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Ning Jiang
,
Minjie Yu
,
Bo Lu
,
Jeremy Cheuk-Hin Leung
, and
Congwen Zhu

Abstract

The persistence barrier (PB), one of the El Niño–Southern Oscillation (ENSO) properties, has exhibited a significant decadal variability, showing enhanced and weakened behavior before and after the late 1970s, respectively. In the present study, both the theoretical solution and the observations indicate that the variability of PB intensity is linearly proportional to the seasonal amplitude of ENSO growth rate, which accounts for the ENSO PB decadal variability. With further use of the Bjerknes–Jin (BJ) index analysis, we find that the decadal reduction in PB intensity since the late 1970s is mainly attributed to the mean advection and the thermocline feedback. In addition, the stronger spring thermal damping delayed the timing of PB in the 1980s and 1990s. Our study establishes a linear relationship between PB intensity and ENSO growth rate, which carries implications for understanding the ENSO predictability and the systematic changes in ENSO properties under climate change.

Restricted access
Alison Cobb
,
Jason Cordeira
,
Michael Dettinger
,
Curt Aikens
,
Chris Delaney
,
Joe Forbis
,
Jay Jasperse
,
Rob Hartman
,
F. Martin Ralph
,
Edwin Sumargo
,
Cary Talbot
,
Anna M. Wilson
, and
Elissa Yeates
Restricted access
Shizuo Liu
,
Qigang Wu
,
Yonghong Yao
, and
Steven R. Schroeder

Abstract

Previous studies indicate observed influences of autumn and winter Tibetan Plateau (TP) snow-cover anomalies on the winter Pacific–North American (PNA) teleconnection. This study simulates atmospheric and oceanic responses to persistent autumn–winter TP snow forcing using an atmospheric general circulation model (AGCM) and a coupled atmospheric-oceanic general circulation model (AOGCM), and quantifies the role of atmosphere–ocean interactions over North Pacific in TP snow effects. The AOGCM experiment induces a stronger and more realistic remote PNA response to heavy TP snow anomalies, and also a significant winter horseshoe-like North Pacific sea surface temperature (SST) pattern resulting from an anomalous equivalent barotropic cyclone, or a strengthened Aleutian low, with associated cyclonic wind stress anomalies. The horseshoe-like SST anomaly pattern is used as boundary forcing (without prescribed heavy TP snow) in another AOGCM experiment, which simulates an enhanced winter Aleutian low and a PNA-like response similar to the original AOGCM responses, indicating that that the direct Pacific–North American atmospheric response to persistent TP snow forcing in the AGCM is amplified in the AOGCM by the North Pacific midlatitude atmosphere–ocean interactions. This suggests that the mechanisms of the winter PNA responses to TP snow forcing involve dynamical atmospheric processes such as horizontal propagation of Rossby wave energy and transient eddy feedbacks, and also North Pacific atmosphere–ocean interactions, which provide a positive feedback on the development of the remote PNA teleconnection.

Significance Statement

The Tibetan Plateau has a 2.5 million km2 area and a 4000 m average elevation, and is often called “the third pole” because of its polar-like climate in midlatitude Eurasia. A heavy Tibetan Plateau snow cover increases the albedo effect and causes tropospheric cold temperature and low height changes that can be carried or advected to the North Pacific by the prevailing westerlies. The purpose of this study is to better understand how Tibetan Plateau snow anomalies influence the North Pacific and the remote atmospheric circulation through numerical simulations. Our results find that those North Pacific responses amply the direct atmospheric response to Tibetan Plateau snow-cover anomalies. This greatly improves our understanding of physical mechanisms of Tibetan Plateau snow impacts.

