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John R. Lanzante

Abstract

The local association between ocean and atmosphere was examined statistically by correlating the anomalous sea surface temperature (SST) gradient and the anomalous geostrophic wind at the 700 mb level using 30 years (1949–78) of monthly data. Under the assumption that anomalous oceanic thermal gradients are transmitted to the lower troposphere via anomalous fluxes of latent and sensible heat, and by applying the thermal wind relationship, a significant positive correlation is expected. This analysis is an extension of earlier work by Harnack and Broccoli and includes results for both the Atlantic and Pacific, for both zonal and meridional components, for lags as well as contemporaneous associations, and includes an examination of spatial variability. The major findings are: 1) the expected association is found in both oceans and for both components, although it is somewhat stronger in the Pacific and when relating the zonal wind to the meridional SST gradient, 2) the best association is found in the zonal band of 35–45°N, although some seasonal variability is experienced in the Pacific, 3) the lag relationships are significant only at zero lag or with atmosphere leading ocean and 4) the effect of the association is enhanced by time averaging (over 3 months).

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John R. Lanzante

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John R. Lanzante

Abstract

A climatological investigation of singularities in the seasonal progression of 5-day means of 700 mb height was undertaken for the region 30–90°N, from 160°E eastward to 0°, for the period 1947–76. A harmonic analysis was performed at each of the 127 gridpoints (10° longitude by 10° latitude spacing) in order to determine the field of deviations (for each 5-day period) between the long-term mean value and the first harmonic value (which represents the smooth seasonal progression of heights). The Students's t-test was applied at each gridpoint to test whether the long-term (population) mean is significantly different from the first harmonic value (i.e., to test if the deviation is zero). The significance of the field of t-statistics for each 5-day period was estimated using a modification of the technique presented by Livezey and Chen (1981).

The results of the analyses described above indicate that the 700 mb height field deviates significantly from the first harmonic during several times of the year. A pattern characterized by height rises centered over Alaska from late December through late January is terminated abruptly by the January thaw. In late February, a regional singularity (manifasted as rapid height rises), perhaps related to the termination of the February minimum in Hawaiian rainfall, is found in the eastern Pacific. The “end of winter” in the eastern North Pacific is heralded by a very rapid northward shift of the westerlies from late February through early March.

During the spring, the rapid rise of heights experienced in most regions is interrupted by a southward advance and strengthening of the westerlies in the eastern Pacific during late May and June. During summer, heights over most of the domain rise to “excessively high” values relative to the first harmonic; the only exception is significantly negative deviations in eastern North America. This phenomenon results in the most deviant 5-day period (29 July–2 August) in terms of percentage of map area (50.1%) having significantly non-zero deviations.

An Indian summer type pattern, characterized by weak positive deviations over most of North America and negative deviations in polar regions, persists from late September through October. This pattern exhibits the greatest persistence, between successive 5-day periods, of all the singularities found.

Examination of the second harmonic of 5-day 700 mb heights suggests the existence of a semi-annual, cast-west oscillation of height in the North Pacific. This phenomenon seems to explain, to a large extent, most of the singularities and irregularities described above. At two of the four extrema are found the “January thaw” and “Indian Summer.” A six-month periodicity in (monthly) North Pacific and sea surface temperature (SST), in phase with the atmospheric oscillation was also found. It is speculated that the apparent association between these two phenomena is due to advection of long-term mean SST's by long-term mean-wind-induced surface currents as proposed by Weare et al. (1976).

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John R. Lanzante

Abstract

Associations between Pacific and Atlantic sea surface temperature (SST) and the 700 mb circulation were studied using 30 years (1949-78) of gridded monthly data. The monthly data were grouped into four (nonstandard) seasons for the analysis. The linear correlation between the two fields (SST and 700 mb heights) was analyzed by finding the eigenvalue solution of the mean product matrix of the cross correlations. This technique, introduced by Prohaska, was modified through the use of a varimax rotation. The result is a set of pairs of patterns (one pattern for each medium) which explains part of the linear correlation between the two fields. The number of significant modes (pairs) was determined by a Monte Carlo simulation.

