All global circulation models (GCMs) suffer from some form of bias, which when used as boundary conditions for regional climate models may impact the simulations, perhaps severely. Here we present a bias correction method that corrects the mean error in the GCM, but retains the sixhourly weather, longer-period climate-variability and climate change from the GCM. We utilize six different bias correction experiments; each correcting different bias components. The impact of the full bias correction and the individual components are examined in relation to tropical cyclones, precipitation and temperature. We show that correcting of all boundary data provides the greatest improvement.

An Anthropogenic Climate Change Index (ACCI) is developed and used to investigate the potential global warming contribution to current tropical cyclone activity. The ACCI is defined as the difference between the means of ensembles of climate simulations with and without anthropogenic gases and aerosols. This index indicates that the bulk of the current anthropogenic warming has occurred in the past four decades, which enables improved confidence in assessing hurricane changes as it removes many of the data issues from previous eras. We find no anthropogenic signal in annual global tropical cyclone or hurricane frequencies. But a strong signal is found in proportions of both weaker and stronger hurricanes: the proportion of Category 4 and 5 hurricanes has increased at a rate of *25-30 % per°C of global warming after accounting for analysis and observing system changes. This has been balanced by a similar decrease in Category 1 and 2 hurricane proportions, leading to development of a distinctly bimodal intensity distribution, with the secondary maximum at Category 4 hurricanes. This global signal is reproduced in all ocean basins. The observed increase in Category 4-5 hurricanes may not continue at the same rate with future global warming. The analysis suggests that following an initial climate increase in intense hurricane proportions a saturation level will be reached beyond which any further global warming will have little effect.

Tropical cyclones have enormous costs to society through both loss of life and damage to infrastructure. There is good reason to believe that such storms will change in the future as a result of changes in the global climate system and that such changes may have important socioeconomic implications. Here a high-resolution regional climate modeling experiment is presented using the Weather Research and Forecasting (WRF) Model to investigate possible changes in tropical cyclones. These simulations were performed for the period 2001–13 using the ERA-Interim product for the boundary conditions, thus enabling a direct comparison between modeled and observed cyclone characteristics. The WRF simulation reproduced 30 of the 32 named storms that entered the model domain during this period. The model simulates the tropical cyclone tracks, storm radii, and translation speeds well, but the maximum wind speeds simulated were less than observed and the minimum central pressures were too large. This experiment is then repeated after imposing a future climate signal by adding changes in temperature, humidity, pressure, and wind speeds derived from phase 5 of the Coupled Model Intercomparison Project (CMIP5). In the current climate, 22 tracks were well simulated with little changes in future track locations. These simulations produced tropical cyclones with faster maximum winds, slower storm translation speeds, lower central pressures, and higher precipitation rates. Importantly, while these signals were statistically significant averaged across all 22 storms studied, changes varied substantially between individual storms. This illustrates the importance of using a large ensemble of storms to understand mean changes.

Although the societal impact of a weather event increases with the rarity of the event, our current ability to assess extreme events and their impacts is limited by not only rarity but also by current model fidelity and a lack of understanding and capacity to model the underlying physical processes. This challenge is driving fresh approaches to assess highimpact weather and climate. Recent lessons learned in modeling high-impact weather and climate are presented using the case of tropical cyclones as an illustrative example. Through examples using the Nested Regional Climate Model to dynamically downscale large-scale climate data the need to treat bias in the driving data is illustrated. Domain size, location, and resolution are also shown to be critical and should be adequate to: include relevant regional climate physical processes; resolve key impact parameters; and accurately simulate the response to changes in external forcing. The notion of sufficient model resolution is introduced together with the added value in combining dynamical and statistical assessments to fill out the parent distribution of high-impact parameters.

Large-scale environmental variables known to be linked to the formation of tropical cyclones have previously been used to develop empirical indices as proxies for assessing cyclone frequency from large-scale analyses or model simulations. Here the authors examine the ability of two recent indices, the genesis potential (GP) and the genesis potential index, to reproduce observed North Atlantic cyclone annual frequency variations and trends. These skillfully estimate the mean seasonal variation of observed cyclones, but they struggle with reproducing interannual frequency variability and change. Examination of the independent contributions by the four terms that make up the indices finds that potential intensity and shear have significant skill, while moisture and vorticity either do not contribute to or degrade the indices’ capacity to reproduce observed interannual variability. It is also found that for assessing basinwide cyclone frequency, averaging indices over the whole basin is less skillful than its application to the general area off the coast of Africa broadly covering the main development region (MDR). These results point to a revised index, the cyclone genesis index (CGI), which comprises only potential intensity and vertical shear. Application of the CGI averaged over the MDR demonstrates high and significant skill at reproducing interannual variations and trends in all-basin cyclones across both reanalyses. The CGI also provides a more accurate reproduction of seasonal variations than the original GP. Future work applying the CGI to other tropical cyclone basins and to the downscaling of relatively course climate simulations is briefly addressed.