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Ruoting Wu
,
Guixing Chen
, and
Zhengzhao Johnny Luo

Abstract

This study investigates the diurnal cycles of convective activities and low-level winds with emphasis on their interactions during the East Asian summer monsoon. We categorize atmospheric convection states using satellite-derived cloud regimes and group southerly monsoon flows with different characteristics of diurnal cycles, and found that they are closely related to each other. Over South China, deep convection and associated cirrus anvils produce a strongly negative shortwave cloud radiative effect and induce anomalous cooling in the ABL in the daytime, which reduces the diurnal amplitude of monsoon flows during the night that follows. Conversely, a fair-weather state in the daytime leads to an anomalously warm ABL that enhances the subsequent nighttime acceleration of the monsoon southerlies. The dominant cloud regimes in the daytime over South China are closely related to whether the organized deep convection over the Yun-Gui Plateau (southeast of the Tibetan Plateau) propagates eastward during the preceding night. Such a precursor of clouds/convection governing wind diurnal amplitude indicates a possible predictability of monsoon diurnal cycles over South China. Further analyses show that the cloud regimes and induced monsoon diurnal cycles over South China can regulate the moist convection over the downstream region (central China) through modulating moisture transport and convergence. Therefore, the observational statistics of this study reveal a strong coupling of clouds, radiation, winds, and precipitation at the diurnal time scale over the summer monsoon regions, in which the cloud radiative effects of atmospheric convection can strongly regulate the diurnal variations of low-level winds that further influence precipitation downstream.

Open access
Taiga Tsukada
and
Takeshi Horinouchi

Abstract

Estimation of the radius of maximum wind (RMW) of tropical cyclone (TC) is helpful for the disaster prevention and mitigation. If RMWs are estimated from infrared (IR) imagery taken by geostationary meteorological satellites, their estimation is available densely in time, regardless of the ocean basin. Kossin et al. showed that when TCs have clear eyes, the eye radii estimated from IR images have a high correlation with the RMW estimated from aircraft reconnaissance. The regression of the former onto that latter was shown to have a mean absolute error (MAE) of 4.7 km. We revisit the IR-based RMW estimation by using C-band synthetic aperture radar (SAR) sea surface wind estimates. The criteria for selecting clear-eye cases are simplified. The MAE of the Kossin et al. method is found to be smaller than previously suggested: 3.1 km when the proposed relation is used and 2.7 km when the regression is revised with the SAR-measured RMWs. We further propose an improvement of the IR-based method to estimate the eye radii. The resultant MAE is shown to be 1.7 km, which indicates that the IR-based RMW estimation is more accurate than has been suggested. A strong correlation between eyewall slope and eye size is confirmed. We also investigated cloud features in the eye that may be closely related to RMW and wind structure around RMW. Potential applications of highly accurate RMW estimation are discussed.

Significance Statement

The radius of maximum wind (RMW) of tropical cyclone (TC) is an important factor for TC intensity estimation and disaster prevention. A previous study suggested that the RMWs of TCs with clear eyes can be estimated from geostationary satellite images at a mean absolute error (MAE) of 4.7 km. Here we improved the method, reducing the MAE by more than one-half. Since the method does not require aircraft or satellite in low Earth orbit, it helps TC monitoring at high frequency. The method can also improve initialization of models used to predict TC hazards and further our physical understanding and the climatology of the wind structures near the centers of TCs.

