Tropical cyclones (TCs) are a hazard to life and property and a prominent element of the global climate system; therefore, understanding and predicting TC location, intensity, and frequency is of both societal and scientific significance. Methodologies exist to predict basinwide, seasonally aggregated TC activity months, seasons, and even years in advance. It is shown that a newly developed high-resolution global climate model can produce skillful forecasts of seasonal TC activity on spatial scales finer than basinwide, from months and seasons in advance of the TC season. The climate model used here is targeted at predicting regional climate and the statistics of weather extremes on seasonal to decadal time scales, and comprises high-resolution (50 km × 50 km) atmosphere and land components as well as more moderate-resolution (~100 km) sea ice and ocean components. The simulation of TC climatology and interannual variations in this climate model is substantially improved by correcting systematic ocean biases through “flux adjustment.” A suite of 12-month duration retrospective forecasts is performed over the 1981–2012 period, after initializing the climate model to observationally constrained conditions at the start of each forecast period, using both the standard and flux-adjusted versions of the model. The standard and flux-adjusted forecasts exhibit equivalent skill at predicting Northern Hemisphere TC season sea surface temperature, but the flux-adjusted model exhibits substantially improved basinwide and regional TC activity forecasts, highlighting the role of systematic biases in limiting the quality of TC forecasts. These results suggest that dynamical forecasts of seasonally aggregated regional TC activity months in advance are feasible.

There is a growing need for skilful predictions of climate up to a decade ahead. Decadal climate predictions show high skill for surface temperature, but confidence in forecasts of precipitation and atmospheric circulation is much lower. Recent advances in seasonal and annual prediction show that the signal-to-noise ratio can be too small in climate models, requiring a very large ensemble to extract the predictable signal. Here, we reassess decadal prediction skill using a much larger ensemble than previously available, and reveal significant skill for precipitation over land and atmospheric circulation, in addition to surface temperature. We further propose a more powerful approach than used previously to evaluate the benefit of initialisation with observations, improving our understanding of the sources of skill. Our results show that decadal climate is more predictable than previously thought and will aid society to prepare for, and adapt to, ongoing climate variability and change.npj Climate and Atmospheric Science (2019)2:13 ; https://doi.

Responses of tropical cyclones (TCs) to CO 2 doubling are explored using coupled global climate models (GCMs) with increasingly refined atmospheric/land horizontal grids (~ 200 km, ~ 50 km and ~ 25 km). The three models exhibit similar changes in background climate fields thought to regulate TC activity, such as relative sea surface temperature (SST), potential intensity, and wind shear. However, global TC frequency decreases substantially in the 50 km model, while the 25 km model shows no significant change. The ~ 25 km model also has a substantial and spatially-ubiquitous increase of Category 3-4-5 hurricanes. Idealized perturbation experiments are performed to understand the TC response. Each model's transient fullycoupled 2 × CO 2 TC activity response is largely recovered by "time-slice" experiments using time-invariant SST perturbations added to each model's own SST climatology. The TC response to SST forcing depends on each model's background climatological SST biases: removing these biases leads to a global TC intensity increase in the ~ 50 km model, and a global TC frequency increase in the ~ 25 km model, in response to CO 2 -induced warming patterns and CO 2 doubling. Isolated CO 2 doubling leads to a significant TC frequency decrease, while isolated uniform SST warming leads to a significant global TC frequency increase; the ~ 25 km model has a greater tendency for frequency increase. Global TC frequency responds to both (1) changes in TC "seeds", which increase due to warming (more so in the ~ 25 km model) and decrease due to higher CO 2 concentrations, and (2) less efficient development of these"seeds" into TCs, largely due to the nonlinear relation between temperature and saturation specific humidity.

The relationship between the North Atlantic Oscillation (NAO) and Atlantic sea surface temperature (SST) variability is investigated using models and observations. Coupled climate models are used in which the ocean component is either a fully dynamic ocean or a slab ocean with no resolved ocean heat transport. On time scales less than 10 yr, NAO variations drive a tripole pattern of SST anomalies in both observations and models. This SST pattern is a direct response of the ocean mixed layer to turbulent surface heat flux anomalies associated with the NAO. On time scales longer than 10 yr, a similar relationship exists between the NAO and the tripole pattern of SST anomalies in models with a slab ocean. A different relationship exists both for the observations and for models with a dynamic ocean. In these models, a positive (negative) NAO anomaly leads, after a decadal-scale lag, to a monopole pattern of warming (cooling) that resembles the Atlantic multidecadal oscillation (AMO), although with smaller-than-observed amplitudes of tropical SST anomalies. Ocean dynamics are critical to this decadal-scale response in the models. The simulated Atlantic meridional overturning circulation (AMOC) strengthens (weakens) in response to a prolonged positive (negative) phase of the NAO, thereby enhancing (decreasing) poleward heat transport, leading to broad-scale warming (cooling). Additional simulations are used in which heat flux anomalies derived from observed NAO variations from 1901 to 2014 are applied to the ocean component of coupled models. It is shown that ocean dynamics allow models to reproduce important aspects of the observed AMO, mainly in the Subpolar Gyre.

