Metagenomic samples from oceans around the globe were used to examine the biogeography of the dominant marine heterotrophic bacterial clade, SAR11. Analysis uncovers evidence of adaptive radiation in response to environmental parameters, particularly temperature.

Even in the absence of external forcing, climate models often exhibit long-term trends that cannot 2 be attributed to natural variability. This so called "climate drift" arises for various reasons including: 3 perturbations to the climate system on coupling component models together and deficiencies in 4 model physics and numerics. When examining trends in historical or future climate simulations, it is 5 important to know the error introduced by drift so that action can be taken where necessary. This 6 study assesses the importance of drift for a number of climate properties at global and local scales. 7To illustrate this we have focussed on simulated trends over the second half of the 20 th century. 8While drift in globally-averaged surface properties is generally considerably smaller than observed 9 and simulated 20th century trends, it can still introduce non-trivial errors in some models. 10 Furthermore, errors become increasingly important at smaller scales. The direction of drift is not 11 systematic across different models or variables; as such drift is considerably reduced in the multi-12 model mean. Despite drift being primarily associated with ocean adjustment, it is also apparent in 13 atmospheric variables. For example, most models have local drift magnitudes that are typically 14 between 15 and 35% of the 20 th century simulation trend magnitudes for 1950-2000. Below depths 15 of 1000 to 2000m, drift dominates over any forced trend in most regions. As such steric sea-level is 16 strongly affected and for some models and regions the sea-level trend direction is reversed. Thus

While the practice of reporting multi-model ensemble climate projections is well established, there is much debate regarding the most appropriate methods of evaluating model performance, for the purpose of eliminating and/or weighting models based on skill. The CMIP3 model evaluation undertaken by the Pacific Climate Change Science Program (PCCSP) is presented here. This includes a quantitative assessment of the ability of the models to simulate 3 climate variables: (1) surface air temperature, (2) precipitation and (3) surface wind); 3 climate features: (4) the South Pacific Convergence Zone, (5) the Intertropical Convergence Zone and (6) the West Pacific Monsoon; as well as (7) the El Niño Southern Oscillation, (8) spurious model drift and (9) the long term warming signal. For each of 1 to 9, it is difficult to identify a clearly superior subset of models, but it is generally possible to isolate particularly poor performing models. Based on this analysis, we recommend that the following models be eliminated from the multi-model ensemble, for the purposes of calculating PCCSP climate projections: INM-CM3.0, PCM and GISS-EH (consistently poor performance on 1 to 9); INGV-SXG (strong model drift); GISS-AOM and GISS-ER (poor ENSO simulation, which was considered a critical aspect of the tropical Pacific climate). Since there are relatively few studies in the peer reviewed literature that have attempted to combine metrics of model performance pertaining to such a wide variety of climate processes and phenomena, we propose that the approach of the PCCSP could be adapted to any region and set of climate model simulations. KEY WORDS: Climate model evaluation · Regional climate projections · CMIP3 · PacificResale or republication not permitted without written consent of the publisher

[1] Climate models participating in the third Coupled Model Inter Comparison Project (CMIP3) suggest a significant increase in the transport of the New Guinea Coastal Undercurrent (NGCU) and the Equatorial Undercurrent (EUC, in the central and western Pacific) and a decrease in the Mindanao current and the Indonesian Throughflow. Most models also project a reduction in the strength of the equatorial Trade winds. Typically, on ENSO time scales, a weakening of the equatorial easterlies would lead to a reduction in EUC strength in the central Pacific. The strengthening of the EUC projected for longer timescales, can be explained by a robust projected intensification of the south-easterly trade winds and an associated off-equatorial wind-stress curl change in the Southern Hemisphere. This drives the intensification of the NGCU and greater water input to the EUC in the west. A 1½-layer shallow water model, driven by projected wind stress trends from the CMIP3 models demonstrates that the projected circulation changes are consistent with a purely wind driven response. While the equatorial winds weaken for both El Niño events and in the projections, the ocean response and the mechanisms driving the projected wind changes are distinct from those operating on interannual timescales. Citation:

Regional climate projections in the Pacific region are potentially sensitive to a range of existing model biases. This study examines the implications of coupled model biases on regional climate projections in the tropical western Pacific. Model biases appear in the simulation of the El Niño Southern Oscillation, the location and movement of the South Pacific Convergence Zone, rainfall patterns, and the mean state of the ocean-atmosphere system including the cold tongue bias and erroneous location of the edge of the Western Pacific warm pool. These biases are examined in the CMIP3 20th century climate models and used to provide some context to the uncertainty in interpretations of regional-scale climate projections for the 21st century. To demonstrate, we provide examples for two island nations that are located in different climate zones and so are affected by different biases: Nauru and Palau. We discuss some of the common approaches to analyze climate projections and whether they are effective in reducing the effect of model biases. These approaches include model selection, calculating multi model means, downscaling and bias correcting.