LEADING - Land usE chAnges anD mItigation of global warmiNG
- FCiências.ID - Associação para a Investigação e desenvolvimento de Ciências(líder)
- Universidade de Évora(parceiro)
Summary
Climate change has been recognised as one of the major challenges for the 21st century. In order to address such challenge, Global Climate simulations with increasingly sophisticated representation of the global atmospheric ocean-land physical mechanisms have been developed. These Earth System Models (ESM) have coarse horizontal resolutions, good enough to reproduce many aspects of large-scale climate (Meehl et al 2007), but unable to represent several processes and systems that drive regional and local climate, where most of the consequences of climate change will be felt. Regional Climate Models (RCMs) have been used to downscale ESMs and realistically capture regional to local scale processes (Rummukainen 2010). The challenges for RCMs include the creation of Regional Earth System Models by incorporating coupled ocean models, water table and dynamic vegetation, as well as other components. An additional challenge is the use of high resolution, but such finer resolution requires careful attention
both to numerical aspects and to physical parameterizations suitability (Arritt and Rummukainen 2011). The link between climate and Land use changes (LUC) has been investigated using RCMs in different regions of the world (Pielke et al. 2011, Mahmood et al. 2014) and can have an impact in regional climate as important as greenhouse gas emissions (Ducoudré et al. 2012). Nevertheless, no coordinated attempt to robustly identify the magnitude of the contribution of LUC to the mitigation or enhancement of climate change has been previously attempted. Firstly, it is essential to quantify the role of land use to the present climate through the use of RCMs forced by reanalysis and
through sensitivity studies to different LUC scenarios. This will contribute to establish how LUC impacted on past climate trends and how it can be used to mitigate the future climate change. The results from the RCM simulations will be evaluated against observations, focusing on water and energy land/atmosphere fluxes, and common atmospheric
variables. Secondly, the influence of LUC in climate change enhancement/mitigation will be investigated through the downscaling of two climate scenarios. The results will be part of the inter-comparison efforts linked to the Flagship Pilot Study LUCAS (Land Use & Climate Across Scales) initiative supported by the WCRP CORDEX and GEWEX GASS international program.The heterogeneity of land use cross Europe requires fine?scale modelling techniques thus very high resolution (
Goals, activities and expected/achieved results
Goals
- O1: Quantification of the relative contribution of LUC to the past climate evolution in Europe: downscaling global reanalyses data with regional climate models based on harmonised reconstructed land use dynamics
- O2: Identification of robust biophysical impacts of LUC on the regional climate under different level of global warming: downscaling identical global climate simulations with WRF based on one extreme and one potential future LUC scenario
- O3: Inter-comparison of simulated land-atmosphere interactions and their sensitivities to LUC and evaluation of model performance against multi-variable observations
- O4: Investigating feedbacks of local scale land use dynamics on climate
- O5:To contribute to a framework for multi-scale earth system analyses to identify optimal land use pathways including mitigation and adaptation to climate change
Activities
The Project consists of one task of coordination and management and six scientific tasks formally organized into three Work Packages (WP): 1) Land-Use contributions to Present climate, 2) Assessing Land-Atmosphere Feedbacks in Future Climate and 3) High resolution Regional Climate: Past, Present and Future. WP1 includes tasks1 and 2. In task 1 Continental scale WRF reanalysis driven simulations with and without land use change will be performed. Both realistic and idealised land use maps with transient vegetation and idealised static vegetation maps for Europe will be used. These will be the basis of task 2 where soil humidity and planetary boundary layer and relationship with extreme weather events under different land use scenarios is the main objective. All the simulations will be evaluated and validated against an array of observational dataset and will also contribute to the CORDEX/LUCAS-compliant simulations.
WP2 comprises tasks 3 and 4. In task 3, two (an extreme and a mild) 21st century climate scenarios will drive WRF continental scale simulations with and without land uses changes. Static, transient and idealise vegetation maps will be considered. Task 4 will be dedicated to the analysis of extreme events under climate change in order to improve the understanding of the importance of biophysical impacts in the context of the atmosphere-land feedbacks at continental scale. These results will not only contribute to CORDEX/LUCAS-compliant simulations, but also to quantify impacts under 2oC warming. WP3 contains task 5 and 6. In task 5 the WRF land system model (LSM) will perform very high resolution (~2km) offline simulations. These will assess the influence of resolution and vegetation parameterization on atmosphere/land feedbacks. Task 6 will address the climate change signal associated to a major land use change (the largest artificial water reservoir in Europe ? Alqueva) through an array of coupled atmosphere/land high resolution simulations (
Results
Expected impact (EI):
EI1: Fill the scientific gap of missing robust information on biophysical feedbacks of LUC on regional climate
EI2: Identify potential biases that arise from missing land use dynamics in regional climate change projections and help to improve the simulated impacts
EI3: Support decision making on local land management by revealing the potential of LUC to attenuate negative impacts of global warming
EI4: Better constrain further strategic development of coupled land-atmosphere and regional earth system models
| Attribute | Type | Value |
|---|---|---|
| id | integer | 3860 |
