Doug Nychka

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discussions regarding the validation of the model and for providing the GMS cloud imagery used in this presentation; T. Hoar for assistance with the acquisition of datasets; J. Tribbia for helpful discussions pertaining to linear wave theory, and N. Cressie for comments on an early draft. We would also like to thank the reviewers, the editor, and associate(More)
  • Wayne Gibson, Christopher Daly, Tim Kittel, Doug Nychka, Craig Johns, Nan Rosenbloom +2 others
  • 2002
1. INTRODUCTION Currently, the only high-quality, high-resolution temperature and precipitation data sets for the continental United States suitable for use on climatological time scales are for mean values. None yet exist that represent sequential monthly values over an extended historical period. Such data sets would enable, for example: transient(More)
High-resolution climate simulations require tremendous computing resources and can generate massive datasets. At present, preserving the data from these simulations consumes vast storage resources at institutions such as the National Center for Atmospheric Research (NCAR). The historical data generation trends are economically unsustainable, and storage(More)
Each year, the Computational & Information Systems Laboratory (CISL) conducts a survey of its current and recent user community to gather a number of metrics about the scientific impact and outcomes from the use of CISL's high-performance computing systems, particularly peer-reviewed publications. However, with a modest response rate and reliance on(More)
Atmospheric Carbon Monoxide (CO) provides a window on the chemistry of the atmosphere since it is one of few chemical constituents that can be remotely sensed, and it can be used to determine budgets of other greenhouse gases such as ozone and OH radicals. Remote sensing platforms in geostationary Earth orbit will soon provide regional observations of CO at(More)
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