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Michael J. DeFlorio, David W. Pierce, Daniel R. Cayan, and Arthur J. Miller

Abstract

Water resources and management over the western United States are heavily impacted by both local climate variability and the teleconnected responses of precipitation to the El Niño–Southern Oscillation (ENSO) and Pacific decadal oscillation (PDO). In this work, regional precipitation patterns over the western United States and linkages to ENSO and the PDO are analyzed using output from a Community Climate System Model version 4 (CCSM4) preindustrial control run and observations, with emphasis on extreme precipitation events. CCSM4 produces realistic zonal gradients in precipitation intensity and duration over the western United States, with higher values on the windward side of the Cascade Mountains and Sierra Nevada and lower values on the leeward. Compared to its predecessor CCSM3, CCSM4 shows an improved teleconnected signal of both ENSO and the PDO to large-scale circulation patterns over the Pacific–North America region and also to the spatial pattern and other aspects of western U.S. precipitation. The so-called drizzle problem persists in CCSM4 but is significantly improved compared to CCSM3. In particular, it is found that CCSM4 has substantially less precipitation duration bias than is present in CCSM3. Both the overall and extreme intensity of wintertime precipitation over the western United States show statistically significant linkages with ENSO and PDO in CCSM4. This analysis provides a basis for future studies using greenhouse gas (GHG)-forced CCSM4 runs.

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Dillon J. Amaya, Yu Kosaka, Wenyu Zhou, Yu Zhang, Shang-Ping Xie, and Arthur J. Miller

Abstract

Studies have indicated that North Pacific sea surface temperature (SST) variability can significantly modulate El Niño–Southern Oscillation (ENSO), but there has been little effort to put extratropical–tropical interactions into the context of historical events. To quantify the role of the North Pacific in pacing the timing and magnitude of observed ENSO, we use a fully coupled climate model to produce an ensemble of North Pacific Ocean–Global Atmosphere (nPOGA) SST pacemaker simulations. In nPOGA, SST anomalies are restored back to observations in the North Pacific (>15°N) but are free to evolve throughout the rest of the globe. We find that the North Pacific SST has significantly influenced observed ENSO variability, accounting for approximately 15% of the total variance in boreal fall and winter. The connection between the North and tropical Pacific arises from two physical pathways: 1) a wind–evaporation–SST (WES) propagating mechanism, and 2) a Gill-like atmospheric response associated with anomalous deep convection in boreal summer and fall, which we refer to as the summer deep convection (SDC) response. The SDC response accounts for 25% of the observed zonal wind variability around the equatorial date line. On an event-by-event basis, nPOGA most closely reproduces the 2014/15 and the 2015/16 El Niños. In particular, we show that the 2015 Pacific meridional mode event increased wind forcing along the equator by 20%, potentially contributing to the extreme nature of the 2015/16 El Niño. Our results illustrate the significant role of extratropical noise in pacing the initiation and magnitude of ENSO events and may improve the predictability of ENSO on seasonal time scales.

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Hyodae Seo, Markus Jochum, Raghu Murtugudde, Arthur J. Miller, and John O. Roads

Abstract

The effects of atmospheric feedbacks on tropical instability waves (TIWs) in the equatorial Atlantic Ocean are examined using a regional high-resolution coupled climate model. The analysis from a 6-yr hindcast from 1999 to 2004 reveals a negative correlation between TIW-induced wind perturbations and TIW-induced ocean currents, which implies damping of the TIWs. On the other hand, the feedback effect from the modification of Ekman pumping velocity by TIWs is small compared to the contribution to TIW growth by baroclinic instability. Overall, the atmosphere reduces the growth of TIWs by adjusting its wind response to the evolving TIWs. The analysis also shows that including ocean current (mean + TIWs) in the wind stress parameterization reduces the surface stress estimate by 15%–20% over the region of the South Equatorial Current. Moreover, TIW-induced perturbation ocean currents can significantly alter surface stress estimations from scatterometers, especially at TIW frequencies. Finally, the rectification effect from the atmospheric response to TIWs on latent heat flux is small compared to the mean latent heat flux.

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Sang-Wook Yeh, Yune-Jung Kang, Yign Noh, and Arthur J. Miller

Abstract

This paper examines characteristic changes in North Pacific sea surface temperature (SST) variability during the boreal winter (December–February) for two subperiods (1956–88 and 1977–2009) during which the 1976/77 and the 1988/89 climate transitions occurred. It is found that the Pacific decadal oscillation (PDO)-like SST variability plays a dominant role in the 1976/77 climate transition, while both the North Pacific Gyre Oscillation (NPGO)-like and PDO-like SST variability contribute to the 1988/89 climate transition. Furthermore, the leading mode changes from PDO-like SST variability during the period 1956–88 to NPGO-like SST variability during the period 1977–2009, indicative of an enhancement of NPGO-like SST variability since 1988. Changes in sea level pressure across the 1976/77 climate transition project strongly onto the Aleutian low pressure system. But sea level pressure changes across the 1988/89 climate transition project primarily onto the North Pacific Oscillation, which is associated with remote changes in the Arctic Oscillation over the polar region as well. This contributes to enhancing the NPGO-like SST variability after 1988. The authors also analyze the output from an ensemble of Tropical Ocean and Global Atmosphere (TOGA) experiments in which the observed SSTs are inserted only at grid points in the tropics between 20°S and 20°N. The results indicate that the changes in the North Pacific atmosphere in the 1976/77 climate transition are mostly due to the tropics, whereas those in the 1988/89 climate transition are not.

