Global Climate Model Projections Research Articles

Soil response to long-term projections of extreme temperature and precipitation in the southern La Plata Basin

Projected changes were estimated considering the main variables which take part in soil-atmosphere interaction. The analysis was focused on the potential impact of these changes on soil hydric condition under extreme precipitation and evapotranspiration, using the combination of Global Climate Models (GCMs) and observational data. The region of study is the southern La Plata Basin that covers part of Argentine territory, where rainfed agriculture production is one of the most important economic activities. Monthly precipitation and maximum and minimum temperatures were used from high quality-controlled observed data from 46 meteorological stations and the ensemble of seven CMIP5 GCMs in two periods: 1970–2005 and 2065–2100. Projected changes in monthly effective temperature and precipitation were analysed. These changes were combined with observed series for each probabilistic interval. The result was used as input variables for the water balance model in order to obtain consequent soil hydric condition (deficit or excess). Effective temperature and precipitation are expected to increase according to the projections of GCMs, with few exceptions. The analysis revealed increase (decrease) in the prevalence of evapotranspiration over precipitation, during spring (winter). Projections for autumn months show precipitation higher than potential evapotranspiration more frequently. Under dry extremes, the analysis revealed higher projected deficit conditions, impacting on crop development. On the other hand, under wet extremes, excess would reach higher values only in particular months. During December, projected increase in temperatures reduces the impact of extreme high precipitation but favours deficit conditions, affecting flower-fructification stage of summer crops.

The 1200 year composite ice core record of Aleutian Low intensification

AbstractFuture changes in North Pacific wintertime climate will be largely determined by the response of the Aleutian Low (ALow) pressure system to anthropogenic forcing. Although the ALow has intensified over the twentieth century, global climate model projections of future ALow variability are equivocal. In order to evaluate decadal to centennial ALow forcing mechanisms and provide context for the modern intensification, here we combine a new Denali ice core (Alaska) sea‐salt sodium record with the Mount Logan ice core (Yukon) sodium record to develop a composite 1200 year record of ALow variability. The composite record indicates that the recent secular ALow intensification began circa 1741 and is unprecedented in magnitude and duration over the past millennium. North Pacific ice core snow accumulation and stable isotope records are consistent with this interpretation. The ALow intensification is associated with warming tropical Pacific sea surface temperatures, consistent with dynamic theory and instrumental correlations.

Identifying water resources management strategies in adaptation to climate change under uncertainty

In this study, an integrated simulation-based allocation modeling system (ISAMS) is developed for identifying water resources management strategies in response to climate change. The ISAMS incorporates global climate models (GCMs), a semi-distributed land use-based runoff process (SLURP) model, and a multistage interval-stochastic programming (MISP) approach within a general framework. The ISAMS can not only handle uncertainties expressed as probability distributions and interval values but also reveal climate change impacts on water resources allocation under different projections of GCMs. The ISAMS is then applied to the Kaidu-kongque watershed with cold arid characteristics in the Tarim River Basin (the largest inland watershed basin in China) for demonstrating its efficiency. Results reveal that different climate change models corresponding to various projections (e.g., precipitation and temperature) would lead to changed water resources allocation patterns. Variations in water availability and demand due to uncertainties could result in different water allocation targets and shortages. A variety of decision alternatives about water allocations adaptive to climate change are generated under combinations of different global climate models and ecological water release plans. These findings indicate that understanding the uncertainties in water resources system, building adaptive methods for generating sustainable water allocation patterns, and taking actions for mitigating water shortage problems are key adaptation strategies responding to climate change.

