scholarly journals What does global mean temperature tell us about local climate?

2015 ◽  
Vol 373 (2054) ◽  
pp. 20140426 ◽  
Author(s):  
Rowan Sutton ◽  
Emma Suckling ◽  
Ed Hawkins
Keyword(s):  
Climate Change ◽  
Climate Model ◽  
Surface Air Temperature ◽  
Internal Variability ◽  
Climate Impacts ◽  
Climate Projections ◽  
Local Climate ◽  
Forced Responses ◽  
The Relationship ◽  
Global Mean

The subject of climate feedbacks focuses attention on global mean surface air temperature (GMST) as the key metric of climate change. But what does knowledge of past and future GMST tell us about the climate of specific regions? In the context of the ongoing UNFCCC process, this is an important question for policy-makers as well as for scientists. The answer depends on many factors, including the mechanisms causing changes, the timescale of the changes, and the variables and regions of interest. This paper provides a review and analysis of the relationship between changes in GMST and changes in local climate, first in observational records and then in a range of climate model simulations, which are used to interpret the observations. The focus is on decadal timescales, which are of particular interest in relation to recent and near-future anthropogenic climate change. It is shown that GMST primarily provides information about forced responses, but that understanding and quantifying internal variability is essential to projecting climate and climate impacts on regional-to-local scales. The relationship between local forced responses and GMST is often linear but may be nonlinear, and can be greatly complicated by competition between different forcing factors. Climate projections are limited not only by uncertainties in the signal of climate change but also by uncertainties in the characteristics of real-world internal variability. Finally, it is shown that the relationship between GMST and local climate provides a simple approach to climate change detection, and a useful guide to attribution studies.

scholarly journals Uncertainty in the relationship between climate forcing and hydrological response in UK catchments

2011 ◽  
Vol 15 (3) ◽  
pp. 897-912 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals The relationship between climate forcing and hydrological response in UK catchments

2010 ◽  
Vol 7 (5) ◽  
pp. 7633-7667 ◽  
Author(s):  
N. W. Arnell
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Climate Model ◽  
Climate Forcing ◽  
Hydrological Response ◽  
Climate Scenarios ◽  
Global Mean Temperature ◽  
Mean Temperature ◽  
The Relationship ◽  
Global Mean

Abstract. This paper assesses the relationship between amount of climate forcing – as indexed by global mean temperature change – and hydrological response in a sample of UK catchments. It constructs climate scenarios representing different changes in global mean temperature from an ensemble of 21 climate models assessed in the IPCC AR4. The results show a considerable range in impact between the 21 climate models, with – for example – change in summer runoff at a 2 °C increase in global mean temperature varying between −40% and +20%. There is evidence of clustering in the results, particularly in projected changes in summer runoff and indicators of low flows, implying that the ensemble mean is not an appropriate generalised indicator of impact, and that the standard deviation of responses does not adequately characterise uncertainty. The uncertainty in hydrological impact is therefore best characterised by considering the shape of the distribution of responses across multiple climate scenarios. For some climate model patterns, and some catchments, there is also evidence that linear climate change forcings produce non-linear hydrological impacts. For most variables and catchments, the effects of climate change are apparent above the effects of natural multi-decadal variability with an increase in global mean temperature above 1 °C, but there are differences between catchments. Based on the scenarios represented in the ensemble, it is likely that the effect of climate change in northern upland catchments will be seen soonest in indicators of high flows, but in southern catchments effects will be apparent soonest in measures of summer and low flows. The uncertainty in response between different climate model patterns is considerably greater than the range due to uncertainty in hydrological model parameterisation.

scholarly journals Future runoff regime changes and their time of emergence for 93 catchments in Switzerland

2020 ◽  
Author(s):  
Regula Muelchi ◽  
Ole Rössler ◽  
Jan Schwanbeck ◽  
Rolf Weingartner ◽  
Olivia Martius
Keyword(s):  
Climate Change ◽  
Strong Influence ◽  
Climate Model ◽  
High Elevation ◽  
Snow Accumulation ◽  
Seasonal Patterns ◽  
Climate Projections ◽  
Local Climate ◽  
Runoff Change ◽  
Runoff Changes

