Chini, Louise: University of Maryland (Project Lead)
Project Funding:
2013 - 2015
NRA: 2012 NASA: Terrestrial Ecology
Funded by NASA
Abstract:
In preparation for the 5th IPCC Assessment almost all Earth System Models (ESMs) have recently incorporated new gridded products of land-use and land-use change that have been harmonized to ensure a continuous transition from the historical to the future data in a consistent format for all models. These Land-Use Harmonization (LUH) data products have now been widely adopted by the ESM community. However, the LUH land-use transitions are estimates, constrained with data where available, and with modeling assumptions, and the remaining challenge is to quantify, and reduce, the uncertainty in these products. At the same time, satellite remote sensing of the terrestrial biosphere has also evolved. Global-scale land cover extent and change monitoring is now possible given systematically acquired earth observation data sets, advanced characterization algorithms and data intensive computing capabilities. With the availability of these products, and our team's prior experience generating land-use transitions for global climate modeling, we have a unique opportunity to address the following key science questions: (1) How can satellite remote sensing products be used to generate new gridded maps of land-use transitions for use in coupled carbon-climate simulations? (2) How can satellite remote sensing products be used to characterize uncertainty in these new maps of global land-use transitions? We will address these questions via two main objectives: (1) We will use NASA remote sensing data to generate maps of global forest extent and change (GFEC) which we will then use as an additional constraint in our LUH process to produce an entirely new generation of land-use transitions that are organized in a format that has been widely adopted by climate models. (2) We will characterize the inherent uncertainty in the remote-sensing-based maps of GFEC from Objective 1 and then propagate this uncertainty through our LUH process via a large ensemble of simulations that will enable us to characterize, for the first time, the uncertainty in the LUH land-use transitions themselves. This proposal is responsive to the NASA Terrestrial Ecology request for "data set development to meet priority needs of the NASA terrestrial ecological community", particularly the request for "global gridded data on land-cover, land-use, land-use transitions, and land-cover changes (past, present, future)". The wide-spread adoption of our current LUH datasets by the climate modeling community will ensure that these new land-use transition datasets are rapidly employed in a new generation of ESM simulations that are based on, and consistent with, observations of actual forest cover change.
Publications:
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenoder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., van Vuuren, D. P., Zhang, X. 2020. Harmonization of global land use change and management for the period 850-2100 (LUH2) for CMIP6. Geoscientific Model Development. 13(11), 5425-5464. DOI: 10.5194/gmd-13-5425-2020
Ma, L., Hurtt, G. C., Chini, L. P., Sahajpal, R., Pongratz, J., Frolking, S., Stehfest, E., Klein Goldewijk, K., O'Leary, D., Doelman, J. C. 2020. Global rules for translating land-use change (LUH2) to land-cover change for CMIP6 using GLM2. Geoscientific Model Development. 13(7), 3203-3220. DOI: 10.5194/gmd-13-3203-2020
2015 NASA Carbon Cycle & Ecosystems Joint Science Workshop Poster(s)
- Using NASA Remote Sensing Data to Reduce Uncertainty of Land-use Transitions in Global Carbon-Climate Models
-- (Louise Chini, Justin Fisk, Matthew Hansen, George Hurtt, Peter Potapov)
[abstract]
More details may be found in the following project profile(s):
