Sampling Errors in the Estimation of Empirical Orthogonal Functions

North, Gerald R.; Bell, Thomas L.; Cahalan, Robert F.; Moeng, Fanthune J.

doi:10.1175/1520-0493(1982)110<0699:seiteo>2.0.co;2

Cited by 2,967 publications

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“…7, top), and these are well separated according to the criterion of North et al (1982). The first mode explains 49% of the total variance and reveals a basin-coherent variation in mass.…”

Section: Spatial and Temporal Variations Of Arctic Obpmentioning

confidence: 93%

Arctic Ocean Circulation Patterns Revealed by GRACE

et al. 2014

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Measurements of ocean bottom pressure (OBP) anomalies from the satellite mission Gravity Recovery and Climate Experiment (GRACE), complemented by information from two ocean models, are used to investigate the variations and distribution of the Arctic Ocean mass from 2002 through 2011. The forcing and dynamics associated with the observed OBP changes are explored. Major findings are the identification of three primary temporal-spatial modes of OBP variability at monthly-to-interannual time scales with the following characteristics. Mode 1 (50% of the variance) is a wintertime basin-coherent Arctic mass change forced by southerly winds through Fram Strait, and to a lesser extent through Bering Strait. These winds generate northward geostrophic current anomalies that increase the mass in the Arctic Ocean. Mode 2 (20%) reveals a mass change along the Siberian shelves, driven by surface Ekman transport and associated with the Arctic Oscillation. Mode 3 (10%) reveals a mass dipole, with mass decreasing in the Chukchi, East Siberian, and Laptev Seas, and mass increasing in the Barents and Kara Seas. During the summer, the mass decrease on the East Siberian shelves is due to the basin-scale anticyclonic atmospheric circulation that removes mass from the shelves via Ekman transport. During the winter, the forcing mechanisms include a large-scale cyclonic atmospheric circulation in the eastern-central Arctic that produces mass divergence into the Canada Basin and the Barents Sea. In addition, strengthening of the Beaufort high tends to remove mass from the East Siberian and Chukchi Seas. Supporting previous modeling results, the month-to-month variability in OBP associated with each mode is predominantly of barotropic character.

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“…7, top), and these are well separated according to the criterion of North et al (1982). The first mode explains 49% of the total variance and reveals a basin-coherent variation in mass.…”

Section: Spatial and Temporal Variations Of Arctic Obpmentioning

confidence: 93%

Arctic Ocean Circulation Patterns Revealed by GRACE

et al. 2014

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“…The detailed procedure can be found in Wang (1992), Wang et al (2008) and Sun et al (2010). Figure 1 shows the first mode (PJ-mode) associated with the EASM, which explains 20.1% of the variance of zonal wind and meridional wind at 850 and 200 hPa in the EASM region and is significantly distinguished from the higher EOF modes according to North et al (1982). As expected, the spatial pattern of the PJ-mode strongly resembles the PJ pattern discussed by Nitta (1987) in both lower and upper troposphere.…”

Section: Methodsmentioning

confidence: 94%

Impact of the MJO on the interannual variation of the Pacific–Japan mode of the East Asian summer monsoon

Gollan

Greatbatch

et al. 2018

Clim Dyn

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The spatial pattern of the first mode of interannual variability associated with the East Asian summer monsoon (EASM), obtained from a multivariate Empirical Orthogonal Functions (MV-EOF) analysis, corresponds to the Pacific-Japan (PJ) pattern and is referred to as the PJ-mode. The present study investigates the interannual variation of the PJ-mode from the perspective of the intraseasonal timescale. In particular, the impact of the Madden-Julian oscillation (MJO) on the interannual variation of the PJ-mode is investigated. The results show that the MJO has a significant influence on the interannual variation of the PJ-mode mainly in the lower troposphere (850 hPa) and that the former accounts for approximately 11% of the amplitude of the latter. The major part of the contribution comes from a change in frequency of the different phases of the MJO, especially that of MJO phase 6. This suggests that intraseasonal variation of the convection anomalies over the tropical eastern Indian and western Pacific Oceans plays an important role in the interannual variation of the PJ-mode. In addition, MJO phase 7 also contributes to the interannual variability of the PJ-mode, in this case induced by both the change in frequency and the change in circulation anomalies associated with MJO phase 7.

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“…According to the rule given by North et al [42], the first two leading modes are statistically distinguished from the higher mode. Therefore, we use the first two EOF modes to learn about the spatial structure of the summer climate.…”

Section: Spatial Structures Of Temperature and Precipitation And Theimentioning

confidence: 91%

Simulated analysis of summer climate on centennial time scale in eastern China during the last millennium

et al. 2011

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Using Lanczos filtered simulation results from the ECHO-G coupled ocean-atmosphere model, this study analyzes the spatiotemporal structure of temperature and precipitation on centennial time scale to examine how climate change in eastern China responded to external forcing during the last millennium. The conclusions are (1) eastern China experienced a warm-cold-warm climate transition, and the transition from the warm period to the cold period was slower than the cold to warm transition which followed it. There was more rainfall in the warm periods, and the transitional peak and valley of precipitation lag those of temperature. The effective solar radiation and solar irradiance have significant impacts on the temporal variation of both temperature and precipitation. Volcanic activity plays an important role in the sudden drop of temperature before the Present Warm Period (PWP). There is a positive correlation between precipitation and volcanic activity before 1400 A.D., and a negative relationship between the two thereafter. The concentration of greenhouse gases increases in the PWP, and the temperature and precipitation increase accordingly. (2) The spatial pattern of the first leading empirical orthogonal function (EOF) mode of temperature on centennial time scale is consistent with that on the inter-annual/inter-decadal (IA-ID) time scales; namely, the entirety of eastern China is of the same sign. This pattern has good coherence with effective solar radiation and the concentrations of greenhouse gases. The first leading EOF mode of precipitation on centennial time scale is totally different from that on the IA-ID time scales. The first leading mode of centennial time scale changes consistently over the entirety of eastern China, while the middle and lower reaches of the Yangtze and Yellow Rivers are the opposite to the rest of eastern China is the leading spatial pattern on IA-ID time scale. The distribution of precipitation on centennial time scale is affected by solar irradiance and greenhouse gas concentrations.

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Sampling Errors in the Estimation of Empirical Orthogonal Functions

Cited by 2,967 publications

References 0 publications

Arctic Ocean Circulation Patterns Revealed by GRACE

Arctic Ocean Circulation Patterns Revealed by GRACE

Impact of the MJO on the interannual variation of the Pacific–Japan mode of the East Asian summer monsoon

Simulated analysis of summer climate on centennial time scale in eastern China during the last millennium

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