Past and future polar amplification of climate change: climate model intercomparisons and ice-core constraints

Climate model simulations available from the PMIP1, PMIP2 and CMIP (IPCC-AR4) intercomparison projects for past and future climate change simulations are examined in terms of polar temperature changes in comparison to global temperature changes and with respect to pre-industrial reference simulations. For the mid-Holocene (MH, 6,000 years ago), the models are forced by changes in the Earth’s orbital parameters. The MH PMIP1 atmosphere-only simulations conducted with sea surface temperatures fixed to modern conditions show no MH consistent response for the poles, whereas the new PMIP2 coupled atmosphere–ocean climate models systematically simulate a significant MH warming both for Greenland (but smaller than ice-core based estimates) and Antarctica (consistent with the range of ice-core based range). In both PMIP1 and PMIP2, the MH annual mean changes in global temperature are negligible, consistent with the MH orbital forcing. The simulated last glacial maximum (LGM, 21,000 years ago) to pre-industrial change in global mean temperature ranges between 3 and 7°C in PMIP1 and PMIP2 model runs, similar to the range of temperature change expected from a quadrupling of atmospheric CO₂ concentrations in the CMIP simulations. Both LGM and future climate simulations are associated with a polar amplification of climate change. The range of glacial polar amplification in Greenland is strongly dependent on the ice sheet elevation changes prescribed to the climate models. All PMIP2 simulations systematically underestimate the reconstructed glacial–interglacial Greenland temperature change, while some of the simulations do capture the reconstructed glacial–interglacial Antarctic temperature change. Uncertainties in the prescribed central ice cap elevation cannot account for the temperature change underestimation by climate models. The variety of climate model sensitivities enables the exploration of the relative changes in polar temperature with respect to changes in global temperatures. Simulated changes of polar temperatures are strongly related to changes in simulated global temperatures for both future and LGM climates, confirming that ice-core-based reconstructions provide quantitative insights on global climate changes. An erratum to this article can be found at     

Role of soil freezing in future boreal climate change

We introduced a simple scheme of soil freezing in the LMDz3.3 atmospheric general circulation model (AGCM) to examine the potential effects of this parameterization on simulated future boreal climate change. In this multi-layer soil scheme, soil heat capacity and conductivity are dependent on soil water content, and a parameterization of the thermal and hydrological effects of water phase changes is included. The impact of these new features is evaluated against observations. By comparing present-day and 2×CO₂ AGCM simulations both with and without the parameterization of soil freezing the role of soil freezing in climate change is analysed. Soil freezing does not have significant global impacts, but regional effects on simulated climate and climate change are important. In present-day conditions, hydrological effects due to freezing lead to dryer summers. In 2×CO₂ climate, thermal effects due to freeze/thaw cycles are more pronounced and contribute to enhance the expected future overall winter warming. Impact of soil freezing on climate sensitivity is not uniform: the annual mean warming is amplified in North America (+15%) and Central Siberia (+36%) whereas it is reduced in Eastern Siberia (–23%). Nevertheless, all boreal lands undergo a strong attenuation of the warming during summertime. In agreement with some previous studies, these results indicate once more that soil freezing effects are significant on regional boreal climate. But this study also demonstrates its importance on regional boreal climate change and thus the necessity to include soil freezing in regional climate change predictions.

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Potential effects of climate change on a semi-permanent prairie wetland

We assessed the potential effects of a greenhouse gas-induced global climate change on the hydrology and vegetation of a semi-permanent prairie wetland using a spatially-defined, rule-based simulation model. An 11-yr simulation was run using current versus enhanced greenhouse gas climates. Projections of climatic change were from the Goddard Institute for Space Studies (GISS) general circulation model. Simulations were also run using a range of temperature (+2 and +4 °C) and precipitation change values (–20, –10, 0, +10, +20%) to determine the responsiveness of wetland vegetation and hydrology to a variety of climate scenarios.Maximum water depths were significantly less under the enhanced greenhouse gas scenario than under the current climate. The wetland dried in most years with increased temperature and changes in precipitation. Simulations also revealed a significant change in the vegetation, from a nearly balanced emergent cover to open water ratio to a completely closed basin with no open water areas. Simulations over a range of climate change scenarios showed that precipitation changes (particularly increases) had a greater impact on water levels and cover ratios when the temperature increase was moderate (+2 °C).These potential changes in wetland hydrology and vegetation could result in a dramatic decline in the quality of habitat for breeding birds, particularly waterfowl. Continued research on climate and wetland modeling is needed.     

