Worst case scenario as stakeholder decision support: a 5- to 6-m sea level rise in the Rhone delta, France

Risk policy and public attitudes appear disconnected from research predicting warmer climate partially due to human activity. To step out of this stalled situation, a worst case scenario of a 5- to 6-m sea level rise (SLR) induced by the collapse of the WAIS and occurring during the period 2030–2130 is constructed and applied to the Rhone delta. Physical and socio-economic scenarios developed with data from the Rhone delta context are developed and submitted to stakeholders for a day-long workshop. Group process analysis shows a high level of trust and cooperation mobilized to face the 5–6 m SLR issue, despite potentially diverging interests. Two sets of recommendations stem from the scenario workshop. A conservative “wait and see” option is decided when the risk of the WAIS collapse is announced in 2030. After WAIS collapse generates an effective 1 m SLR rise by 2050, decisions are taken for total retreat and rendering of the Rhone delta to its hydrological function. The transposition of these results into present-day policy decisions could be considered. The methodology developed here could be applied to other risk objects and situations, and serve for policy exercises and crisis prevention.     

Comparison of three methods for estimating the sea level rise effect on storm surge flooding

Two linear methods, including the simple linear addition and linear addition by expansion, and numerical simulations were employed to estimate storm surges and associated flooding caused by Hurricane Andrew for scenarios of sea level rise (SLR) from 0.15 m to 1.05 m with an interval of 0.15 m. The interaction between storm surge and SLR is almost linear at the open Atlantic Ocean outside Biscayne Bay, with slight reduction in peak storm surge heights as sea level rises. The nonlinear interaction between storm surges and SLR is weak in Biscayne Bay, leading to small differences in peak storm surge heights estimated by three methods. Therefore, it is appropriate to estimate elevated storm surges caused by SLR in these areas by adding the SLR magnitude to storm surge heights. However, the magnitude and extent of inundation at the mainland area by Biscayne Bay estimated by numerical simulations are, respectively, 22–24 % and 16–30 % larger on average than those generated by the linear addition by expansion and the simple linear addition methods, indicating a strong nonlinear interaction between storm surge and SLR. The population and property affected by the storm surge inundation estimated by numerical simulations differ up to 50–140 % from that estimated by two linear addition methods. Therefore, it is inappropriate to estimate the exacerbated magnitude and extent of storm surge flooding and affected population and property caused by SLR by using the linear addition methods. The strong nonlinear interaction between surge flooding and SLR at a specific location occurs at the initial stage of SLR when the water depth under an elevated sea level is less than 0.7 m, while the interaction becomes linear as the depth exceeds 0.7 m.     

Assessing vulnerability due to sea-level rise in Maui, Hawai‘i using LiDAR remote sensing and GIS

Sea-level rise (SLR) threatens islands and coastal communities due to vulnerable infrastructure and populations concentrated in low-lying areas. LiDAR (Light Detection and Ranging) data were used to produce high-resolution DEMs (Digital Elevation Model) for Kahului and Lahaina, Maui, to assess the potential impacts of future SLR. Two existing LiDAR datasets from USACE (U.S. Army Corps of Engineers) and NOAA (National Oceanic and Atmospheric Administration) were compared and calibrated using the Kahului Harbor tide station. Using tidal benchmarks is a valuable approach for referencing LiDAR in areas lacking an established vertical datum, such as in Hawai‘i and other Pacific Islands. Exploratory analysis of the USACE LiDAR ground returns (point data classified as ground after the removal of vegetation and buildings) indicated that another round of filtering could reduce commission errors. Two SLR scenarios of 0.75 (best-case) to 1.9 m (worst-case) (Vermeer and Rahmstorf Proc Natl Acad Sci 106:21527–21532, 2009) were considered, and the DEMs were used to identify areas vulnerable to flooding. Our results indicate that if no adaptive strategies are taken, a loss ranging from $18.7 million under the best-case SLR scenario to $296 million under the worst-case SLR scenario for Hydrologically Connected (HC; marine inundation) and Hydrologically Disconnected (HD; drainage problems due to a higher water table) areas combined is possible for Kahului; a loss ranging from $57.5 million under the best-case SLR scenario to $394 million under the worst-case SLR scenario for HC and HD areas combined is possible for Lahaina towards the end of the century. This loss would be attributable to inundation between 0.55 km² to 2.13 km² of area for Kahului, and 0.04 km² to 0.37 km² of area for Lahaina.     