Open access
Liping Wang
,
Haijun Yang
,
Qin Wen
,
Yimin Liu
, and
Guoxiong Wu

Abstract

As the highest and most extensive plateau in the world, the Tibetan Plateau (TP) has remarkable effects on global climate. Through coupled model sensitivity experiments with and without the TP, we show that the TP can affect the Arctic directly via orography-forced stationary waves, and influence the Antarctic indirectly via stationary waves forced by sea surface temperature (SST) in the Indian Ocean. These far-reaching impacts occur mainly in wintertime. The fast atmospheric processes play an important role; particularly, the midlatitude westerly flow, which is stronger and closer to the equator in winter, provides a favorable condition for the eastward and poleward energy propagation of the forced waves. In the Northern Hemisphere, removing the TP causes a wave train traveling from the Asian continent to the North America–Atlantic Ocean region, resulting in intensified westerlies and thus an enhancement of stratospheric polar vortex and Arctic cooling. The pathways are northeastward directly in the upper level due to the background westerlies, while they are eastward and then northeastward in the lower level, modulated by the winter monsoon. To the south, the TP perturbation causes an anomalous cross-equatorial flow, leading to an anomalous SST dipole pattern in the Indian Ocean in the austral winter; this generates stationary waves propagating energy southeastward from the tropical Indian Ocean to the Antarctic, resulting in a Rossby wave train circulating around the Antarctic. Our study identifies the seasonality and pathways of the TP affecting the polar regions, which may help to understand the role of the TP in the future climate changes in polar regions.

Open access
Bart Geerts
,
Coltin Grasmick
,
Robert M. Rauber
,
Troy J. Zaremba
,
Lulin Xue
, and
Katja Friedrich

Abstract

Airborne vertically profiling Doppler radar data and output from a ∼1-km-grid-resolution numerical simulation are used to examine how relatively small-scale terrain ridges (∼10–25 km apart and ∼0.5–1.0 km above the surrounding valleys) impact cross-mountain flow, cloud processes, and surface precipitation in deep stratiform precipitation systems. The radar data were collected along fixed flight tracks aligned with the wind, about 100 km long between the Snake River Plain and the Idaho Central Mountains, as part of the 2017 Seeded and Natural Orographic Wintertime clouds: the Idaho Experiment (SNOWIE). Data from repeat flight legs are composited in order to suppress transient features and retain the effect of the underlying terrain. Simulations closely match observed series of terrain-driven deep gravity waves, although the simulated wave amplitude is slightly exaggerated. The deep waves produce pockets of supercooled liquid water in the otherwise ice-dominated clouds (confirmed by flight-level observations and the model) and distort radar-derived hydrometeor trajectories. Snow particles aloft encounter several wave updrafts and downdrafts before reaching the ground. No significant wavelike modulation of radar reflectivity or model ice water content occurs. The model does indicate substantial localized precipitation enhancement (1.8–3.0 times higher than the mean) peaking just downwind of individual ridges, especially those ridges with the most intense wave updrafts, on account of shallow pockets of high liquid water content on the upwind side, leading to the growth of snow and graupel, falling out mostly downwind of the crest. Radar reflectivity values near the surface are complicated by snowmelt, but suggest a more modest enhancement downwind of individual ridges.

Significance Statement

Mountains in the midlatitude belt and elsewhere receive more precipitation than the surrounding lowlands. The mountain terrain often is complex, and it remains unclear exactly where this precipitation enhancement occurs, because weather radars are challenged by beam blockage and the gauge network is too sparse to capture the precipitation heterogeneity over complex terrain. This study uses airborne profiling radar and high-resolution numerical simulations for four winter storms over a series of ridges in Idaho. One key finding is that while instantaneous airborne radar transects of the cross-mountain flow, vertical drafts, and reflectivity contain much transient small-scale information, time-averaged transects look very much like the model transects. The model indicates substantial surface precipitation enhancement over terrain, peaking over and just downwind of individual ridges. Radar observations suggest less enhancement, but the radar-based assessment is uncertain. The second key conclusion is that, even though orographic gravity waves are felt all the way up into the upper troposphere, the orographic precipitation enhancement is due to processes very close to the terrain.

Restricted access
Yukio Kurihara

Abstract

Stripe noise is a common issue in sea surface temperatures (SSTs) retrieved from thermal infrared data obtained by satellite-based multidetector radiometers. We developed a bispectral filter (BSF) to reduce the stripe noise. The BSF is a Gaussian filter and an optimal estimation method for the differences between the data obtained at the split window. A kernel function based on the physical processes of radiative transfer has made it possible to reduce stripe and random noise in retrieved SSTs without degrading the spatial resolution or generating bias. The Second-Generation Global Imager (SGLI) is an optical sensor on board the Global Change Observation Mission–Climate (GCOM-C) satellite. We applied the BSF to SGLI data and validated the retrieved SSTs. The validation results demonstrate the effectiveness of BSF, which reduced stripe noise in the retrieved SGLI SSTs without blurring SST fronts. It also improved the accuracy of the SSTs by about 0.04 K (about 13%) in the robust standard deviation.