One well-known atmospheric teleconnections pattern, referred to as the Pacific/North American (PNA) pattern by Wallace and Gutzler, was found in all seasons; however, seasonal differences were noted. During the warm season, the PNA pattern manifests itself as the Great Plains (GP) pattern. The OP pattern results in dry/hot (wet/cool) conditions over much of the central and eastern United States. Another, the Northeast (NE) pattern, has a center along the coast of the eastern United States and can result in dry/cool (wet/warm) weather in the Northeast. Additionally, the North Atlantic Oscillation was identified during both the coldand warm seasons.

In the examination of lag associations, significant relationships in which the atmosphere leads the ocean were found for all seasons (and many modes) in the Pacific, but only for the case of January-March 700 mb heights leading SST (by one to two months) in the Atlantic. In the case of the ocean leading the atmosphere (by one to two months), significant results were found only for Pacific SST leading JanuaryMarch 100 mb heights.

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John R. Lanzante

Abstract

This paper reviews the considerations in evaluating the skill and significance of screening multiple linear regression (SMLR) models. Formulations and procedures are given along with relevant references to prior studies. Topics discussed include predictor selection, serial correlation, artificial skill, true skill, and Monte Carlo significance testing. New results with wide applicability in the assessment of SMLR model skill and significance are presented in graphical form. However, the results are restricted to situations involving predictors which are independent of one another and are serially uncorrelated. The methodology presented is suggested for use in both model evaluation and experimental design.

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John R. Lanzante

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John R. Lanzante

Abstract

The 10–30 day variability of extratropical, cold season (November–March) 700 mb geopotential height data of the Northern Hemisphere was studied through the use of rotated complex principal component (RCPC) analysis. The intramonthly modes (IMMs), which result from RCPC analysis of 36 years of 10–30 day bandpass filtered data, were examined. In order to assess seasonality separate analyses were done for three subseasons within the cold season.

Tests of sensitivity (to the number of eigenvectors rotated) and robustness (to the deletion of part of the sample) were conducted to ensure the stability of the RCPC analysis. A Monte Carlo procedure was used to objectively identify episodes of occurrence. Based on the episodes a sequence of ten composite maps was constructed for each mode to depict the evolution over a typical lifecycle. The significance of these lifecycle composite maps was tested using a Monte Carlo procedure.

The average periods of the IMMs are 16–18 days; almost all occurrences fall in the range 13–22 days. For objectively defined episodes (which occur about 10%–30% of the time) each IMM explains about 30%–45% of the 10–30 day bandpass variance averaged over those gridpoints deemed significant at the 1% level (which cover about 20%–40% of the grid area). Since a number of distinct IMMs were found their collective impact is considerable for intramonthly time scales.

Initial interpretation of RCPC loading maps was difficult due to the superposition of phenomena and non-idealized evolution. Composite maps which depict the evolution of each IMM over a typical lifecycle were found to be invaluable for interpretation.

Three classes of IMMs were found. The first class contains several modes which each involve a high latitude transient disturbance (zonal wavenumber 1 or 2) and an oscillating standing wave. The distinction between the modes is mostly in the location of the standing wave pattern. The wavenumber 1 transient is probably the “16-day wave” or (1,3) Rossby normal mode that has been identified in the atmosphere by others; however, the strong association of these transients with regional standing waves has not previously been documented. It is speculated that regional index cycle-like variations in the winds associated with oscillation of the standing wave may excite the transient component. The second class consists of only one mode, which is to a first approximation, an oscillating dipole concentrated in the Atlantic sector; it is speculated to be the result of a regional, baroclinic zonal index cycle. The third class contains several distinct regional midlatitude wave trains; the two most important are located over Eurasía and North America. In a broad sense, IMMs represent favored “modes of evolution” or “paths through phase space”, which the atmosphere follows on the 10–30 day time scale.

