@article{CannonCarvalhoJonesetal.2017,
  author    = {Cannon, Forest and Carvalho, Leila M. V. and Jones, Charles and Norris, Jesse and Bookhagen, Bodo and Kiladis, George N.},
  title     = {Effects of topographic smoothing on the simulation of winter precipitation in High Mountain Asia},
  series = {Journal of Geophysical Research: Atmospheres},
  volume    = {122},
  journal   = {Journal of Geophysical Research: Atmospheres},
  number    = {3},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {2169-897X},
  doi       = {10.1002/2016JD026038},
  pages     = {1456 -- 1474},
  year      = {2017},
  abstract  = {Numerous studies have projected future changes in High Mountain Asia water resources based on temperature and precipitation from global circulation models (GCMs) under future climate scenarios. Although the potential benefit of such studies is immense, coarse grid-scale GCMs are unable to resolve High Mountain Asia's complex topography and thus have a biased representation of regional weather and climate. This study investigates biases in the simulation of physical mechanisms that generate snowfall and contribute to snowpack in High Mountain Asia in coarse topography experiments using the Weather Research and Forecasting model. Regional snowpack is event driven, thus 33 extreme winter orographic precipitation events are simulated at fine atmospheric resolution with 6.67 km resolution topography and smoothed 1.85° × 1.25° GCM topography. As with many modified topography experiments performed in other regions, the distribution of precipitation is highly dependent on first-order orographic effects, which dominate regional meteorology. However, we demonstrate that topographic smoothing enhances circulation in simulated extratropical cyclones, with significant impacts on orographic precipitation. Despite precipitation reductions of 28\% over the highest ranges, due to reduced ascent on windward slopes, total precipitation over the study domain increased by an average of 9\% in smoothed topography experiments on account of intensified extratropical cyclone dynamics and cross-barrier moisture flux. These findings identify an important source of bias in coarse-resolution simulated precipitation in High Mountain Asia, with important implications for the application of GCMs toward projecting future hydroclimate in the region.},
  language  = {en}
}
@article{NorrisCarvalhoJonesetal.2017,
  author    = {Norris, Jesse and Carvalho, Leila M. V. and Jones, Charles and Cannon, Forest and Bookhagen, Bodo and Palazzi, Elisa and Tahir, Adnan Ahmad},
  title     = {The spatiotemporal variability of precipitation over the Himalaya: evaluation of one-year WRF model simulation},
  series = {Climate dynamics : observational, theoretical and computational research on the climate system},
  volume    = {49},
  journal   = {Climate dynamics : observational, theoretical and computational research on the climate system},
  publisher = {Springer},
  address   = {New York},
  issn      = {0930-7575},
  doi       = {10.1007/s00382-016-3414-y},
  pages     = {2179 -- 2204},
  year      = {2017},
  abstract  = {The Weather Research and Forecasting (WRF) model is used to simulate the spatiotemporal distribution of precipitation over central Asia over the year April 2005 through March 2006. Experiments are performed at 6.7 km horizontal grid spacing, with an emphasis on winter and summer precipitation over the Himalaya. The model and the Tropical Rainfall Measuring Mission show a similar inter-seasonal cycle of precipitation, from extratropical cyclones to monsoon precipitation, with agreement also in the diurnal cycle of monsoon precipitation. In winter months, WRF compares better in timeseries of daily precipitation to stations below than above 3-km elevation, likely due to inferior measurement of snow than rain by the stations, highlighting the need for reliable snowfall measurements at high elevations in winter. In summer months, the nocturnal precipitation cycle in the foothills and valleys of the Himalaya is captured by this 6.7-km WRF simulation, while coarser simulations with convective parameterization show near zero nocturnal precipitation. In winter months, higher resolution is less important, serving only to slightly increase precipitation magnitudes due to steeper slopes. However, even in the 6.7-km simulation, afternoon precipitation is overestimated at high elevations, which can be reduced by even higher-resolution (2.2-km) simulations. These results indicate that WRF provides skillful simulations of precipitation relevant for studies of water resources over the complex terrain in the Himalaya.},
  language  = {en}
}
@article{SmithBookhagenCannon2015,
  author    = {Smith, Taylor and Bookhagen, Bodo and Cannon, Forest},
  title     = {Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia},
  series = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union},
  volume    = {9},
  journal   = {The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union},
  number    = {5},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1994-0416},
  doi       = {10.5194/tc-9-1747-2015},
  pages     = {1747 -- 1759},
  year      = {2015},
  abstract  = {Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity. In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10\% of glacier areas, as compared to a similar to 750 glacier control data set, and can reliably classify a given Landsat scene in 3-5 min. The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.},
  language  = {en}
}