Abstract. Drought is a cumulative event, often difficult to define and involving wide-reaching consequences for agriculture, ecosystems, water availability, and society. Understanding how the occurrence of drought may change in the future and which sources of uncertainty are dominant can inform appropriate decisions to guide drought impacts assessments. Our study considers both climate model uncertainty associated with future climate projections, and future emissions of greenhouse gases (future scenario uncertainty). Four drought indices (the Standardised Precipitation Index (SPI), Soil Moisture Anomaly (SMA), the Palmer Drought Severity Index (PDSI) and the Standardised Runoff Index (SRI)) are calculated for the A1B and RCP2.6 future emissions scenarios using monthly model output from a 57-member perturbed parameter ensemble of climate simulations of the HadCM3C Earth System model, for the baseline period , and the period 2070-2099 ("the 2080s"). We consider where there are statistically significant increases or decreases in the proportion of time spent in drought in the 2080s compared to the baseline. Despite the large range of uncertainty in drought projections for many regions, projections for some regions have a clear signal, with uncertainty associated with the magnitude of change rather than direction. For instance, a significant increase in time spent in drought is generally projected for the Amazon, Central America and South Africa whilst projections for northern India consistently show significant decreases in time spent in drought. Whilst the patterns of changes in future drought were similar between scenarios, climate mitigation, represented by the RCP2.6 scenario, tended to reduce future changes in drought. In general, climate mitigation reduced the area over which there was a significant increase in drought but had little impact on the area over which there was a significant decrease in time spent in drought.

A B S T R A C TSeasonal climate forecasts (SCFs) have significant potential to support shorter-term agricultural decisions and longer-term climate adaptation plans, but uptake in Europe has to date been low. Under the European Union funded project, European Provision Of Regional Impacts Assessments on Seasonal and Decadal Timescales (EUPORIAS) we have developed the Land Management Tool (LMTool), a prototype seasonal climate service for land managers, working closely in collaboration with two stakeholder organizations, Clinton Devon Estates (CDE) and the National Farmers Union (NFU). LMTool was one of several prototype climate services selected for development within EUPORIAS, including those for the UK transport network, food security in Ethiopia, renewable energy production, hydroelectric energy production in Sweden, and river management in two French basins. The LMTool provides SCFs (1-3 months ahead) to farmers in the Southwest UK, alongside 14-day site specific weather forecasts during the winter months when the skill of seasonal forecasts is greatest.We describe the processes through which the LMTool was co-designed and developed with the farmers, its technical development and key features; critically examine the lessons learned and their implications for providing future climate services for land managers; and finally assess the feasibility of delivering an operational winter seasonal climate service for UK land managers.A number of key learning points from developing the prototype may benefit future work in climate services for the land management and agriculture sector; many of these points are also valid for climate services in other sectors. Prototype development strongly benefitted from; working with intermediaries to identify representative, engaged land managers; an iterative and flexible process of co-design with the farmer group; and from an interdisciplinary project team. Further work is needed to develop a better understanding of the role of forecast skill in land management decision making, the potential benefits of downscaling and how seasonal forecasts can help support land managers decision-making processes. The prototype would require considerable work to implement a robust operational forecast system, and a longer period to demonstrate the value of the services provided. Finally, the potential for such services to be applied more widely in Europe is not well understood and would require further stakeholder engagement and forecast development. Practical implicationsAs part of the EU project EUPORIAS (Buontempo and Hewitt, 2017), the UK Met Office, University of Leeds, Predictia and KNMI-in close collaboration with Clinton Devon Estates (CDE) and the National Farmers Union (NFU)-have developed the Land Management Tool (LMTool), a prototype http://dx

Drought is a cumulative event, often difficult to define and involving wide reaching consequences for agriculture, ecosystems, water availability, and society. Understanding how the occurrence of drought may change in the future and which sources of uncertainty are dominant can inform appropriate decisions to guide drought impacts assessments. Uncertainties in future projections of drought arise from several sources and our aim is to understand how these sources of uncertainty contribute to future projections of drought. We consider four sources of uncertainty; climate model uncertainty associated with future climate projections, future emissions of greenhouse gases (future scenario uncertainty), type of drought (drought index uncertainty) and drought event definition (threshold uncertainty). Three drought indices (the Standardised Precipitation Index (SPI), Soil Moisture Anomaly (SMA) and Palmer Drought Severity Index (PDSI)) are calculated for the A1B and RCP2.6 future emissions scenarios using monthly model output from a 57 member perturbed parameter ensemble of climate simulations of the HadCM3C Earth system model, for the baseline period, 1961–1990, and the period 2070–2099 (representing the 2080s). We consider where there are significant increases or decreases in the proportion of time spent in drought in the 2080s compared to the baseline and compare the effects from the four sources of uncertainty. Our results suggest that, of the included uncertainty sources, choice of drought index is the most important factor influencing uncertainty in future projections of drought (60%–85% of total included uncertainty). There is a greater range of uncertainty between drought indices than that between the mitigation scenario RCP2.6 and the A1B emissions scenario (5%–6% in the 2050s to 17%–18% in the 2080s) and across the different model variants in the ensemble (9%–17%). Choice of drought threshold has the least influence on uncertainty in future drought projections (0.4%–7%). Despite the large range of uncertainty in drought projections for many regions, projections for some regions have a clear signal, with uncertainty associated with the magnitude of change rather than direction. For instance, a significant increase in time spent in drought is consistently projected for the Amazon, Central America and South Africa whilst projections for Northern India consistently show significant decreases in time spent in drought. We conclude that choice of which drought index (or drought indices) to use when undertaking drought impacts assessments is of considerable importance relative to choices relating to the other three included sources of uncertainty in this study. This information will help ensure that future drought impacts assessments are designed appropriately to account for uncertainty

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