Temperature response to future urbanization and climate change

This study examines the impact of future urban expansion on local near-surface temperature for Sydney (Australia) using a future climate scenario (A2). The Weather Research and Forecasting model was used to simulate the present (1990–2009) and future (2040–2059) climates of the region at 2-km spatial resolution. The standard land use of the model was replaced with a more accurate dataset that covers the Sydney area. The future simulation incorporates the projected changes in the urban area of Sydney to account for the expected urban expansion. A comparison between areas with projected land use changes and their surroundings was conducted to evaluate how urbanization and global warming will act together and to ascertain their combined effect on the local climate. The analysis of the temperature changes revealed that future urbanization will strongly affect minimum temperature, whereas little impact was detected for maximum temperature. The minimum temperature changes will be noticeable throughout the year. However, during winter and spring these differences will be particularly large and the increases could be double the increase due to global warming alone at 2050. Results indicated that the changes were mostly due to increased heat capacity of urban structures and reduced evaporation in the city environment.     

A regional climate model downscaling projection of China future climate change

Climate changes over China from the present (1990–1999) to future (2046–2055) under the A1FI (fossil fuel intensive) and A1B (balanced) emission scenarios are projected using the Regional Climate Model version 3 (RegCM3) nests with the National Center for Atmospheric Research (NCAR) Community Climate System Model (CCSM). For the present climate, RegCM3 downscaling corrects several major deficiencies in the driving CCSM, especially the wet and cold biases over the Sichuan Basin. As compared with CCSM, RegCM3 produces systematic higher spatial pattern correlation coefficients with observations for precipitation and surface air temperature except during winter. The projected future precipitation changes differ largely between CCSM and RegCM3, with strong regional and seasonal dependence. The RegCM3 downscaling produces larger regional precipitation trends (both decreases and increases) than the driving CCSM. Contrast to substantial trend differences projected by CCSM, RegCM3 produces similar precipitation spatial patterns under different scenarios except autumn. Surface air temperature is projected to consistently increase by both CCSM and RegCM3, with greater warming under A1FI than A1B. The result demonstrates that different scenarios can induce large uncertainties even with the same RCM-GCM nesting system. Largest temperature increases are projected in the Tibetan Plateau during winter and high-latitude areas in the northern China during summer under both scenarios. This indicates that high elevation and northern regions are more vulnerable to climate change. Notable discrepancies for precipitation and surface air temperature simulated by RegCM3 with the driving conditions of CCSM versus the model for interdisciplinary research on climate under the same A1B scenario further complicated the uncertainty issue. The geographic distributions for precipitation difference among various simulations are very similar between the present and future climate with very high spatial pattern correlation coefficients. The result suggests that the model present climate biases are systematically propagate into the future climate projections. The impacts of the model present biases on projected future trends are, however, highly nonlinear and regional specific, and thus cannot be simply removed by a linear method. A model with more realistic present climate simulations is anticipated to yield future climate projections with higher credibility.     

Effects of climate change on coastal fresh groundwater resources

This study evaluates the impacts of climate change on fresh groundwater resources specifically salinity intrusion in water resources stressed coastal aquifers. Our assessment used the Hadley Centre climate model, HadCM3 with high and low emission scenarios (SRES A2 and B2) for years 2000–2099. In both scenarios, the annual fresh groundwater resources losses indicate an increasing long-term trend in all stressed areas, except in the northern Africa/Sahara region. We also found that precipitation and temperature individually did not show good correlations with fresh groundwater loss. However, the relationship between the aridity index and fresh groundwater loss exhibited a strong negative correlation. We also discuss the impacts of loss of fresh groundwater resources on socio-economic activities, mainly population growth and per capita fresh groundwater resources.     

Influence of SST biases on future climate change projections

We use a quantile-based bias correction technique and a multi-member ensemble of the atmospheric component of NCAR CCSM3 (CAM3) simulations to investigate the influence of sea surface temperature (SST) biases on future climate change projections. The simulations, which cover 1977?C1999 in the historical period and 2077?C2099 in the future (A1B) period, use the CCSM3-generated SSTs as prescribed boundary conditions. Bias correction is applied to the monthly time-series of SSTs so that the simulated changes in SST mean and variability are preserved. Our comparison of CAM3 simulations with and without SST correction shows that the SST biases affect the precipitation distribution in CAM3 over many regions by introducing errors in atmospheric moisture content and upper-level (lower-level) divergence (convergence). Also, bias correction leads to significantly different precipitation and surface temperature changes over many oceanic and terrestrial regions (predominantly in the tropics) in response to the future anthropogenic increases in greenhouse forcing. The differences in the precipitation response from SST bias correction occur both in the mean and the percent change, and are independent of the ocean?Catmosphere coupling. Many of these differences are comparable to or larger than the spread of future precipitation changes across the CMIP3 ensemble. Such biases can affect the simulated terrestrial feedbacks and thermohaline circulations in coupled climate model integrations through changes in the hydrological cycle and ocean salinity. Moreover, biases in CCSM3-generated SSTs are generally similar to the biases in CMIP3 ensemble mean SSTs, suggesting that other GCMs may display a similar sensitivity of projected climate change to SST errors. These results help to quantify the influence of climate model biases on the simulated climate change, and therefore should inform the effort to further develop approaches for reliable climate change projection.     

