6 *email: cmpatricola@lbl.gov 7 8There is no consensus on whether climate change has yet impacted tropical cyclone (TC) 9 statistics, owing to large natural variability and a limited period of consistent observations. 10In addition, projections of future TC activity are uncertain, as they often rely on coarse-11 resolution climate models that parameterize convection and have difficulty directly 12representing TCs. Here we investigated how historically destructive TCs could change if 13 similar events occurred in pre-industrial and future climates, using convection-permitting 14 regional climate model simulations. We found that climate change to date enhanced 15 average and extreme rainfall of Hurricanes Katrina, Irma, and Maria, but did not change 16 TC intensity. In addition, future anthropogenic warming robustly increases wind speed 17 and rainfall of intense TCs among 15 events sampled globally. Additional simulations 18 suggest convective parameterization introduces minimal uncertainty into the sign of 19 projected TC intensity and rainfall changes, supporting confidence in projections from 20 models with parameterized convection and TC-permitting resolution. 21 22 Tropical cyclones (TCs) are among the deadliest and most destructive natural disasters. 23 Hurricane Katrina holds the record for costliest U.S. natural disaster and caused at least 1,833 24 disentangling the influences of climate variability and change on trends in TC activity all the 47 more challenging. 48Looking into the future, there is no consensus regarding how anthropogenic emissions are 49 expected to change global TC frequency, with the majority of climate models projecting fewer 50 TCs 18-22 but others more TCs 23 (see also references within 2-4 ). However, maximum potential 51 intensity (MPI) theory and recent climate modeling studies suggest increases in the future 52 number of intense TCs [24][25][26][27][28][29][21][22] . In addition, climate model simulations suggest rainfall 53 associated with TCs will increase in future warmer climates, but with large uncertainty in 54 magnitude 18,20,28,[30][31][32][33] . The Clausius-Clapeyron (C-C) relation dictates that the saturation specific 55 humidity of the atmosphere increases by 7% per 1°C of warming, providing a constraint on 56 changes in moisture available for precipitation. If TC precipitation efficiency does not change, 57 then changes in precipitation follow C-C scaling as the oceans warm 34 . However, recent studies 58 of Hurricane Harvey found 15-38% increases in storm total precipitation attributable to global 59 warming, well above the C-C limit of 7% given anthropogenic warming of 1°C in the Gulf of 60Mexico [35][36][37] . Such rainfall over Houston -a 2,000-year event in the late 20 th century -is 61 expected to become a more common 100-year event by the end of the 21 st century 38 . 62There is no theory of TC formation to predict how TCs are expected to change in the 63 future, and the problem is complicated by potentially compensating influences of greenhouse 64 gases. Alt...

Although a theory of the climatology of tropical cyclone formation remains elusive, high-resolution climate models can now simulate many aspects of tropical cyclone climate. T he effect of climate change on tropical cyclones has been a controversial scientific issue for a number of years. Advances in our theoretical understanding of the relationship between climate and tropical cyclones have been made, enabling us to understand better the links between the mean climate and the potential intensity (PI; the theoretical maximum intensity of a tropical cyclone for a given climate condition) of tropical cyclones. Improvements in the capabilities of climate models, the main tool used to predict future climate, have enabled them to achieve a considerably improved and more credible simulation of the present-day climatology of tropical cyclones. Finally, the increasing ability of such models to predict the interannual variability of tropical cyclone formation in various regions of the globe indicates that they are capturing some of the essential physical relationships governing the links between climate and tropical cyclones. HURRICANES AND CLIMATEPrevious climate model simulations, however, have suggested some ambiguity in projections of future numbers of tropical cyclones in a warmer world. While many models have projected fewer tropical cyclones globally (Sugi et al. 2002;Bengtsson et al. 2007b; Gualdi et al. 2008; Knutson et al. 2010), other climate models and related downscaling methods have suggested some increase in future numbers (e.g., Broccoli and Manabe 1990;Haarsma et al. 1993; Emanuel 2013a). When future projections for individual basins are made, the issue becomes more serious: for example, for the Atlantic basin there appears to be little consensus on the future number of tropical cyclones or on the relative importance of forcing factors such as aerosols or increases in carbon dioxide (CO 2 ) concentration. One reason could be statistical: annual numbers of tropical cyclones in the Atlantic are relatively small, making the identification of such storms sensitive to the detection method used.Further, there is substantial spread in projected responses of regional tropical cyclone (TC) frequency and intensity over the twenty-first century from downscaling studies (Knutson et al. 2007; Emanuel 2013a). Interpreting the sources of those differences is complicated by different projections of large-scale climate and by differences in the present-day reference period and sea surface temperature (SST) datasets used. A natural question is whether the diversity in responses to projected twenty-firstcentury climate of each of the studies is primarily | a reflection of uncertainty arising from different large-scale forcing (as has been suggested by, e.g., Villarini et al. 2011;Villarini and Vecchi 2012;Knutson et al. 2013) or whether this spread reflects principally different inherent sensitivities across the various downscaling techniques, even including different sensitivity of responses within the same model due to...

