ABSTRACT
The climate science and applications communities need a broad and demand-driven concept to assess physical climate conditions that are relevant for impacts on human and natural systems. Here, we augment the description of the "climatic impact-driver" (CID) approach adopted in the Working Group I (WGI) contribution to the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. CIDs are broadly defined as "physical climate system conditions (e.g., means, events, and extremes) that affect an element of society or ecosystems. Depending on system tolerance, CIDs and their changes can be detrimental, beneficial, neutral, or a mixture of each across interacting system elements and regions." We give background information on the IPCC Report process that led to the development of the 7 CID types (heat and cold, wet and dry, wind, snow and ice, coastal, open ocean, and other) and 33 distinct CID categories, each of which may be evaluated using a variety of CID indices. This inventory of CIDs was co-developed with WGII to provide a useful collaboration point between physical climate scientists and impacts/risk experts to assess the specific climatic phenomena driving sectoral responses and identify relevant CID indices within each sector. The CID Framework ensures that a comprehensive set of climatic conditions informs adaptation planning and risk management and may also help prioritize improvements in modeling sectoral dynamics that depend on climatic conditions. CIDs contribute to climate services by increasing coherence and neutrality when identifying and communicating relevant findings from physical climate research to risk assessment and planning activities.
ABSTRACT
The Po River is a crucial resource for the Italian economy, since 40% of the gross domestic product comes from this area. It is thus crucial to quantify the impact of climate change on this water resource in order to plan for future water use. In this paper a mini ensemble of 8 hydrological simulations is completed from 1960 to 2050 under the A1B emission scenario, by using the output of two regional climate models as input (REMO and RegCM) at two different resolutions (25 km-10 km and 25 km-3 km). The river discharge at the outlet point of the basin shows a change in the spring peak of the annual cycle, with a one month shift from May to April. This shift is entirely due to the change in snowmelt timing which drives most of the discharge during this period. Two other important changes are an increase of discharge in the wintertime and a decrease in the fall from September to November. The uncertainty associated with the winter change is larger compared to that in the fall. The spring shift and the fall decrease of discharge imply an extension of the hydrological dry season and thus an increase in water stress over the basin. The spatial distributions of the discharge changes are in agreement with what is observed at the outlet point and the uncertainty associated with these changes is proportional to the amplitude of the signal. The analysis of the changes in the anomaly distribution of discharge shows that both the increases and decreases in seasonal discharge are tied to the changes in the tails of the distribution, i.e. to the increase or decrease of extreme events.