Climate Change driven evolution of hazards to Europe’s transport infrastructure throughout the twenty-first century

Road authorities, freight, and logistic industries face a multitude of challenges in a world changing at an ever growing pace. While globalization, changes in technology, demography, and traffic, for instance, have received much attention over the bygone decades, climate change has not been treated with equal care until recently. However, since it has been recognized that climate change jeopardizes many business areas in transport, freight, and logistics, research programs investigating future threats have been initiated. One of these programs is the Conference of European Directors of Roads’ (CEDR) Transnational Research Programme (TRP), which emerged about a decade ago from a cooperation between European National Road Authorities and the EU. This paper presents findings of a CEDR project called CliPDaR, which has been designed to answer questions from road authorities concerning climate-driven future threats to transport infrastructure. Pertaining results are based on two potential future socio-economic pathways of mankind (one strongly economically oriented “A2” and one more balanced scenario “A1B”), which are used to drive global climate models (GCMs) producing global and continental scale climate change projections. In order to achieve climate change projections, which are valid on regional scales, GCM projections are downscaled by regional climate models. Results shown here originate from research questions raised by European Road Authorities. They refer to future occurrence frequencies of severely cold winter seasons in Fennoscandia, to particularly hot summer seasons in the Iberian Peninsula and to changes in extreme weather phenomena triggering landslides and rutting in Central Europe. Future occurrence frequencies of extreme winter and summer conditions are investigated by empirical orthogonal function analyses of GCM projections driven with by A2 and A1B pathways. The analysis of future weather phenomena triggering landslides and rutting events requires downscaled climate change projections. Hence, corresponding results are based on an ensemble of RCM projections, which was available for the A1B scenario. All analyzed risks to transport infrastructure are found to increase over the decades ahead with accelerating pace towards the end of this century. Mean Fennoscandian winter temperatures by the end of this century may match conditions of rather warm winter season experienced in the past and particularly warm future winter temperatures have not been observed so far. This applies in an even more pronounced manner to summer seasons in the Iberian Peninsula. Occurrence frequencies of extreme climate phenomena triggering landslides and rutting events in Central Europe are also projected to rise. Results show spatially differentiated patterns and indicate accelerated rates of increases.

Bayesian multi-model projections of extreme hydroclimatic events under RCPs scenarios

A Bayesian multi-model inference framework was used to assess the changes in the occurrence of extreme hydroclimatic events in four major river basins in China (i.e., Liaohe River Basin, Yellow River Basin, Yangtze River Basin, and Pearl River Basin) under RCP2.6, RCP4.5, and RCP8.5 scenarios using multiple global climate model projections from the IPCC Fifth Assessment Report. The results projected more summer days and fewer frost days in 2006–2099. The ensemble prediction shows the Pearl River Basin is projected to experience more summer days than other basins with the increasing trend of 16.3, 38.0, and 73.0 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively. Liaohe River Basin and Yellow River Basin are forecasted to become wetter and warmer with the co-occurrence of increases in summer days and wet days. Very heavy precipitation days (R20, daily precipitation ≥20 mm) are projected to increase in all basins. The R20 in the Yangtze River Basin are projected to have the highest change rate in 2006–2099 of 1.8, 2.5, and 3.8 d per 100 years for RCP2.6, RCP4.5 and RCP8.5, respectively.

Refining multi-model projections of temperature extremes by evaluation against land–atmosphere coupling diagnostics