Abstract. Assessments of climate change impacts on runoff regimes are essential for adaptation and mitigation planning. Changing runoff regimes and thus changing seasonal patterns of water availability have strong influence on various sectors such as agriculture, energy production or fishery. In this study, we use the most up to date local climate projections for Switzerland (CH2018) that were downscaled with a post-processing method (quantile mapping). This enables detailed information on changes in runoff regimes and their time of emergence for 93 rivers in Switzerland under three emission pathways RCP2.6, RCP4.5, and RCP8.5. Changes in seasonal patterns are projected with increasing winter runoff and decreasing summer and autumn runoff. Spring runoff is projected to increase in high elevation catchments and to decrease in lower lying catchments. Despite strong increases in winter and partly in spring, the yearly mean runoff is projected to decrease in most catchments. Results show a strong elevation dependence for the signal and magnitude of change. Compared to lower lying catchments, runoff changes in high elevation catchments (above 1500 masl) are larger in winter, spring, and summer due to the strong influence of reduced snow accumulation and earlier snow melt as well as glacier melt. Under RCP8.5 (RCP2.6) and for catchments with mean altitude below 1500 masl, average relative runoff change in winter is +27 % (+5 %), in spring −5 % (−6 %), in summer −31 % (−4 %), in autumn −21 % (−6 %), and −8 % (−4 %) throughout the year. For catchments with mean elevation above 1500 masl, runoff changes on average by +77 % (+24 %) in winter, by +28 % (+16 %) in spring, by −41 % (−9 %) in summer, by −15 % (−4 %) in autumn, and by −9 % (−0.6 %) in the yearly mean. The changes and the climate model agreement on the signal of change increase with increasing global mean temperatures or stronger emission scenarios. This amplification highlights the importance of climate change mitigation. Under RCP8.5, early times of emergence in winter (before 2065; period 2036–2065) and summer (before 2065) were found for catchments with mean altitudes above 1500 masl. Significant changes in catchments below 1500 masl emerge later in the century. However, not all catchments show a time of emergence in all seasons and in some catchments the detected significant changes are not persistent over time.

scholarly journals Climate Impacts from Afforestation and Deforestation in Europe

2019 ◽  
Vol 23 (1) ◽  
pp. 1-27 ◽  
Author(s):  
G. Strandberg ◽  
E. Kjellström
Keyword(s):  
Climate Change ◽  
Vegetation Change ◽  
Climate Model ◽  
Climate Impacts ◽  
Heat Fluxes ◽  
Maximum Temperature ◽  
Vegetation Changes ◽  
Near Surface ◽  
Local Climate ◽  
Mean Temperature

Abstract Changes in vegetation are known to have an impact on climate via biogeophysical effects such as changes in albedo and heat fluxes. Here, the effects of maximum afforestation and deforestation are studied over Europe. This is done by comparing three regional climate model simulations—one with present-day vegetation, one with maximum afforestation, and one with maximum deforestation. In general, afforestation leads to more evapotranspiration (ET), which leads to decreased near-surface temperature, whereas deforestation leads to less ET, which leads to increased temperature. There are exceptions, mainly in regions with little water available for ET. In such regions, changes in albedo are relatively more important for temperature. The simulated biogeophysical effect on seasonal mean temperature varies between 0.5° and 3°C across Europe. The effect on minimum and maximum temperature is larger than that on mean temperature. Increased (decreased) mean temperature is associated with an even larger increase (decrease) in maximum summer (minimum winter) temperature. The effect on precipitation is found to be small. Two additional simulations in which vegetation is changed in only one-half of the domain were also performed. These simulations show that the climatic effects from changed vegetation in Europe are local. The results imply that vegetation changes have had, and will have, a significant impact on local climate in Europe; the climatic response is comparable to climate change under RCP2.6. Therefore, effects from vegetation change should be taken into account when simulating past, present, and future climate for this region. The results also imply that vegetation changes could be used to mitigate local climate change.

