In the context of atmospheric models, operational systems are those that dependably provide important, time-critical forecasts for use in decision-support systems.  They are characterized by the need for rapid data acquisition and model setup, reliable execution of the model, and post-processing activities that sometimes require delivery of model output timesteps as soon as they are completed.  In Alaska, reliable and timely weather forecasts are essential for a variety of commercial, recreational, and simple day-to-day living activities.  In addition to routine operational forecasting, Alaskans need to be prepared for surprise events.  Volcanic eruptions occur with some regularity in Alaska and Russia, affecting air transport and sometimes shutting down urban areas.  Uncontrolled wildfires in unpopulated regions are a fact of life, and Alaskans are sometimes subject to huge smoke emissions during the summer.   Additionally, Alaska is affected by non-predictable anthropogenic events such as toxic emissions and nuclear fallout.

 In addition to providing the tools for decision support, operational products from Alaska are also useful in a number of "downstream" research endeavors including road weather prediction systems, aviation icing products and greenhouse gas studies.  

 With a decade of experience in provision of operational products, often for large areas at high resolutions, we have gained a fair amount of experience and wisdom, and still have much to learn.  In this presentation we discuss some of the systems we have deployed, lessons learned, and the many exciting ambitions we have.

How can observations be used to best evidence the influence on climate of human activities, among other forcings? Statistical methods of Detection and Attribution (D&A)were designed to answer this question. Conventional D&A methods are based on linear regression of spatial or temporal patterns extracted from one or several climate models ("optimal fingerprinting").

On the other hand, how can observations be used to best constrain a numerical model’s state variables and parameters? Methods of Data Assimilation (DA) meet this general purpose. Could D&A methods take advantage of recent progresses in DA? We argue that one may hope so. Indeed, under an inverse problem formulation of D&A, observations can be seen as a complex function of the forcings consisting of the full climate model itself. Under this perspective, D&A consists "merely" in reconstructing forcings from available observations by inverting the full climate model itself - a challenge for which recent DA-based parameter estimation schemes might be an answer.

We will discuss this general idea and illustrate it qualitatively by applying a simple data assimilation algorithm (AEKF) to a 1D radiative column model. The model simulates the vertical temperature structure of the atmosphere resulting from prescribed vertical profiles of key optical properties, as well as its dynamics when these optical properties are affected by changes in atmospheric constituents. In particular, it allows to represent the characteristic pattern of cooling of the stratosphere and warming of the troposphere under greenhouse gas forcing, which is a historical fingerprint used in D&A. We show that it is possible to reconstruct these forcings from the observation of the evolution of the vertical temperature profile based on data assimilation and thereby to evidence the influence of anthropogenic forcing on the evolution of climate.

The zonal mean mass circulation of the stratosphere (i.e. the Brewer-Dobson circulation) is characterized by upwelling in the tropics and downwelling at high latitudes. The ascent near the tropical tropopause largely controls the composition of air entering the stratosphere. Despite its relevance, tropical upwelling is poorly constrained by observations and its magnitude, variability and specific forcings are currently uncertain.

The variability of upwelling is especially evident on tracers with steep vertical gradients across the tropical tropause, such as ozone and carbon monoxide. We use satellite observations of these tracers to investigate the circulation near and above the tropical tropopause, and compare different indirect estimates of upwelling. The observations are complemented by parallel analyses using WACCM, and we quantify the influence of tropical upwelling and eddy transport on tracer variability spanning daily to seasonal timescales.

Finally, we identify the dynamical forcings leading to the observed sub-seasonal fluctuations in upwelling (linked to variability in the tracers). The Brewer-Dobson circulation is dynamically driven, and our results demonstrate the importance of extratropical synoptic-scale and planetary waves in forcing upwelling across the tropical tropopause.

The 2013 NCAR Workshop on Climate and Health will focus on two related atmospheric hazards, the individual and combined effects of extreme heat and air pollution on human health. The purpose of the workshop is to train researchers (graduate students, post-docs and early career scientists and faculty) on how to develop robust interdisciplinary research projects in the complex area of climate and health. The four-day workshop will take place from 9-12 July 2013 and will include lectures on relevant topics in climate and climate change and in public health and human health, vulnerability studies, urban studies, statistics, and special tools for analysis (e.g., GIS or NCAR model output datasets). In addition, a few successful research projects will be highlighted, providing detailed analyses of the methods and components of the projects that led to their success. There also will be multiple opportunities to engage public health practitioners and climate scientists to discuss the integration of epidemiology, ecology, behavioral science, modeling and atmospheric science.

The 2013 NCAR Workshop on Climate and Health will focus on two related atmospheric hazards, the individual and combined effects of extreme heat and air pollution on human health. The purpose of the workshop is to train researchers (graduate students, post-docs and early career scientists and faculty) on how to develop robust interdisciplinary research projects in the complex area of climate and health. The four-day workshop will take place from 9-12 July 2013 and will include lectures on relevant topics in climate and climate change and in public health and human health, vulnerability studies, urban studies, statistics, and special tools for analysis (e.g., GIS or NCAR model output datasets). In addition, a few successful research projects will be highlighted, providing detailed analyses of the methods and components of the projects that led to their success. There also will be multiple opportunities to engage public health practitioners and climate scientists to discuss the integration of epidemiology, ecology, behavioral science, modeling and atmospheric science.