Abstract. The Earth's land surface and the atmosphere are strongly interlinked through the exchange of energy and matter. This coupled behaviour causes various land–atmosphere feedbacks, and an insufficient understanding of these feedbacks contributes to uncertain global climate model projections. For example, a crucial role of the land surface in exacerbating summer heat waves in midlatitude regions has been identified empirically for high-impact heat waves, but individual climate models differ widely in their respective representation of land–atmosphere coupling. Here, we compile an ensemble of 54 combinations of observations-based temperature (T) and evapotranspiration (ET) benchmarking datasets and investigate coincidences of T anomalies with ET anomalies as a proxy for land–atmosphere interactions during periods of anomalously warm temperatures. First, we demonstrate that a large fraction of state-of-the-art climate models from the Coupled Model Intercomparison Project (CMIP5) archive produces systematically too frequent coincidences of high T anomalies with negative ET anomalies in midlatitude regions during the warm season and in several tropical regions year-round. These coincidences (high T, low ET) are closely related to the representation of temperature variability and extremes across the multi-model ensemble. Second, we derive a land-coupling constraint based on the spread of the T–ET datasets and consequently retain only a subset of CMIP5 models that produce a land-coupling behaviour that is compatible with these benchmark estimates. The constrained multi-model simulations exhibit more realistic temperature extremes of reduced magnitude in present climate in regions where models show substantial spread in T–ET coupling, i.e. biases in the model ensemble are consistently reduced. Also the multi-model simulations for the coming decades display decreased absolute temperature extremes in the constrained ensemble. On the other hand, the differences between projected and present-day climate extremes are affected to a lesser extent by the applied constraint, i.e. projected changes are reduced locally by around 0.5 to 1 °C – but this remains a local effect in regions that are highly sensitive to land–atmosphere coupling. In summary, our approach offers a physically consistent, diagnostic-based avenue to evaluate multi-model ensembles and subsequently reduce model biases in simulated and projected extreme temperatures.

Effects of climate change on probable maximum precipitation: A sensitivity study over the Alabama‐Coosa‐Tallapoosa River Basin

AbstractProbable maximum precipitation (PMP), defined as the largest rainfall depth that could physically occur under a series of adverse atmospheric conditions, has been an important design criterion for critical infrastructures such as dams and nuclear power plants. To understand how PMP may respond to projected future climate forcings, we used a physics‐based numerical weather simulation model to estimate PMP across various durations and areas over the Alabama‐Coosa‐Tallapoosa (ACT) River Basin in the southeastern United States. Six sets of Weather Research and Forecasting (WRF) model experiments driven by both reanalysis and global climate model projections, with a total of 120 storms, were conducted. The depth‐area‐duration relationship was derived for each set of WRF simulations and compared with the conventional PMP estimates. Our results showed that PMP driven by projected future climate forcings is higher than 1981–2010 baseline values by around 20% in the 2021–2050 near‐future and 44% in the 2071–2100 far‐future periods. The additional sensitivity simulations of background air temperature warming also showed an enhancement of PMP, suggesting that atmospheric warming could be one important factor controlling the increase in PMP. In light of the projected increase in precipitation extremes under a warming environment, the reasonableness and role of PMP deserve more in‐depth examination.

Monitoring and projecting snow on Hawaii Island

AbstractThe highest mountain peaks on Hawaii Island are snow covered for part of almost every year. This snow has aesthetic and recreational value as well as cultural significance for residents and visitors. Thus far there have been almost no systematic observations of snowfall, snow cover, or snow depth in Hawaii. Here we use satellite observations to construct a daily index of Hawaii Island snow cover starting from 2000. The seasonal mean of our index displays large interannual variations that are correlated with the seasonal mean freezing level and frequency of trade wind inversions as determined from nearby balloon soundings. Our snow cover index provides a diagnostic for monitoring climate variability and trends within the extensive area of the globe dominated by the North Pacific trade wind meteorological regime. We have also conducted simulations of the Hawaii climate with a regional atmospheric model. Retrospective simulations for 1990–2015 were run with boundary conditions prescribed from gridded observational analyses. Simulations for the end of 21st century employed boundary conditions based on global climate model projections that included standard scenarios for anticipated anthropogenic climate forcing. The future projections indicate that snowfall will nearly disappear by the end of the current century.

Downscaling wind and wavefields for 21st century coastal flood hazard projections in a region of complex terrain

