Using satellite observations to measure the direct climate impacts of oil palm expansion in Indonesia Natalie Schultz Heat budget group meeting June 13, 2013

Background Deforestation Agricultural Expansion Biogeochemical EffectsBiophysical Effects CO2 emissions Other GHGs N2O CH4 Evapotranspiration Albedo Surface roughness Net climate impact Climate policy Land management

Background Global demand for food and fuel is driving agricultural expansion in the tropics Dramatic loss of forests in recent years in Indonesia, caused in large part by the expansion of oil palm plantations World Resources Institute

Background Previous studies in the Amazon have shown that the conversion of rainforest to cropland or pasture can influence regional and global climate through changes in the surface energy and water budgets – Higher temperatures, changes in cloud cover and precipitation in addition to increased CO2 emissions – This research has focused on annual crops such as soybean, sugarcane, etc. – Indonesia LUC unique because oil palm lifespan is ~25 yrs and grows to ~20 m tall What are the direct climate effects of oil palm expansion in Indonesia?

Data Sources Landsat TM from January 2010 and reference image from 2000 (path 119, row 62). – Subset to ~3000 km 2 region MODIS Products – LST 8day 1km (MOD11A2) – NDVI 16 day 1km (MOD13A2) – ET annual 1km (MOD16A3) – Albedo 16 day 1km (MCD43B3)

Uneven-aged stands Use annual minimum NDVI to determine year of field conversion Landsat TM Jan 16, 2010

Oil palm expansion from NDVI

Site selection 4km 2 palm field 4km 2 forest

Temperature YearMeanStd Dev

Evapotranspiration YearMeanStd Dev

NDVI YearMeanStd Dev

Albedo YearMeanStd Dev

TemperatureET

NDVIAlbedo

Surface energy budget ET has stronger influence on surface temperature than albedo – 425 mm/year (1.16 mm/day) ET reduction  average reduction in latent heat flux of 30 W/m 2 – increase in albedo  approx 3.5 W/m 2 reflected Roughness effect not quantified

Additional considerations Results valid for clear-sky conditions only – Preliminary examination of NDVI “pixel reliability” index Uncertainties in MODIS data– validation Limited in space and time

Conclusions Changes in LST, ET, NDVI, and albedo were observed following the conversion of forest to oil palm field. Is the spatial extent and rate of change occurring in ways that could trigger larger scale climate feedbacks (e.g precip, clouds, veg changes)? Should this type of information be incorporated into a metric of the total land use change effect on climate? How to quantify?