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Abstract In response to greenhouse gas forcing, most coupled global climate models project the tropical Pacific SST trend toward an “El Niño–like” state, with a reduced zonal SST gradient and a weakened Walker circulation. However, observations over the last five decades reveal a trend toward a more “La Niña–like” state with a strengthening zonal SST gradient. Recent research indicates that the identified trend differences are unlikely to be entirely due to internal variability and probably result, at least in part, from systematic model biases. In this study, Community Earth System Model, version 2 (CESM2), is used to explore how mean-state biases within the model may influence its forced response to radiative forcing in the tropical Pacific. The results show that using flux adjustment to reduce the mean-state bias in CESM2 over the tropical regions results in a more La Niña–like trend pattern in the tropical Pacific, with a strengthening of the tropical Pacific zonal SST gradient and a relatively enhanced Walker circulation, as hypothesized to occur if the ocean thermostat mechanism is stronger than the atmospheric mechanisms which by themselves would weaken the Walker circulation. We also find that the historical strengthening of the tropical Pacific zonal gradient is transient but persists into the near term in a high-emissions future warming scenario. These results suggest the potential of flux adjustment as a method for developing alternative projections that represent a wider range of possible future tropical Pacific warming scenarios, especially for a better understanding of regional patterns of climate risk in the near term. 

Abstract Studying convection, which is one of the least understood physical mechanisms in the tropical atmosphere, is very important for weather and climate predictions of extreme events such as storms, hurricanes, monsoons, floods and hail. Collecting more observations to do so is critical. It is also a challenge. The OTREC (Organization of Tropical East Pacific Convection) field project took place in the summer of 2019. More than thirty scientists and twenty students from the US, Costa Rica, Colombia, México and UK were involved in collecting observations over the ocean (East Pacific and Caribbean) and land (Costa Rica, Colombia). We used the NSF NCAR Gulfstream V airplane to fly at 13 kilometers altitude sampling the tropical atmosphere under diverse weather conditions. The plane was flown in a ‘lawnmower’ pattern and every 10 minutes deployed dropsondes that measured temperature, wind, humidity and pressure from flight level to the ocean. Similarly, over the land we launched radiosondes, leveraged existing radars and surface meteorological networks across the region, some with co-located Global Positioning System (GPS) receivers and rain sensors, and installed a new surface GPS meteorological network across Costa Rica, culminating in an impressive systematic data set that when assimilated into weather models immediately gave better forecasts. We are now closer than ever in understanding the environmental conditions necessary for convection as well as how convection influences extreme events. The OTREC data set continues to be studied by researchers all over the globe. This article aims to describe the lengthy process that precedes science breakthroughs. 

Most current climate models predict that the equatorial Pacific will evolve under greenhouse gas–induced warming to a more El Niño-like state over the next several decades, with a reduced zonal sea surface temperature gradient and weakened atmospheric Walker circulation. Yet, observations over the last 50 y show the opposite trend, toward a more La Niña-like state. Recent research provides evidence that the discrepancy cannot be dismissed as due to internal variability but rather that the models are incorrectly simulating the equatorial Pacific response to greenhouse gas warming. This implies that projections of regional tropical cyclone activity may be incorrect as well, perhaps even in the direction of change, in ways that can be understood by analogy to historical El Niño and La Niña events: North Pacific tropical cyclone projections will be too active, North Atlantic ones not active enough, for example. Other perils, including severe convective storms and droughts, will also be projected erroneously. While it can be argued that these errors are transient, such that the models’ responses to greenhouse gases may be correct in equilibrium, the transient response is relevant for climate adaptation in the next several decades. Given the urgency of understanding regional patterns of climate risk in the near term, it would be desirable to develop projections that represent a broader range of possible future tropical Pacific warming scenarios—including some in which recent historical trends continue—even if such projections cannot currently be produced using existing coupled earth system models. 

