustion) and atmospheric conditions in this area. These results suggest that further measurements are needed to determine how the Hg transformation paths in snow cover change in response to longer/shorter duration of snow cover occurrence and to determine the interactions between mercury and absorbing carbonaceous aerosols in the light of climate change.

This paper examines the subject of hydrologic variability and its changes in two separate integrations of a coupled ocean-atmosphere general circulation model developed at the Geophysical Fluid Dynamics Laboratory/NOAA assuming a 1% per year increase to a doubling and quadrupling of CO2, respectively. Changes in time mean state and variability of precipitation, runoff and soil moisture are evaluated using monthly and seasonal mean data derived from these integrations. Various statistical tests are then performed on the resulting time mean and variability changes. The patterns of hydrologic change for these three quantities are similar to those obtained from previous studies. In northern middle to higher latitudes for the time means, the changes include increases in monthly mean precipitation, increases in monthly mean runoff during the fall, winter and spring seasons and decreases of monthly mean soil moisture during summer. Many of these changes are found to be statistically significant at the 5% significance level for both the time mean and variability especially for the results where CO2 is quadrupled such as monthly mean precipitation. Significant changes also include increases of runoff variability during spring, winter and spring and increases of soil moisture variability during the summer season. These results support statements made in previous IPCC reports that increasing greenhouse gases can lead to more severe and frequent floods and droughts depending upon season and latitude. This study also indicates that the approaches to equilibrium of these two integrations, and the resulting hydrologic changes, take place over time scales of hundreds of years in agreement with several previous investigations.

This paper summarizes the main elements of four IPY projects that examine the Arctic Atmosphere. All four projects focus on present conditions with a view to anticipating possible climate change. All four investigate the Arctic atmosphere, ocean, ice, and land interfacial surfaces. One project uses computer models to simulate the dynamics of the Arctic atmosphere, storms, and their interactions with the ocean and ice interface. Another project uses statistical methods to infer transports of pollutants as simulated in large-scale global atmospheric and oceanic models verifying results with available observations. A third project focuses on measurements of pollutants at the ice-ocean–atmosphere interface, with reference to model estimates. The fourth project is concerned with multiple, high accuracy measurements at Eureka in the Canadian Archipelago. While these projects are distinctly different, led by different teams and interdisciplinary collaborators, with different technical approaches and methodologies, and differing objectives, they all strive to understand the processes of the Arctic atmosphere and climate, and to lay the basis for projections of future changes. Key findings include: • Decreased sea ice leads to more intense storms, higher winds, reduced surface albedo, increased surface air temperature, and enhanced vertical mixing in the upper ocean. • Arctic warming may affect toxic chemicals by remobilizing persistent organic pollutants and augmenting mercury deposition/retention in the environment. • Changes in sea ice can dramatically change processes in and at the ice surface related to ozone, mercury and bromine oxide and related chemical/physical properties. • Structure and properties of the Arctic atmospheric—troposphere to stratosphere—and tracking of transport of pollution and smoke plumes from mid-latitudes to the poles.

This paper evaluates the effect of climate change (described in terms of temperature and rainfall) on forest cover and vegetation (described in terms of Normalized Difference Vegetation Index) in the Betwa river basin, a tributary of River Yamuna in Central India. Temperature and rainfall data of 18 stations, forest cover and vegetation (derived using 5 years data from Landsat images employing ERDAS Imagine and ArcGIS) were used in the analysis. The effect of climate change was studied for both the pre-monsoon and post-monsoon seasons. In this study, the simple regression method was used to evaluate their relationship. In pre-monsoon season, temperature and forest cover analysis shows regression coefficient value of 0.6876 and, temperature and vegetation analysis shows regression coefficient value of 0.5751. Further, in post-monsoon season analysis rainfall and forest cover shows regression coefficient value of 0.8417 and, temperature and vegetation analysis shows regression coefficient value of 0.6854. The study reveals that, in pre-monsoon season temperature was significantly related with forest cover and vegetation. In post-monsoon season rainfall exhibited positive response to forest cover and, temperature exhibited negative response to vegetation in the Betwa river basin.

