Earth System Dynamics

Abstract. Statistical bias correction is commonly applied within climate impact modelling to correct climate model data for systematic deviations of the simulated historical data from observations. Methods are based on transfer functions generated to map the distribution of the simulated historical data to that of the observations. Those are subsequently applied to correct the future projections. Here, we present the bias correction method that was developed within ISI-MIP, the first Inter-Sectoral Impact Model Intercomparison Project. ISI-MIP is designed to synthesise impact projections in the agriculture, water, biome, health, and infrastructure sectors at different levels of global warming. Bias-corrected climate data that are used as input for the impact simulations could be only provided over land areas. To ensure consistency with the global (land + ocean) temperature information the bias correction method has to preserve the warming signal. Here we present the applied method that preserves the absolute changes in monthly temperature, and relative changes in monthly values of precipitation and the other variables needed for ISI-MIP. The proposed methodology represents a modification of the transfer function approach applied in the Water Model Intercomparison Project (Water-MIP). Correction of the monthly mean is followed by correction of the daily variability about the monthly mean. Besides the general idea and technical details of the ISI-MIP method, we show and discuss the potential and limitations of the applied bias correction. In particular, while the trend and the long-term mean are well represented, limitations with regards to the adjustment of the variability persist which may affect, e.g. small scale features or extremes.

Abstract. To sustain growing food demand and increasing standard of living, global water withdrawal and consumptive water use have been increasing rapidly. To analyze the human perturbation on water resources consistently over large scales, a number of macro-scale hydrological models (MHMs) have been developed in recent decades. However, few models consider the interaction between terrestrial water fluxes, and human activities and associated water use, and even fewer models distinguish water use from surface water and groundwater resources. Here, we couple a global water demand model with a global hydrological model and dynamically simulate daily water withdrawal and consumptive water use over the period 1979–2010, using two re-analysis products: ERA-Interim and MERRA. We explicitly take into account the mutual feedback between supply and demand, and implement a newly developed water allocation scheme to distinguish surface water and groundwater use. Moreover, we include a new irrigation scheme, which works dynamically with a daily surface and soil water balance, and incorporate the newly available extensive Global Reservoir and Dams data set (GRanD). Simulated surface water and groundwater withdrawals generally show good agreement with reported national and subnational statistics. The results show a consistent increase in both surface water and groundwater use worldwide, with a more rapid increase in groundwater use since the 1990s. Human impacts on terrestrial water storage (TWS) signals are evident, altering the seasonal and interannual variability. This alteration is particularly large over heavily regulated basins such as the Colorado and the Columbia, and over the major irrigated basins such as the Mississippi, the Indus, and the Ganges. Including human water use and associated reservoir operations generally improves the correlation of simulated TWS anomalies with those of the GRACE observations.

Abstract. Robust appraisals of climate impacts at different levels of global-mean temperature increase are vital to guide assessments of dangerous anthropogenic interference with the climate system. The 2015 Paris Agreement includes a two-headed temperature goal: "holding the increase in the global average temperature to well below 2 °C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C". Despite the prominence of these two temperature limits, a comprehensive overview of the differences in climate impacts at these levels is still missing. Here we provide an assessment of key impacts of climate change at warming levels of 1.5 °C and 2 °C, including extreme weather events, water availability, agricultural yields, sea-level rise and risk of coral reef loss. Our results reveal substantial differences in impacts between a 1.5 °C and 2 °C warming that are highly relevant for the assessment of dangerous anthropogenic interference with the climate system. For heat-related extremes, the additional 0.5 °C increase in global-mean temperature marks the difference between events at the upper limit of present-day natural variability and a new climate regime, particularly in tropical regions. Similarly, this warming difference is likely to be decisive for the future of tropical coral reefs. In a scenario with an end-of-century warming of 2 °C, virtually all tropical coral reefs are projected to be at risk of severe degradation due to temperature-induced bleaching from 2050 onwards. This fraction is reduced to about 90 % in 2050 and projected to decline to 70 % by 2100 for a 1.5 °C scenario. Analyses of precipitation-related impacts reveal distinct regional differences and hot-spots of change emerge. Regional reduction in median water availability for the Mediterranean is found to nearly double from 9 % to 17 % between 1.5 °C and 2 °C, and the projected lengthening of regional dry spells increases from 7 to 11 %. Projections for agricultural yields differ between crop types as well as world regions. While some (in particular high-latitude) regions may benefit, tropical regions like West Africa, South-East Asia, as well as Central and northern South America are projected to face substantial local yield reductions, particularly for wheat and maize. Best estimate sea-level rise projections based on two illustrative scenarios indicate a 50 cm rise by 2100 relative to year 2000-levels for a 2 °C scenario, and about 10 cm lower levels for a 1.5 °C scenario. In a 1.5 °C scenario, the rate of sea-level rise in 2100 would be reduced by about 30 % compared to a 2 °C scenario. Our findings highlight the importance of regional differentiation to assess both future climate risks and different vulnerabilities to incremental increases in global-mean temperature. The article provides a consistent and comprehensive assessment of existing projections and a good basis for future work on refining our understanding of the difference between impacts at 1.5 °C and 2 °C warming.