Implications of recent sea level rise science for low-elevation areas in coastal cities of the conterminous U.S.A.

Recently published work estimates that global sea level rise (SLR) approaching or exceeding 1 m by 2100 is plausible, thus significantly updating projections by the Fourth Assessment of the Intergovernmental Panel on Climate Change. Furthermore, global greenhouse gas (GHG) emissions over the 21st century will not only influence SLR in the next ??90 years, but will also commit Earth to several meters of additional SLR over subsequent centuries. In this context of worsening prospects for substantial SLR, we apply a new geospatial dataset to calculate low-elevation areas in coastal cities of the conterminous U.S.A. potentially impacted by SLR in this and following centuries. In total, 20 municipalities with populations greater than 300,000 and 160 municipalities with populations between 50,000 and 300,000 have land area with elevations at or below 6 m and connectivity to the sea, as based on the 1 arc-second National Elevation Dataset. On average, approximately 9% of the area in these coastal municipalities lies at or below 1 m. This figure rises to 36% when considering area at or below 6 m. Areal percentages of municipalities with elevations at or below 1?C6 m are greater than the national average along the Gulf and southern Atlantic coasts. In contrast to the national and international dimensions of and associated efforts to curb GHG emissions, our comparison of low-elevation areas in coastal cities of the conterminous U.S.A. clearly shows that SLR will potentially have very local, and disproportionate, impacts.     

Greenland Ice Sheet Contribution to Future Global Sea Level Rise based on CMIP5 Models简

Sea level rise （SLR） is one of the major socioeconomic risks associated with global warming. Mass losses from the Greenland ice sheet （GrIS） will be partially responsible for future SLR, although there are large uncertainties in modeled climate and ice sheet behavior. We used the ice sheet model SICOPOLIS （Simulation COde for POLythermal Ice Sheets） driven by climate projections from 20 models in the fifth phase of the Coupled Model Intercomparison Project （CMIP5） to estimate the GrlS contribution to global SLR. Based on the outputs of the 20 models, it is estimated that the GrIS will contribute 0-16 （0-27） cm to global SLR by 2100 under the Representative Concentration Pathways （RCP） 4.5 （RCP 8.5） scenarios. The projected SLR increases further to 7-22 （7-33） cm with 2~basal sliding included. In response to the results of the multimodel ensemble mean, the ice sheet model projects a global SLR of 3 cm and 7 cm （10 cm and 13 cm with 2~basal sliding） under the RCP 4.5 and RCP 8.5 scenarios, respectively. In addition, our results suggest that the uncertainty in future sea level projection caused by the large spread in climate projections could be reduced with model-evaluation and the selective use of model outputs.     

Effects of projected climate change on the hydrology in the Mono Lake Basin, California

The Californian Mono Lake Basin (MLB) is a fragile ecosystem, for which a 1983 ruling carefully balanced water diversions with ecological needs without the consideration of global climate change. The hydroclimatologic response to the impact of projected climatic changes in the MLB has not been comprehensively assessed and is the focus of this study. Downscaled temperature and precipitation projections from 16 Global Climate Models (GCMs), using two emission scenarios (B1 and A2), were used to drive a calibrated Soil and Water Assessment Tool (SWAT) hydrologic model to assess the effects on streamflow on the two significant inflows to the MLB, Lee Vining and Rush Creeks. For the MLB, the GCM ensemble output suggests significant increases in annual temperature, averaging 2.5 and 4.1 °C for the B1 and A2 emission scenarios, respectively, with concurrent small (1–3 %) decreases in annual precipitation by the end of the century. Annual total evapotranspiration is projected to increase by 10 mm by the end of the century for both emission scenarios. SWAT modeling results suggest a significant hydrologic response in the MLB by the end of the century that includes a) decreases in annual streamflow by 15 % compared to historical conditions b) an advance of the peak snowmelt runoff to 1 month earlier (June to May), c) a decreased (10–15 %) occurrence of ‘wet’ hydrologic years, and d) and more frequent (7–22 %) drought conditions. Ecosystem health and water diversions may be affected by reduced water availability in the MLB by the end of the century.     

