The role of air–sea coupling on November–April intraseasonal rainfall variability over the South Pacific

We investigate the impact of resolving air-sea interaction on the simulation of the intraseasonal rainfall variability over the South Pacific using the ECHAM5 atmospheric general circulation model coupled with the Snow-Ice-Thermocline (SIT) ocean model. We compare the fully coupled simulation with two uncoupled ECHAM5 simulations, one forced with sea surface temperature (SST) climatology and one forced with daily SST from the coupled model. The intraseasonal rainfall variability over the South Pacific is reduced by 17% in the uncoupled model forced with SST climatology and increased by 8% in the uncoupled simulation forced with daily SST, suggesting the role of air–sea coupling and SST variability. The coupled model best simulates the key characteristics of the two dominant patterns (modes) of intraseasonal rainfall variability over the South Pacific with reasonable propagation and correct periodicity. The spatial structure of the two rainfall modes in all three simulations is very similar, suggesting the dynamics of the atmosphere primarily generate these modes. The southeastward propagation of rainfall anomalies associated with two leading rainfall modes in the South Pacific depends upon the eastward propagating Madden–Julian Oscillation (MJO) signals from the Indian Ocean and western Pacific. Air-sea interaction improves such propagation as both eastward and southeastward propagations are substantially reduced in the uncoupled model forced with SST climatology. The simulation of both eastward and southeastward propagations considerably improved in the uncoupled model forced with daily SST; however, the periodicity differs from the coupled model. Such discrepancy in the periodicity is attributed to the changes in the SST-rainfall relationship with weaker correlations and the nearly in-phase relationship, attributed to enhanced positive latent heat flux feedbacks.publishedVersio

Resolving the upper-ocean warm layer improves the simulation of the Madden-Julian oscillation

Here we show that coupling a high-resolution one-column ocean model to an atmospheric general circulation model dramatically improves simulation of the Madden–Julian oscillation (MJO) to have realistic strength, period, and propagation speed. The mechanism for the simulated MJO involves both frictional wave-convective conditional instability of the second kind (Frictional wave-CISK) and air–sea convective intraseasonal interaction (ASCII). In particular, better resolving the fine structure of upper ocean temperature, especially the warm layer, produces more vigorous atmosphere–ocean interaction and strengthens intraseasonal variations in both SST and atmospheric circulation. This helps organize and strengthen deep convection, inducing a stronger Kelvin-wave like perturbation and frictional near-surface convergence to the east. In addition, the warmer SST ahead of the MJO also acts to destabilize the boundary layer and enhance frictional convergence. These lead to a more realistic eastward-propagating MJO. A suite of sensitivity experiments were performed to show the robustness of the mechanisms and to demonstrate: (1) that mean state differences are not the main contributors to the improved simulation of our coupled model; (2) the role of SST variability in enhancing frictional convergence and intraseasonal variations in precipitation, and (3) that the simulation is significantly degraded when the first ocean model layer is thicker than 10 m. Our coupled model results are consistent with observations and demonstrate a simple but effective means to significantly improve MJO simulation and potentially also forecasts

The role of air–sea coupling on November–April intraseasonal rainfall variability over the South Pacific

We investigate the impact of resolving air-sea interaction on the simulation of the intraseasonal rainfall variability over the South Pacific using the ECHAM5 atmospheric general circulation model coupled with the Snow-Ice-Thermocline (SIT) ocean model. We compare the fully coupled simulation with two uncoupled ECHAM5 simulations, one forced with sea surface temperature (SST) climatology and one forced with daily SST from the coupled model. The intraseasonal rainfall variability over the South Pacific is reduced by 17% in the uncoupled model forced with SST climatology and increased by 8% in the uncoupled simulation forced with daily SST, suggesting the role of air–sea coupling and SST variability. The coupled model best simulates the key characteristics of the two dominant patterns (modes) of intraseasonal rainfall variability over the South Pacific with reasonable propagation and correct periodicity. The spatial structure of the two rainfall modes in all three simulations is very similar, suggesting the dynamics of the atmosphere primarily generate these modes. The southeastward propagation of rainfall anomalies associated with two leading rainfall modes in the South Pacific depends upon the eastward propagating Madden–Julian Oscillation (MJO) signals from the Indian Ocean and western Pacific. Air-sea interaction improves such propagation as both eastward and southeastward propagations are substantially reduced in the uncoupled model forced with SST climatology. The simulation of both eastward and southeastward propagations considerably improved in the uncoupled model forced with daily SST; however, the periodicity differs from the coupled model. Such discrepancy in the periodicity is attributed to the changes in the SST-rainfall relationship with weaker correlations and the nearly in-phase relationship, attributed to enhanced positive latent heat flux feedbacks

