On the contribution of lakes in predicting near-surface temperature in a global weather forecasting model

Empirical evidence demonstrates that lakes and reservoirs are warming across the globe. Consequently, there is an increased need to project future changes in lake thermal structure and resulting changes in lake biogeochemistry in order to plan for the likely impacts. Previous studies of the impacts of climate change on lakes have often relied on a single model forced with limited scenario-driven projections of future climate for a relatively small number of lakes. As a result, our understanding of the effects of climate change on lakes is fragmentary, based on scattered studies using different data sources and modelling protocols, and mainly focused on individual lakes or lake regions. This has precluded identification of the main impacts of climate change on lakes at global and regional scales and has likely contributed to the lack of lake water quality considerations in policy-relevant documents, such as the Assessment Reports of the Intergovernmental Panel on Climate Change (IPCC). Here, we describe a simulation protocol developed by the Lake Sector of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) for simulating climate change impacts on lakes using an ensemble of lake models and climate change scenarios for ISIMIP phases 2 and 3. The protocol prescribes lake simulations driven by climate forcing from gridded observations and different Earth system models under various representative greenhouse gas concentration pathways (RCPs), all consistently bias-corrected on a 0.5^∘ × 0.5^∘ global grid. In ISIMIP phase 2, 11 lake models were forced with these data to project the thermal structure of 62 well-studied lakes where data were available for calibration under historical conditions, and using uncalibrated models for 17 500 lakes defined for all global grid cells containing lakes. In ISIMIP phase 3, this approach was expanded to consider more lakes, more models, and more processes. The ISIMIP Lake Sector is the largest international effort to project future water temperature, thermal structure, and ice phenology of lakes at local and global scales and paves the way for future simulations of the impacts of climate change on water quality and biogeochemistry in lakes.

The quality control and monitoring of surface freshwaters is crucial, since some of these water masses constitute essential renewable water resources for a variety of purposes. In addition, changes in the surface water composition may affect the physical properties of lake water, such as temperature, which in turn may impact the interactions of the water surface with the lower atmosphere. The use of satellite remote sensing to estimate the water turbidity of Alqueva reservoir, located in the south of Portugal, is explored. A validation study of the satellite derived water leaving spectral reflectance is firstly presented, using data taken during three field campaigns carried out during 2010 and early 2011. Secondly, an empirical algorithm to estimate lake water surface turbidity from the combination of in situ and satellite measurements is proposed. Finally, the importance of water turbidity on the surface energy balance is tested in the form of a study of the sensitivity of a lake model to the extinction coefficient of water (estimated from turbidity), showing that this is an important parameter that affects the lake surface temperature.

Salinization and sodification are important processes of soil degradation affecting irrigated lands. A large proportion of the global irrigated area is affected by some degree of soil salinity or sodicity caused by the intensification of irrigation. The increase of the frequency of adverse climatic conditions, like high temperatures and variations in precipitation patterns caused by climate change, will potentially amplify these processes in arid, semi-arid, and Mediterranean areas. The use of integrated approaches for the spatial and temporal prediction of the risk of salinization and sodification in irrigated areas is of great value, helping in the decision-making regarding land uses and choice of more suitable agricultural practices. In this study, based on key criteria for the assessment of irrigation-related salinization processes (e.g., climate, topography, soil drainage, water quality for irrigation, and crop irrigation method), we developed a methodology for the prediction of soil salinity and sodicity risk in irrigated lands, using two composite indices, the Salinization Risk (RSA) index and the Sodification Risk (RSO) index. The application of these indices to a real scenario (a Mediterranean area in Southern Portugal) showed that 67% of the potentially irrigated area presented a low risk of salinity development, 68% had a moderate risk of sodification, and 16% was of high risk of sodicity development. Areas under moderate risk of salinization (26%) were mostly characterized by low slopes and fine-textured soils, like Luvisols and Vertisols, with limited drainage conditions. Areas with high risk of soil sodification presented a large incidence of low slope terrain, moderate-to-restricted soil drainage, in high clay content Luvisols, Vertisols and Cambisols, and land use dominated by annual crops irrigated with surface or sprinkler systems. These risk prediction tools have the potential to be used for resource use planning by policymakers and on-farm management decision by farmers, contributing to the sustainability of irrigated agriculture in Mediterranean regions.