scholarly journals Ocean–atmosphere interactions modulate irrigation's climate impacts

2016 ◽  
Vol 7 (4) ◽  
pp. 863-876 ◽  
Author(s):  
Nir Y. Krakauer ◽  
Michael J. Puma ◽  
Benjamin I. Cook ◽  
Pierre Gentine ◽  
Larissa Nazarenko
Keyword(s):  
Regional Climate ◽  
Surface Air Temperature ◽  
Climate Impacts ◽  
Irrigated Agriculture ◽  
Local Climate ◽  
Climate Effects ◽  
Ocean Atmosphere ◽  
Ocean Atmosphere Interaction ◽  
Atmosphere Interaction ◽  
Global Mean

Abstract. Numerous studies have focused on the local and regional climate effects of irrigated agriculture and other land cover and land use change (LCLUC) phenomena, but there are few studies on the role of ocean–atmosphere interaction in modulating irrigation climate impacts. Here, we compare simulations with and without interactive sea surface temperatures of the equilibrium effect on climate of contemporary (year 2000) irrigation geographic extent and intensity. We find that ocean–atmosphere interaction does impact the magnitude of global-mean and spatially varying climate impacts, greatly increasing their global reach. Local climate effects in the irrigated regions remain broadly similar, while non-local effects, particularly over the oceans, tend to be larger. The interaction amplifies irrigation-driven standing wave patterns in the tropics and midlatitudes in our simulations, approximately doubling the global-mean amplitude of surface temperature changes due to irrigation. The fractions of global area experiencing significant annual-mean surface air temperature and precipitation change also approximately double with ocean–atmosphere interaction. Subject to confirmation with other models, these findings imply that LCLUC is an important contributor to climate change even in remote areas such as the Southern Ocean, and that attribution studies should include interactive oceans and need to consider LCLUC, including irrigation, as a truly global forcing that affects climate and the water cycle over ocean as well as land areas.

scholarly journals River runoff in Switzerland in a changing climate – runoff regime changes and their time of emergence

2021 ◽  
Vol 25 (6) ◽  
pp. 3071-3086
Author(s):  
Regula Muelchi ◽  
Ole Rössler ◽  
Jan Schwanbeck ◽  
Rolf Weingartner ◽  
Olivia Martius
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
High Elevation ◽  
Snow Accumulation ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Climate Signal ◽  
Local Climate ◽  
Runoff Changes ◽  
Global Mean

Abstract. Assessments of climate change impacts on runoff regimes are essential to climate change adaptation and mitigation planning. Changing runoff regimes and thus changing seasonal patterns of water availability strongly influence various economic sectors such as agriculture, energy production, and fishery and also affect river ecology. In this study, we use new transient hydrological scenarios driven by the most up-to-date local climate projections for Switzerland, the Swiss Climate Change Scenarios. These provide detailed information on changes in runoff regimes and their time of emergence for 93 rivers in Switzerland under three Representative Concentration Pathways (RCPs): RCP2.6, RCP4.5, and RCP8.5. These transient scenarios also allow changes to be framed as a function of global mean temperature. The new projections for seasonal runoff changes largely confirm the sign of changes in runoff from previous hydrological scenarios with increasing winter runoff and decreasing summer and autumn runoff. Spring runoff is projected to increase in high-elevation catchments and to decrease in lower-lying catchments. Despite the increases in winter and some increases in spring, the annual mean runoff is projected to decrease in most catchments. Compared to lower-lying catchments, runoff changes in high-elevation catchments (above 1500 m a.s.l.) are larger in winter, spring, and summer due to the large influence of reduced snow accumulation and earlier snowmelt and glacier melt. The changes in runoff and the agreement between climate models on the sign of change both increase with increasing global mean temperatures and higher-emission scenarios. This amplification highlights the importance of climate change mitigation. The time of emergence is the time when the climate signal emerges significantly from natural variability. Under RCP8.5, times of emergence were found early, before the period 2036–2065, in winter and summer for catchments with mean altitudes above 1500 m a.s.l. Significant changes in catchments below 1500 m a.s.l. emerge later in the century. Not all catchments show significant changes in the distribution of seasonal means; thus, no time of emergence could be determined in these catchments. Furthermore, the significant changes of seasonal mean runoff are not persistent over time in some catchments due to nonlinear changes in runoff.

