Spectral Coherence and the Statistical Significance of Turbulent Flux Computations

Biltoft, Christopher A.; Pardyjak, Eric R.

doi:10.1175/2008jtecha1141.1

Cited by 21 publications

(19 citation statements)

References 11 publications

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“…Both methods gave similar results, but we show coherence computed via segments as that method maximized the usable portion of each time series. The dotted line indicates the 95 % confidence level following Biltoft and Pardyjak's (2009) coherence significance test (their Eq. 3).…”

Section: Coherence and Phase Relationship Betweenmentioning

confidence: 99%

Analysis of MJO Wind-Flux Feedbacks in the Indian Ocean Using RAMA Buoy Observations

Dellaripa

Maloney

2015

Journal of the Meteorological Society of Japan

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Observations spanning 2004-2012 from two Research Moored Array for African-Asian-Australian Monsoon Analysis and Prediction (RAMA) buoys along the equator in the Indian Ocean are used in conjunction with Tropical Rainfall Measuring Mission (TRMM) to assess the relative importance of surface latent heat fluxes to intraseasonal convection. This work is motivated by previous observational and modeling studies that have suggested the importance of wind-induced surface fluxes to the dynamics of the Madden-Julian Oscillation (MJO).Intraseasonal variability is isolated in two ways: 1) 20-100-day bandpass filtering and 2) using the global real time multivariate MJO index. Linear regression shows latent heat flux anomalies to be between 4 % and 8 % of precipitation anomalies when the two variables are compared using similar Wm −2 energy units. From a moist static energy budget viewpoint, these results confirm the potential of wind-induced latent heat fluxes to aid destabilization of MJO convection. Results derived from using both simple intraseasonal filtering and global MJO indices indicate that precipitation leads latent heat flux on the order of a few days, indicating surface fluxes may be more important for maintenance of deep MJO convection in addition to helping set the MJO's propagation speed. Sensitivity tests using smoothed wind speed or thermodynamics (i.e., air temperature, relative humidity, and sea surface temperature) to compute latent heat flux show wind speed variability explains most of the latent heat flux variability on intraseasonal timescales. A similar conclusion is found via linearization of the latent heat flux formula. Additional analysis shows mesoscale and synoptic scale wind variability have negligible impact on intraseasonal latent heat flux anomalies.

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Section: Coherence and Phase Relationship Betweenmentioning

confidence: 99%

Analysis of MJO Wind-Flux Feedbacks in the Indian Ocean Using RAMA Buoy Observations

Dellaripa

Maloney

2015

Journal of the Meteorological Society of Japan

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“…The number of independent samples is calculated by (Bretherton et al, )

N * = N ([], \frac{1 - r_{x} r_{y}}{1 + r_{x} r_{y}}),

where r x and r y are the lag‐one autocorrelation of x and y . Biltoft and Pardyjak () recommends that the eDOF fall within 10 to 100 for reliable significance testing. By using values nfft = 128 and an overlap of 64, most of the eDOFs fall within 40 to 60, which is in the recommended range.…”

Section: Time Series Processing and Cross‐spectral Analysismentioning

confidence: 99%

“…Significance testing of coherence also follows Biltoft and Pardyjak (). A coherence value is statistically significant at the (1− p )×100 % level if it is greater than the value calculated from

χ_{1 - p} = \frac{2 F_{p}}{eDOF - 2 - 2 F_{p}},

where F p is the value of the F (2,eDOF−2) distribution at 1− p .…”

Section: Time Series Processing and Cross‐spectral Analysismentioning

confidence: 99%

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Role of Latent Heating Vertical Distribution in the Formation of the Tropical Cold Trap