Observational estimate of climate sensitivity from changes in the rate of ocean heat uptake and comparison to CMIP5 models

Climate sensitivity is estimated based on 0–2,000 m ocean heat content and surface temperature observations from the second half of the 20th century and first decade of the 21st century, using a simple energy balance model and the change in the rate of ocean heat uptake to determine the radiative restoration strength over this time period. The relationship between this 30–50 year radiative restoration strength and longer term effective sensitivity is investigated using an ensemble of 32 model configurations from the Coupled Model Intercomparison Project phase 5 (CMIP5), suggesting a strong correlation between the two. The mean radiative restoration strength over this period for the CMIP5 members examined is 1.16 Wm^?2K^?1, compared to 2.05 Wm^?2K^?1 from the observations. This suggests that temperature in these CMIP5 models may be too sensitive to perturbations in radiative forcing, although this depends on the actual magnitude of the anthropogenic aerosol forcing in the modern period. The potential change in the radiative restoration strength over longer timescales is also considered, resulting in a likely (67 %) range of 1.5–2.9 K for equilibrium climate sensitivity, and a 90 % confidence interval of 1.2–5.1 K.     

Climate-model induced differences in the 21st century global and regional glacier contributions to sea-level rise

The large uncertainty in future global glacier volume projections partly results from a substantial range in future climate conditions projected by global climate models. This study addresses the effect of global and regional differences in climate input data on the projected twenty-first century glacier contribution to sea-level rise. Glacier volume changes are calculated with a surface mass balance model combined with volume-area scaling, applied to 89 glaciers in different climatic regions. The mass balance model is based on a simplified energy balance approach, with separated contributions by net solar radiation and the combined other fluxes. Future mass balance is calculated from anomalies in air temperature, precipitation and atmospheric transmissivity, taken from eight global climate models forced with the A1B emission scenario. Regional and global sea-level contributions are obtained by scaling the volume changes at the modelled glaciers to all glaciers larger than 0.1 km² outside the Greenland and Antarctic ice sheets. This results in a global value of 0.102 ± 0.028 m (multi-model mean and standard deviation) relative sea-level equivalent for the period 2012–2099, corresponding to 18 ± 5 % of the estimated total volume of glaciers. Glaciers in the Antarctic, Alaska, Central Asia and Greenland together account for 65 ± 4 % of the total multi-model mean projected sea-level rise. The projected sea-level contribution is 35 ± 17 % larger when only anomalies in air temperature are taken into account, demonstrating an important compensating effect by increased precipitation and possibly reduced atmospheric transmissivity. The variability in projected precipitation and atmospheric transmissivity changes is especially large in the Arctic regions, making the sea-level contribution for these regions particularly sensitive to the climate model used. Including additional uncertainties in the modelling procedure and the input data, the total uncertainty estimate for the future projections becomes ±0.063 m.     

Incorporating uncertainty of future sea-level rise estimates into vulnerability assessment: A case study in Kahului, Maui

Accurate sea-level rise (SLR) vulnerability assessments are essential in developing effective management strategies for coastal systems at risk. In this study, we evaluate the effect of combining vertical uncertainties in Light Detection and Ranging (LiDAR) elevation data, datum transformation and future SLR estimates on estimating potential land area and land cover loss, and whether including uncertainty in future SLR estimates has implications for adaptation decisions in Kahului, Maui. Monte Carlo simulation is used to propagate probability distributions through our inundation model, and the output probability surfaces are generalized as areas of high and low probability of inundation. Our results show that considering uncertainty in just LiDAR and transformation overestimates vulnerable land area by about 3 % for the high probability threshold, resulting in conservative adaptation decisions, and underestimates vulnerable land area by about 14 % for the low probability threshold, resulting in less reliable adaptation decisions for Kahului. Not considering uncertainty in future SLR estimates in addition to LiDAR and transformation has variable effect on SLR adaptation decisions depending on the land cover category and how the high and low probability thresholds are defined. Monte Carlo simulation is a valuable approach to SLR vulnerability assessments because errors are not required to follow a Gaussian distribution.     