We use a regional coupled chemistry-transport model to assess changes in surface ozone over the summertime U.S. between present and a 2050 future time period at high spatial resolution under the A2 climate and Representative Concentration Pathway (RCP) 8.5 anthropogenic precursor emission scenarios. Predicted changes in regional climate and globally enhanced ozone are estimated to increase surface ozone over most of the U.S.; the 95th percentile for daily 8 h maximum surface ozone increases from 79 ppb to 87 ppb. The analysis suggests that changes in meteorological drivers likely will add to increasing ozone, but the simulations do not allow separating meteorological feedbacks from that due to enhanced global ozone. Stringent emission controls can counteract these feedbacks; if implemented as in RCP8.5, the 95th percentile for surface ozone is reduced to 55 ppb. A comparison of regional to global model projections shows that the global model is biased high in surface ozone compared to the regional model and compared to observations. On average, both the global and the regional model predict similar future changes but reveal pronounced differences in urban and rural regimes that cannot be resolved at the coarse resolution of the considered global model. This study confirms the key role of emission control strategies in future air quality projections and demonstrates the need for considering degradation of air quality with future climate change in policy making. It also illustrates the need for high-resolution modeling when the objective is to address regional and local air quality or establish links to human health and society.

According to three recent assessments, global warming will likely cause increased hurricane activity1 in the future. If true, this raises the possibility that new coastal and offshore facilities are being under-designed, and that older facilities may need hardening in order to maintain presently accepted risk levels. As these three assessments readily admit, many uncertainties remain concerning the accuracy of their forecast. The study summarized in this paper has sought to narrow the uncertainties by using several methods. A set of relatively high resolution regional climate simulations are being made with the NCAR Nested Regional Climate Model (NRCM) embedded in the global Community Climate System Model (CCSM). These are being combined with statistical and statistical-dynamical downscaling techniques to provide an assessment of changes in North Atlantic hurricane activity out to 2050. Comparisons with the historical record show that the model can reasonably duplicate both the observed frequency and severity of hurricanes in the North Atlantic as well as in the Gulf of Mexico. This initial analysis suggests that under the business as usual IPCC A2 scenario North Atlantic tropical cyclones will experience an accelerated increase in numbers from 3.4% per decade near the present to 10% per decade leading up to 2050; the region of maximum storm frequency and formation will move equatorward over the same time period; and there will be a modest increase of mean intensity of ~2 ms-1, but a more marked increase in the frequency and intensity (~3.5 ms-1) of the most intense hurricanes that can be resolved by the model (Cat 3). All of these changes are statistically significant at the 95% level or greater. For the Gulf of Mexico, the results are more ambiguous in part because of the limited number of storms in each decadal time slice which is exacerbated by a strong multi-decadal natural climate variability. These are preliminary results from a more comprehensive prediction and analysis program that is in progress. We invite community involvement in helping to analyze the several hundred terabytes of model output from existing and in-process model simulations that are being archived. Introduction Recent synthesis reports (IPCC 2007, CCSP 2008) concluded that global warming will likely result in increased hurricane activity1 in the North Atlantic. Their conclusion is based onModeling and observational evidence that shows near-surface ocean temperatures have increased due to global warming, and are very likely to increase in the future (Meehl et al. 2007, Gillett et al. 2008). It is also well established from theoretical and observational considerations that hurricane activity tends to increase with warming ocean temperatures (Henderson-Sellers et al.. 1998, Emanuel 2007, Elsner et al. 2008);An increase in the observed hurricane power associated with the near-surface sea temperature in the hurricane generation region of the North Atlantic (Emanuel 2005);Numerical model results which have almost universally found an increase in intensity and rainfall, but there are substantial differences on whether the numbers of storms will increase or decrease (Knutson and Tuleya 2004, Knutson et al. 2007, Bengtsson et al. 2007).

Easterly waves (EWs) are important moisture carriers and their variability can impact the total May-November rainfall, defined as seasonal precipitation, over the Tropical Americas. The contribution of EWs to the seasonal precipitation is explored over the tropical Americas using rain gauge stations, reanalysis data and a regional model ensemble during the 1980-2013 period. In the present study, EWs are found to produce up to 50% of seasonal rainfall mainly over the north of South America and contribute substantially to interannual regional rainfall variability. An observational analysis shows that the El Niño Southern Oscillation (ENSO) affects EW frequency and therefore, their contribution to seasonal rainfall. In recent years, tropical cyclone (TC) activity over the Main Development Region (MDR) of the tropical North Atlantic has a negative impact on regional seasonal precipitation over northern South America. High TC activity over MDR corresponds to below-normal precipitation because it reduces the EW activity reaching northern South America through the recurving of TC tracks. Recurving TC tracks redirect moisture away from the tropical belt and into the mid-latitudes. However, this relationship only holds under neutral ENSO conditions and the positive phase of the Atlantic Multidecadal Oscillation. A 10-member regional model multi-physics ensemble simulation for the period 1990-2000 was analyzed to show the relationships are robust to different representations of physical processes. This new understanding of seasonal rainfall over the tropical Americas may support improved regional seasonal and climate outlooks.