Abstract An open‐source, physics‐based tropical cyclone (TC) downscaling model is developed, in order to generate a large climatology of TCs. The model is composed of three primary components: (a) a random seeding process that determines genesis, (b) an intensity‐dependent beta‐advection model that determines the track, and (c) a non‐linear differential equation set that determines the intensification rate. The model is entirely forced by the large‐scale environment. Downscaling ERA5 reanalysis data shows that the model is generally able to reproduce observed TC climatology, such as the global seasonal cycle, genesis locations, track density, and lifetime maximum intensity distributions. Inter‐annual variability in TC count and power‐dissipation is also well captured, on both basin‐wide and global scales. Regional TC hazard estimated by this model is also analyzed using return period maps and curves. In particular, the model is able to reasonably capture the observed return period curves of landfall intensity in various sub‐basins around the globe. The incorporation of an intensity‐dependent steering flow is shown to lead to regionally dependent changes in power dissipation and return periods. Advantages and disadvantages of this model, compared to other downscaling models, are also discussed. 

Abstract Surface winds and precipitation over the tropical oceans are related to sea surface temperature (SST) through multiple mechanisms. Greater SST is associated with greater conditional instability, which in turn is more conducive to deep convection. The associated mass and flow responses can extend to the surface, via associated pressure gradients imprinted on the top of the planetary boundary layer (PBL). SST also influences surface pressure and wind directly through its control over PBL temperature, as explained by Lindzen and Nigam. The authors examine the relative magnitudes of these two influences over the eastern tropical Pacific on subseasonal precipitation variability during northern summer, when and where SST gradients are largest and the direct influence via PBL temperature is expected to be strongest. Geopotential at 1000 hPa is partitioned into two components: the geopotential at the PBL top (the PBL top is chosen to be 850 hPa, supported by an analysis of the vertical structure of geopotential and temperature) and the PBL thickness. These fields are composited on quintiles of daily ITCZ precipitation both with and without a high-pass filter that isolates subseasonal time scales. The PBL thickness varies little between the highest and lowest precipitation quintiles, while the PBL top geopotential varies much more. This supports a view in which the direct contribution of SST to the surface pressure and flow fields, including the associated PBL convergence over sharp SST maxima, can be viewed as a steady forcing on the rest of the column, while free-tropospheric transients contribute most of the variability associated with precipitation on subseasonal time scales. 

Abstract Observational studies show a strong connection between the intraseasonal Madden-Julian oscillation (MJO) and the stratospheric quasi-biennial oscillation (QBO): the boreal winter MJO is stronger, more predictable, and has different teleconnections when the QBO in the lower stratosphere is easterly versus westerly. Despite the strength of the observed connection, global climate models do not produce an MJO-QBO link. Here the authors use a current-generation ocean-atmosphere coupled NASA Goddard Institute for Space Studies global climate model (Model E2.1) to examine the MJO-QBO link. To represent the QBO with minimal bias, the model zonal mean stratospheric zonal and meridional winds are relaxed to reanalysis fields from 1980-2017. The model troposphere, including the MJO, is allowed to freely evolve. The model with stratospheric nudging captures QBO signals well, including QBO temperature anomalies. However, an ensemble of nudged simulations still lacks an MJO-QBO connection. 

Abstract The stratospheric quasi-biennial oscillation (QBO) induces temperature anomalies in the lower stratosphere and tropical tropopause layer (TTL) that are cold when lower-stratospheric winds are easterly and warm when winds are westerly. Recent literature has indicated that these QBO temperature anomalies are potentially important in influencing the tropical troposphere, and particularly in explaining the relationship between the QBO and the Madden–Julian oscillation (MJO). The authors examine the variability of QBO temperature anomalies across several time scales using reanalysis and observational datasets. The authors find that, in boreal winter relative to other seasons, QBO temperature anomalies are significantly stronger (i.e., colder in the easterly phase of the QBO and warmer in the westerly phase of the QBO) on the equator, but weaker off the equator. The equatorial and subtropical changes compensate such that meridional temperature gradients and thus (by thermal wind balance) equatorial zonal wind anomalies do not vary in amplitude as the temperature anomalies do. The same pattern of stronger on-equatorial and weaker off-equatorial QBO temperature anomalies is found on decadal time scales: stronger anomalies are seen for 1999–2019 compared to 1979–99. The causes of these changes to QBO temperature anomalies, as well as their possible relevance to the MJO–QBO relationship, are not known.