63 research outputs found

    A decreasing glacier mass balance gradient from the edge of the Upper Tarim Basin to the Karakoram during 2000-2014

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    In contrast to the glacier mass losses observed at other locations around the world, some glaciers in the High Mountains of Asia appear to have gained mass in recent decades. However, changes in digital elevation models indicate that glaciers in Karakoram and Pamir have gained mass, while recent laser altimetry data indicate mass gain centred on West Kunlun. Here, we obtain results that are essentially consistent with those from altimetry, but with two-dimensional observations and higher resolution. We produced elevation models using radar interferometry applied to bistatic data gathered between 2011 and 2014 and compared them to a model produced from bistatic data collected in 2000. The glaciers in West Kunlun, Eastern Pamir and the northern part of Karakoram experienced a clear mass gain of 0.043 ± 0.078~0.363 ± 0.065 m w.e. yr−1. The Karakoram showed a near-stable mass balance in its western part (−0.020 ± 0.064 m w.e. yr−1), while the Eastern Karakoram showed mass loss (−0.101 ± 0.058 m w.e. yr−1). Significant positive glacier mass balances are noted along the edge of the Upper Tarim Basin and indicate a decreasing gradient from northeast to southwest

    Challenges of operational river forecasting

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    Skillful and timely streamflow forecasts are critically important to water managers and emergency protection services. To provide these forecasts, hydrologists must predict the behavior of complex coupled human–natural systems using incomplete and uncertain information and imperfect models. Moreover, operational predictions often integrate anecdotal information and unmodeled factors. Forecasting agencies face four key challenges: 1) making the most of available data, 2) making accurate predictions using models, 3) turning hydrometeorological forecasts into effective warnings, and 4) administering an operational service. Each challenge presents a variety of research opportunities, including the development of automated quality-control algorithms for the myriad of data used in operational streamflow forecasts, data assimilation, and ensemble forecasting techniques that allow for forecaster input, methods for using human-generated weather forecasts quantitatively, and quantification of human interference in the hydrologic cycle. Furthermore, much can be done to improve the communication of probabilistic forecasts and to design a forecasting paradigm that effectively combines increasingly sophisticated forecasting technology with subjective forecaster expertise. These areas are described in detail to share a real-world perspective and focus for ongoing research endeavors
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