scholarly journals Amplified Impact of Climate Change on Fine-Sediment Delivery to a Subsiding Coast, Humboldt Bay, California

2021 ◽  
Author(s):  
Jennifer A. Curtis ◽  
Lorraine E. Flint ◽  
Michelle A. Stern ◽  
Jack Lewis ◽  
Randy D. Klein
Keyword(s):  
Climate Change ◽  
Climate Change Impacts ◽  
Baseline Period ◽  
Climate Impacts ◽  
Sediment Supply ◽  
Balance Model ◽  
Climate Projections ◽  
Sediment Delivery ◽  
Beneficial Reuse ◽  
Coastal Margin

AbstractIn Humboldt Bay, tectonic subsidence exacerbates sea-level rise (SLR). To build surface elevations and to keep pace with SLR, the sediment demand created by subsidence and SLR must be balanced by an adequate sediment supply. This study used an ensemble of plausible future scenarios to predict potential climate change impacts on suspended-sediment discharge (Qss) from fluvial sources. Streamflow was simulated using a deterministic water-balance model, and Qss was computed using statistical sediment-transport models. Changes relative to a baseline period (1981–2010) were used to assess climate impacts. For local basins that discharge directly to the bay, the ensemble means projected increases in Qss of 27% for the mid-century (2040–2069) and 58% for the end-of-century (2070–2099). For the Eel River, a regional sediment source that discharges sediment-laden plumes to the coastal margin, the ensemble means projected increases in Qss of 53% for the mid-century and 99% for the end-of-century. Climate projections of increased precipitation and streamflow produced amplified increases in the regional sediment supply that may partially or wholly mitigate sediment demand caused by the combined effects of subsidence and SLR. This finding has important implications for coastal resiliency. Coastal regions with an increasing sediment supply may be more resilient to SLR. In a broader context, an increasing sediment supply from fluvial sources has global relevance for communities threatened by SLR that are increasingly building resiliency to SLR using sediment-based solutions that include regional sediment management, beneficial reuse strategies, and marsh restoration.

scholarly journals Sensitivity of projected climate impacts to climate model weighting: multi-sector analysis in eastern Africa

2021 ◽  
Vol 164 (3-4) ◽  
Author(s):  
Seshagiri Rao Kolusu ◽  
Christian Siderius ◽  
Martin C. Todd ◽  
Ajay Bhave ◽  
Declan Conway ◽  
...  
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Investment Decisions ◽  
Climate Impacts ◽  
Future Climate ◽  
Eastern Africa ◽  
Climate Projections ◽  
Systematic Effect ◽  
Risk Profiles ◽  
Model Weighting

AbstractUncertainty in long-term projections of future climate can be substantial and presents a major challenge to climate change adaptation planning. This is especially so for projections of future precipitation in most tropical regions, at the spatial scale of many adaptation decisions in water-related sectors. Attempts have been made to constrain the uncertainty in climate projections, based on the recognised premise that not all of the climate models openly available perform equally well. However, there is no agreed ‘good practice’ on how to weight climate models. Nor is it clear to what extent model weighting can constrain uncertainty in decision-relevant climate quantities. We address this challenge, for climate projection information relevant to ‘high stakes’ investment decisions across the ‘water-energy-food’ sectors, using two case-study river basins in Tanzania and Malawi. We compare future climate risk profiles of simple decision-relevant indicators for water-related sectors, derived using hydrological and water resources models, which are driven by an ensemble of future climate model projections. In generating these ensembles, we implement a range of climate model weighting approaches, based on context-relevant climate model performance metrics and assessment. Our case-specific results show the various model weighting approaches have limited systematic effect on the spread of risk profiles. Sensitivity to climate model weighting is lower than overall uncertainty and is considerably less than the uncertainty resulting from bias correction methodologies. However, some of the more subtle effects on sectoral risk profiles from the more ‘aggressive’ model weighting approaches could be important to investment decisions depending on the decision context. For application, model weighting is justified in principle, but a credible approach should be very carefully designed and rooted in robust understanding of relevant physical processes to formulate appropriate metrics.