Spatially-resolved readout of a Fabry-Perot ultrasound sensor interrogated through a multimode optical fibre using wavefront shaping

The spatially-resolved interrogation of a Fabry-Perot ultrasound sensor using a laser beam focussed through a multimode fibre is demonstrated. To scan the beam across the sensor as required to read it out, optical wavefront shaping was employed to compensate for the scrambling of light in the fibre. By providing a means to map ultrasound through inexpensive, lightweight fibres, this could lead to new ultrasonic and photoacoustic imaging systems such as endoscopes and flexible handheld probes

Semiconductor disk laser in bi-frequency operation by laser ablation micromachining of a laser mirror

We present bi-frequency continuous wave oscillation in a semiconductor disk laser through direct writing of loss-inducing patterns onto an intra-cavity high reflector mirror. The laser is a Vertical External Cavity Surface Emitting Laser which is optically pumped by up to 1.1 W of 808 nm light from a fibre coupled multi-mode diode laser, and oscillates on two Hermite-Gaussian spatial modes simultaneously, achieving wavelength separations between 0.2 nm and 5 nm around 995 nm. We use a Digital Micromirror Device (DMD) enabled laser ablation system to define spatially specific loss regions on a laser mirror by machining away the Bragg layers from the mirror surface. The ablated pattern is comprised of two orthogonal lines with the centermost region undamaged, and is positioned in the laser cavity so as to interact with the lasing mode, thereby promoting the simultaneous oscillation of the fundamental and a higher order spatial mode. We demonstrate bi-frequency oscillation over a range of mask gap sizes and pump powers

The Madden-Julian Oscillation in a warmer world

Global warming's impact on the Madden-Julian Oscillation (MJO) is assessed using one of the few models capable in reproducing its key features. In a warmer climate predicted for the end of the century, the MJO increases in amplitude (by ~30%) and frequency, showing a more circumglobal propagation tendency. The MJO spatial extent becomes enhanced, deeper, and more zonally extended but meridionally confined. A stronger vertical tilting structure in diabatic heating, moisture, and convergence fields is seen. Our findings indicate that these changes result from an intensification of the frictional wave-conditional instability of the second kind mechanism via the coupling of dynamical and thermodynamic response to the warming. The warming and moistening of the mean state contribute to the enhanced deep convective heating, driving a stronger-forced Kelvin wave-like perturbation. This reinforces the frictional low-level convergence, leading to larger shallow convective heating and therefore to a faster development and enhancement of the deep convection in the MJO

Decadal prediction: can it be skilful?

© Copyright 2009 American Meteorological Society (AMS). Permission to use figures, tables, and brief excerpts from this work in scientific and educational works is hereby granted provided that the source is acknowledged. Any use of material in this work that is determined to be “fair use” under Section 107 of the U.S. Copyright Act or that satisfies the conditions specified in Section 108 of the U.S. Copyright Act (17 USC §108, as revised by P.L. 94-553) does not require the AMS’s permission. Republication, systematic reproduction, posting in electronic form, such as on a web site or in a searchable database, or other uses of this material, except as exempted by the above statement, requires written permission or a license from the AMS. Additional details are provided in the AMS Copyright Policy, available on the AMS Web site located at (http://www.ametsoc.org/) or from the AMS at 617-227-2425 or [email protected] new field of study, “decadal prediction,” is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10–30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving three-dimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr

Decadal Prediction. Can It Be Skillful?

A new field of study, “decadal prediction,” is emerging in climate science. Decadal prediction lies between seasonal/interannual forecasting and longer-term climate change projections, and focuses on time-evolving regional climate conditions over the next 10–30 yr. Numerous assessments of climate information user needs have identified this time scale as being important to infrastructure planners, water resource managers, and many others. It is central to the information portfolio required to adapt effectively to and through climatic changes. At least three factors influence time-evolving regional climate at the decadal time scale: 1) climate change commitment (further warming as the coupled climate system comes into adjustment with increases of greenhouse gases that have already occurred), 2) external forcing, particularly from future increases of greenhouse gases and recovery of the ozone hole, and 3) internally generated variability. Some decadal prediction skill has been demonstrated to arise from the first two of these factors, and there is evidence that initialized coupled climate models can capture mechanisms of internally generated decadal climate variations, thus increasing predictive skill globally and particularly regionally. Several methods have been proposed for initializing global coupled climate models for decadal predictions, all of which involve global time-evolving three-dimensional ocean data, including temperature and salinity. An experimental framework to address decadal predictability/prediction is described in this paper and has been incorporated into the coordinated Coupled Model Intercomparison Model, phase 5 (CMIP5) experiments, some of which will be assessed for the IPCC Fifth Assessment Report (AR5). These experiments will likely guide work in this emerging field over the next 5 yr