Past and future changes in climate and hydrological indicators in the US Northeast

To assess the influence of global climate change at the regional scale, we examine past and future changes in key climate, hydrological, and biophysical indicators across the US Northeast (NE). We first consider the extent to which simulations of twentieth century climate from nine atmosphere-ocean general circulation models (AOGCMs) are able to reproduce observed changes in these indicators. We then evaluate projected future trends in primary climate characteristics and indicators of change, including seasonal temperatures, rainfall and drought, snow cover, soil moisture, streamflow, and changes in biometeorological indicators that depend on threshold or accumulated temperatures such as growing season, frost days, and Spring Indices (SI). Changes in indicators for which temperature-related signals have already been observed (seasonal warming patterns, advances in high-spring streamflow, decreases in snow depth, extended growing seasons, earlier bloom dates) are generally reproduced by past model simulations and are projected to continue in the future. Other indicators for which trends have not yet been observed also show projected future changes consistent with a warmer climate (shrinking snow cover, more frequent droughts, and extended low-flow periods in summer). The magnitude of temperature-driven trends in the future are generally projected to be higher under the Special Report on Emission Scenarios (SRES) mid-high (A2) and higher (A1FI) emissions scenarios than under the lower (B1) scenario. These results provide confidence regarding the direction of many regional climate trends, and highlight the fundamental role of future emissions in determining the potential magnitude of changes we can expect over the coming century.

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The importance of population,climate change and CO2 plant physiological forcing in determining future global water stress

Future levels of water stress depend on changes in several key factors including population, climate-change driven water availability, and a carbon dioxide physiological-forcing effect on evaporation and run-off. In this study we use an ensemble of the HadCM3 climate model forced with a range of future emissions scenarios combined with a simple water scarcity index to assess the contribution of each of these factors to the projected population living in water stress over the 21st century.Population change only scenarios increase the number of people living in water stress such that at peak global population 65% of people experience some level of water stress. Globally, the climate model ensemble projects an increase in water availability which partially offsets some of the impacts of population growth. The result is 1 billion fewer people living in water stress by the 2080s under the high end emissions scenarios than if population increased in the absence of climate change.This study highlights the important role plant-physiological forcing has on future water resources. The effect of rising CO₂ is to increase available water and to reduce the number of people living in high water stress by around 200 million compared to climate only projections. This effect is of a similar order of magnitude to climate change.     

Perceptions of climate and climate change by Amazonian communities

The Amazon region has been undergoing profound transformations since the late ‘70s through forest degradation, land use changes and effects of global climate change. The perception of such changes by local communities is important for risk analysis and for subsequent societal decision making. In this study, we compare and contrast observations and perceptions of climate change by selected Amazonian communities particularly vulnerable to alterations in precipitation regimes. Two main points were analysed: (i) the notion of changes in the annual climate cycle and (ii) the notion of changes in rainfall patterns. About 72% of the sampled population reports perceptions of climate changes, and there is a robust signal of increased perception with age. Other possible predictive parameters such as gender, fishing frequency and changes in/planning of economic activities do not appear overall as contributing to perceptions. The communities’ perceptions of the changes in 2013–2014 were then compared to earlier results (2007–2008), providing an unprecedented cohort study of the same sites. Results show that climate change perceptions and measured rainfall variations differ across the basin. It was only in the southern part of the Amazon that both measured and perceived changes in rainfall patterns were consistent with decreased precipitation. However, the perception of a changing climate became more widespread and frequently mentioned, signalling an increase in awareness of climate risk.     