Climate change impacts on international seaports: knowledge, perceptions, and planning efforts among port administrators

Seaports are located in vulnerable areas to climate change impacts: on coasts susceptible to sea-level rise and storms or at mouths of rivers susceptible to flooding. They serve a vital function within the local, regional, and global economy. Their locations in the heart of sensitive estuarine environments make it an imperative to minimize the impacts of natural hazards. Climate impacts, like a projected SLR of .6?m to 2?m and doubling of Category 4 and 5 hurricanes by 2100, will result in more extreme events at many seaports. To assess the current state of knowledge on this issue, we surveyed port authorities from around the world about how administrators felt climate change might impact their operations, what sea-level change would create operational problems, and how they planned to adapt to new environmental conditions. The planned rapid expansion of ports reported by the survey respondents indicates that adaptation measures should be considered as ports construct new infrastructure that may still be in use at the end of the century. Respondents agreed that the ports community needs to address this issue and most felt relatively uninformed about potential climate impacts. Although most ports felt that SLR would not be an issue at their port this century, sea-level rise was nevertheless an issue of great concern. Our results suggest opportunities for the scientific community to engage with port practitioners to prepare proactively for climate change impacts on this sector.     

Global warming mitigation by sulphur loading in the stratosphere: dependence of required emissions on allowable residual warming rate

An approach to mitigate global warming via sulphur loading in the stratosphere (geoengineering) is studied, employing a large ensemble of numerical experiments with the climate model of intermediate complexity IAP RAS CM. The model is forced by the historical+SRES A1B anthropogenic greenhouse gases+tropospheric sulphates scenario for 1860–2100 with additional sulphur emissions in the stratosphere in the twenty-first century. Different ensemble members are constructed by varying values of the parameters governing mass, horizontal distribution and radiative forcing of the stratospheric sulphates. It is obtained that, given a global loading of the sulphates in the stratosphere, among those studied in this paper latitudinal distributions of geoengineering aerosols, the most efficient one at the global basis is that peaked between 50°N and 70°N and with a somewhat smaller burden in the tropics. Uniform latitudinal distribution of stratospheric sulphates is a little less efficient. Sulphur emissions in the stratosphere required to stop the global temperature at the level corresponding to the mean value for 2000–2010 amount to more than 10 TgS/year in the year 2100. These emissions may be reduced if some warming is allowed to occur in the twenty-first century. For instance, if the global temperature trend S _g in every decade of this century is limited not to exceed 0.10 K/decade (0.15 K/decade), geoengineering emissions of 4–14 TgS/year (2–7 TgS/year) would be sufficient. Even if the global warming is stopped, temperature changes in different regions still occur with a magnitude up to 1 K. Their horizontal pattern depends on implied latitudinal distribution of stratospheric sulphates. In addition, for the stabilised global mean surface air temperature, global precipitation decreases by about 10%. If geoengineering emissions are stopped after several decades of implementation, their climatic effect is removed within a few decades. In this period, surface air temperature may grow with a rate of several Kelvins per decade. The results obtained with the IAP RAS CM are further interpreted employing a globally averaged energy–balance climate model. With the latter model, an analytical estimate for sulphate aerosol emissions in the stratosphere required climate mitigation is obtained. It is shown that effective vertical localisation of the imposed radiative forcing is important for geoengineering efficiency.     