AbstractWhile global climate models (GCMs) provide useful projections of near‐surface wind vectors into the 21st century, resolution is not sufficient enough for use in regional wave modeling. Statistically downscaled GCM projections from Multivariate Adaptive Constructed Analogues provide daily averaged near‐surface winds at an appropriate spatial resolution for wave modeling within the orographically complex region of San Francisco Bay, but greater resolution in time is needed to capture the peak of storm events. Short‐duration high wind speeds, on the order of hours, are usually excluded in statistically downscaled climate models and are of key importance in wave and subsequent coastal flood modeling. Here we present a temporal downscaling approach, similar to constructed analogues, for near‐surface winds suitable for use in local wave models and evaluate changes in wind and wave conditions for the 21st century. Reconstructed hindcast winds (1975–2004) recreate important extreme wind values within San Francisco Bay. A computationally efficient method for simulating wave heights over long time periods was used to screen for extreme events. Wave hindcasts show resultant maximum wave heights of 2.2 m possible within the Bay. Changes in extreme over‐water wind speeds suggest contrasting trends within the different regions of San Francisco Bay, but 21th century projections show little change in the overall magnitude of extreme winds and locally generated waves

Modeling the effect of land use and climate change scenarios on future soil loss rate in Kasilian watershed of northern Iran

Accelerated erosion processes caused by global climate and land use changes in many regions of the world constitute a major restrictive factor in their sustainability. This study proposes a method to estimate soil loss rate under changes in future land use and climate in Kasilian watershed of northern Iran within two periods. The first period is related to current climate and land use (1991–2010), and the second concerns climate and land use scenarios (2011–2030). Downscaling global climate model projections of future climate was applied at the regional scale. A statistical downscaling model was then used to downscale precipitation for three scenarios, i.e., 10% increase in rainfall, 10% decrease in rainfall, and unchanged rainfall. Next, cellular automata–Markov model was used for characterization based on two scenarios of land use future that were designed using suitability maps. The soil loss mean for the current period was found to be 6.3 t $${\text{ha}}^{ - 1} \;{\text{year}}^{ - 1}$$ , thereby indicating a low sustainability of soils. The results of simulated soil loss maps indicate a similar pattern in spatial distribution of loss rates compared with those of current periods, but the amount of risk has increased such that simulated erosion mean was 31–58% higher than the current period in all scenarios. Soil loss is thoroughly influenced by climate and land cover patterns in future. In other words, rainfall erosivity has increased by 20 MJ mm $${\text{ha}}^{ - 1} {\text{h}}^{ - 1} {\text{year}}^{ - 1}$$ , based on unchanged rainfall scenario and National Centers for Environmental Prediction data, simulated that cover management factor has increased by 35% compared with the current period. However, simulations indicated that land use changes may potentially induce much larger changes in erosion. The results also showed that soil loss is closely related to land use change and various scenarios of climate change and that revised universal soil loss equation is suitable model to investigate these relationships.

Addressing rainfall data selection uncertainty using connections between rainfall and streamflow

Studies of the hydroclimate at regional scales rely on spatial rainfall data products, derived from remotely-sensed (RS) and in-situ (IS, rain gauge) observations. Because regional rainfall cannot be directly measured, spatial data products are biased. These biases pose a source of uncertainty in environmental analyses, attributable to the choices made by data-users in selecting a representation of rainfall. We use the rainforest-savanna transition region in Brazil to show differences in the statistics describing rainfall across nine RS and interpolated-IS daily rainfall datasets covering the period of 1998–2013. These differences propagate into estimates of temporal trends in monthly rainfall and descriptive hydroclimate indices. Rainfall trends from different datasets are inconsistent at river basin scales, and the magnitude of index differences is comparable to the estimated bias in global climate model projections. To address this uncertainty, we evaluate the correspondence of different rainfall datasets with streamflow from 89 river basins. We demonstrate that direct empirical comparisons between rainfall and streamflow provide a method for evaluating rainfall dataset performance across multiple areal (basin) units. These results highlight the need for users of rainfall datasets to quantify this “data selection uncertainty” problem, and either justify data use choices, or report the uncertainty in derived results.

