Declining Snow Cover Reduces Radia4ve Cooling from Historic Land Use Change in the Western Great Lakes Region Bethany Blakely, Adrian Rocha, Jason McLachlan Department of Biological Sciences, University of Notre Dame, Notre Dame IN ° Land Surface Changes Combined Forcing Acknowledgements Literature Cited Ques4ons Reconstruc4ng Historic Vegeta4on vForest cover has decreased since European seMlement vDeciduous and mixed forests have mostly replaced evergreen forests where forest regrowth is occurring Figure 2: Vegeta4on cover on the (a) historic landscape (b) modern landscape. Percent change in vegeta4on cover is shown in (c). We used gridded Public Land Survey (PLS) data to assign land cover classifica4ons using Interna4onal Geosphere Biosphere Programme (IGBP) designa4ons as follows: evergreen forest ( > 60% evergreen sp. cover), deciduous forest (> 60% deciduous sp. cover), mixed forest ( > 60% forest cover, mixed composi4on), vegeta4on mosaic (20% - 60% forest cover), and cropland/ grassland( < 20% forest cover). The Midwest in the Anthropocene v Land use and snow cover have changed in the Great Lakes Region since European seMlement v These changes alter the brightness and temperature of the land surface with implica4ons for climate Figure 1: Typical land use history in the Great Lakes Region. Landscapes (a) before deforesta4on, (b) immediately a_er deforesta4on, and (c, d) today. I would like to thank A. Rocha and J. McLachlan for their ideas and guidance on this project, X. Yang and B. Naimi for their MODIS processing scripts, the McLachlan lab undergraduates for digi4zing PLS data, and S. Goring for crea4on of the gridded PLS product. This project is funded by the Arthur J SchmiM Founda4on, the Paleon project, and the University of Notre Dame. v How have historic changes in land use altered the albedo and surface temperature of the Great Lakes Region? v What are the radia2ve forcings of these changes and how do they offset each other? v How has the clima4cally driven decrease in snow cover impacted these effects? Reconstruc4ng Land Surface Traits Snow Cover Changes MODIS Albedo MODIS Snow MODIS Land Cover MODIS Quality Control and Ten-year Aggrega4on Reconstructed Vegeta4on MODIS Surface Temp. MODIS Land Cover Reconstructed Albedo Reconstructed Surface Temp. Figure 3: Methodology for reconstruc4ng historic albedo and surface temperature, calcula4ng changes since European seMlement and calcula4ng radia4ve forcing of those changes. Interpola4ons of modern MODIS data were used to assign biophysical proper4es to the map of historically reconstructed vegeta4on. Albedo Surface Temperature P r o c e s s M o d e l A s s i g n Albedo Differences and Radia4ve Forcing Surface Temp. Differences and Radia4ve Forcing C o m p a r e • Chen, J., Jönsson, P., Tamura, M., Gu, Z., Matsushita, B., & Eklundh, L. (2004). A simple method for reconstruc4ng a high-quality NDVI 4me-series data set based on the Savitzky–Golay filter. Remote Sensing of Environment, 91(3–4), 332-344. • Zhao, K., & Jackson, R. B. (2014). Biophysical forcings of land-use changes from poten4al forestry ac4vi4es in north america. Ecological Monographs, 84(2), 329-353. a b c d a b c The nega2ve forcings of historic land use change currently provide a “discount” on regional warming but these benefits are likely to disappear with 2me as snow cover decreases and forest regrowth con2nues Lowess Interpola4ons of MODIS data GHCN SWE 2000-2010 GHCN SWE 1900-1910 Reconstructed Albedo Calculated shi_ in snow seasonality: Hsnow norm - Msnow norm Applied to Seasonally shi_ed Albedo Seasonal shi_ differences and radia4ve forcing v Surface temperature forcing is strongly posi4ve in summer and weakly nega4ve in winter. v Net forcing from surface temperature change weighted by day length is small and posi4ve (μ = +0.37W/m 2 ) -2°C +2° C Figure 6: Surface temperature differences for Winter (Jan 1), Spring (Apr 7), Summer (Jul 12), and Fall (Oct 16). Nega4ve values (green) indicate areas where modern surface temperature is lower than historic surface temperature. Figure 7: Seasonal profile of radia4ve forcing for surface temperature change. Gray shading designates 10% and 90% quan4les. v Spring snow melt is delayed, increasing albedo in Feb - May v Spring forcings are typically an order of magnitude larger than fall v Net forcing from the shi_ in snow seasonality is posi4ve but small (+0.45 W/m 2 ) Figure 5: Albedo differences for Winter (Jan 1), Spring (Apr 7), Summer (Jul 12), and Fall (Oct 16). Posi4ve values (green) indicate areas where modern albedo is higher than historic albedo. - 0.3 + 0.3 Surface Temperature Albedo Figure 4: Seasonal profile of radia4ve forcing for albedo change. Gray shading designates 10% and 90% quan4les. Figure 8: Spring (a) and Fall (b) shi_s in Albedo due to changes in snow cover. Black lines represent historically reconstructed Albedo shi_ed to reflect historic snow cover. Red lines show non-shi_ed historically reconstructed Albedo. Figure 9: Seasonal profile of radia4ve forcing for surface temperature change. Gray shading designates 10% and 90% quan4les. Figure 10: Methodology for seasonal shi_ in albedo based on changes in snow cover. Global Historic Climate Network (GHCN) snow water equivalents were used to calculate seasonal shi_ vSurface temperature changes offset 23% of year-round albedo forcing vClima4c shi_s in snow seasonality offset 18% of year- round albedo forcing vCombined forcing is 41% lower than vegeta4on-mediated albedo forcing alone Figure 11: Albedo (a) and total (b) radia4ve forcings of land use change in the Great Lakes Region. Dashed lines indicate component forcings. Conclusions v Albedo forcing is always nega4ve with the greatest cooling in winter v Overall radia4ve forcing from albedo change is large and nega4ve (μ = -1.64 W/m 2 ) a b a b