Evaluation of the twenty-first century RCM simulations driven by multiple GCMs over the Eastern Mediterranean–Black Sea region

In this study, human-induced climate change over the Eastern Mediterranean–Black Sea region has been analyzed for the twenty-first century by performing regional climate model simulations forced with large-scale fields from three different global circulation models (GCMs). Climate projections have been produced with Special Report on Emissions Scenarios A2, A1FI and B1 scenarios, which provide greater diversity in climate information for future period. The gradual increases for temperature are widely apparent during the twenty-first century for each scenario simulation, but ECHAM5-driven simulation generally has a weaker signal for all seasons compared to CCSM3 simulations except for the Fertile Crescent. The contrast in future temperature change between the winter and summer seasons is very strong for CCSM3-A2-driven and HadCM3-A2-driven simulations over Carpathians and Balkans, 4–5 °C. In addition, winter runoff over mountainous region of Turkey, which feeds many river systems including the Euphrates and Tigris, increases in second half of the century since the snowmelt process accelerates where the elevation is higher than 1,500 m. Moreover, analysis of daily temperature outputs reveals that the gradual decrease in daily minimum temperature variability for January during the twenty-first century is apparent over Carpathians and Balkans. Analysis of daily precipitation extremes shows that positive trend is clear during the last two decades of the twenty-first century over Carpathians for both CCSM3-driven and ECHAM5-driven simulations. Multiple-GCM driven regional climate simulations contribute to the quantification of the range of climate change over a region by performing detailed comparisons between the simulations.     

Future surface mass balance of the Antarctic ice sheet and its influence on sea level change, simulated by a regional atmospheric climate model

A regional atmospheric climate model with multi-layer snow module (RACMO2) is forced at the lateral boundaries by global climate model (GCM) data to assess the future climate and surface mass balance (SMB) of the Antarctic ice sheet (AIS). Two different GCMs (ECHAM5 until 2100 and HadCM3 until 2200) and two different emission scenarios (A1B and E1) are used as forcing to capture a realistic range in future climate states. Simulated ice sheet averaged 2 m air temperature (T_2m) increases (1.8–3.0 K in 2100 and 2.4–5.3 K in 2200), simultaneously and with the same magnitude as GCM simulated T_2m. The SMB and its components increase in magnitude, as they are directly influenced by the temperature increase. Changes in atmospheric circulation around Antarctica play a minor role in future SMB changes. During the next two centuries, the projected increase in liquid water flux from rainfall and snowmelt, together 60–200 Gt year^?1, will mostly refreeze in the snow pack, so runoff remains small (10–40 Gt year^?1). Sublimation increases by 25–50 %, but remains an order of magnitude smaller than snowfall. The increase in snowfall mainly determines future changes in SMB on the AIS: 6–16 % in 2100 and 8–25 % in 2200. Without any ice dynamical response, this would result in an eustatic sea level drop of 20–43 mm in 2100 and 73–163 mm in 2200, compared to the twentieth century. Averaged over the AIS, a strong relation between $\Updelta$ SMB and $\Updelta\hbox{T}_{2{\rm m}}$ of 98 ± 5 Gt w.e. year^?1 K^?1 is found.     

Alpine snow cover in a changing climate: a regional climate model perspective

An analysis is presented of an ensemble of regional climate model (RCM) experiments from the ENSEMBLES project in terms of mean winter snow water equivalent (SWE), the seasonal evolution of snow cover, and the duration of the continuous snow cover season in the European Alps. Two sets of simulations are considered, one driven by GCMs assuming the SRES A1B greenhouse gas scenario for the period 1951–2099, and the other by the ERA-40 reanalysis for the recent past. The simulated SWE for Switzerland for the winters 1971–2000 is validated against an observational data set derived from daily snow depth measurements. Model validation shows that the RCMs are capable of simulating the general spatial and seasonal variability of Alpine snow cover, but generally underestimate snow at elevations below 1,000 m and overestimate snow above 1,500 m. Model biases in snow cover can partly be related to biases in the atmospheric forcing. The analysis of climate projections for the twenty first century reveals high inter-model agreement on the following points: The strongest relative reduction in winter mean SWE is found below 1,500 m, amounting to 40–80 % by mid century relative to 1971–2000 and depending upon the model considered. At these elevations, mean winter temperatures are close to the melting point. At higher elevations the decrease of mean winter SWE is less pronounced but still a robust feature. For instance, at elevations of 2,000–2,500 m, SWE reductions amount to 10–60 % by mid century and to 30–80 % by the end of the century. The duration of the continuous snow cover season shows an asymmetric reduction with strongest shortening in springtime when ablation is the dominant factor for changes in SWE. We also find a substantial ensemble-mean reduction of snow reliability relevant to winter tourism at elevations below about 1,800 m by mid century, and at elevations below about 2,000 m by the end of the century.     