Pronounced climate changes have occurred since the 1970s, including rapid loss of Arctic sea ice 1 , large-scale warming 2 and increased tropical storm activity 3 in the Atlantic. Anthropogenic radiative forcing is likely to have played a major role in these changes 4 , but the relative influence of anthropogenic forcing and natural variability is not well established. The above changes have also occurred during a period in which the North Atlantic Oscillation has shown marked multidecadal variations 5 . Here we investigate the role of the North Atlantic Oscillation in these rapid changes through its influence on the Atlantic meridional overturning circulation and ocean heat transport. We use climate models to show that observed multidecadal variations of the North Atlantic Oscillation can induce multidecadal variations in the Atlantic meridional overturning circulation and poleward ocean heat transport in the Atlantic, extending to the Arctic. Our results suggest that these variations have contributed to the rapid loss of Arctic sea ice, Northern Hemisphere warming, and changing Atlantic tropical storm activity, especially in the late 1990s and early 2000s. These multidecadal variations are superimposed on long-term anthropogenic forcing trends that are the dominant factor in long-term Arctic sea ice loss and hemispheric warming.There has been pronounced multidecadal variability of the North Atlantic Oscillation (NAO) over the past century 6 , with a negative phase of the NAO from the 1960s into the 1970s (Fig. 1a), associated with weakened westerly winds and cold ocean surface temperatures in the subpolar North Atlantic. This was followed by a rapid switch to a positive NAO phase from the 1980s into the early 2000s, along with strengthened westerly winds and rapid warming in the subpolar North Atlantic. These regional variations were coincident with long-term trends and multidecadal variability in Northern Hemisphere (NH) surface air temperature 2 and Arctic sea ice 1 . The relatively cool period of the 1970s was coincident with enhanced Arctic sea ice 7 , although observations before the satellite era are uncertain. This was followed by a rapid warming of the NH and reduction of Arctic sea ice from the late 1970s through the 2000s. There have been substantial multidecadal variations in Atlantic tropical storm activity 3 , with a relatively quiescent period from the late 1960s through the 1980s, followed by enhanced activity after the mid 1990s.Studies have suggested an important role for anthropogenic forcing in driving some of the above changes 4,8 , and yet the relative roles of natural variability and anthropogenic forcing are uncertain. In particular, the degree to which natural climate variability contributes to these past variations is a critical factor in our confidence in projections of future climate.We use simulations with three different climate models to explore the contribution of multidecadal variations of the NAO 9 to the above changes. The novel experimental design (see Methods) adds NAO-relate...

This study demonstrates skillful seasonal prediction of 2-m air temperature and precipitation over land in a new high-resolution climate model developed by the Geophysical Fluid Dynamics Laboratory and explores the possible sources of the skill. The authors employ a statistical optimization approach to identify the most predictable components of seasonal mean temperature and precipitation over land and demonstrate the predictive skill of these components. First, the improved skill of the high-resolution model over the previous lowerresolution model in seasonal prediction of the Niño-3.4 index and other aspects of interest is shown. Then, the skill of temperature and precipitation in the high-resolution model for boreal winter and summer is measured, and the sources of the skill are diagnosed. Last, predictions are reconstructed using a few of the most predictable components to yield more skillful predictions than the raw model predictions. Over three decades of hindcasts, the two most predictable components of temperature are characterized by a component that is likely due to changes in external radiative forcing in boreal winter and summer and an ENSO-related pattern in boreal winter. The most predictable components of precipitation in both seasons are very likely ENSO-related. These components of temperature and precipitation can be predicted with significant correlation skill at least 9 months in advance. The reconstructed predictions using only the first few predictable components from the model show considerably better skill relative to observations than raw model predictions. This study shows that the use of refined statistical analysis and a high-resolution dynamical model leads to significant skill in seasonal predictions of 2-m air temperature and precipitation over land.

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Decadal prediction experiments were conducted as part of phase 5 of the Coupled Model Intercomparison Project (CMIP5) using the GFDL Climate Model, version 2.1 (CM2.1) forecast system. The abrupt warming of the North Atlantic Subpolar Gyre (SPG) that was observed in the mid-1990s is considered as a case study to evaluate forecast capabilities and better understand the reasons for the observed changes. Initializing the CM2.1 coupled system produces high skill in retrospectively predicting the mid-1990s shift, which is not captured by the uninitialized forecasts. All the hindcasts initialized in the early 1990s show a warming of the SPG; however, only the ensemble-mean hindcasts initialized in 1995 and 1996 are able to reproduce the observed abrupt warming and the associated decrease and contraction of the SPG. Examination of the physical mechanisms responsible for the successful retrospective predictions indicates that initializing the ocean is key to predicting the mid-1990s warming. The successful initialized forecasts show an increased Atlantic meridional overturning circulation and North Atlantic Current transport, which drive an increased advection of warm saline subtropical waters northward, leading to a westward shift of the subpolar front and, subsequently, a warming and spindown of the SPG. Significant seasonal climate impacts are predicted as the SPG warms, including a reduced sea ice concentration over the Arctic, an enhanced warming over the central United States during summer and fall, and a northward shift of the mean ITCZ. These climate anomalies are similar to those observed during a warm phase of the Atlantic multidecadal oscillation, which is encouraging for future predictions of North Atlantic climate.