scholarly journals The Leading Pattern of Intraseasonal and Interannual Indian Ocean Precipitation Variability and Its Relationship with Asian Circulation during the Boreal Cold Season

2012 ◽  
Vol 25 (21) ◽  
pp. 7509-7526 ◽  
Author(s):  
Andrew Hoell ◽  
Mathew Barlow ◽  
Roop Saini
Keyword(s):  
Indian Ocean ◽  
Time Scales ◽  
Southern Oscillation ◽  
Function Analysis ◽  
Intraseasonal Variability ◽  
Longwave Radiation ◽  
Severe Drought ◽  
Monthly Precipitation ◽  
Southwest Asia ◽  
The Mean

The leading pattern of precipitation for the Indian Ocean, one of the most intense areas of rainfall on the globe, is calculated for November–April 1979–2008. The associated regional circulation and thermodynamic forcing of precipitation over Asia are examined at both intraseasonal and interannual time scales. The leading pattern is determined using both empirical orthogonal function analysis of monthly precipitation data and a closely related index of daily outgoing longwave radiation filtered into intraseasonal (33–105 days) and interannual (greater than 105 days) components. The leading pattern has a maximum in the tropical eastern Indian Ocean, and is closely associated with the Madden–Julian oscillation at intraseasonal time scales and related to the El Niño–Southern Oscillation at interannual time scales. Both time scales are associated with baroclinic Gill–Matsuno-like circulation responses extending over southern Asia, but the interannual component also has a strong equivalent barotropic circulation. Thermodynamically, both time scales are associated with cold temperature advection and subsidence over southwest Asia, with advection of the mean temperature by the anomalous wind more important at lower and midlevels and advection of the anomalous temperature by the mean wind more important at upper levels. For individual months, the intraseasonal variability can overwhelm the interannual variability. Enhanced Indian Ocean convection persisted for almost the entire 2007/08 season in association with severe drought over southwest Asia, but a strong intraseasonal signal in January 2008 reversed the pattern, resulting in damaging floods in the midst of drought.

Indian Ocean mediates the ENSO teleconnections to the Central Southwest Asia during the wet season 

2021 ◽  
Author(s):  
Muhammad Adnan Abid ◽  
Moetasim Ashfaq ◽  
Fred Kucharski ◽  
Katherine J. Evans ◽  
Mansour Almazroui
Keyword(s):  
Indian Ocean ◽  
Rossby Wave ◽  
Southern Oscillation ◽  
Intraseasonal Variability ◽  
Tropical Indian Ocean ◽  
Polar Regions ◽  
Southwest Asia ◽  
Wet Season ◽  
Enso Teleconnections ◽  
Hydroclimate Variability

<p>Central Southwest Asia (CSWA) is a region with the largest number of glaciers, outside the polar regions in its northeast and the Arabian desert to its southwest. The region receives precipitation from November to April period also known as the wet season, which contributes to the regional freshwater resources. Mainly, El Niño–Southern Oscillation (ENSO) modulates the wet season precipitation over CSWA, with a positive relationship. However, the intraseasonal characteristics of ENSO influence are largely unknown, which may be important to understand the regional sub-seasonal to seasonal hydroclimate variability. We noted that the ENSO‐CSWA teleconnection varies intraseasonally and is a combination of direct and indirect positive influences. The ENSO direct influence is through a Rossby wave‐like pattern in the tail months of the wet season, while the indirect influence is noted through an ENSO‐forced atmospheric dipole of diabatic heating anomalies in the tropical Indian Ocean (TIO), which also generates a Rossby wave‐like forcing and persists throughout the wet season. The stronger ENSO influence is found when both direct and indirect modes are in phase, while the relationship breaks down when the two modes are out of phase. Moreover, the idealized numerical simulations confirm and reproduce the observed circulation patterns. This suggests that improvements in sub-seasonal to seasonal scale predictability requires the better representation of intraseasonal variability of ENSO teleconnection, as well as the role of interbasin interactions in its propagation.</p>

