Publications Published in EOS

1. A Method for Prediction of California Summer Air Surface Temperature. E.ALFARO,A.GERSHUNOV,D.CAYAN, A. STEINEMANN,D.PIERCE, T. BARNETT.
   EOS: 2004
   
   
2. El Nino-induced flooding in the U.S. West: What can we expect?. Pizarro, Gonzalo; Lall, Upmanu.
   EOS: 2002
   
   
3. Forest Disturbance and North American Carbon Flux. Goward, Samuel N.; Masek, Jeffrey G.; Cohen, Warren; Gretchen, Moisen; Collatz, James; Healey, Sean; Houghton, R. A.; Huang, Chengquan; Kennedy, Robert; Law, Beverly.
   EOS: 2008
   Notes
   North America's forests are thought to be a significant sink for atmospheric carbon. Currently, the rate of sequestration by forests on the continent has been estimated at 0.23 petagrams of carbon per year, though the uncertainty about this estimate is nearly 50%. This offsets about 13% of the fossil fuel emissions from the continent [Pacala et al., 2007]. However, the high level of uncertainty in this estimate and the scientific community's limited ability to predict the future direction of the forest carbon flux reflect a lack of detailed knowledge about the effects of forest disturbance and recovery across the continent.
   
   
   
4. Integrating Climate-Hydrology Forecasts and Multi-Objective Reservoir Management for Northern California. Georgakakos, K.P.; Graham, N.E.; Carpenter, T.M.; Georgakakos, A.P.; Yao, H..
   EOS: 2005
   
   
5. Interpreting Recent Temperature Trends in California . Duffy, P.B.; Bonfils, C.; Lobell, David.
   EOS: 2007
   Notes
   Regional-scale climate change and associated societal impacts result from large-scale “forcing” (perturbing) agents, such as wellmixed greenhouse gases, and from land-use changes and other, more local phenomena. In order to predict future climate and societal impacts, it is essential to understand these forcings and the climate responses to them. California serves as a good example of the complex effects of multiple climate forcings. The state’s natural climate is diverse, highly variable, and strongly influenced by the El Niño–Southern Oscillation (ENSO) phenomenon. Humans are perturbing this complex climate system through urbanization, irrigation, and the emission of multiple types of aerosols and greenhouse gases. Despite better-thanaverage observational coverage, scientists are only beginning to understand the manifestations of these forcings in California’s temperature record. Neither the nature of climate trends in California nor their causes are well understood. This article discusses recent temperature trends in California, the role of climate models in understanding these trends, and research needed to improve the ability to predict regional climate change.
   
   
   
6. Land Warming as Part of Global Warming . Huang, S..
   EOS: 2006
   Notes
   The recent warming of Earth’s surface is well documented in meteorological records. According to the World Meteorological Organization, the Earth’s average surface air temperature (SAT) rose about 0.6°C in the twentieth century [
   
   
   
7. New Tools for Analyzing Time Series Relationships and Trends. Moore, J.C.; Grinsted, A.; Jevrejeva, S..
   EOS: 2005
   Notes
   Geophysical studies are plagued by short and noisy time series. These time series are typically nonstationary, contain various long-period quasi-periodic components, and have rather low signal-to-noise ratios and/or poor spatial sampling. Classic examples of these time series are tide gauge records, which are influenced by ocean and atmospheric circulation patterns, twentieth-century warming, and other long-term variability. Remarkable progress recently has been made in the statistical analysis of time series. Ghil et al. [2002] presented a general review of several advanced statistical methods with a solid theoretical foundation. This present article highlights several new approaches that are easy to use and that may be of general interest. Extracting trends from data is a key element of many geophysical studies; however, when the best fit is clearly not linear, it can be difficult to evaluate appropriate errors for the trend. Here, a method is suggested of finding a data-adaptive nonlinear trend and its error at any point along the trend. The method has significant advantages over, e.g., low-pass filtering or fitting by polynomial functions in that as the fit is data adaptive, no preconceived functions are forced on the data; the errors associated with the trend are then usually much smaller than individual measurement errors.
   
   
   
8. Permafrost Temperature Records: Indicators of climate Change. Romanovsky, V; Burgess, M; Smith, S; Yoshikawa, K; Brown, J.
   EOS: 2002
   
   
9. Toward a New Generation of Ice Sheet Models . Little, Christopher M.; Oppenheimer, Michael; Alley, Richard B.; Balaj, Venkatramani; Clarke, Garry K.C.; Delworth, Thomas L.; Hallbergy, Robert; Holland, David M.; Hulbe, Christina L.; Jacobs, Stan.
   EOS: 2007
   Notes
   Large ice sheets, such as those presently covering Greenland and Antarctica, are important in driving changes of global climate and sea level. Yet numerical models developed to predict climate change and ice sheet–driven sea level fluctuations have substantial limitations: Poorly represented physical processes in the ice sheet component likely lead to an underestimation of sea level rise forced by a warming climate.
   
   
   
10. Tracking Climate Forcing: The Annual Greehouse Gas Index. Hofmann, D.J.; Butler, J.H.; Conway, T.J..
    EOS: 2006
    Notes
    Global monitoring of atmospheric greenhouse gases, in particular carbon dioxide (CO2), has been a goal of the U.S. government for over 30 years. The monitoring program evolved into high-precision measurements of global, long-lived greenhouse gases that are used to calculate changes in radiative climate forcing. The change in global radiative forcing caused by increases in atmospheric abundances of long-lived greenhouse gases has been used to define the Annual Greenhouse Gas Index [Hofmann et al., 2006]. This article presents a brief history of global greenhouse gas measurements of the U.S. National Oceanic and Atmospheric Administration (NOAA), and how these data are being made accessible and user-friendly.