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Aneesh C. Subramanian, Ibrahim Hoteit, Bruce Cornuelle, Arthur J. Miller, and Hajoon Song

Abstract

This paper investigates the role of the linear analysis step of the ensemble Kalman filters (EnKF) in disrupting the balanced dynamics in a simple atmospheric model and compares it to a fully nonlinear particle-based filter (PF). The filters have a very similar forecast step but the analysis step of the PF solves the full Bayesian filtering problem while the EnKF analysis only applies to Gaussian distributions. The EnKF is compared to two flavors of the particle filter with different sampling strategies, the sequential importance resampling filter (SIRF) and the sequential kernel resampling filter (SKRF). The model admits a chaotic vortical mode coupled to a comparatively fast gravity wave mode. It can also be configured either to evolve on a so-called slow manifold, where the fast motion is suppressed, or such that the fast-varying variables are diagnosed from the slow-varying variables as slaved modes. Identical twin experiments show that EnKF and PF capture the variables on the slow manifold well as the dynamics is very stable. PFs, especially the SKRF, capture slaved modes better than the EnKF, implying that a full Bayesian analysis estimates the nonlinear model variables better. The PFs perform significantly better in the fully coupled nonlinear model where fast and slow variables modulate each other. This suggests that the analysis step in the PFs maintains the balance in both variables much better than the EnKF. It is also shown that increasing the ensemble size generally improves the performance of the PFs but has less impact on the EnKF after a sufficient number of members have been used.

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Hyodae Seo, Markus Jochum, Raghu Murtugudde, Arthur J. Miller, and John O. Roads

Abstract

A regional coupled climate model is configured for the tropical Atlantic to explore the role of synoptic-scale African easterly waves (AEWs) on the simulation of mean precipitation in the marine intertropical convergence zone (ITCZ). Sensitivity tests with varying atmospheric resolution in the coupled model show that these easterly waves are well represented with comparable amplitudes on both fine and coarse grids of the atmospheric model. Significant differences in the model simulations are found in the precipitation fields, however, where heavy rainfall events occur in the region of strong cyclonic shear of the easterly waves only on the higher-resolution grid. This is because the low-level convergence due to the waves is much larger and more realistic in the fine-resolution simulation, which enables heavier precipitation events that skew the rainfall distributions toward longer tails. The variability in rainfall on these time scales accounts for more than 60%–70% of the total variability. As a result, the simulation of mean rainfall in the ITCZ and its seasonal migration improves in the higher-resolution case. This suggests that capturing these transient waves and the resultant strong low-level convergence is one of the key ingredients for improving the simulation of precipitation in global coupled climate models.

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Momme C. Hell, Bruce D. Cornelle, Sarah T. Gille, Arthur J. Miller, and Peter D. Bromirski

Abstract

Strong surface winds under extratropical cyclones exert intense surface stresses on the ocean that lead to upper-ocean mixing, intensified heat fluxes, and the generation of waves, that, over time, lead to swell waves (longer than 10-s period) that travel long distances. Because low-frequency swell propagates faster than high-frequency swell, the frequency dependence of swell arrival times at a measurement site can be used to infer the distance and time that the wave has traveled from its generation site. This study presents a methodology that employs spectrograms of ocean swell from point observations on the Ross Ice Shelf (RIS) to verify the position of high wind speed areas over the Southern Ocean, and therefore of extratropical cyclones. The focus here is on the implementation and robustness of the methodology in order to lay the groundwork for future broad application to verify Southern Ocean storm positions from atmospheric reanalysis data. The method developed here combines linear swell dispersion with a parametric wave model to construct a time- and frequency-dependent model of the dispersed swell arrivals in spectrograms of seismic observations on the RIS. A two-step optimization procedure (deep learning) of gradient descent and Monte Carlo sampling allows detailed estimates of the parameter distributions, with robust estimates of swell origins. Median uncertainties of swell source locations are 110 km in radial distance and 2 h in time. The uncertainties are derived from RIS observations and the model, rather than an assumed distribution. This method is an example of supervised machine learning informed by physical first principles in order to facilitate parameter interpretation in the physical domain.

