The match between climate services demands and Earth System Models supplies

Hurk, Bart van den; Hewitt, Chris; Jacob, Daniela; Bessembinder, Janette; Doblas‐Reyes, Francisco J.; Döscher, Ralf

doi:10.1016/j.cliser.2018.11.002

Cited by 36 publications

(13 citation statements)

References 25 publications

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“…There is a scientific consensus on the need for spatially detailed information on urban landscapes at a global scale to support a range of environmental services 1 . The consensus has emerged as the simulation and forecasting capabilities of models have improved radically over the last decade and the demand for reliable urban-scale information that can inform policies has increased 2 . The latter is an acknowledgment of cities as places of: intense resource consumption and waste generation and; foci of population and infrastructure that are exposed to multiple hazards of natural and anthropogenic origin.…”

Section: Background and Summarymentioning

confidence: 99%

Combining expert and crowd-sourced training data to map urban form and functions for the continental US

et al. 2020

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Although continental urban areas are relatively small, they are major drivers of environmental change at local, regional and global scales. Moreover, they are especially vulnerable to these changes owing to the concentration of population and their exposure to a range of hydro-meteorological hazards, emphasizing the need for spatially detailed information on urbanized landscapes. These data need to be consistent in content and scale and provide a holistic description of urban layouts to address different user needs. Here, we map the continental United States into Local Climate Zone (LCZ) types at a 100 m spatial resolution using expert and crowd-sourced information. There are 10 urban LCZ types, each associated with a set of relevant variables such that the map represents a valuable database of urban properties. These data are benchmarked against continental-wide existing and novel geographic databases on urban form. We anticipate the dataset provided here will be useful for researchers and practitioners to assess how the configuration, size, and shape of cities impact the important human and environmental outcomes.

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Section: Background and Summarymentioning

confidence: 99%

Combining expert and crowd-sourced training data to map urban form and functions for the continental US

et al. 2020

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“…In fact, they have to be used with caution because PBIAS may be influenced by the uncertainty (Moriasi et al, 2007) and the rating values recommended for the NSE may be too restrictive, since only negative values of NSE indicate an unacceptable performance (Moriasi et al, 2007), and this did not happen in the case of Molinar, Tous, and Sueca when the HBV was tested with historical data, even though they were very low (≈ 0.2). The hydrological model is another source of uncertainty and it has to be considered (Muerth et al, 2013), but it is significantly less important than that provided by the RCMs (Vetter et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

Risk assessment in water resources planning under climate change at the Júcar River basin

Suárez-Almiñana¹,

Solera²,

Madrigal³

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. Climate change and its possible effects on water resources has become an increasingly near threat. Therefore, the study of these impacts in highly regulated systems and those suffering extreme events is essential to deal with them effectively. This study responds to the need for an effective method to integrate climate change projections into water planning and management analysis in order to guide the decision-making, taking into account drought risk assessments. Therefore, this document presents a general and adaptive methodology based on a modeling chain and correction processes, whose main outcomes are the impacts on future natural inflows, a drought risk indicator, and the simulation of future water storage in the water resources system (WRS). This method was applied in the Júcar River basin (JRB) due to its complexity and the multiannual drought events it suffers recurrently. The results showed a worrying decrease in future inflows, as well as a high probability (≈80 %) of being under 50 % of total capacity of the WRS in the near future. However, the uncertainty of the results was considerable from the mid-century onwards, indicating that the skill of climate projections needs to be improved in order to obtain more reliable results. Consequently, this paper also highlights the difficulties of developing this type of method, taking partial decisions to adapt them as far as possible to the basin in an attempt to obtain clearer conclusions on climate change impact assessments. Despite the high uncertainty, the results of the JRB call for action and the tool developed can be considered as a feasible and robust method to facilitate and support decision-making in complex basins for future water planning and management.

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“…The climate data were thus produced with another purpose than climate impact assessments. Data for scientists require a different quality control and assurance system than a climate service aimed at non-scientific users from the public and private sectors (van den Hurk et al 2018). So to use these datasets for climate services there is a need for addition quality control.…”

Section: Introductionmentioning

confidence: 99%

Comparison of open access global climate services for hydrological data

Merks

Photiadou

Ludwig

et al. 2020

Hydrological Sciences Journal

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There is a high demand for openly accessible hydroclimatic data for climate change adaptation. Different data sources are available, however, discrepancy between the data can confuse users and should be evaluated and explained. This study, investigates how climate impact indicators (CIIs) developed for global users in the Copernicus Climate Change Service (C3S) are comparable to other openly available global data for water and climate. We found that, for temperature, datasets are comparable and climate impacts are thus considered robust. Important discrepancies arise in the precipitation indicators. Of the CIIs analysed in this study, the hydrological CIIs differ most so they should be used with care. These differences are probably caused by model uncertainty (hydrological model, HM; global climate model, GCM), ensemble size and model selection. A HM ensemble, as well as a GCM ensemble combined with improved model performance and selection criteria, should be used to ensure high-quality global water and climate services.

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The match between climate services demands and Earth System Models supplies

Cited by 36 publications

References 25 publications

Combining expert and crowd-sourced training data to map urban form and functions for the continental US

Combining expert and crowd-sourced training data to map urban form and functions for the continental US

Risk assessment in water resources planning under climate change at the Júcar River basin

Comparison of open access global climate services for hydrological data

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