Coastal safety may be influenced by climate change, as changes in wave conditions (height, period, direction) may increase the vulnerability of dunes and other coastal defences. Dune erosion depends on mean water level, storm surge height and wave conditions. In this paper, we investigate the change in wave conditions in the North Sea in a changing climate. Until now, the effect of climate change on annual maximum wave conditions has been investigated, while events with higher return periods are actually most damaging for the coast (e.g. severe dune erosion). Here, we use the 17-member Ensemble SimulationS of Extreme weather under Nonlinear Climate changeE (ESSENCE) change of climate change simulations, to analyse A1b-induced changes in the mean wave climate, the annual maxima and wave conditions with return periods of up to 1:10,000 years in front of the Dutch coast. The mean wave climate is not projected to differ between 1961–1990 and 2071– 2100, with both wave height (Hs) and wave period (Tm) remaining unaltered. In the annual maximum conditions, a decrease is projected; especially, the annual Tm maximum decreases significantly by 0.3 to 0.6 s over Responsible Editor: Birgit Andrea Klein S. L. Weber, deceased 12 August 2011. R. C. de Winter (B) · S. L. Weber · B. G. Ruessink Department of Physical Geography, Faculty of Geosciences, Institute for Marine and Atmospheric Research, Utrecht University, P.O. Box 80.115, 3508 TC Utrecht, Netherlands e-mail: r.c.dewinter@uu.nl R. C. de Winter · A. Sterl · J. W. de Vries · S. L. Weber Royal Netherlands Meteorological Institute (KNMI), P.O. Box 201, 3730 AE De Bilt, Netherlands the whole study area. Furthermore, we find that the direction of the annual maximum wave conditions shifts from north and north-west to west and south-west for both Hs and Tm. This is induced by a similar shift in the direction of the extreme wind speeds. Despite the decrease in annual maximum conditions, the return Hs and Tm are not projected to change significantly as a result of climate change in front of the Dutch coast for the period 2071–2100 relative to 1961–1990.

Coastal inundation from hurricane storm surges causes catastrophic damage to lives and property, as evidenced by recent hurricanes including Katrina and Wilma in 2005 and Ike in 2008. Changes in hurricane activity and sea level due to a warming climate, together with growing coastal population, are expected to increase the potential for loss of property and lives. Current inundation hazard maps: Base Flood Elevation maps and Maximum of Maximums are computationally expensive to create in order to fully represent the hurricane climatology, and do not account for climate change. This paper evaluates the coastal inundation hazard in Southwest Florida for present and future climates, using a high resolution storm surge modeling system, CH3D-SSMS, and an optimal storm ensemble with multivariate interpolation, while accounting for climate change. Storm surges associated with the optimal storms are simulated with CH3D-SSMS and the results are used to obtain the response to any storm via interpolation, allowing accurate representation of the hurricane climatology and efficient generation of hazard maps. Incorporating the impact of anticipated climate change on hurricane and sea level, the inundation maps for future climate scenarios are made and affected people and property estimated. The future climate scenarios produce little change to coastal inundation, due likely to the reduction in hurricane frequency, except when extreme sea level rise is included. Calculated coastal inundation due to sea level rise without using a coastal surge model is also determined and shown to significantly overestimate the inundation due to neglect of land dissipation.

The unprecedented availability of 6-hourly data from a multi-model GCM ensemble in the CMIP5 data archive presents the new opportunity to dynamically downscale multiple GCMs to develop high-resolution climate projections relevant to detailed assessment of climate vulnerability and climate change impacts. This enables the development of high resolution projections derived from the same set of models that are used to characterise the range of future climate changes at the global and large-scale, and as assessed in the IPCC AR5. However, the technical and human resource required to dynamically-downscale the full CMIP5 ensemble are significant and not necessary if the aim is to develop scenarios covering a representative range of future climate conditions relevant to a climate change risk assessment. This paper illustrates a methodology for selecting from the available CMIP5 models in order to identify a set of 8–10 GCMs for use in regional climate change assessments. The selection focuses on their suitability across multiple regions—Southeast Asia, Europe and Africa. The selection (a) avoids the inclusion of the least realistic models for each region and (b) simultaneously captures the maximum possible range of changes in surface temperature and precipitation for three continental-scale regions. We find that, of the CMIP5 GCMs with 6-hourly fields available, three simulate the key regional aspects of climate sufficiently poorly that we consider the projections from those models ‘implausible’ (MIROC-ESM, MIROC-ESM-CHEM, and IPSL-CM5B-LR). From the remaining models, we demonstrate a selection methodology which avoids the poorest models by including them in the set only if their exclusion would significantly reduce the range of projections sampled. The result of this process is a set of models suitable for using to generate downscaled climate change information for a consistent multi-regional assessment of climate change impacts and adaptation.

Climate change is a significant global issue of concern especially in context of its impact on environment. It affects the different ecosystems with significant impact on water resources, agriculture, forestry, health, industrial sectors and biodiversity as well. For sustainable management of biodiversity in the context of changing scenario of climate change, a coordinated strategy across the various levels of geographic/governance hierarchy as well as across strategic elements such as capacity building, knowledge dissemination, institutions partnerships, policy/instruments and technology, needs to be pursued. The paper covers the trends and impact of climate change especially on sustainable management of biodiversity in Asia and India.