The Role of Intraseasonal Variability in the Nature of Asian Monsoon Precipitation

2007 ◽  
Vol 20 (17) ◽  
pp. 4402-4424 ◽  
Author(s):  
Carlos D. Hoyos ◽  
Peter J. Webster
Keyword(s):  
Indian Ocean ◽  
Time Scales ◽  
Temporal Variability ◽  
Asian Monsoon ◽  
Monsoon Rainfall ◽  
Mountain Range ◽  
Monsoon Precipitation ◽  
The West ◽  
The Mean ◽  
Rainfall Estimates

Abstract The structure of the mean precipitation of the south Asian monsoon is spatially complex. Embedded in a broad precipitation maximum extending eastward from 70°E to the northwest tropical Pacific Ocean are strong local maxima to the west of the Western Ghats mountain range of India, in Cambodia extending into the eastern China Sea, and over the eastern tropical Indian Ocean and the Bay of Bengal (BoB), where the strongest large-scale global maximum in precipitation is located. In general, the maximum precipitation occurs over the oceans and not over the land regions. Distinct temporal variability also exists with time scales ranging from days to decades. Neither the spatial nor temporal variability of the monsoon can be explained simply as the response to the cross-equatorial pressure gradient force between the continental regions of Asia and the oceans of the Southern Hemisphere, as suggested in classical descriptions of the monsoon. Monthly (1979–2005) and daily (1997–present) rainfall estimates from the Global Precipitation Climatology Project (GPCP), 3-hourly (1998–present) rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI) estimates of sea surface temperature (SST), reanalysis products, and satellite-determined outgoing longwave radiation (OLR) data were used as the basis of a detailed diagnostic study to explore the physical basis of the spatial and temporal nature of monsoon precipitation. Propagation characteristics of the monsoon intraseasonal oscillations (MISOs) and biweekly signals from the South China Sea, coupled with local and regional effects of orography and land–atmosphere feedbacks are found to modulate and determine the locations of the mean precipitation patterns. Long-term variability is found to be associated with remote climate forcing from phenomena such as El Niño–Southern Oscillation (ENSO), but with an impact that changes interdecadally, producing incoherent responses of regional rainfall. A proportion of the interannual modulation of monsoon rainfall is found to be the direct result of the cumulative effect of rainfall variability on intraseasonal (25–80 day) time scales over the Indian Ocean. MISOs are shown to be the main modulator of weather events and encompass most synoptic activity. Composite analysis shows that the cyclonic system associated with the northward propagation of a MISO event from the equatorial Indian Ocean tends to drive moist air toward the Burma mountain range and, in so doing, enhances rainfall considerably in the northeast corner of the bay, explaining much of the observed summer maximum oriented parallel to the mountains. Similar interplay occurs to the west of the Ghats. While orography does not seem to play a defining role in MISO evolution in any part of the basin, it directly influences the cumulative MISO-associated rainfall, thus defining the observed mean seasonal pattern. This is an important conclusion since it suggests that in order for the climate models to reproduce the observed seasonal monsoon rainfall structure, MISO activity needs to be well simulated and sharp mountain ranges well represented.

A Model-Based Assessment and Design of a Tropical Indian Ocean Mooring Array

2007 ◽  
Vol 20 (13) ◽  
pp. 3269-3283 ◽  
Author(s):  
Peter R. Oke ◽  
Andreas Schiller
Keyword(s):  
Indian Ocean ◽  
Interannual Variability ◽  
Time Scales ◽  
Ocean Circulation ◽  
Mixed Layer Depth ◽  
Intraseasonal Variability ◽  
Circulation Model ◽  
Tropical Indian Ocean ◽  
Empirical Orthogonal Functions ◽  
Analysis System