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Hyodae Seo, Shang-Ping Xie, Raghu Murtugudde, Markus Jochum, and Arthur J. Miller

Abstract

Effects of freshwater forcing from river discharge into the Indian Ocean on oceanic vertical structure and the Indian monsoons are investigated using a fully coupled, high-resolution, regional climate model. The effect of river discharge is included in the model by restoring sea surface salinity (SSS) toward observations. The simulations with and without this effect in the coupled model reveal a highly seasonal influence of salinity and the barrier layer (BL) on oceanic vertical density stratification, which is in turn linked to changes in sea surface temperature (SST), surface winds, and precipitation.

During both boreal summer and winter, SSS relaxation leads to a more realistic spatial distribution of salinity and the BL in the model. In summer, the BL in the Bay of Bengal enhances the upper-ocean stratification and increases the SST near the river mouths where the freshwater forcing is largest. However, the warming is limited to the coastal ocean and the amplitude is not large enough to give a significant impact on monsoon rainfall.

The strengthened BL during boreal winter leads to a shallower mixed layer. Atmospheric heat flux forcing acting on a thin mixed layer results in an extensive reduction of SST over the northern Indian Ocean. Relatively suppressed mixing below the mixed layer warms the subsurface layer, leading to a temperature inversion. The cooling of the sea surface induces a large-scale adjustment in the winter atmosphere with amplified northeasterly winds. This impedes atmospheric convection north of the equator while facilitating it in the austral summer intertropical convergence zone, resulting in a hemispheric-asymmetric response pattern. Overall, the results suggest that freshwater forcing from the river discharges plays an important role during the boreal winter by affecting SST and the coupled ocean–atmosphere interaction, with potential impacts on the broadscale regional climate.

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Aneesh C. Subramanian, Markus Jochum, Arthur J. Miller, Raghu Murtugudde, Richard B. Neale, and Duane E. Waliser

Abstract

This study assesses the ability of the Community Climate System Model, version 4 (CCSM4) to represent the Madden–Julian oscillation (MJO), the dominant mode of intraseasonal variability in the tropical atmosphere. The U.S. Climate Variability and Predictability (CLIVAR) MJO Working Group’s prescribed diagnostic tests are used to evaluate the model’s mean state, variance, and wavenumber–frequency characteristics in a 20-yr simulation of the intraseasonal variability in zonal winds at 850 hPa (U850) and 200 hPa (U200), and outgoing longwave radiation (OLR). Unlike its predecessor, CCSM4 reproduces a number of aspects of MJO behavior more realistically.

The CCSM4 produces coherent, broadbanded, and energetic patterns in eastward-propagating intraseasonal zonal winds and OLR in the tropical Indian and Pacific Oceans that are generally consistent with MJO characteristics. Strong peaks occur in power spectra and coherence spectra with periods between 20 and 100 days and zonal wavenumbers between 1 and 3. Model MJOs, however, tend to be more broadbanded in frequency than in observations. Broad-scale patterns, as revealed in combined EOFs of U850, U200, and OLR, are remarkably consistent with observations and indicate that large-scale convergence–convection coupling occurs in the simulated MJO.

Relations between MJO in the model and its concurrence with other climate states are also explored. MJO activity (defined as the percentage of time the MJO index exceeds 1.5) is enhanced during El Niño events compared to La Niña events, both in the model and observations. MJO activity is increased during periods of anomalously strong negative meridional wind shear in the Asian monsoon region and also during strong negative Indian Ocean zonal mode states, in both the model and observations.

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Hyodae Seo, Aneesh C. Subramanian, Arthur J. Miller, and Nicholas R. Cavanaugh

Abstract

This study quantifies, from a systematic set of regional ocean–atmosphere coupled model simulations employing various coupling intervals, the effect of subdaily sea surface temperature (SST) variability on the onset and intensity of Madden–Julian oscillation (MJO) convection in the Indian Ocean. The primary effect of diurnal SST variation (dSST) is to raise time-mean SST and latent heat flux (LH) prior to deep convection. Diurnal SST variation also strengthens the diurnal moistening of the troposphere by collocating the diurnal peak in LH with those of SST. Both effects enhance the convection such that the total precipitation amount scales quasi-linearly with preconvection dSST and time-mean SST. A column-integrated moist static energy (MSE) budget analysis confirms the critical role of diurnal SST variability in the buildup of column MSE and the strength of MJO convection via stronger time-mean LH and diurnal moistening. Two complementary atmosphere-only simulations further elucidate the role of SST conditions in the predictive skill of MJO. The atmospheric model forced with the persistent initial SST, lacking enhanced preconvection warming and moistening, produces a weaker and delayed convection than the diurnally coupled run. The atmospheric model with prescribed daily-mean SST from the coupled run, while eliminating the delayed peak, continues to exhibit weaker convection due to the lack of strong moistening on a diurnal basis. The fact that time-evolving SST with a diurnal cycle strongly influences the onset and intensity of MJO convection is consistent with previous studies that identified an improved representation of diurnal SST as a potential source of MJO predictability.

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