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Surface radiative fluxes over the pan-Arctic land region: variability and trends

Surface radiative fluxes over the pan-Arctic land region: variability and trends. Xiaogang Shi Martin Wild Dennis P. Lettenmaier a Dept of Civil and Env Engr., University of WA b Institute for Atmospheric and Climate Science, ETH Zurich Annual PI Meeting NASA Energy and Water Cycle Study

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Surface radiative fluxes over the pan-Arctic land region: variability and trends

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  1. Surface radiative fluxes over the pan-Arctic land region: variability and trends Xiaogang Shi Martin Wild Dennis P. Lettenmaier aDept of Civil and Env Engr., University of WA bInstitute for Atmospheric and Climate Science, ETH Zurich Annual PI Meeting NASA Energy and Water Cycle Study Columbia, MD December 2, 2009

  2. We evaluated the reanalysis products (ERA-40 and ERA-Interim), satellite product (ISCCP), and land surface model (VIC) off-line simulation against in situ surface radiation measurements. • The temporal, spatial and latitudinal variability of downward shortwave radiation, downward longwave radiation and albedo (abbreviated as DSW, DLW and AL, respectively, hereinafter) from different estimates was compared explicitly for the entire pan-Arctic land region. • For a few observed stations with long-term DSW records from GEBA, their trends were detected.

  3. Surface radiative fluxes evaluation Mean diurnal cycle difference of DSW at Barrow, Alaska Global Energy Balance Archive (GEBA) Mean seasonal cycle with observations

  4. Surface radiative fluxes variability and trends DSW DLW AL

  5. Next steps • Investigate the temporal variability and trends in snow cover extent over the pan-Arctic from the reanalysis and satellite products. • Examine if land surface hydrologic model could reveal similar variability and trends. • Investigate the impact (correlation and sensitivity) on snow cover extent from the dimming/brightening phenomenon in downward solar radiation.

  6. Global water balance: Continental River discharge and reservoir storage Elizabeth Clarka, Hester Biermanb, and Dennis P. Lettenmaiera aDepartment of Civil and Environmental Engr., University of WA Earth Science System Group, Wageningen University Annual PI Meeting NASA Energy and Water Cycle Study Columbia, MD December 2, 2009

  7. Estimating river discharge Dai et al. (2009) used observations from 925 gaging stations, in concert with CLM 3.0 estimates of streamflow, to estimate global river discharge to the ocean We are replacing CLM 3.0 with VIC estimates of discharge for scaling observations to unmonitored areas We intend to adapt the Biemans et al. (2009) method to produce global estimates of anthropogenic effects on the land surface water budget for NEWS.

  8. River Discharge Streamflow Observations Hydrologic model Reservoir Locations and Uses

  9. Location of reservoirs globally Global reservoir capacity and storage

  10. Next Steps • Apply the Dai et al. (2009) approach to three VIC model implementations (primary difference in atmospheric forcings) and compare differences • Examine annual trends and inter-annual to decadal variations in resulting streamflow estimates • Weigh the effects of reservoir and irrigation withdrawals on these trends and variations

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