Abstract A series of observing system simulation experiments (OSSEs) are performed for the tropical Indian Ocean (±15° from the equator) using a simple analysis system. The analysis system projects an array of observations onto the dominant empirical orthogonal functions (EOFs) derived from an intermediate-resolution (2° × 0.5°) ocean circulation model. This system produces maps of the depth of the 20°C isotherm (D20), representing interannual variability, and the high-pass-filtered mixed layer depth (MLD), representing intraseasonal variability. The OSSEs are designed to assess the suitability of the proposed Indian Ocean surface mooring array for resolving intraseasonal to interannual variability. While the proposed array does a reasonable job of resolving the interannual time scales, it may not adequately resolve the intraseasonal time scales. A procedure is developed to rank the importance of observation locations by determining the observation array that best projects onto the EOFs used in the analysis system. OSSEs using an optimal array clearly outperform the OSSEs using the proposed array. The configuration of the optimal array is sensitive to the number of EOFs considered. The optimal array is also different for D20 and MLD, and depends on whether fixed observations are included that represent an idealized Argo array. Therefore, a relative frequency map of observation locations identified in 24 different OSSEs is compiled and a single, albeit less optimal, array that is referred to as a consolidated array is objectively determined. The consolidated array reflects the general features of the individual optimal arrays derived from all OSSEs. It is found that, in general, observations south of 8°S and off of the Indonesian coast are most important for resolving the interannual variability, while observations a few degrees south of the equator, and west of 75°E, and a few degrees north of the equator, and east of 75°E, are important for resolving the intraseasonal variability. In a series of OSSEs, the consolidated array is shown to outperform the proposed array for all configurations of the analysis system for both D20 and MLD.

scholarly journals Enhanced MJO-like Variability at High SST

2013 ◽  
Vol 26 (3) ◽  
pp. 988-1001 ◽  
Author(s):  
Nathan P. Arnold ◽  
Zhiming Kuang ◽  
Eli Tziperman
Keyword(s):  
Intraseasonal Variability ◽  
Lower Troposphere ◽  
Longwave Radiation ◽  
Positive Contribution ◽  
Physical Processes ◽  
Tropical Variability ◽  
Community Atmosphere Model ◽  
The Mean ◽  
Static Energy ◽  
The Relationship

Abstract The authors report a significant increase in Madden–Julian oscillation (MJO)–like variability in a superparameterized version of the NCAR Community Atmosphere Model run with high sea surface temperatures (SSTs). A series of aquaplanet simulations exhibit a tripling of intraseasonal outgoing longwave radiation variance as equatorial SST is increased from 26° to 35°C. The simulated intraseasonal variability also transitions from an episodic phenomenon to one with a semiregular period of 25 days. Moist static energy (MSE) budgets of composite MJO events are used to diagnose the physical processes responsible for the relationship with SST. This analysis points to an increasingly positive contribution from vertical advection, associated in part with a steepening of the mean vertical MSE profile in the lower troposphere. The change in MSE profile is a natural consequence of increasing SST while maintaining a moist adiabat with a fixed profile of relative humidity. This work has implications for tropical variability in past warm climates as well as anthropogenic global warming scenarios.

scholarly journals Intraseasonal and Seasonal-to-Interannual Indian Ocean Convection and Hemispheric Teleconnections

2013 ◽  
Vol 26 (22) ◽  
pp. 8850-8867 ◽  
Author(s):  
Andrew Hoell ◽  
Mathew Barlow ◽  
Roop Saini
Keyword(s):  
Indian Ocean ◽  
Ray Tracing ◽  
Northern Hemisphere ◽  
Southern Oscillation ◽  
Longwave Radiation ◽  
Teleconnection Pattern ◽  
Western Pacific ◽  
Wave Ray ◽  
The Indian Ocean ◽  
Ocean Convection

