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Nan Feng

Oil Palm Plantation as Biomass Energy Sources over Maritime Southeast Asia and Their Impacts on Regional Climate. Nan Feng Department of Atmospheric Sciences, University of Alabama in Huntsville, Huntsville AL, USA feng@nsstc.uah.edu. ESS632 Final Project 30 th November 2015. Outlines.

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Nan Feng

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  1. Oil Palm Plantation as Biomass Energy Sources over Maritime Southeast Asia and Their Impacts on Regional Climate Nan Feng Department of Atmospheric Sciences, University of Alabama in Huntsville, Huntsville AL, USA feng@nsstc.uah.edu ESS632 Final Project 30th November 2015

  2. Outlines • Introduction & Motivation • Datasets and Methodology • Results • Conclusion

  3. Introduction & Motivation Oil Palm Plantation, is a basic source of income for many farmers in Southeast Asia. It is mainly used as the world’s most consumed plant oil, and also increasing demand as biodiesel energy.

  4. Background: Palm oil used as biofuel energy Palm oil is more efficient and with much lower price than other biofuel sources

  5. Significant changes over the last decades, peat swamp forest to oil palm plantation However, the rise of palm oil comes at a heavy cost. Over the past 20 years, forest destruction for the expansion of the palm oil market has continued relatively unchecked. Governments, such as Indonesia, have done little to stop the conversion of forests to palm plantations. About 62% of the world’s tropical Peatswamp forests are in SE Asia, which is one of the most important carbon storage place.

  6. Future expansion of palm oil plantation • The clearing process for agriculture used land is still going, and will keep going like this if the government and local residents has been noticed that their climate and environment will be permanently changed.

  7. Background: Regional Climate and Environment Change in Southeast Asia due to Land cover and Land-use Changes Biogeochemical Processes

  8. Background: Regional Climate Change in Southeast Asia due to Land cover and Land-use Changes Biogeophysical Processes Pielkeet al., 2007 Land Use and Land Cover (LULC) change has a measureable and equal significant impact on climate at multiple geographic scales [Pielke et al., 2005; Mahmood et al., 2010, 2014; IPCC 2014a].

  9. Objective: • The intent of study is to quantitatively evaluate anthropogenic land use change impacts on climate over SE Asia through applications of satellite data, in-situ observations and numerical models. • Questions to be answered: • To what extent does the land cover transition from peat swamp forest to oil palm plantation over southeast Asia impact the surface energy budget, boundary layer development, cloud formation and precipitations?

  10. Datasets

  11. Datasets: CRISP MODIS LAND Product • LULC changes • Sarawak, Malaysia • Deforestation • (Peatswamp + • Montane Forest)1710 km2 (16.5%) • Replantation • (Oil Palm Plantation) • 1037 km2 (9.6%)

  12. Methodology Nested grid simulations based on Weather Research Forecasting Version 3.6 modelling system (WRFV3.6) over the central region of the Sarawak coast for 2000 and 2010 LULC scenarios (From CRISP MODIS), both assuming August 2009 atmospheric conditions. All of the experiments utilized in this study use a hierachy of four nested grids, with the outmost grid of 64km grid spacing covering a domain that includes a substantial portion of Southeast Asia. Atmosphere initialized every 24 hours, but soil conditions are propagated between cycles

  13. Methodology: Land cover representation improved

  14. Results • Evaluation of the WRF Simulations • Surface Temperature, Dew Point, and Wind Comparisons • Rainfall Comparisons • Land Use Change Impacts on Diurnal Temperature Range • Sensible Heat (SH) and Latent Heat Flux (HFX) • Wind speed • Cloud Formation • Precipitation Differences

  15. Validation: Surface Temperature, Dew Point, and Wind Comparisons

  16. Validation: Rainfall Comparisons The bias and RMSE for modulated simulated rainfall compared to ground-based rainfall observations are compared above, while most points fall into ±10% error lines. Inter-comparison of TRMM rainfall estimates and ground observations show an RMSE of 18.11 mm and a bias of -5.0 mm.

  17. Results: Monthly Averaged 2 meter Diurnal Temperature Range (K) - 0.3K

  18. Results: Monthly Averaged Sensible Heat (Wm-2) +1.8W/m2

  19. Results: Monthly Averaged Latent Heat Flux (Wm-2) -7.6 W/m2

  20. Results: Monthly Averaged Wind Pattern (m/s) +0.2 m/s • Tropical deforestation leads to roughness length  • Further results in apparent increase of low level wind speed. • Meso-scale wind circulation are particularly sensitive to LULC change, more obvious in the transition area.

  21. Results: Monthly Cloud total water path (g/m2) -12.0g/m2 • Apparently decreasing of cloud total water path due to LULC change • Convective clouds tend to develop over tropical forested area. • Consistent with previous studies [e.g. Takahashi et al., 2010; Fairman et al., 2011; Nair et al., 2011]

  22. Results: Monthly Averaged Rainfall (mm/month) • Decrease in monthly averaged precipitations (6.7 mm/month) • Tropical deforestation may result in up to 2.0 mm per day reduction in rain fall over land area. • Decreasing of Precipitation is coincide with regions of reduced CWP

  23. Conclusion • Numerical model projects significant changes in non radiative transfer fluxes, cloud formations, boundary layer development and precipitation pattern due to observed LULC changes from peat swamp forest to oil palm plantation over the last decade • Not only the right land classification, it’s also important to get the parameterizations right to be better matched with measurements (e.g. satellite).

  24. Conclusion • LULC change studies for all scales should be incorporated into developing global climate model that addressing impacts on energy balance, atmospheric circulation, hydrological cycle. • Palm oil is bad not because of what it is, but because of where it is. Southeast Asian Forests are some of the most naturally diverse and carbon rich environments on earth….best left alone. • Until a truly sustainable market of Palm Oil (for food & fuel) is established, the fate of Southeast Asian forests hangs in a delicate balance.

  25. Acknowledgements • CRISP MODIS Land group, Singapore • NASA Langley Research Center (MTSAT Cloud product, Minnis et al. 2008) • National Centers For Environmental Prediction Global Forecast System (NECP GFS) • MODIS team • ARW WRF system handled by Mesoscale and Microscale Meteorology (MMM) Laboratory of NCAR

  26. Questions?

  27. Backup slides

  28. Backup slide :Table 1. WRF model Configuration for all of the experiments

  29. Diurnal variations of a) Albedo b) roughness length c) soil moistures d) Leaf area index e) Vegetation Fraction f) PBLH g) LST and 2 meter Temperature (dashed) h) Sensible Heat i) Latent Heat for Peatswamp evergreen forest (green), deforested lowland open (red) and Agriculture land (brown) based on model simulations

  30. Validation: Comparisons of Cloud Liquid Water Path Between WRF, MODIS and MTSAT

  31. Validation: Day time cloud frequency comparisons • Definition of Prediction evaluation [Fairman et al., 2011]

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