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Axel Lauer, Chunxi Zhang, Oliver Elison-Timm, Yuqing Wang, and Kevin Hamilton


The Weather Research and Forecasting (WRF) model has been configured as a regional climate model for the Hawaii region (HRCM) to assess the uncertainties associated with the pseudo–global warming (PGW) downscaling method using different warming increments from phase 5 of the Coupled Model Intercomparison Project (CMIP5) model experiments. Results from 15-km downscaling experiments using warming increments from 10 individual CMIP5 models for the two warming scenarios representative concentration pathway 4.5 (RCP4.5) and 8.5 (RCP8.5) are compared with experiments using multimodel mean warming increments. The results show that changes in 2-m temperatures, 10-m wind speed, rainfall, water vapor path, and trade wind inversion vary significantly among the individual model experiments. This translates into large uncertainties when picking one particular CMIP5 model to provide the warming increments for dynamical downscaling in the Hawaii region. The simulations also show that, despite the large interexperiment spread, a single downscaling experiment using multimodel mean warming increments gives very similar results to the ensemble mean of downscaling experiments using warming increments obtained from 10 individual CMIP5 models. Robust changes of the projected climate by the end of the twenty-first century in the Hawaii region shown by most downscaling experiments include increasing 2-m temperatures with stronger warming at higher elevations, a large increase in precipitable water, and an increase in the number of days with a trade wind inversion (TWI). Furthermore, most experiments agree on a reduction in TWI height and an increase in the TWI strength. Uncertainties in the projected changes in rainfall and 10-m wind speed are large and there is little consensus among the individual downscaling experiments.

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Axel Lauer, Kevin Hamilton, Yuqing Wang, Vaughan T. J. Phillips, and Ralf Bennartz


Cloud simulations and cloud–climate feedbacks in the tropical and subtropical eastern Pacific region in 16 state-of-the-art coupled global climate models (GCMs) and in the International Pacific Research Center (IPRC) Regional Atmospheric Model (iRAM) are examined. The authors find that the simulation of the present-day mean cloud climatology for this region in the GCMs is very poor and that the cloud–climate feedbacks vary widely among the GCMs. By contrast, iRAM simulates mean clouds and interannual cloud variations that are quite similar to those observed in this region. The model also simulates well the observed relationship between lower-tropospheric stability (LTS) and low-level cloud amount.

To investigate cloud–climate feedbacks in iRAM, several global warming scenarios were run with boundary conditions appropriate for late twenty-first-century conditions. All the global warming cases simulated with iRAM show a distinct reduction in low-level cloud amount, particularly in the stratocumulus regime, resulting in positive local feedback parameters in these regions in the range of 4–7 W m−2 K−1. Domain-averaged (30°S–30°N, 150°–60°W) feedback parameters from iRAM range between +1.8 and +1.9 W m−2 K−1. At most locations both the LTS and cloud amount are altered in the global warming cases, but the changes in these variables do not follow the empirical relationship found in the present-day experiments.

The cloud–climate feedback averaged over the same east Pacific region was also calculated from the Special Report on Emissions Scenarios (SRES) A1B simulations for each of the 16 GCMs with results that varied from −1.0 to +1.3 W m−2 K−1, all less than the values obtained in the comparable iRAM simulations. The iRAM results by themselves cannot be connected definitively to global climate feedbacks; however, among the global GCMs the cloud feedback in the full tropical–subtropical zone is correlated strongly with the east Pacific cloud feedback, and the cloud feedback largely determines the global climate sensitivity. The present iRAM results for cloud feedbacks in the east Pacific provide some support for the high end of current estimates of global climate sensitivity.

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William Randel, Petra Udelhofen, Eric Fleming, Marvin Geller, Mel Gelman, Kevin Hamilton, David Karoly, Dave Ortland, Steve Pawson, Richard Swinbank, Fei Wu, Mark Baldwin, Marie-Lise Chanin, Philippe Keckhut, Karin Labitzke, Ellis Remsberg, Adrian Simmons, and Dong Wu


An updated assessment of uncertainties in “observed” climatological winds and temperatures in the middle atmosphere (over altitudes ∼10–80 km) is provided by detailed intercomparisons of contemporary and historic datasets. These datasets include global meteorological analyses and assimilations, climatologies derived from research satellite measurements, historical reference atmosphere circulation statistics, rocketsonde wind and temperature data, and lidar temperature measurements. The comparisons focus on a few basic circulation statistics (temperatures and zonal winds), with special attention given to tropical variability. Notable differences are found between analyses for temperatures near the tropical tropopause and polar lower stratosphere, temperatures near the global stratopause, and zonal winds throughout the Tropics. Comparisons of historical reference atmosphere and rocketsonde temperatures with more recent global analyses show the influence of decadal-scale cooling of the stratosphere and mesosphere. Detailed comparisons of the tropical semiannual oscillation (SAO) and quasi- biennial oscillation (QBO) show large differences in amplitude between analyses; recent data assimilation schemes show the best agreement with equatorial radiosonde, rocket, and satellite data.

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