Challenges posed by and approaches to the study of seasonal-to-decadal climate variability

The tasks of providing multi-decadal climate projections and seasonal plus sub-seasonal climate predictions are of significant societal interest and pose major scientific challenges. An outline is presented of the challenges posed by, and the approaches adopted to, tracing the possible evolution of the climate system on these various time-scales. First an overview is provided of the nature of the climate system's natural internal variations and the uncertainty arising from the complexity and non-linearity of the system. Thereafter consideration is given sequentially to the range of extant approaches adopted to study and derive multi-decadal climate projections, seasonal predictions, and significant sub-seasonal weather phenomena. For each of these three time-scales novel results are presented that indicate the nature (and limitations) of the models used to forecast the evolution, and illustrate the techniques adopted to reduce or cope with the forecast uncertainty. In particular, the contributions (i) appear to exemplify that in simple climate models uncertainties in radiative forcing outweigh uncertainties associated with ocean models, (ii) examine forecast skills for a state-of-the-art seasonal prediction system, and (iii) suggest that long-lived weather phenomena can help shape intra-seasonal climate variability. Finally, it is argued, that co-consideration of all these scales can enhance our understanding of the challenges associated with uncertainties in climate predictio

Modeling the Arctic Freshwater System and its integration in the global system: Lessons learned and future challenges

This is the final version of the article. Available from the publisher via the DOI in this record.Numerous components of the Arctic freshwater system (atmosphere, ocean, cryosphere, and terrestrial hydrology) have experienced large changes over the past few decades, and these changes are projected to amplify further in the future. Observations are particularly sparse, in both time and space, in the polar regions. Hence, modeling systems have been widely used and are a powerful tool to gain understanding on the functioning of the Arctic freshwater system and its integration within the global Earth system and climate. Here we present a review of modeling studies addressing some aspect of the Arctic freshwater system. Through illustrative examples, we point out the value of using a hierarchy of models with increasing complexity and component interactions, in order to dismantle the important processes at play for the variability and changes of the different components of the Arctic freshwater system and the interplay between them. We discuss past and projected changes for the Arctic freshwater system and explore the sources of uncertainty associated with these model results. We further elaborate on some missing processes that should be included in future generations of Earth system models and highlight the importance of better quantification and understanding of natural variability, among other factors, for improved predictions of Arctic freshwater system change.The first two authors have contributed equally to the publication. The Arctic Freshwater Synthesis has been sponsored by the World Climate Research Programme’s Climate and the Cryosphere project (WCRP-CliC), the International Arctic Science Committee (IASC), and the Arctic Monitoring and Assessment Programme (AMAP). C.L. acknowledges support from the UK Natural Environment Research Council. M.M.H. acknowledges support from NSF PLR-1417642. D.M.L. is supported by funding from the U.S. Department of Energy BER, as part of its Climate Change Prediction Program, Cooperative Agreement DE-FC03-97ER62402/A010, and NSF grants AGS-1048996, PLS-1048987, and PLS-1304220. J.A.S. is supported by Natural Environment Research Council grant NE/J019585/1. Y.D. is supported by Environment Canada’s Northern Hydrology program. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP, the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. The CMIP data and CESM-LE data are available through the relevant Web data portal

Climate change adaptation and mitigation in agriculture: Science workshop report

CGIAR and partner scientists met in Cancun, Mexico, with the purpose to advance science on climate change adaptation and mitigation, according to the scope of the CGIAR Research Program on Climate Change, Agriculture and Food security (CCAFS). The objectives of the workshop were to (1) understand ongoing research as a foundation for future collaboration and advances, and (2) explore research that shows the highest promise for scientific breakthroughs

Chapter 12 - Long-term climate change: Projections, commitments and irreversibility

This chapter assesses long-term projections of climate change for the end of the 21st century and beyond, where the forced signal depends on the scenario and is typically larger than the internal variability of the climate system. Changes are expressed with respect to a baseline period of 1986-2005, unless otherwise stated

Exploring, exploiting and evolving diversity of aquatic ecosystem models: A community perspective

