Impact of atmosphere–ocean interactions on propagation and initiation of boreal winter and summer intraseasonal oscillations

2021 ◽  
pp. 17-60
Author(s):  
Tim Li ◽  
Tianyi Wang
Keyword(s):  
Boreal Winter ◽  
Intraseasonal Oscillations

scholarly journals A Precipitation-Based Index for Tropical Intraseasonal Oscillations

2020 ◽  
Vol 33 (3) ◽  
pp. 805-823 ◽  
Author(s):  
Shuguang Wang
Keyword(s):  
Real Time ◽  
Decadal Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Eof Analysis ◽  
Intraseasonal Oscillations ◽  
Precipitation Anomalies ◽  
Tropical Intraseasonal Oscillations

AbstractCharacteristic patterns of precipitation-associated tropical intraseasonal oscillations, including the Madden–Julian oscillation (MJO) and boreal summer intraseasonal oscillation (BSISO), are identified using local empirical orthogonal function (EOF) analysis of the Tropical Rainfall Measuring Mission (TRMM) precipitation data as a function of the day of the year. The explained variances of the EOF analysis show two peaks across the year: one in the middle of the boreal winter corresponding to the MJO and the other in the middle of summer corresponding to the BSISO. Comparing the fractional variance indicates that the BSISO is more coherent than the MJO during the TRMM period. Similar EOF analyses with the outgoing longwave radiation (OLR) confirm this result and indicate that the BSISO is less coherent before the TRMM era (1979–98). In contrast, the MJO exhibits much less decadal variability. A precipitation-based index for tropical intraseasonal oscillation (PII) is derived by projecting bandpass-filtered precipitation anomalies to the two leading EOFs as a function of day of the year. A real-time version that approximates the PII is further developed using precipitation anomalies without any bandpass filtering. It is further shown that this real-time PII index may be used to diagnose precipitation in the subseasonal forecasts.

Initiation and termination of intraseasonal oscillations in nonlinear Laplacian spectral analysis-based indices

2016 ◽  
Vol 2 (1) ◽  
Author(s):  
Eniko Székely ◽  
Dimitrios Giannakis ◽  
Andrew J. Majda
Keyword(s):  
Spectral Analysis ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Time Interval ◽  
Dimensional Phase Space ◽  
Intraseasonal Oscillations ◽  
The Indian Ocean ◽  
Gaussian Statistics ◽  
Non Gaussian ◽  
Infrared Brightness

AbstractWe present a statistical analysis of the initiation and termination of boreal winter and boreal summer intraseasonal oscillations (ISOs). This study uses purely convection (infrared brightness temperature) data over a 23-year time interval from 1984–2006. The indices are constructed via the nonlinear Laplacian spectral analysis (NLSA) method and display high intermittency and non-Gaussian statistics. We first define primary, terminal, and full events in the NLSA-based indices, and then examine their statistics through the associated two-dimensional phase space representations. Roughly one full event per year was detected for the Madden-Julian oscillation (MJO), and 1.3 full events per year for the boreal summer ISO.We also find that 91%of the recovered full MJO events are circumnavigating and exhibit very little to no retrograde (westward) propagation. The Indian Ocean emerges as the most active region in terms of both the onset and decay of events, however relevant activity occurs over all phases, consistent with previous work.

scholarly journals Estimate of the Predictability of Boreal Summer and Winter Intraseasonal Oscillations from Observations

2011 ◽  
Vol 139 (8) ◽  
pp. 2421-2438 ◽  
Author(s):  
Ruiqiang Ding ◽  
Jianping Li ◽  
Kyong-Hwan Seo
Keyword(s):  
Spatial Distribution ◽  
Intraseasonal Variability ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Potential Predictability ◽  
The North ◽  
Intraseasonal Oscillations ◽  
The North Pacific

AbstractTropical intraseasonal variability (TISV) shows two dominant modes: the boreal winter Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO). The two modes differ in intensity, frequency, and movement, thereby presumably indicating different predictabilities. This paper investigates differences in the predictability limits of the BSISO and the boreal winter MJO based on observational data. The results show that the potential predictability limit of the BSISO obtained from bandpass-filtered (30–80 days) outgoing longwave radiation (OLR), 850-hPa winds, and 200-hPa velocity potential is close to 5 weeks, comparable to that of the boreal winter MJO. Despite the similarity between the potential predictability limits of the BSISO and MJO, the spatial distribution of the potential predictability limit of the TISV during summer is very different from that during winter. During summer, the limit is relatively low over regions where the TISV is most active, whereas it is relatively high over the North Pacific, North Atlantic, southern Africa, and South America. The spatial distribution of the limit during winter is approximately the opposite of that during summer. For strong phases of ISO convection, the initial error of the BSISO shows a more rapid growth than that of the MJO. The error growth is rapid when the BSISO and MJO enter the decaying phase (when ISO signals are weak), whereas it is slow when convection anomalies of the BSISO and MJO are located in upstream regions (when ISO signals are strong).