Abstract Deep tropical convection over the Indian Ocean leads to intense diabatic heating, a main driver of the climate system. The Northern Hemisphere circulation and precipitation associated with intraseasonal and seasonal-to-interannual components of the leading pattern of Indian Ocean convection are investigated for November–April 1979–2008. The leading pattern of Indian Ocean convection is separated into intraseasonal and seasonal-to-interannual components by filtering an index of outgoing longwave radiation at 33–105 days and greater than 105 days, yielding Madden–Julian oscillation (MJO)- and El Niño–Southern Oscillation (ENSO)-influenced patterns, respectively. Observations and barotropic Rossby wave ray tracing experiments suggest that Indian Ocean convection can influence the ENSO-related hemispheric teleconnection pattern in addition to the regional Asian teleconnection. Equivalent barotropic circulation anomalies throughout the Northern Hemisphere subtropics are associated with both seasonal-to-interannual Indian Ocean convection and ENSO. The hemispheric teleconnection associated with seasonal-to-interannual Indian Ocean convection is investigated with ray tracing, which suggests that forcing over the Indian Ocean can propagate eastward across the hemisphere and back to Asia. The relationship between the seasonal-to-interannual component of Indian Ocean convection and ENSO is investigated in terms of a gradient in sea surface temperatures (SST) over the equatorial western Pacific Ocean. When the western Pacific SST gradient is strong during ENSO, strong Maritime Continent precipitation extends further westward into the Indian Ocean, which is accompanied by enhanced tropospheric Asian circulation, similar to the seasonal-to-interannual component of Indian Ocean convection. Analysis of the three strongest interannual convection seasons shows that the strong Indian Ocean pattern of ENSO can dominate individual seasons.

scholarly journals Contributing Factors to Spatiotemporal Variations of Outgoing Longwave Radiation (OLR) in the Tropics

2019 ◽  
Vol 32 (15) ◽  
pp. 4621-4640
Author(s):  
Faiz R. Fajary ◽  
Tri W. Hadi ◽  
Shigeo Yoden
Keyword(s):  
Indian Ocean ◽  
Wavelet Transforms ◽  
Outgoing Longwave Radiation ◽  
Southern Oscillation ◽  
Linear Trend ◽  
Longwave Radiation ◽  
Spatiotemporal Variations ◽  
Contributing Factors ◽  
Quasi Biennial Oscillation ◽  
The Indian Ocean

Abstract Factors governing spatiotemporal variations of the daily outgoing longwave radiation (OLR) are studied using 35-yr (1979–2013) data records by employing multiple linear regression, wavelet transforms, and bandpass filtering methods. From the regression coefficients of nine predictors and the explained variances, we found that the largest contributions to OLR variability are associated with the Madden–Julian oscillation and El Niño–Southern Oscillation (ENSO). The ENSO signatures on OLR show dipole patterns over the Maritime Continent (MC) and Pacific regions with an extension to the Atlantic. Subsequently, the third significant contribution of the Indian Ocean dipole is confined to the Indian Ocean and Africa. Then, the solar cycle and stratospheric aerosols show mainly negative correlations, while a positive linear trend is observed mainly in the Northern Hemisphere. Lastly, factors associated with the stratospheric quasi-biennial oscillation (QBO) are the least significant contributor to OLR. In terms of oscillatory signals, time–longitude variations of the annual cycle (AC) show pairs of contrasting phases that characterize monsoon systems, in which the MC and Pacific regions are found to be in the same phase group. The most consistent AC signals are found to correspond with North and South American monsoons that respectively exhibit weakening and strengthening trends. Wavelet spectra and filtered OLR signals in intraseasonal oscillation, QBO, and ENSO frequency bands show an interdependent relationship that largely varies with time scale and longitudes.

scholarly journals Strong Intraseasonal Variability of Meridional Currents near 5°N in the Eastern Indian Ocean: Characteristics and Causes