Toward a physically plausible upper bound of sea-level rise projections

Anthropogenic sea-level rise (SLR) causes considerable risks. Designing a sound SLR risk-management strategy requires careful consideration of decision-relevant uncertainties such as the reasonable upper bound of future SLR. The recent Intergovernmental Panel on Climate Change’s (IPCC) Fourth Assessment reported a likely upper SLR bound in the year 2100 near 0.6 m (meter). More recent studies considering semi-empirical modeling approaches and kinematic constraints on glacial melting suggest a reasonable 2100 SLR upper bound of approximately 2 m. These recent studies have broken important new ground, but they largely neglect uncertainties surrounding thermal expansion (thermosteric SLR) and/or observational constraints on ocean heat uptake. Here we quantify the effects of key parametric uncertainties and observational constraints on thermosteric SLR projections using an Earth system model with a dynamic three-dimensional ocean, which provides a mechanistic representation of deep ocean processes and heat uptake. Considering these effects nearly doubles the contribution of thermosteric SLR compared to previous estimates and increases the reasonable upper bound of 2100 SLR projections by 0.25 m. As an illustrative example of the effect of overconfidence, we show how neglecting thermosteric uncertainty in projections of the SLR upper bound can considerably bias risk analysis and hence the design of adaptation strategies. For conditions close to the Port of Los Angeles, the 0.25 m increase in the reasonable upper bound can result in a flooding-risk increase by roughly three orders of magnitude. Results provide evidence that relatively minor underestimation of the upper bound of projected SLR can lead to major downward biases of future flooding risks.     

The contribution of snow condition trends to future ground climate

Global climate models predict that terrestrial northern high-latitude snow conditions will change substantially over the twenty-first century. Results from a Community Climate System Model simulation of twentieth and twenty-first (SRES A1B scenario) century climate show increased winter snowfall (+10–40%), altered maximum snow depth (?5 ± 6 cm), and a shortened snow-season (?14 ± 7 days in spring, +20 ± 9 days in autumn). By conducting a series of prescribed snow experiments with the Community Land Model, we isolate how trends in snowfall, snow depth, and snow-season length affect soil temperature trends. Increasing snowfall, by countering the snowpack-shallowing influence of warmer winters and shorter snow seasons, is effectively a soil warming agent, accounting for 10–30% of total soil warming at 1 m depth and ~16% of the simulated twenty-first century decline in near-surface permafrost extent. A shortening snow season enhances soil warming due to increased solar absorption whereas a shallowing snowpack mitigates soil warming due to weaker winter insulation from cold atmospheric air. Snowpack deepening has comparatively less impact due to saturation of snow insulative capacity at deeper snow depths. Snow depth and snow-season length trends tend to be positively related, but their effects on soil temperature are opposing. Consequently, on the century timescale the net change in snow state can either amplify or mitigate soil warming. Snow state changes explain less than 25% of total soil temperature change by 2100. However, for the latter half of twentieth century, snow state variations account for as much as 50–100% of total soil temperature variations.     

Estimation and Projection of Non-Linear Relative Sea-Level Rise in the Seto Inland Sea,Japan

Future sea-level rise (SLR) in and around the Seto Inland Sea (SIS), Japan, is estimated in 2050 and 2100 using ensemble empirical mode decomposition (EEMD) and long-term sea-level records. Ensemble empirical mode decomposition, an adaptive data analysis method, can separate sea-level records into intrinsic mode functions (IMFs) from high to low frequencies and a residual. The residual is considered a non-linear trend in the sea-level records. The mean SLR trend at Tokuyama in the SIS from EEMD is 3.00?mm?y^?1 from 1993 to 2010, which is slightly lower than the recent altimetry-based global rate of 3.3?±?0.4?mm?y^?1 during the same period. Uncertainty in SLR is estimated by considering interdecadal variations in the sea levels. The resulting SLR in 2050 and 2100 for Tokuyama is 0.19?±?0.06?m and 0.56?±?0.18?m, respectively. The stations along the coast of the Pacific Ocean display a greater and more rapid SLR in 2100 compared with other stations in the SIS. The SLR is caused not only by mass and volume changes in the sea water but also by other factors, such as local subsidence, tectonic motion, and river discharge. The non-linear trend of SLR, which is the residual from EEMD, is interpreted as the sum of the local factors that contribute to the sea-level budget.     