The Potential Roles of Background Surface Wind in the SST Variability Associated with Intraseasonal Oscillations

2014 ◽  
Vol 27 (18) ◽  
pp. 7053-7068 ◽  
Author(s):  
Kaya Kanemaru ◽  
Hirohiko Masunaga
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Heat Budget ◽  
Surface Wind ◽  
Boreal Summer ◽  
Boreal Winter ◽  
Westerly Wind ◽  
Sst Variability ◽  
Intraseasonal Oscillations

Abstract The current study is aimed at exploring the potential roles of the seasonally altering background surface wind in the seasonality of the intraseasonal oscillations (ISOs) with a focus on the sea surface temperature (SST) variability. A composite analysis of the ocean mixed layer heat budget in term of ISO phases with various satellite data is performed for boreal winter and summer. The scalar wind is found to be a dominant factor that accounts for the ocean surface heat budget, implying that the background surface wind as well as its anomaly is important for the SST variability. An easterly anomaly to the east of convection diminishes scalar wind, and thus latent heat flux, when superposed onto a background westerly wind, implying that the presence of basic westerly wind is important for the development of a warm SST anomaly ahead of the ISO convection. On the other hand, an easterly anomaly in combination with basic easterly wind magnifies scalar wind and latent heat flux and cancels out the shortwave heat flux anomaly. The seasonal migration of the background westerly wind, which is confined to a southern equatorial belt in boreal winter but spread across the northern Indian Ocean in boreal summer, may offer a mechanism that partly accounts for the seasonal characteristics of ISO propagation. The northward propagation of the SST variability associated with the boreal summer ISO is found to also involve a similar mechanism with the meridional wind modulation of scalar wind.

scholarly journals Dynamics of the Intraseasonal Oscillations in the Indian Ocean South Equatorial Current

2008 ◽  
Vol 38 (1) ◽  
pp. 121-132 ◽  
Author(s):  
Lei Zhou ◽  
Raghu Murtugudde ◽  
Markus Jochum
Keyword(s):  
Indian Ocean ◽  
Baroclinic Instability ◽  
Phase Speed ◽  
Boreal Winter ◽  
Temporal Features ◽  
Intraseasonal Oscillations ◽  
Main Driver ◽  
The Indian Ocean ◽  
Equatorial Current ◽  
Southwestern Indian Ocean

Abstract The spatial and temporal features of intraseasonal oscillations in the southwestern Indian Ocean are studied by analyzing model simulations for the Indo-Pacific region. The intraseasonal oscillations have periods of 40–80 days with a wavelength of ∼650 km. They originate from the southeastern Indian Ocean and propagate westward as Rossby waves with a phase speed of ∼25 cm s−1 in boreal winter and spring. The baroclinic instability is the main driver for these intraseasonal oscillations. The first baroclinic mode dominates during most of the year, but during boreal winter and spring the second mode contributes significantly and often equally. Consequently, the intraseasonal oscillations are relatively strong in boreal winter and spring. Whether the atmospheric intraseasonal oscillations are also important for forcing the oceanic intraseasonal oscillations in the southwestern Indian Ocean needs further investigation.

Surface and Subsurface Signatures of Monsoon Intraseasonal Oscillations from Moored Buoys Observation in the Bay of Bengal

2021 ◽  
pp. 101240
Author(s):  
Debi Prasad Bhuyan ◽  
Samiran Mandal ◽  
Arkaprava Ray ◽  
Sourav Sil ◽  
R. Venkatesan
Keyword(s):  
Bay Of Bengal ◽  
Intraseasonal Oscillations

scholarly journals Remote Sensing of Snow Cover Variability and Its Influence on the Runoff of Sápmi’s Rivers

Geosciences ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 130
Author(s):  
Sebastian Rößler ◽  
Marius S. Witt ◽  
Jaakko Ikonen ◽  
Ian A. Brown ◽  
Andreas J. Dietz
Keyword(s):  
Remote Sensing ◽  
Snow Cover ◽  
Air Temperature ◽  
Kendall Test ◽  
The Arctic ◽  
Boreal Winter ◽  
Snowmelt Runoff ◽  
River Catchment ◽  
Catchment Areas ◽  
Runoff Model

The boreal winter 2019/2020 was very irregular in Europe. While there was very little snow in Central Europe, the opposite was the case in northern Fenno-Scandia, particularly in the Arctic. The snow cover was more persistent here and its rapid melting led to flooding in many places. Since the last severe spring floods occurred in the region in 2018, this raises the question of whether more frequent occurrences can be expected in the future. To assess the variability of snowmelt related flooding we used snow cover maps (derived from the DLR’s Global SnowPack MODIS snow product) and freely available data on runoff, precipitation, and air temperature in eight unregulated river catchment areas. A trend analysis (Mann-Kendall test) was carried out to assess the development of the parameters, and the interdependencies of the parameters were examined with a correlation analysis. Finally, a simple snowmelt runoff model was tested for its applicability to this region. We noticed an extraordinary variability in the duration of snow cover. If this extends well into spring, rapid air temperature increases leads to enhanced thawing. According to the last flood years 2005, 2010, 2018, and 2020, we were able to differentiate between four synoptic flood types based on their special hydrometeorological and snow situation and simulate them with the snowmelt runoff model (SRM).

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