Interannual variability of Great Plains precipitation in the warm-season months is analyzed using gridded station observations, satellite-based estimates, NCEP and ERA-40 global reanalysis, the recently released North American Regional Reanalysis (NARR), and the half-century long NCAR/CAM and NASA/NSIPP AMIP simulations. Great Plains precipitation variability is represented differently, and only quasi-realistically, in the global reanalyses. NCEP has larger amplitude but less traction with observations in comparison with ERA-40. Model simulations exhibit amplitudes that are closer to the reanalysis mean, but the simulated variability is essentially uncorrelated with observations. The regional atmosphere water-balance is also different: Stationary fluxes provide moisture for Great Plains precipitation variability in ERA-40 and NARR, but not in the NCEP reanalysis and model simulations; evaporation is more important in the latter. The apportioning between local and remote water sources is not without implications for the surface energy budget (and surface temperature) and hydroclimate predictability. Connections with the adjoining ocean basins are examined to foster understanding of moisture transport into the Great Plains.

Recently, the National Centers of Environment Prediction (NCEP) implemented a new coupled forecast system (CFS) for seasonal and inter-annual climate forecast. The CFS is a fully coupled model for global ocean, land and atmosphere. Its moderate climate drift in long-term integrations indicates a remarkable advancement in climate model development. Owing to its excellence in this respect, the CFS is able to forecast sea surface temperatures (SSTs) and climate simultaneously, having no need to adopt the widely used "two-tier" approach. In order to assess the ability of CFS in climate forecast, a series of climate hindcasts have been conducted for the period of 1981-2003. With this hindcast dataset, we have investigated the following issues: (1) model climate drift in seasonal forecast and its dependence on the lead time, and the tropics-extratropic teleconnection in the climate drift; (2) variability and predictability of seasonal climate in the coupled system; (3) characteristics of ENSO related climate anomalies forecasted by CFS; (4) the reality and the potential (or upper limit) of the CFS skill in seasonal climate forecast. Our analysis starts from the DJF season and is going be extended to other seasons. This presentation focuses on the DJF season only.

More than one third of the Canadian land surface drains to into Hudson, James, and Ungava Bays. These rivers transport up to 700 cubic kilometers of freshwater to Hudson Bay and Hudson Strait, and hence affect high-latitude oceanic, atmospheric cryospheric, and biologic processes.In this presentation, we will first examine Canadian river discharge to high-latitude oceans based on observed streamflow records archived in Environment Canada's Hydrometric Database (HYDAT). Daily discharge data will be analyzed to obtain the mean characteristics and recent trends of river runoff into Hudson Bay. We will then investigate possible links between the Arctic Oscillation and the variability in Hudson Bay river discharge. The final part of the talk will discuss the water budget of the entire Hudson Bay Basin using observations and reanalysis products (ERA40 and NARR), with an emphasis on precipitation, evapotranspiration, and river runoff between 1979-2001.

The recent Arctic Climate Impact Assessment reports that "annual average arctic temperature has increased at almost twice the rate as the rest of the world over the past few decades". Furthermore, the rapid surface warming in high-latitudes is particularly strong in winter. Local thermodynamical feedbacks act to amplify the surface warmings in high latitudes more strongly than the low-latitude warmings. We here present theoretical, observational, and modeling evidences suggesting that the dynamical poleward heat transport feedbacks may further amplify the enhanced high-latitude surface warmings due to each individual thermodynamical feedbacks in response to an anthropogenic radiative forcing. It can be shown that as a result of an enhanced poleward heat transport due to an anthropogenic radiative forcing, part of the extra amount of thermal energy intercepted by the low-latitude atmosphere due to an increase in its opacity is transported to high latitudes. This effectively implies a "greenhouse-plus" ("greenhouse-minus") feedback to the high (low) latitude surface temperatures, thereby amplifying (weakening) the direct response to the anthropogenic radiative forcing in high (low) latitudes. The non-local dynamical feedbacks and local ice-albedo feedbacks are strongest in winter whereas local thermodynamical feedbacks associated with water cycle are dominant in summer. Due to the suppression of the negative dynamical feedback in low-latitudes by the Stefan-Boltzmann feedback, the net dynamical feedbacks also further amplify the global mean surface temperature warmings. For an anthropogenic radiative forcing of 4 Wm-2 in a simple moist radiative-transportive coupled atmosphereland/ ocean model, the dynamical amplifier yields an additional surface warming of 0.64 K in high latitudes in winter season on top of the 1.24K warming due to sum of the anthropogenic radiative forcing and all local thermodynamic feedbacks. It also adds a 0.16K warming to the global surface warming of 1.27K due to the direct and indirect thermodynamic forcings.

