Convective-Scale Impacts of Deforestation on Amazonian Rainfall

Lead Research Organisation: University of Manchester
Department Name: Earth Atmospheric and Env Sciences

Abstract

The Amazon rainforest contains 40% of all remaining tropical rainforest in the world, but has seen rapid deforestation since the 1960s, and as much as 40% of the Brazilian Amazon could be deforested by 2050. Land-use change is an important man-made driver of climate change. We know that deforestation will generally make the atmosphere both warmer and drier, but how these changes will affect rainfall is more complex. Climate models mostly predict that deforestation will reduce rainfall, but the amount varies from 0 to 60% across different studies. Climate models use grid boxes of 10s to 100s km, which are much larger than a typical cloud. While cloud properties can be estimated from the conditions in the grid box, calculating the amount of rainfall is very uncertain, especially in the tropics. One solution is to run a model with much smaller grid boxes, but focusing on a small region, so that clouds and the detailed deforestation patterns found in the Amazon can be represented explicitly. These studies show that the surface patterns alter local weather patterns, increasing rainfall over the deforested patches, which contradicts climate models. However, because these studies focus on smaller regions, we do not know if these local effects are important for the water cycle of the entire Amazon.

This project will combine both approaches, using the increased computing power now available to simulate, for the first time, the entire Amazon basin while also explicitly representing clouds. This is a crucial improvement, because past studies have shown that resolving clouds leads to a complete change in model behaviour, greatly improving how tropical rainfall is represented, including climate extremes like flooding and droughts which have the most impact on local populations. We will use these simulations to investigate how increasing deforestation will affect rainfall over the Amazon, and how these changes compare to those caused by global climate change driven by increasing carbon dioxide levels.

The project is particularly exciting because it will provide a comprehensive understanding of how deforestation affects rainfall, simulating both changes in regional climate and the local weather patterns within it which directly affect people. Tropical rainfall is a key area of research in climate modelling, because although it is the most important climatic parameter to end users, it is also the most uncertain. For example rainfall drives a number of economic sectors such as agriculture and hydroelectric power, and while deforestation is used to clear land for agriculture, reductions in rainfall could reduce the yield per hectare, negating any economic gain from increasing the agricultural area. Patterns of deforestation can also affect where it rains, which could help planners identify ways to mitigate some of the negative effects on the remaining forest. This project will engage with stakeholders in the region through workshops to improve our physical understanding in a targeted way to address global challenges which have direct relevance to many people.
 
Description Brazilian partners 
Organisation National Institute for Space Research Brazil
Country Brazil 
Sector Public 
PI Contribution We are contributing to a project recently funded by the Brazilian National Council for Scientific and Technological Development. Our team is providing model simulations that are being run as part of CIDAR to this project, modelling expertise, as well as planned joint work between the PDRAs in our and their project for joint papers.
Collaborator Contribution The staff funded by the Brazilian project will contribute to the evaluation of our model simulations, as well as part of the analysis where there are overlapping objectives, thus contributing to publications coming out from this project.
Impact Project funded for Brazilian partners with in-kind contributions from our project.
Start Year 2023
 
Description Brazilian partners 
Organisation University of Taubaté
Country Brazil 
Sector Academic/University 
PI Contribution We are contributing to a project recently funded by the Brazilian National Council for Scientific and Technological Development. Our team is providing model simulations that are being run as part of CIDAR to this project, modelling expertise, as well as planned joint work between the PDRAs in our and their project for joint papers.
Collaborator Contribution The staff funded by the Brazilian project will contribute to the evaluation of our model simulations, as well as part of the analysis where there are overlapping objectives, thus contributing to publications coming out from this project.
Impact Project funded for Brazilian partners with in-kind contributions from our project.
Start Year 2023
 
Description Brazilian partners 
Organisation University of the State of Amazonas
Country Brazil 
Sector Academic/University 
PI Contribution We are contributing to a project recently funded by the Brazilian National Council for Scientific and Technological Development. Our team is providing model simulations that are being run as part of CIDAR to this project, modelling expertise, as well as planned joint work between the PDRAs in our and their project for joint papers.
Collaborator Contribution The staff funded by the Brazilian project will contribute to the evaluation of our model simulations, as well as part of the analysis where there are overlapping objectives, thus contributing to publications coming out from this project.
Impact Project funded for Brazilian partners with in-kind contributions from our project.
Start Year 2023
 
Description UK Met Office (CIDAR) 
Organisation Meteorological Office UK
Country United Kingdom 
Sector Academic/University 
PI Contribution We are providing technical expertise in the interpretation of these climate-model simulations. We will also be sharing our own simulations with the Met Office once these are complete.
Collaborator Contribution The UK Met Office have shared data from very computationally expensive climate-model simulations done for Brazil, as part of their CSSP Brazil research programme, which form the basis of the control simulation for our project. The in-kind value is estimated based on the computing cost associated with these simulations (~1,000,000 node-hours).
Impact Model simulations generated by this project thanks to input by the UK Met Office (no doi yet).
Start Year 2021
 
Description Stakeholder workshop 2022 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Policymakers/politicians
Results and Impact Ran an online workshop bringing together policymakers and users of climate data in the Amazon region, including representatives from civil defence, regional and state environmental agencies, health and fire services, with a total of ~30 participants. The activity was aimed at disseminating information on this project, and using break-out groups to gather information from the participants on what their climate-data needs are and how our project could contribute to these. Outputs from this workshop include plans for a data visualisation portal to allow stakeholders to easily access project results, and plans for a further workshop for dissemination of project results. Workshop participants were very engaged and interested in participating in future workshops.
Year(s) Of Engagement Activity 2022