scholarly journals Cross-validation of bias-corrected climate simulations is misleading

2018 ◽  
Vol 22 (9) ◽  
pp. 4867-4873 ◽  
Author(s):  
Douglas Maraun ◽  
Martin Widmann
Keyword(s):  
Climate Change ◽  
Bias Correction ◽  
Cross Validation ◽  
Climate Model ◽  
False Negative ◽  
Internal Variability ◽  
Validation Period ◽  
Climate Simulations ◽  
Free Running ◽  
The Difference

Abstract. We demonstrate both analytically and with a modelling example that cross-validation of free-running bias-corrected climate change simulations against observations is misleading. The underlying reasoning is as follows: a cross-validation can have in principle two outcomes. A negative (in the sense of not rejecting a null hypothesis), if the residual bias in the validation period after bias correction vanishes; and a positive, if the residual bias in the validation period after bias correction is large. It can be shown analytically that the residual bias depends solely on the difference between the simulated and observed change between calibration and validation periods. This change, however, depends mainly on the realizations of internal variability in the observations and climate model. As a consequence, the outcome of a cross-validation is also dominated by internal variability, and does not allow for any conclusion about the sensibility of a bias correction. In particular, a sensible bias correction may be rejected (false positive) and a non-sensible bias correction may be accepted (false negative). We therefore propose to avoid cross-validation when evaluating bias correction of free-running bias-corrected climate change simulations against observations. Instead, one should evaluate non-calibrated temporal, spatial and process-based aspects.

scholarly journals Ensemble Projections of Regional Climatic Changes over Ontario, Canada

2015 ◽  
Vol 28 (18) ◽  
pp. 7327-7346 ◽  
Author(s):  
Xiuquan Wang ◽  
Guohe Huang ◽  
Jinliang Liu ◽  
Zhong Li ◽  
Shan Zhao
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Regional Climate ◽  
Climatic Changes ◽  
Climate Projections ◽  
Climate Change Scenarios ◽  
Local Climate ◽  
Ensemble Simulations ◽  
Extreme Precipitation Events ◽  
Data Portal

Abstract In this study, high-resolution climate projections over Ontario, Canada, are developed through an ensemble modeling approach to provide reliable and ready-to-use climate scenarios for assessing plausible effects of future climatic changes at local scales. The Providing Regional Climates for Impacts Studies (PRECIS) regional modeling system is adopted to conduct ensemble simulations in a continuous run from 1950 to 2099, driven by the boundary conditions from a HadCM3-based perturbed physics ensemble. Simulations of temperature and precipitation for the baseline period are first compared to the observed values to validate the performance of the ensemble in capturing the current climatology over Ontario. Future projections for the 2030s, 2050s, and 2080s are then analyzed to help understand plausible changes in its local climate in response to global warming. The analysis indicates that there is likely to be an obvious warming trend with time over the entire province. The increase in average temperature is likely to be varying within [2.6, 2.7]°C in the 2030s, [4.0, 4.7]°C in the 2050s, and [5.9, 7.4]°C in the 2080s. Likewise, the annual total precipitation is projected to increase by [4.5, 7.1]% in the 2030s, [4.6, 10.2]% in the 2050s, and [3.2, 17.5]% in the 2080s. Furthermore, projections of rainfall intensity–duration–frequency (IDF) curves are developed to help understand the effects of global warming on extreme precipitation events. The results suggest that there is likely to be an overall increase in the intensity of rainfall storms. Finally, a data portal named Ontario Climate Change Data Portal (CCDP) is developed to ensure decision-makers and impact researchers have easy and intuitive access to the refined regional climate change scenarios.

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