Future Projections of Heat and Fire-Risk Indices for the Contiguous United States

AbstractIncreasing temperatures and changes in precipitation associated with climate change are expected to have increasing impacts on the contiguous United States in the coming decades, including military training and outdoor activities in general. Projections of daily temperature and precipitation from multiple global climate model projections are used to calculate the days with high heat and drought indices, which also indicate heat-related illness and fire risks. The heat stress index [the wet-bulb black-globe temperature (WBGT)] and drought index (Keetch–Byram drought index) are calculated from climate model projections from 1950–99 and 2070–99 and compared with those calculated from observed weather data for stations across the contiguous United States. Significant increases are projected across the southern United States for the days in the high index category above 32.2°C and high drought category. The higher humidity of the southeastern United States contributes to high WBGT as well, while the air temperatures are greatest in the Southwest. The highest WBGT categories occur for the daytime maximum; however, daily minimum WBGTs in the restricting category also are projected for more than 50 days per year in the Southeast. The high drought index is projected to increase across the Great Plains and the central and southern United States, affecting wildfire risks for military and public lands, including large agricultural regions. These projected impacts can be characterized as widespread and severe for large portions of the United States, with expected impacts to military planning, public health and safety, and natural resource management.

Selection of a representative subset of global climate models that captures the profile of regional changes for integrated climate impacts assessment

We present the Representative Temperature and Precipitation (T&P) GCM Subsetting Approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative T&P GCM Subsetting Approach identifies five individual GCMs that capture a profile of the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate coherence across space, time, and greenhouse gas concentration pathway. The Representative T&P GCM Subsetting Approach provides a quantitative basis for the determination of useful GCM subsets, provides a practical and coherent approach where previous assessments selected solely on availability of scenarios, and may be extended for application to a range of scales and sectoral impacts.

Potential future risk of cholera due to climate change in northern Nigeria

Cholera is one of the infectious diseases that remains a major health burden in West-Africa and especially in Nigeria. Several studies have raised concern that climate change may exacerbate the risk of the disease in the future. Projecting the future risk of this disease is essential, especially for regions where the projected climate change impacts, and infectious disease risk, are both large. Projections were made by forcing an empirical model of cholera with monthly simulations of four meteorological variables from an ensemble of ten statistically downscaled global climate model projections for Representative Concentration Pathways 2.6, 6.0 and 8.5 scenarios. Result indicates statistically significant increases in cases during April-September for RCPs 6.0 and 8.5 in both near (2020-2035) and far (2060-2075) future. The months with the largest increases coincide with the months (May and June) in which maximum temperature increases are also large. Cases only showed potential increases in the wettest months of July and August in the far future projections for RCPs 6.5 (8.3 and 7.9%) and 8.0 (17 and 21%) respectively. Keywords: Climate change; Cholera; Projections; Nigeria

Evaluating extreme climate indices from CMIP3&5 global climate models and reanalysis data sets: a case study for present climate in the Andes of Ecuador

ABSTRACTThe reliability of climate models depends ultimately on their adequacy in relevant real situations. However, climate in mountains, a very sensitive system, is scarcely monitored, making the assessment of global climate models (GCMs) projections problematic. This is even more critical for tropical mountain regions, where complex atmospheric processes acting across scales are specially challenging for GCMs. To help bridge this gap, we evaluated the representation of extreme climate indices by GCMs and reanalysis data in the Andes of Ecuador. This work presents an intercomparison of 11 climate precipitation indices (Climate Change Detection and Indices, ETCCDIs) reconstructed for the period 1 January 1981–31 December 2000 using the data of six climate stations situated in a medium‐sized Andean catchment in southern Ecuador, reanalysis data sets (RAD) ERA40, ERA‐Interim, NCEP/NCAR Reanalysis 1 (NCEP/NCAR‐R1) and NCEP/DOE Reanalysis 2 (NCEP/DOE‐R2), and the data sets of 19 and 29 models of the Coupled Model Intercomparison Project, Phases 3 and 5 (CMIP3&5). Temporal and spatial analysis highlights that the values and the variability of ETCCDIs based on reanalysis and CMIP3&5 data overestimate observations, especially in ENSO years. However, frequency‐type indices are in general better captured than amount‐related indices in RAD. In general, reanalysis data displayed a similar uncertainty as the CMIP model data sets and some indices present lower uncertainty. The uncertainty of ETCCDIs based on CMIP5 remains similar to CMIP3 GCMs, with small variations. The indices using NCEP/NCAR‐R1, NCEP/DOE‐R2, and ERA‐Interim data performed better than those obtained with the ERA40 data sets, with no discernible improvement between both NCEP products. It can be concluded that for the given study region CMIP3&5 models and reanalysis products with respectively good and poor performance, exist, however data should be carefully screened before use. Furthermore, these results confirm that the specificity of the studied region is a key to identify limiting aspects on the GCMs and reanalysis extreme climate representation.