The discharge of the River Brah maputra is highly affected by the melting of snow at the upper part of its catchment. Increase in discharge due to significant retreat of snow in turn affects the downstream flow characteristics of the river giving rise to severe catastrophic problems such as flood and erosion. Rising temperature is one of the major reasons of melting of snow at the upper Brahmaputra catchment. Keeping in mind such issue, in this paper, a study has been conducted to see how the snow cover area of the Brahmaputra river basin changes with respect to the change in temperature. MODIS image MOD09A1.5 (MODIS/Terra Surface Reflectance 8-Day L3 Global 500 m SIN Grid) of 500 m resolution consisting of seven bands has been taken to prepare the normalized difference snow index maps of the study area. The normalized difference snow index map is then used to obtain the areal extent of snow in the Brahmaputra catchment area. The normalized difference snow index maps were prepared starting from 2002 to 2012 for four different months, viz. January, April, July and October. For temperature data, HadCM3 data of spatial resolution 2.5° × 3.75° (latitude by longitude) has been used. The evaluation of the results shows that the snow cover area of the basin shows decreasing trends with respect to the increasing trend of temperature except for the month of January. Further, this study also shows that MODIS data can efficiently be used for snow cover area variation study. Variation of snow cover area is an indication of climate change as the melting of snow clearly reflects the rise in temperature. The attenuation of river flow due to the melting of snow in the river Brahmaputra basin may affect the downstream discharge of the river giving rise to severe flood and erosion problem. It has also been observed that MODIS data can efficiently be used in mapping snow cover of large areas, because of its good spatial as well as high temporal resolution.

Water scarcity threatens economic growth, social cohesion, and environmental sustainability in many deltas. This situation is likely to worsen due to future climate change. To reduce water scarcity and limit salt water intrusion in deltas, many countries have launched policies to allocate water resources. However, it is difficult to develop long-term adaptive water management policies due to large uncertainties. In this paper, we present a Robust Assessment Model for Water Allocation (RAMWA) to support decision making about water release of different key reservoirs under future climate change. The model was applied in the Pearl River basin, China to improve reservoir management, to ensure sufficient flow into the delta to reduce salt intrusion, and to provide sufficient freshwater for human and industrial consumption. Results show that performance of the existing water allocation plans reduces under climate change, as the plans are unable to sustain the required minimum river discharge. However alternatives generated by a Generic Evolutionary Algorithm (GEA) suggest that new plans can be developed which ensure minimum flows into the delta under most future climate change scenarios. The GEA plans perform better than existing plans because rather than following a fixed allocation schedule, the optimal water release for each reservoir is recalculated every 10 days based on observed discharge and storage in key reservoirs.

Global climate change creates critical challenges with increasing temperature, reducing snowpack, and changing precipitation for water, energy, and food, as well as ecosystem processes at regional scales. Ecosystem services provide life support, goods, and natural resources from water, energy, and food, as well as the environments. There are knowledge gaps from the lack of conceptual framework and practices to interlink major climate change drivers of water resources with water-energy-food nexus and related ecosystem processes. This paper provided an overview of research background, developed a conceptual framework to bridge these knowledge gaps, summarized California case studies for practices in cross sector ecosystem services, and identified future research needs. In this conceptual framework, climate change drivers of changing temperature, snowpack, and precipitation are interlinked with life cycles in water, energy, food, and related key elements in ecosystem processes. Case studies in California indicated climate change affected variation in increasing temperature and changing hydrology at the regional scales. A large variation in average energy intensity values was also estimated from ground water and federal, state, and local water supplies both within each hydrological region and among the ten hydrological regions in California. The increased regional temperature, changes in snowpack and precipitation, and increased water stresses from drought can reduce ecosystem services and affect the water and energy nexus and agricultural food production, as well as fish and wildlife habitats in the Sacramento-San Joaquin Delta (Delta) and Central Valley watersheds. Regional decisions and practices in integrated management of water, energy, food, and related ecosystem processes are essential to adapt and mitigate global climate change impacts at the regional scales. Science and policy support for interdisciplinary research are critical to develop the database and tools for comprehensive analysis to fill knowledge gaps and address ecosystem service complexity, the related natural resource investment, and integrated planning needs.