气候变化条件下雅砻江流域未来径流变化趋势研究

雅砻江为我国重要的水电基地,未来气候变化条件下流域径流变化将直接影响雅砻江梯级水库群运行安全和发电调度,因此研究气候变化对雅砻江流域径流的影响十分必要。首先建立了流域月尺度的SWAT模型,然后使用统计降尺度模型（SDSM）模拟未来2006—2100年流域内各站点的气象数据,最后使用流域SWAT模型对未来2006—2100年月径流进行模拟。结果表明,未来雅砻江流域径流呈上升趋势,且增幅随着辐射强迫的增加同步增大,RCP2.6、RCP4.5、RCP8.5这3种典型浓度路径下年平均径流增幅分别为8.9%、12.5%、16.7%,且2020S（2006—2035年)、2050S（2036—2065年)、2080S（2066—2100年）这3个时期年径流量呈现不同的变化趋势,其中RCP2.6浓度路径下为先逐步增加达到峰值后略有减少,RCP4.5浓度路径下为先逐步增加达到峰值后趋于稳定,RCP8.5浓度路径下为持续增加。流域径流年内分配方面,3种典型浓度路径下汛期径流占全年比例在2020S、2050S、2080S这3个时期均为先降后升趋势,整个预测期总体为降低趋势,RCP2.6、RCP4.5及RCP8.5这3种浓度路径下整个预测期的均值分别由基准期的75.9%降低为72.9%、72.0%、71.2%。径流增加会对流域洪水特性产生较大影响,为此应该修正流域设计洪水计算结果和调整防洪调度方案,以降低雅砻江流域梯级水库群因气候变化而产生的运行风险,并提高发电调度效率。     

Downscaling future climate change projections over Puerto Rico using a non-hydrostatic atmospheric model

We present results from 20-year “high-resolution” regional climate model simulations of precipitation change for the sub-tropical island of Puerto Rico. The Japanese Meteorological Agency Non-Hydrostatic Model (NHM) operating at a 2-km grid resolution is nested inside the Regional Spectral Model (RSM) at 10-km grid resolution, which in turn is forced at the lateral boundaries by the Community Climate System Model (CCSM4). At this resolution, the climate change experiment allows for deep convection in model integrations, which is an important consideration for sub-tropical regions in general, and on islands with steep precipitation gradients in particular that strongly influence local ecological processes and the provision of ecosystem services. Projected precipitation change for this region of the Caribbean is simulated for the mid-twenty-first century (2041–2060) under the RCP8.5 climate-forcing scenario relative to the late twentieth century (1986–2005). The results show that by the mid-twenty-first century, there is an overall rainfall reduction over the island for all seasons compared to the recent climate but with diminished mid-summer drought (MSD) in the northwestern parts of the island. Importantly, extreme rainfall events on sub-daily and daily time scales also become slightly less frequent in the projected mid-twenty-first-century climate over most regions of the island.     

Quantification of uncertainty sources in a probabilistic climate change assessment of future water shortages

As the incorporation of probabilistic climate change information into UK water resource management gathers apace, understanding the relative scales of the uncertainty sources in projections of future water shortage metrics is necessary for the resultant information to be understood and used effectively. Utilising modified UKCP09 weather generator data and a multi-model approach, this paper represents a first attempt at extending an uncertainty assessment of future stream flows under forced climates to consider metrics of water shortage based on the triggering of reservoir control curves. It is found that the perturbed physics ensemble uncertainty, which describes climate model parameter error uncertainty, is the cause of a far greater proportion of both the overall flow and water shortage per year probability uncertainty than that caused by SRES emissions scenario choice in the 2080s. The methodology for producing metrics of future water shortage risk from UKCP09 weather generator information described here acts as the basis of a robustness analysis of the North Staffordshire WRZ to climate change, which provides an alternative approach for making decisions despite large uncertainties, which will follow.     

Impact of climate change on potential evapotranspiration under a historical and future climate scenario in the Huang-Huai-Hai Plain,China

Theoretical and Applied Climatology - Climate change is widely accepted to be one of the most critical problems faced by the Huang-Huai-Hai Plain (3H Plain), which is a region in which there is an...     

East African food security as influenced by future climate change and land use change at local to regional scales

Climate change impacts food production systems, particularly in locations with large, vulnerable populations. Elevated greenhouse gases (GHG), as well as land cover/land use change (LCLUC), can influence regional climate dynamics. Biophysical factors such as topography, soil type, and seasonal rainfall can strongly affect crop yields. We used a regional climate model derived from the Regional Atmospheric Modeling System (RAMS) to compare the effects of projected future GHG and future LCLUC on spatial variability of crop yields in East Africa. Crop yields were estimated with a process-based simulation model. The results suggest that: (1) GHG-influenced and LCLUC-influenced yield changes are highly heterogeneous across this region; (2) LCLUC effects are significant drivers of yield change; and (3) high spatial variability in yield is indicated for several key agricultural sub-regions of East Africa. Food production risk when considered at the household scale is largely dependent on the occurrence of extremes, so mean yield in some cases may be an incomplete predictor of risk. The broad range of projected crop yields reflects enormous variability in key parameters that underlie regional food security; hence, donor institutions’ strategies and investments might benefit from considering the spatial distribution around mean impacts for a given region. Ultimately, global assessments of food security risk would benefit from including regional and local assessments of climate impacts on food production. This may be less of a consideration in other regions. This study supports the concept that LCLUC is a first-order factor in assessing food production risk.