Chang

L’Ecuyer

2019

JGR Atmospheres

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This study examines the role of latent heating (LH) vertical distribution in tropical tropopause layer (TTL) cooling and upper‐tropospheric warming associated with equatorial wave responses using LH from the Tropical Rainfall Measurement Mission and temperature from radio occultation observations. We distinguish the effects of convective and stratiform LH in tropical convection on temperature in the upper troposphere and lower stratosphere. Cross‐spectral analysis of time series of temperature and LH shows that stratiform LH exhibits higher coherence with temperature throughout most of the upper troposphere and lower stratosphere, especially in the equatorial Rossby wave response. Coherence between total LH and temperature tends to increase with the altitude of heating. Highest coherences occur almost exclusively at time scales of the Madden‐Julian Oscillation, suggesting the importance of mesoscale convective activity in TTL cooling and subsequent dehydration processes. These results demonstrate that TTL and upper‐tropospheric temperature perturbations depend on the vertical distribution of LH and that stratiform LH release has strong relationship with the formation of the horseshoe‐shaped cold trap over the Maritime Continent and West Pacific.

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“…Transforming from the time to the frequency domain and computing the squared spectral coherence (CH) provides frequency-stratified results that can be tested for statistical significance using the F-distribution [37]. Coherence, also known as coherency spectrum, or magnitude-squared coherence, is a widely used measure for characterizing linear dependence between two time series and classical books on time series analysis present coherence as "the frequency domain analogue of the autocorrelation function" [38].…”

Section: Estimation Of Coherence Between Enso Index and Lake Level Vamentioning

confidence: 99%

Linkage between Water Level Dynamics and Climate Variability: The Case of Lake Hawassa Hydrology and ENSO Phenomena

Belete

Diekkrüger

Roehrig

2017

Climate

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Lake Hawassa is a topographically closed lake in the Central Main Ethiopian Rift Valley. The water level of this lake has been reported to dramatically rise without falling back to the original level. The cause of this rise is not yet sufficiently investigated and subjected to this study. This study argues that the general variability in the lake level and its resultant rise has significant linkage to the temperature variability at the Pacific Ocean. The linkage between water level dynamics and climate variability was analyzed through the application of diverse statistical techniques. It comprises the Mann-Kendall trend analysis to test monotonic variations over time; sequential regime shift index (RSI) to detect significant shifts in the mean values of time-series records of lake level; and coherence analysis to investigate the linear relationship between ENSO index and records of local hydrology. Despite the multiple rises and falls, the results of the trend analysis revealed that the lake level experienced a significant resultant upward trend with Mann-Kendall τ values of 0.558, 0.629, and 0.545 (at α = 0.05 and p < 0.01%) for monthly maximum, average and minimum values respectively. The sequential regime shift evidenced that most of the significant shifts coincide with the occurrences of ENSO events. Generally, the lake level tends to be high during El Niño and low during La Niña episodes. The typical examples are the coincidence of extreme historical maximum lake level to the strongest El Niño event of the century that occurred in 1997/98 and the lowest lake level record in the year 1975 with a strong La Niña year. The coincidence of climate regime shift in the Pacific Ocean in 1976/77 with an equivalent regime shift in the lake level is an additional confirmation for the possible climate-hydrology linkage. The likely involvement of anthropogenic factors (at least in modifying the effect of climate) is justified by the interplay between the non-trending rainfall and potential evapotranspiration and trending streamflow. The coherence analysis between 492 pairs of monthly step datasets of 3.4ENSO index and lake level changes is also found to have a significant linear relationship over frequencies ranging from 0.13 to 0.14 cycles/month or 1.56 to 1.68 cycles/year. This corresponds to a dominant average periodicity (coincident cycle) of about 7.4 months which is thought to be related to the time span of the two rainy season in the locality.

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Spectral Coherence and the Statistical Significance of Turbulent Flux Computations

Cited by 21 publications

References 11 publications

Analysis of MJO Wind-Flux Feedbacks in the Indian Ocean Using RAMA Buoy Observations

Analysis of MJO Wind-Flux Feedbacks in the Indian Ocean Using RAMA Buoy Observations

Role of Latent Heating Vertical Distribution in the Formation of the Tropical Cold Trap

Linkage between Water Level Dynamics and Climate Variability: The Case of Lake Hawassa Hydrology and ENSO Phenomena

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