Background Forest management faces a climate induced shift in growth potential and increasing current and emerging new risks. Vulnerability analysis provides decision support based on projections of natural resources taking risks and uncertainties into account. In this paper we (1) characterize differences in forest dynamics under three management scenarios, (2) analyse the effects of the three scenarios on two risk factors, windthrow and drought stress, and (3) quantify the effects and the amount of uncertainty arising from climate projections on height increment and drought stress. Methods In four regions in northern Germany, we apply three contrasting management scenarios and project forest development under climate change until 2070. Three climate runs (minimum, median, maximum) based on the emission scenario RCP 8.5 control the site-sensitive forest growth functions. The minimum and maximum climate run define the range of prospective climate development. Results The projections of different management regimes until 2070 show the diverging medium-term effects of thinnings and harvests and long-term effects of species conversion on a regional scale. Examples of windthrow vulnerability and drought stress reveal how adaptation measures depend on the applied management path and the decision-maker’s risk attitude. Uncertainty analysis shows the increasing variability of drought risk projections with time. The effect of climate projections on height growth are quantified and uncertainty analysis reveals that height growth of young trees is dominated by the age-trend whereas the climate signal in height increment of older trees is decisive. Conclusions Drought risk is a serious issue in the eastern regions independent of the applied silvicultural scenario, but adaptation measures are limited as the proportion of the most drought tolerant species Scots pine is already high. Windthrow risk is no serious overall threat in any region, but adequate counter-measures such as species conversion, species mixture or reduction of target diameter can be taken. This simulation study of three silvicultural scenarios and three climate runs spans a decision space of potential forest development to be used for decision making. Which adaptation measures to counteract climate induced risks and uncertainty are to be taken is, however, a matter of individual risk attitude.

Background Global forests capture and store significant amounts of CO2 through photosynthesis. When carbon is removed from forests through harvest, a portion of the harvested carbon is stored in wood products, often for many decades. The United States Forest Service (USFS) and other agencies are interested in accurately accounting for carbon flux associated with harvested wood products (HWP) to meet greenhouse gas monitoring commitments and climate change adaptation and mitigation objectives. This paper uses the Intergovernmental Panel on Climate Change (IPCC) production accounting approach and the California Forest Project Protocol (CFPP) to estimate HWP carbon storage from 1906 to 2010 for the USFS Northern Region, which includes forests in northern Idaho, Montana, South Dakota, and eastern Washington. Results Based on the IPCC approach, carbon stocks in the HWP pool were increasing at one million megagrams of carbon (MgC) per year in the mid 1960s, with peak cumulative storage of 28 million MgC occurring in 1995. Net positive flux into the HWP pool over this period is primarily attributable to high harvest levels in the mid twentieth century. Harvest levels declined after 1970, resulting in less carbon entering the HWP pool. Since 1995, emissions from HWP at solid waste disposal sites have exceeded additions from harvesting, resulting in a decline in the total amount of carbon stored in the HWP pool. The CFPP approach shows a similar trend, with 100-year average carbon storage for each annual Northern Region harvest peaking in 1969 at 937,900 MgC, and fluctuating between 84,000 and 150,000 MgC over the last decade. Conclusions The Northern Region HWP pool is now in a period of negative net annual stock change because the decay of products harvested between 1906 and 2010 exceeds additions of carbon to the HWP pool through harvest. However, total forest carbon includes both HWP and ecosystem carbon, which may have increased over the study period. Though our emphasis is on the Northern Region, we provide a framework by which the IPCC and CFPP methods can be applied broadly at sub-national scales to other regions, land management units, or firms.

The impact of a changing climate is already being felt on several hydrological systems both on a regional and sub-regional scale of the globe. Southeast Asia is one of the regions strongly affected by climate change. With climate change, one of the anticipated impacts is an increase in the intensity and frequency of extreme rainfall which further increase the region’s flood catastrophes, human casualties and economic loss. Optimal mitigation measures can be undertaken only when stormwater systems are designed using rainfall Intensity-Duration-Frequency (IDF) curves derived from a long and good quality rainfall data. Developing IDF curves for the future climate can be even more challenging especially for ungauged sites. The current practice to derive current climate’s IDF curves for ungauged sites is, for example, to ‘borrow’ or ‘interpolate’ data from regions of climatologically similar characteristics. Recent measures to derive IDF curves for present climate was performed by extracting rainfall data from a high spatial resolution Regional Climate Model driven by ERA-40 reanalysis dataset. This approach has been demonstrated on an ungauged site (Java, Indonesia) and the results were quite promising. In this paper, the authors extend the application of the approach to other ungauged sites particularly in Peninsular Malaysia. The results of the study undoubtedly have significance contribution in terms of local and regional hydrology (Malaysia and Southeast Asian countries). The anticipated impacts of climate change especially increase in rainfall intensity and its frequency appreciates the derivation of future IDF curves in this study. It also provides policy makers better information on the adequacy of storm drainage design, for the current climate at the ungauged sites, and the adequacy of the existing storm drainage to cope with the impacts of climate change.