Here, we present a community perspective on how to explore, exploit and evolve the diversity in aquatic ecosystem models. These models play an important role in understanding the functioning of aquatic ecosystems, filling in observation gaps and developing effective strategies for water quality management. In this spirit, numerous models have been developed since the 1970s. We set off to explore model diversity by making an inventory among 42 aquatic ecosystem modellers, by categorizing the resulting set of models and by analysing them for diversity. We then focus on how to exploit model diversity by comparing and combining different aspects of existing models. Finally, we discuss how model diversity came about in the past and could evolve in the future. Throughout our study, we use analogies from biodiversity research to analyse and interpret model diversity. We recommend to make models publicly available through open-source policies, to standardize documentation and technical implementation of models, and to compare models through ensemble modelling and interdisciplinary approaches. We end with our perspective on how the field of aquatic ecosystem modelling might develop in the next 5–10 years. To strive for clarity and to improve readability for non-modellers, we include a glossary

Cross-Disciplinarity in the Advance of Antarctic Ecosystem Research

The biodiversity, ecosystem services and climate variability of the Antarctic continent, and the Southern Ocean are major components of the whole Earth system. Antarctic ecosystems are driven more strongly by the physical environment than many other marine and terrestrial ecosystems. As a consequence, to understand ecological functioning, cross-disciplinary studies are especially important in Antarctic research. The conceptual study presented here is based on a workshop initiated by the Research Programme Antarctic Thresholds - Ecosystem Resilience and Adaption of the Scientific Committee on Antarctic Research, which focused on challenges in identifying and applying cross-disciplinary approaches in the Antarctic. Novel ideas, and first steps in their implementation, were clustered into eight themes, ranging from scale problems, risk maps, organism and ecosystem responses to multiple environmental changes, to evolutionary processes. Scaling models and data across different spatial and temporal scales were identified as an overarching challenge. Approaches to bridge gaps in the research programmes included multi-disciplinary monitoring, linking biomolecular findings and simulated physical environments, as well as integrative ecological modelling. New strategies in academic education are proposed. The results of advanced cross-disciplinary approaches can contribute significantly to our knowledge of ecosystem functioning, the consequences of climate change, and to global assessments that ultimately benefit humankind

The Geographical Imagination of Luka Bloom

There are very many geographical themes and metaphors in the songs of Luka Bloom. If we take Geography as being concerned with, to paraphrase Alexander von Humboldt (1769-1859), the study of the Earth as our home and if we follow the common practice of identifying Space, Place, and Environment as the fundamental building blocks of geographical theory, then, Luka Bloom’s art is profoundly geographical

The critical role of uncertainty in projections of hydrological extremes

This paper aims to quantify the uncertainty in projections of future hydrological extremes in the Biala Tarnowska River at Koszyce gauging station, south Poland. The approach followed is based on several climate projections obtained from the EURO-CORDEX initiative, raw and bias-corrected realizations of catchment precipitation, and flow simulations derived using multiple hydrological model parameter sets. The projections cover the 21st century. Three sources of uncertainty are considered: one related to climate projection ensemble spread, the second related to the uncertainty in hydrological model parameters and the third related to the error in fitting theoretical distribution models to annual extreme flow series. The uncertainty of projected extreme indices related to hydrological model parameters was conditioned on flow observations from the reference period using the generalized likelihood uncertainty estimation (GLUE) approach, with separate criteria for high- and low-flow extremes. Extreme (low and high) flow quantiles were estimated using the generalized extreme value (GEV) distribution at different return periods and were based on two different lengths of the flow time series. A sensitivity analysis based on the analysis of variance (ANOVA) shows that the uncertainty introduced by the hydrological model parameters can be larger than the climate model variability and the distribution fit uncertainty for the low-flow extremes whilst for the high-flow extremes higher uncertainty is observed from climate models than from hydrological parameter and distribution fit uncertainties. This implies that ignoring one of the three uncertainty sources may cause great risk to future hydrological extreme adaptations and water resource planning and management

The Role of Hydrological Modelling Uncertainties in Climate Change Impact Assessments of Irish River Catchments

Conceptual Rainfall Runoff (CRR) models forced with regional climate change scenarios downscaled from Global Climate Models (GCMs) are widely employed to assess the impacts of climate change at the catchment scale. This approach is subject to a range of uncertainties associated with future emissions of greenhouse gases, the response of the climate system to these changes at global and local scales, and uncertainties associated with the impact models. These uncertainties then cascade through the climate change impact assessment methodology with potentially large uncertainties associated with critical future impacts at the local scale where key decisions are required in order to increase the resilience of water supply management and infrastructure to future changes. Given that uncertainty in modelling will not be significantly reduced in the short or medium term future, ensuring that potentially expensive and irreversible adaptation decisions made now are robust to the uncertainty in future climate change impacts means that considerable effort is required in investigating and quantifying sources of uncertainty