Significance Statement

This method reduces stripe noise and improves the accuracy of SST data with minimal compromise of spatial resolution. The method assumes the relationship between the brightness temperature and the brightness temperature difference in the split window based on the physical background of atmospheric radiative transfer. The physical background of the data provides an easy solution to a complex problem. Although destriping generally requires a complex algorithm, our approach is based on a simple Gaussian filter and is easy to implement.

Open access
Clemente Lopez-Bravo
,
Claire L. Vincent
,
Yi Huang
, and
Todd P. Lane

Abstract

A West Sumatra squall line occurred on 10 January 2016, with a clear offshore propagation of convection. Satellite-derived products from Himawari-8 Advanced Himawari Imager and the Geostationary Cloud Algorithm Testbed Geocat are used to investigate the westward propagation of cloudiness from Sumatra to the Indian Ocean with a lifetime of 1.5 days. A convective mask based on deep convective cell detection and a cell-tracking algorithm are used to estimate the propagation speed of the cloud system. Two distinct mesoscale convective responses are identified: 1) a rapid development in South Sumatra is influenced by the convective environment over the Indian Ocean. The propagation speed is estimated to be ∼5 m s−1 within the first 200 km from the coast. This speed is consistent with density currents. In contrast, 2) the coupling to the inertia–gravity wave is only evident for the northwest of Sumatra with speeds of ∼12 m s−1. The analysis of brightness temperature from the 10.4-μm spectral band and cloud-top temperature showed that the lifetime of the squall line is approximately 30 h with a propagating distance of ∼1000 km. Retrieved cloud properties and tracking of the offshore propagation indicated that the cloud structure consisted of multiple types of cells, propagating as envelopes of convection, and revealed the influence of large-scale variability of the Indian Ocean. Filtered OLR anomalies, satellite-derived rainfall, moisture flux convergence, and background winds flow around Sumatra are used to explore the effects of Kelvin wave activity that likely influenced the lifetime of the squall line.

Restricted access
S. Sharmila
,
H. Hendon
,
O. Alves
,
A. Weisheimer
, and
M. Balmaseda

Abstract

Despite the growing demand for long-range ENSO predictions beyond 1 year, quantifying the skill at these lead times remains limited. This is partly due to inadequate long records of seasonal reforecasts that make skill estimates of irregular ENSO events quite challenging. Here, we investigate ENSO predictability and the dependency of prediction skill on the ENSO cycle using 110 years of 24-month-long 10-member ensemble reforecasts from ECMWF’s coupled model (SEAS5-20C) initialized on 1 November and 1 May during 1901–2010. Results show that Niño-3.4 SST can be skillfully predicted up to ∼18 lead months when initialized on 1 November, but skill drops at ∼12 lead months for May starts that encounter the boreal spring predictability barrier in year 2. The skill beyond the first year is highly conditioned to the phase of ENSO: Forecasts initialized at peak El Niño are more skillful in year 2 than those initialized at peak La Niña, with the transition to La Niña being more predictable than to El Niño. This asymmetry is related to the subsurface initial conditions in the western equatorial Pacific: peak El Niño states evolving into La Niña are associated with strong upper-ocean heat discharge of the western Pacific, the memory of which stays beyond 1 year. In contrast, the western Pacific recharged state associated with La Niña is usually weaker and shorter-lived, being a weaker preconditioner for subsequent El Niño, the year after. High prediction skill of ENSO events beyond 1 year provides motivation for extending the lead time of operational seasonal forecasts up to 2 years.

Open access