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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.

Full access
William E. Chapman
,
Aneesh C. Subramanian
,
Shang-Ping Xie
,
Michael D. Sierks
,
F. Martin Ralph
, and
Youichi Kamae

Abstract

Using a high-resolution atmospheric general circulation model simulation of unprecedented ensemble size, we examine potential predictability of monthly anomalies under El Niño–Southern Oscillation (ENSO) forcing and background internal variability. This study reveals the pronounced month-to-month evolution of both the ENSO forcing signal and internal variability. Internal variance in upper-level geopotential height decreases (~10%) over the North Pacific during El Niño as the westerly jet extends eastward, allowing forced signals to account for a greater fraction of the total variability, and leading to increased potential predictability. We identify February and March of El Niño years as the most predictable months using a signal-to-noise analysis. In contrast, December, a month typically included in teleconnection studies, shows little to no potential predictability. We show that the seasonal evolution of SST forcing and variability leads to significant signal-to-noise relationships that can be directly linked to both upper-level and surface variable predictability for a given month. The stark changes in forced response, internal variability, and thus signal-to-noise across an ENSO season indicate that subseasonal fields should be used to diagnose potential predictability over North America associated with ENSO teleconnections. Using surface air temperature and precipitation as examples, this study provides motivation to pursue “windows of forecast opportunity” in which statistical skill can be developed, tested, and leveraged to determine times and regions in which this skill may be elevated.

Free access
Karsten Haustein
,
Friederike E. L. Otto
,
Victor Venema
,
Peter Jacobs
,
Kevin Cowtan
,
Zeke Hausfather
,
Robert G. Way
,
Bethan White
,
Aneesh Subramanian
, and
Andrew P. Schurer

Abstract

The early twentieth-century warming (EW; 1910–45) and the mid-twentieth-century cooling (MC; 1950–80) have been linked to both internal variability of the climate system and changes in external radiative forcing. The degree to which either of the two factors contributed to EW and MC, or both, is still debated. Using a two-box impulse response model, we demonstrate that multidecadal ocean variability was unlikely to be the driver of observed changes in global mean surface temperature (GMST) after AD 1850. Instead, virtually all (97%–98%) of the global low-frequency variability (>30 years) can be explained by external forcing. We find similarly high percentages of explained variance for interhemispheric and land–ocean temperature evolution. Three key aspects are identified that underpin the conclusion of this new study: inhomogeneous anthropogenic aerosol forcing (AER), biases in the instrumental sea surface temperature (SST) datasets, and inadequate representation of the response to varying forcing factors. Once the spatially heterogeneous nature of AER is accounted for, the MC period is reconcilable with external drivers. SST biases and imprecise forcing responses explain the putative disagreement between models and observations during the EW period. As a consequence, Atlantic multidecadal variability (AMV) is found to be primarily controlled by external forcing too. Future attribution studies should account for these important factors when discriminating between externally forced and internally generated influences on climate. We argue that AMV must not be used as a regressor and suggest a revised AMV index instead [the North Atlantic Variability Index (NAVI)]. Our associated best estimate for the transient climate response (TCR) is 1.57 K (±0.70 at the 5%–95% confidence level).

Open access
Yassir A. Eddebbar
,
Keith B. Rodgers
,
Matthew C. Long
,
Aneesh C. Subramanian
,
Shang-Ping Xie
, and
Ralph F. Keeling

Abstract

The oceanic response to recent tropical eruptions is examined in Large Ensemble (LE) experiments from two fully coupled global climate models, the Community Earth System Model (CESM) and the Geophysical Fluid Dynamics Laboratory Earth System Model (ESM2M), each forced by a distinct volcanic forcing dataset. Following the simulated eruptions of Agung, El Chichón, and Pinatubo, the ocean loses heat and gains oxygen and carbon, in general agreement with available observations. In both models, substantial global surface cooling is accompanied by El Niño–like equatorial Pacific surface warming a year after the volcanic forcing peaks. A mechanistic analysis of the CESM and ESM2M responses to Pinatubo identifies remote wind forcing from the western Pacific as a major driver of this El Niño–like response. Following eruption, faster cooling over the Maritime Continent than adjacent oceans suppresses convection and leads to persistent westerly wind anomalies over the western tropical Pacific. These wind anomalies excite equatorial downwelling Kelvin waves and the upwelling of warm subsurface anomalies in the eastern Pacific, promoting the development of El Niño conditions through Bjerknes feedbacks a year after eruption. This El Niño–like response drives further ocean heat loss through enhanced equatorial cloud albedo, and dominates global carbon uptake as upwelling of carbon-rich waters is suppressed in the tropical Pacific. Oxygen uptake occurs primarily at high latitudes, where surface cooling intensifies the ventilation of subtropical thermocline waters. These volcanically forced ocean responses are large enough to contribute to the observed decadal variability in oceanic heat, carbon, and oxygen.

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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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