2017 ◽  
Vol 47 (5) ◽  
pp. 979-998 ◽  
Author(s):  
Gengxin Chen ◽  
Weiqing Han ◽  
Yuanlong Li ◽  
Michael J. McPhaden ◽  
Ju Chen ◽  
...  
Keyword(s):  
Indian Ocean ◽  
Rossby Waves ◽  
Intraseasonal Variability ◽  
Upper Ocean ◽  
Mean Flow ◽  
Eastern Boundary ◽  
Typical Period ◽  
The Indian Ocean ◽  
The Mean

AbstractThis paper reports on strong, intraseasonal, upper-ocean meridional currents observed in the Indian Ocean between the Bay of Bengal (BOB) and the equator and elucidates the underlying physical processes responsible for them. In situ measurements from a subsurface mooring at 5°N, 90.5°E reveal strong intraseasonal variability of the meridional current with an amplitude of ~0.4 m s−1 and a typical period of 30–50 days in the upper 150 m, which by far exceeds the magnitudes of the mean flow and seasonal cycle. Such prominent intraseasonal variability is, however, not seen in zonal current at the same location. Further analysis suggests that the observed intraseasonal flows are closely associated with westward-propagating eddylike sea surface height anomalies (SSHAs) along 5°N. The eddylike SSHAs are largely manifestations of symmetric Rossby waves, which result primarily from intraseasonal wind stress forcing in the equatorial waveguide and reflection of the equatorial Kelvin waves at the eastern boundary. Since the wave signals are generally symmetric about the equator, similar variability is also seen at 5°S but with weaker intensity because of the inclined coastline at the eastern boundary. The Rossby waves propagate westward, causing pronounced intraseasonal SSHA and meridional current in the upper ocean across the entire southern BOB between 84° and 94°E. They greatly weaken in the western Indian Basin, but zonal currents near the equator remain relatively strong.

HHT ANALYSIS OF THE GLOBAL AVERAGE MONTHLY PRECIPITATION DATA

2012 ◽  
Vol 04 (03) ◽  
pp. 1250018 ◽  
Author(s):  
SAMUEL S. P. SHEN ◽  
DAVID NEW ◽  
THOMAS M. SMITH ◽  
PHILLIP A. ARKIN
Keyword(s):  
Time Series ◽  
Annual Cycle ◽  
Climate Models ◽  
Southern Oscillation ◽  
Frequency Variation ◽  
Frequency Change ◽  
Monthly Precipitation ◽  
Precipitation Time Series ◽  
Time Frequency ◽  
The Mean

This paper uses the Hilbert–Huang transform (HHT) method to make time–frequency diagnostic analyses of four monthly time series of the global precipitation: MERG (1900–2008), REOF (1900–2008), GPCP (1979–2009), and CMAP (1979–2009). All these data are the global land and ocean average of precipitation anomalies with respect to the mean of the entire data period. The MERG and REOF are spectral reconstructions based on historical data. The GPCP and CMAP are based on station gauge data and satellite remote sensing data. We have made the following analysis of the four datasets: (a) extract intrinsic mode functions (IMF) by HHT empirical model decomposition (EMD) sifting, (b) calculate the mean frequency and energy of each IMF, (c) calculate the Fourier spectra to compare with the IMF spectral properties, (d) calculate the Hilbert spectra and display the time–frequency variation of the precipitation time series, and (e) calculate the basic statistics of the four datasets, including mean, standard deviation, skewness, kurtosis and inter-correlation among the datasets. Our analysis results indicate the following: (i) IMFs may contain physical signals of MJO (Madden–Julian oscillation), monsoon, annual cycle, and ENSO (El Nino southern oscillation), (ii) Hilbert spectra appears to be an effective tool to display the time-frequency change of a precipitation time series and can help identify critical characteristics for improving data aggregation method and climate models, (iii) among the four datasets, MERG is the smoothest data and has the smallest variance and hence the smallest IMF energies, while the CMAP has the largest, followed by GPCP and REOF, and (iv) the nonlinear and nonstationary annual cycle is the IMF3 for all the four datasets, which is modulated by ENSO signals.