Estimates of twenty-first century sea-level changes for Norway

In this work we establish a framework for estimating future regional sea-level changes for Norway. Following recently published works, we consider how different physical processes drive non-uniform sea-level changes by accounting for spatial variations in (1) ocean density and circulation (2) ice and ocean mass changes and associated gravitational effects on sea level and (3) vertical land motion arising from past surface loading change and associated gravitational effects on sea level. An important component of past and present sea-level change in Norway is glacial isostatic adjustment. Central to our study, therefore, is a reassessment of vertical land motion using a far larger set of new observations from a permanent GNSS network. Our twenty-first century sea-level estimates are split into two parts. Firstly, we show regional projections largely based on findings from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4) and dependent on the emission scenarios A2, A1B and B1. These indicate that twenty-first century relative sea-level changes in Norway will vary between ?0.2 to 0.3 m (1-sigma ± 0.13 m). Secondly, we explore a high-end scenario, in which a global atmospheric temperature rise of up to 6 °C and emerging collapse for some areas of the Antarctic ice sheets are assumed. Using this approach twenty-first century relative sea-level changes in Norway are found to vary between 0.25 and 0.85 m (min/max ± 0.45 m). We attach no likelihood to any of our projections owing to the lack of understanding of some of the processes that cause sea-level change.     

Global and regional trends in greenhouse gas emissions from livestock

Following IPCC guidelines (IPCC 2006), we estimate greenhouse gas emissions related to livestock in 237 countries and 11 livestock categories during the period 1961–2010. We find that in 2010 emissions of methane and nitrous oxide related to livestock worldwide represented approximately 9 % of total greenhouse gas (GHG) emissions. Global GHG emissions from livestock increased by 51 % during the analyzed period, mostly due to strong growth of emissions in developing (Non-Annex I) countries (+117 %). In contrast, developed country (Annex I) emissions decreased (?23 %). Beef and dairy cattle are the largest source of livestock emissions (74 % of global livestock emissions). Since developed countries tend to have lower CO₂-equivalent GHG emissions per unit GDP and per quantity of product generated in the livestock sector, the amount of wealth generated per unit GHG emitted from the livestock sector can be increased by improving both livestock farming practices in developing countries and the overall state of economic development. Our results reveal important details of how livestock production and associated GHG emissions have occurred in time and space. Discrepancies with higher tiers, demonstrate the value of more detailed analyses, and discourage over interpretation of smaller-scale trends in the Tier 1 results, but do not undermine the value of global Tier 1 analysis.     

A comparison of sea level projections based on the observed and reconstructed sea level data around the Korean Peninsula

In an attempt to estimate accurate local sea level change, “sea level trend” modes are identified and separated from natural variability via cyclostationary empirical orthogonal function (CSEOF) analysis applied to both the tide gauge data (1965–2013) and the reconstruction data (1950–2010) around the Korean Peninsula. For the tide gauge data, ensemble empirical mode decomposition (EEMD) method is also used to estimate sea level trend to understand an uncertainty from different analysis tools. The three trend models—linear, quadratic, and exponential—are fitted to the amplitude time series of the trend mode so that future projection of sea level can be made. Based on a quadratic model, the rate of local sea level rise (SLR) is expected to be 4.63?±?1.1 mm year^?1 during 2010–2060. The estimates of “local” sea level trend vary up to ～30%. It should be noted that, although the three trend models estimate similar sea level trends during the observational period, the projected sea level trend and subsequent SLR differ significantly from one model to another and between the tide gauge data and the reconstruction data; this results in a substantial uncertainty in the future SLR around the Korean Peninsula.