Climate Change Impact on Monthly Precipitation Wet and Dry Spells in Arid Regions: Case Study over Wadi Al-Lith Basin

Durations of monthly precipitation wet and dry spells are calculated using historical records and regional climate model (RCM) simulations for the Wadi Al-Lith basin in western Saudi Arabia. The characteristics of durations of wet and dry spells are based on the 50% risk level corresponding to the monthly records for average regional precipitation. The duration of wet spells in the model data is compared with observations for the base period 1971–2000. The impact of climate change on the durations of wet and dry spells is obtained using three global climate models projections with RCP4.5 and RCP8.5 scenarios downscaled by RCM. The probability distribution functions (PDFs) of the climate model scenarios and the precipitation records for the base period prove that climate change has a clear impact on the durations of wet and dry spells over the study area. There is an increase in wet spells frequency in the far future (2070–2099) compared to the near future (2020–2049). The increase in wet spells can be partly explained by the increase in extreme rainfall events and by the decrease in dry spells expected to occur over the study area towards the end of 21st century.

Local-scale projections of coral reef futures and implications of the Paris Agreement.

Increasingly frequent severe coral bleaching is among the greatest threats to coral reefs posed by climate change. Global climate models (GCMs) project great spatial variation in the timing of annual severe bleaching (ASB) conditions; a point at which reefs are certain to change and recovery will be limited. However, previous model-resolution projections (~1 × 1°) are too coarse to inform conservation planning. To meet the need for higher-resolution projections, we generated statistically downscaled projections (4-km resolution) for all coral reefs; these projections reveal high local-scale variation in ASB. Timing of ASB varies >10 years in 71 of the 87 countries and territories with >500 km2 of reef area. Emissions scenario RCP4.5 represents lower emissions mid-century than will eventuate if pledges made following the 2015 Paris Climate Change Conference (COP21) become reality. These pledges do little to provide reefs with more time to adapt and acclimate prior to severe bleaching conditions occurring annually. RCP4.5 adds 11 years to the global average ASB timing when compared to RCP8.5; however, >75% of reefs still experience ASB before 2070 under RCP4.5. Coral reef futures clearly vary greatly among and within countries, indicating the projections warrant consideration in most reef areas during conservation and management planning.

Implications of future climate on water availability in the western Canadian river basins

ABSTRACTPrecipitation, temperature, and evaporative demand are the most dominant factors affecting water availability in a region. This study examines projected changes in these hydro‐climatic variables over western Canada under two greenhouse gas emissions scenarios using statistically downscaled, high resolution climate data generated by six Global Climate Models (GCMs) from the latest Coupled Model Intercomparison Project (CMIP5). Potential changes in the spatial and seasonal distributions of water availability over nine major western Canadian river basins are examined by computing the 3‐ and 12‐month standardized precipitation and evapotranspiration indices (SPEI‐3 and SPEI‐12). While individual GCM projections vary on the rate and seasonality of changes, they all indicate similar spatial and temporal patterns. The highest projected increases in precipitation and temperature are primarily in the northern basins, with some decreases in summer precipitation in the southern basins. The evolution of the SPEI‐12 values for the southern basins such as Columbia, Saskatchewan, Fraser and Athabasca indicate a gradual increase in the magnitude and duration of water deficit, while the reverse was found for most of the northern basins such as Peel/Lower Mackenzie, Liard, and Northern Pacific that show a gradual increase in water surplus on an annual basis. The SPEI‐3, however, shows that almost all river basins in western Canada, with the exception of Peel/Lower Mackenzie that are located in the extreme north of the study region, are projected to experience decreasing water availability in summer. In general, the study highlights the potential changes in the spatial and seasonal distribution of western Canadian water resources and sets the stage for a more detailed and process based hydro‐climate modelling study to be conducted in the region.