Interdecadal Change in the Relationship between ENSO and the Intraseasonal Oscillation in East Asia

2010 ◽  
Vol 23 (13) ◽  
pp. 3599-3612 ◽  
Author(s):  
Kyung-Sook Yun ◽  
Kyong-Hwan Seo ◽  
Kyung-Ja Ha
Keyword(s):  
Indian Ocean ◽  
North Pacific ◽  
Southern Oscillation ◽  
Asian Summer Monsoon ◽  
Intraseasonal Oscillation ◽  
Longwave Radiation ◽  
Strong Relationship ◽  
Early Summer ◽  
Boreal Summer ◽  
Interdecadal Change

Abstract The northward-propagating intraseasonal oscillation (NPISO) during the boreal summer is closely linked to the onset/retreat and intensity of the East Asian summer monsoon (EASM). In this study, interdecadal variability in the relationships between the NPISO and El Niño–Southern Oscillation (ENSO) was investigated using long-term outgoing longwave radiation data obtained from the 40-yr ECMWF Re-Analysis (ERA-40) for a 44-yr period (1958 to 2001). It was found that before the late 1970s, the preceding winter ENSO influenced the early summer (i.e., May to June) NPISO activity, whereas after the late 1970s a strong relationship appeared during the later summertime (i.e., July to August). The May–June NPISO before the late 1970s was modulated by springtime Indian Ocean sea surface temperature warming and central North Pacific suppressed convection anomalies and was consequently related to the ENSO-induced west Pacific (WP) pattern, which shows a north–south dipole structure over the North Pacific from winter through spring. After the late 1970s, because of an anomalously strengthened Walker–Hadley circulation, Indian Ocean SST warming was significantly maintained until summer, which promoted a strong suppressed convection anomaly over the Philippine Sea during summer and consequently an enhanced western North Pacific subtropical high and Pacific–Japan (PJ) pattern.

scholarly journals A multi-year short-range hindcast experiment for evaluating climate model moist processes from diurnal to interannual time scales

2020 ◽  
Author(s):  
Hsi-Yen Ma ◽  
Chen Zhou ◽  
Yunyan Zhang ◽  
Stephen A. Klein ◽  
Mark D. Zelinka ◽  
...  
Keyword(s):  
Time Scales ◽  
Short Range ◽  
Large Scale ◽  
Climate Models ◽  
Climate Model ◽  
Southern Oscillation ◽  
Model Errors ◽  
Moist Processes ◽  
The Mean ◽  
Mean State

Abstract. We present a multi-year short-range hindcast experiment and its experiment procedure for better evaluating both the mean state and variability of atmospheric moist processes in climate models from diurnal to interannual time scales to facilitate model development. We use the Community Earth System Model version 1 as the based model and performed a suite of 3-day long hindcasts every day starting at 00Z from 1997 to 2012. Three processes – the diurnal cycle of clouds during different cloud regimes over the Central U.S., precipitation and diabatic heating associated with the Madden-Julian Oscillation propagation, and the response of moist processes to sea surface temperature anomalies associated with the El Niño-Southern Oscillation – are evaluated as examples to demonstrate how one can better utilize simulations from this experiment design to gain insights into model errors and their connection to physical parameterizations or large-scale state. This is achieved by comparing the hindcasts with corresponding long-term observations for periods based on different phenomena. These analyses can only be done through this multi-year hindcast approach to establish robust statistics of the processes under well-controlled large-scale environment. Furthermore, comparison of hindcasts to the typical simulations in climate mode with the same model allows one to infer what portion of a model’s climate error directly comes from fast errors in the parameterizations of moist processes. As demonstrated here, model biases in the mean state and variability associated parameterized moist processes usually develop within a few days, and manifest within weeks to affect the simulations of large-scale circulation and ultimately the climate mean state and variability. Therefore, model developers can achieve additional useful understanding of the underlying problems in model physics by conducting a multi-year hindcast experiment.

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