Simulations from 18 coupled atmosphere–ocean GCMs are analyzed to predict changes in the climatological Great Plains low-level jet (GPLLJ) and Midwest U.S. hydrology resulting from greenhouse gas increases during the twenty-first century. To build confidence in the prediction, models are selected for analysis based on their twentieth-century simulations, and their simulations of the future are diagnosed to ensure that the response is reasonable. Confidence in the model projections is also bolstered by agreement among models, in a so-called multimodel ensemble, and by analogy with present-day interannual variability. The GCMs agree that the GPLLJ will be more intense in April, May, and June in the future. The selected models even agree on the reason for this intensification, namely, a westward extension and strengthening of the North Atlantic subtropical high (the Bermuda high) that occurs when greenhouse gas–induced warming over the continental United States exceeds that of the subtropical Atlantic in the spring. Accompanying the changes in the GPLLJ are springtime precipitation increases of 20%–40% in the upper Mississippi Valley, which are closely associated with intensified meridional moisture convergence by the jet, with decreases to the south, which results in reduced moist static stability in the region. The simulated differences in the Midwest circulation and hydrology in the spring for the twenty-first century are similar to the observed moisture balance and circulation anomalies for May and, especially, June of 1993, a year of devastating floods throughout the Mississippi Valley.

Well-known problems trouble coupled general circulation models of the eastern Atlantic and Pacific Ocean basins. Model climates are significantly more symmetric about the equator than is observed. Model sea surface temperatures are biased warm south and southeast of the equator, and the atmosphere is too rainy within a band south of the equator. Near-coastal eastern equatorial SSTs are too warm, producing a zonal SST gradient in the Atlantic opposite in sign to that observed. The U.S. Climate Variability and Predictability Program (CLIVAR) Eastern Tropical Ocean Synthesis Working Group (WG) has pursued an updated assessment of coupled model SST biases, focusing on the surface energy balance components, on regional error sources from clouds, deep convection, winds, and ocean eddies; on the sensitivity to model resolution; and on remote impacts. Motivated by the assessment, the WG makes the following recommendations: 1) encourage identification of the specific parameterizations contributing to the biases in individual models, as these can be model dependent; 2) restrict multimodel intercomparisons to specific processes; 3) encourage development of high-resolution coupled models with a concurrent emphasis on parameterization development of finer-scale ocean and atmosphere features, including low clouds; 4) encourage further availability of all surface flux components from buoys, for longer continuous time periods, in persistently cloudy regions; and 5) focus on the eastern basin coastal oceanic upwelling regions, where further opportunities for observational–modeling synergism exist.

A method for simulating future climate on regional space scales is developed and applied to northern Africa. Simulation with a regional model allows for the horizontal resolution needed to resolve the region's strong meridional gradients and the optimization of parameterizations and land-surface model. The control simulation is constrained by reanalysis data, and realistically represents the present day climate. Atmosphere-ocean general circulation model (AOGCM) output provides SST and lateral boundary condition anomalies for 2081-2100 under a business-as-usual emissions scenario, and the atmospheric CO 2 concentration is increased to 757 ppmv. A ninemember ensemble of future climate projections is generated by using output from nine AOGCMs. The consistency of precipitation projections for the end of the twenty-first century is much greater for the regional model ensemble than among the AOGCMs. More than 77% of ensemble members produce the same sign rainfall anomaly over much of northern Africa. For West Africa, the regional model projects wetter conditions in spring, but a midsummer drought develops during June and July, and the heat stoke risk increases across the Sahel. Wetter conditions resume in late summer, and the likelihood of flooding increases. The regional model generally projects wetter conditions over eastern Central Africa in June and drying during August through September. Severe drought impacts parts of East Africa in late summer. Conditions become wetter in October, but the enhanced rainfall does not compensate for the summertime deficit. The risk of heat stroke increases over this region, although the threat is not projected to be as great as in the Sahel.

Until recently, the El Niño-Southern Oscillation (ENSO) was considered a reliable source of winter precipitation predictability in the western US, with a historically strong link between extreme El Niño events and extremely wet seasons. However, the 2015-2016 El Niño challenged our understanding of the ENSO-precipitation relationship. California precipitation was near-average during the 2015-2016 El Niño, which was characterized by warm sea surface temperature (SST) anomalies of similar magnitude compared to the extreme 1997-1998 and 1982-1983 El Niño events. We demonstrate that this precipitation response can be explained by El Niño's spatial pattern, rather than internal atmospheric variability. In addition, observations and large-ensembles of regional and global climate model simulations indicate that extremes in seasonal and daily precipitation during strong El Niño events are better explained using the ENSO Longitude Index (ELI), which captures the diversity of ENSO's spatial patterns in a single metric, compared to the traditional Niño3.4 index, which measures SST anomalies in a fixed region and therefore fails to capture ENSO diversity. The physically-based ELI better explains western US precipitation variability because it tracks the zonal shifts in tropical Pacific deep convection that drive teleconnections through the response in the extratropical wave-train, integrated vapor transport, and atmospheric rivers. This research provides evidence that ELI improves the value of ENSO as a predictor of California's seasonal hydroclimate extremes compared to traditional ENSO indices, especially during strong El Niño events.

The tropical Atlantic is home to multiple coupled climate variations covering a wide range of timescales and impacting societally relevant phenomena such as continental rainfall, Atlantic hurricane activity, oceanic biological productivity, and atmospheric circulation in the equatorial Pacific. The tropical Atlantic also connects the southern

We show that the well‐known failure of any single index to capture the diversity and extremes of El Niño‐Southern Oscillation (ENSO) results from the inability of existing indices to uniquely characterize the average longitude of deep convection in the Walker Circulation. We present a simple sea surface temperature (SST)‐based index of this longitude that compactly characterizes the different spatial patterns, or flavors of observed and projected ENSO events. It recovers the familiar global responses of temperature, precipitation, and tropical cyclones to ENSO and identifies historical extreme El Niño events. Despite its simplicity, the new longitude index describes the nonlinear relationship between the first two principal components of SST, and unlike previous indices, accounts for background SST changes associated with the seasonal cycle and climate change. The index reveals that extreme El Niño, El Niño Modoki, and La Niña events are projected to become more frequent in the future at the expense of neutral ENSO conditions.