Impacts of rising air temperatures on electric transmission ampacity and peak electricity load in the United States

Climate change may constrain future electricity supply adequacy by reducing electric transmission capacity and increasing electricity demand. The carrying capacity of electric power cables decreases as ambient air temperatures rise; similarly, during the summer peak period, electricity loads typically increase with hotter air temperatures due to increased air conditioning usage. As atmospheric carbon concentrations increase, higher ambient air temperatures may strain power infrastructure by simultaneously reducing transmission capacity and increasing peak electricity load. We estimate the impacts of rising ambient air temperatures on electric transmission ampacity and peak per-capita electricity load for 121 planning areas in the United States using downscaled global climate model projections. Together, these planning areas account for roughly 80% of current peak summertime load. We estimate climate-attributable capacity reductions to transmission lines by constructing thermal models of representative conductors, then forcing these models with future temperature projections to determine the percent change in rated ampacity. Next, we assess the impact of climate change on electricity load by using historical relationships between ambient temperature and utility-scale summertime peak load to estimate the extent to which climate change will incur additional peak load increases. We find that by mid-century (2040–2060), increases in ambient air temperature may reduce average summertime transmission capacity by 1.9%–5.8% relative to the 1990–2010 reference period. At the same time, peak per-capita summertime loads may rise by 4.2%–15% on average due to increases in ambient air temperature. In the absence of energy efficiency gains, demand-side management programs and transmission infrastructure upgrades, these load increases have the potential to upset current assumptions about future electricity supply adequacy.

Uncertainty in climate projections for the 21st century northwest European shelf seas

There are a number of sources of uncertainty that impact climate projections for regional seas. We have assessed the impact that uncertain large-scale climate forcings have on the projections for the north-west European shelf seas. An ensemble of global Atmosphere-Ocean climate model (GCM) projections made by perturbed (atmospheric) parameter model variants which were designed to span uncertainty in climate sensitivity, was dynamically downscaled with the shelf seas model POLCOMS. The simulations were run as transient experiments (from 1952 to 2098) under a medium emissions scenario (SRES A1B). This study has focused on centennial changes over the period 2069–2098 relative to 1960–1989, but also refers to the full transient simulation to assess the significance of projected changes given interannual and low-frequency variability. The ensemble mean of the POLCOMS projections showed a shelf and annual mean Sea Surface Temperature (SST) rise of 2.90°C (±2σ=0.82°C), and a Sea Surface Salinity (SSS) freshening of −0.41psu (±2σ=0.47psu) between these periods. We described the spread in a field for a particular period using the variances associated with both the time mean ensemble dispersion (ensemble variance) and with the interannual variability. For SST in the present-day period, the magnitudes of both ensemble and interannual variance were fairly spatially homogenous. While the future interannual variance is of similar magnitude to that of the present day, the ensemble variance increased considerably into the future period. For SSS, both sources of variance were more spatially heterogeneous, and both increased into the future period. We investigated relationships between the projected shelf seas changes across the ensemble and changes in the large-scale climate forcing. We found that the near surface-air temperature from the driving GCM (averaged over the domain) and the GCM surface salinity to the west of the POLCOMS domain are good proxies for the changes within the shelf seas. We then compared these GCM indicators of shelf changes in our ensemble (under A1B) to the same measures across a number of CMIP5 models, under the RCP6.0 and RCP8.5 scenarios. The spread of these indicators, for our ensemble, fall within the range of the CMIP5 models (particularly under RCP8.5), suggesting our shelf projections would be consistent with an ensemble of projections driven by CMIP5 models.