Vertical structures of the IMMs were found to be generally consistent with those of other studies of large-scale atmospheric motions. Vertical tilt was found to be large over the continents (especially central and eastern portions) while over the oceans, the IMMs were found to be nearly equivalent barotropic.

About a third of the IMMs were found to be associated with a particular low frequency state. These states are configured in the form of two well-known atmospheric teleconnection patterns. They are such that weaker than normal midlatitude westerlies occur during episodes of some IMMs.

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John R. Lanzante

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Measurements from radiosonde temperatures have been used in studies that seek to identify the human influence on climate. However, such measurements are known to be contaminated by artificial inhomogeneities introduced by changes in instruments and recording practices that have occurred over time. Some simple diagnostics are used to compare vertical profiles of temperature trends from the observed data with simulations from a GCM driven by several different sets of forcings. Unlike most earlier studies of this type, both raw (i.e., fully contaminated) as well as adjusted observations (i.e., treated to remove some of the contamination) are utilized. The comparisons demonstrate that the effect of observational data adjustment can be as important as the inclusion of some major climate forcings in the model simulations. The effects of major volcanic eruptions critically influence temperature trends, even over a time period nearly four decades in length.

In addition, it is seen that the adjusted data show consistently better agreement than the unadjusted data, with simulations from a climate model for 1959–97. Particularly noteworthy is the fact that the adjustments supply missing warming in the tropical upper troposphere that has been attributed to model error in a number of earlier studies.

Finally, an evaluation of the fidelity of the model’s temperature response to major volcanic eruptions is conducted. Although the major conclusions of this study are unaffected by shortcomings of the simulations, they highlight the fact that even using a fairly long period of record (∼40 yr), any such shortcomings can have an important impact on trends and trend comparisons.

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John R. Lanzante

Abstract

Climate studies often involve comparisons between estimates of some parameter derived from different observed and/or model-generated datasets. It is common practice to present estimates of two or more statistical quantities with error bars about each representing a confidence interval. If the error bars do not overlap, it is presumed that there is a statistically significant difference between them. In general, such a procedure is not valid and usually results in declaring statistical significance too infrequently. Simple examples that demonstrate the nature of this pitfall, along with some formulations, are presented. It is recommended that practitioners use standard hypothesis testing techniques that have been derived from statistical theory rather than the ad hoc approach involving error bars.

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Melissa Free and John Lanzante

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Both observed and modeled upper-air temperature profiles show the tropospheric cooling and tropical stratospheric warming effects from the three major volcanic eruptions since 1960. Detailed comparisons of vertical profiles of Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC) and Hadley Centre Atmospheric Temperatures, version 2 (HadAT2), radiosonde temperatures with output from six coupled GCMs show good overall agreement on the responses to the 1991 Mount Pinatubo and 1982 El Chichón eruptions in the troposphere and stratosphere, with a tendency of the models to underestimate the upper-tropospheric cooling and overestimate the stratospheric warming relative to observations. The cooling effect at the surface in the tropics is amplified with altitude in the troposphere in both observations and models, but this amplification is greater for the observations than for the models. Models and observations show a large disagreement around 100 mb for Mount Pinatubo in the tropics, where observations show essentially no change, while models show significant warming of ∼0.7 to ∼2.6 K. This difference occurs even in models that accurately simulate stratospheric warming at 50 mb. Overall, the Parallel Climate Model is an outlier in that it simulates more volcanic-induced stratospheric warming than both the other models and the observations in most cases.

From 1979 to 1999 in the tropics, RATPAC shows a trend of less than 0.1 K decade−1 at and above 300 mb before volcanic effects are removed, while the mean of the models used here has a trend of more than 0.3 K decade−1, giving a difference of ∼0.2 K decade−1. At 300 mb, from 0.02 to 0.10 K decade−1 of this difference may be due to the influence of volcanic eruptions, with the smaller estimate appearing more likely than the larger. No more than ∼0.03 K of the ∼0.1-K difference in trends between the surface and troposphere at 700 mb or below in the radiosonde data appears to be due to volcanic effects.

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