Abstract. Climate change is a global environmental threat to all economic sectors, particularly the agricultural sector. Pakistan is one of the countries negatively affected by climate change due to its high exposure to extreme events and low adaptive capacity. In Pakistan, farmers are the primary stakeholders in agriculture and are more at risk due to climate vulnerability. Based on farm household data from 450 households collected from three districts in three agroecological zones in the Punjab province of Pakistan, this study examines how farmers perceive climate change and how they adapt their farming in response to perceived changes in climate. The results demonstrate that awareness of climate change is widespread throughout the area, and farm households make adjustments to adapt their agriculture in response to climatic change. Overall 58% of the farm households adapted their farming to climate change. Changing crop varieties, changing planting dates, planting of shade trees and changing fertilizers were the main adaptation methods implemented by farm households in the study area. The results from the binary logistic model reveal that education, farm experience, household size, land area, tenancy status, ownership of a tube well, access to market information, information on weather forecasting and agricultural extension services all influence farmers' choices of adaptation measures. The results also indicate that adaptation to climate change is constrained by several factors such as lack of information, lack of money, resource constraints and shortage of irrigation water in the study area. Findings of the study suggest the need for greater investment in farmer education and improved institutional setup for climate change adaptation to improve farmers' wellbeing.

Abstract. The Tibetan Plateau (TP) plays a key role in the water cycle of high Asia and its downstream regions. The respective influence of the Indian and East Asian summer monsoon on TP precipitation and regional water resources, together with the detection of moisture transport pathways and source regions are the subject of recent research. In this study, we present a 12-year high-resolution climatology of the atmospheric water transport (AWT) over and towards the TP using a new data set, the High Asia Refined analysis (HAR), which better represents the complex topography of the TP and surrounding high mountain ranges than coarse-resolution data sets. We focus on spatiotemporal patterns, vertical distribution and transport through the TP boundaries. The results show that the mid-latitude westerlies have a higher share in summertime AWT over the TP than assumed so far. Water vapour (WV) transport constitutes the main part, whereby transport of water as cloud particles (CP) also plays a role in winter in the Karakoram and western Himalayan regions. High mountain valleys in the Himalayas facilitate AWT from the south, whereas the high mountain regions inhibit AWT to a large extent and limit the influence of the Indian summer monsoon. No transport from the East Asian monsoon to the TP could be detected. Our results show that 36.8 ± 6.3% of the atmospheric moisture needed for precipitation comes from outside the TP, while the remaining 63.2% is provided by local moisture recycling.

Abstract. Global climate change has numerous implications for members of mountain communities who feel the impacts in both physical and social dimensions. In the western Himalayas of India, a majority of residents maintain a livelihood strategy that includes a combination of subsistence or small-scale agriculture, livestock rearing, seasonal or long-term migration, and localized natural resource extraction. While warming temperatures, irregular patterns of precipitation and snowmelt, and changing biological systems present challenges to the viability of these traditional livelihood portfolios in general, we find that climate change is also undermining local communities' livelihood assets in gender-specific ways. In this paper, we present a case study from the Nanda Devi Biosphere Reserve (Uttarakhand, India) that both outlines the implications of climate change for women farmers in the area and highlights the potential for ecotourism (as a form of livelihood diversification) to strengthen both key livelihood assets of women and local communities' adaptive capacity more broadly. The paper intentionally employs a categorical focus on women but also addresses issues of inter-group and gender diversity. With this special issue in mind, suggestions for related research are proposed for consideration by climate scientists and social systems and/or policy modelers seeking to support gender justice through socially transformative perspectives and frameworks.