We propose a method for studying the influence of intraseasonal variability on the interannual variability of seasonal mean fields. The method, using monthly mean data, provides estimates of the interannual variance and covariance, in the seasonal mean field, associated with intraseasonal variability. These estimates can be used to derive patterns of interannual variability associated with meteorological phenomena that vary significantly within a season, such as atmospheric blocking, or intraseasonal oscillations. Removing this intraseasonal component from the total interannual variance/covariance, one can define a slow component of interannual variability that is closely related to very slowly varying (interannual/supra-annual) external forcings and internal dynamics. Together these patterns may help in our understanding of the source of climate predictive skill, and also the influence of intraseasonal variability on interannual variability. The method is then applied to study the causes of the predictability of New Zealand seasonal mean rainfalls. In terms of predictability, the Southern Oscillation is identified as the most important cause of variability for both the winter and summer New Zealand rainfall, especially for the North Island. Indian Ocean sea surface temperature variability and the Southern Annular Mode are the second most important cause of variability for winter and summer rainfalls, respectively. Based on this study, a statistical prediction scheme has been developed. The achieved predictive skill, in term of percentage of explained variance, for the verification period (1993-2000) is more than 20%, which is significantly higher than that achieved previously.

In two 1000-yr CO2 sensitivity experiments, the amplitude of model ENSO decreases slightly and the period of oscillation increases relative to the control run in response to either doubling or quadrupling of CO2. This decreases variability is due in part to CO2-induced change in the model’s time-mean basic state, including a reduced zonal SST gradient and increased depth of thermocline. In contrast to the weaker overall amplitude, the multidecadal amplitude modulations become more pronounced with increased CO2. Since the multidecadal fluctuations in the amplitude of the model ENSO’s amplitude are comparable in magnitude to the reduction in variability due to a quadrupling of CO2, the result suggest that the impact of increased CO2 on ENSO is unlikely to be clearly distinguishable from the climate system noise in near future.

The "hockey stick" was elevated to an icon-status by the IPCC. While in the technical part of the TAR, the reconstruction of the last millennium's temperature was presented with the proper caveats and uncertainties, in the publicly more visible parts of the TAR these caveats were less and less emphasized. The result is that in many quarters the hockey stick is considered to be an unquestionable indication of the detection and attribution of anthropogenic climate change.The problem was, and is, that the methodology behind the hockey stick has not been adequately tested. The methodology was not properly explained in the original "Nature" publication. Scientists still have difficulties what exactly is "in" the method. We have tested the method in the artificial laboratory of the output of a global climate model, and found it to significantly underestimate both low-frequency variability and associated uncertainties.Our work focuses on multi-century simulations with two global climate models to generate a realistic mix of natural and externally (greenhouse gases, solar output, volcanic load) forced climate variations. Such simulations are then used to examine the performance of empirically based methods to reconstruct historical climate. This is done by deriving "pseudo proxies" from the model output, which provide incomplete and spatially limited evidence about the global distribution of a variable.These pseudo proxies serve as input in reconstruction methods - the result of which is then compared with the true state simulated by the model. Obviously, this is a valid test of the reconstruction method, independently of the ability of the model to capture accurately the historical temperature record.Our simulation study was published in "Science" after proper review. The response was surprising - almost no open response, a bit in the media, and many colleagues who indicated privately that such a publication would damage the good case of a climate protection policy. It would play into the hands of the "sceptics".It seems that exaggerating claims pass the internal quality checks of science relatively easily, whereas more reasoned and scientifically accurate claims find an unwelcome audience among scientists. The practice of scientists exaggerating threatening perspectives of anthropogenic climate change and its implications serves not only the purpose of supporting a policy perceived as "good" but also personal agendas of career and public visibility. The problem is, however, that the desired public attention can only be achieved if these perspectives are continuously topped by even more threatening perspectives. Thus, the credibility of climate science is endangered, and its important role of advising policy (in the naive sense of "knowledge speaks to power") becomes an unsustainable practice. We have a situation similar to the case of "tragedy of the commons".In this talk I first present the methodical critique of the hockey stick methodology then engage in a rather personal discussion about the problem of post-normal climate science operating in a highly politicized environment.

Ensembles of simulations for the 20th century
have recently been conducted at GFDL as part of the 2007 IPCC
process. The simulations were conducted with two new climate
models recently developed at GFDL. The new models (CM2.0 and CM2.1)
consist of recently developed atmospheric, oceanic, sea ice, and
land component models, and do not use flux adjustments. The
models simulate current climate in a realistic manner, including
a substantially improved simulation of ENSO relative to previous
models. Much of the output from these simulations is
freely available on the web.

In this presentation we examine several aspects of 20th
century climate change simulated n these models. We first assess
to what degree simulated trends in atmospheric and oceanic
temperature are consistent with observations, and to what extent
they are attributable to both natural and anthropogenic forcings.

We next examine the nature of simulated changes in the
Atlantic thermohaline circulation (THC). Previous work has suggested
that the THC will decrease in response to increasing
greenhouse gases. Our results suggest that increasing anthropogenic
aerosols in the 20th century may play an important role in delaying
any THC weakening.

Finally, we examine the simulation of the Sahelian drought
in the latter half of the 20th century. The Sahelian
drought emerges as a response to anthropogenic forcing in
these coupled model simulations, and is inconsistent with internal
variability as estimated from the coupled model. Diagnostics
relevant to the simulated Sahelian drought are presented, including
the relationship between the drought and global SST patterns.