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Bryan C. Weare

Abstract

Longwave and shortwave cloud radiative forcing from the recently released National Center for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) reanalyses are compared to Earth Radiation Budget Experiment (ERBE) observations. The observed differences are analyzed utilizing concurrent International Satellite Cloud Climatology Project (ISCCP) estimates of cloudiness and other satellite observations.

The results show that the NCEP–NCAR longwave cloud forcing agrees well with that of ERBE not only for the annual means but also for seasonal and climatic variations. Areas of disagreement are generally related to disagreements between NCEP–NCAR high cloudiness and observations. Overall, the NCEP–NCAR shortwave cloud forcing is in poorer agreement with ERBE observations. NCEP–NCAR annual means in the Tropics are often 20–30 W m−2 too negative. On the other hand the NCEP–NCAR total cloud cover in this region is 10%–20% less than the ISCCP observations, which should lead to less, rather than more, negative shortwave cloud forcing. Thus the primary error in the mean shortwave cloud forcing is likely due to specification of clouds that are too reflective in the NCEP analysis model. Moderate errors in the variability of NCEP–NCAR SWCF are apparently related to errors in the analyzed seasonal variability of total cloudiness, which are exacerbated by NCEP model specification of clouds that are too bright and underestimates of the seasonal variability of the clear-sky fluxes.

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Bryan C. Weare

Abstract

Regional estimates of low, middle, high, and total cloud amounts derived from bispectral measurements from Nimbus-7 have been analyzed for the six-year period April 1979 through March 1985. Fractional cloud cover for the three height categories was used to calculate a proxy mean cloud-top height. Intra- and interannual standard deviations of total cloud amount and mean cloud height show realistic patterns throughout most of the globe except at very high latitudes. Over much of the cash, intra-annual and interannual variations in total cloud amount are strongly positively correlated with variations in cloud height. Furthermore, both total cloud amount and cloud height variations are moderately correlated with sea surface temperature variations. The strongest correlations are positive in the tropics for both intra-annual and interannual variations. In middle latitudes, moderate negative correlations are positive with intra-annual variations, whereas moderate positive correlations occur on interannual time frames. In the tropics 1°C changes in temperature are statistically related to a change of total cloudiness of at least 2% and a change in cloud height of more than 0.5 km.

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Bryan C. Weare

Abstract

The role of moisture variations in the initiation of Madden–Julian oscillation (MJO) variability is reexamined through composite singular value decomposition (CSVD) analyses using the European Centre for Medium-Range Weather Forecasts (ECMWF) 40-yr Re-Analyses (ERA-40) data. The CSVD analyses at various time lags are carried out to discern the complex space–time relationships between convection identified using outgoing longwave radiation and 1000-hPa divergence, 850-hPa specific humidity, and surface evaporation. The most striking difference from the earlier analyses using NCEP–NCAR reanalysis data is that the observed relations between 20–100-day filtered OLR and · V 1000 anomalies are weaker and less significant in the current analyses. On the other hand, both analyses show increasing low-level moisture near and to the east of the developing convection. Thus, both results imply that moisture preconditioning of convective events is not totally driven by boundary layer moisture convergence.

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Bryan C. Weare

Abstract

Monthly means of selected variables of the 2.5° International Satellite Cloud Climatology Project (ISCCP) C2 total cloud cover (CC), cloud-top pressure (CTP), and cloud water (CW) are statistically related to sea surface temperature (SST). The statistical tools utilized include intra- and interannual correlation, regression, and composite empirical orthogonal function (EOF) analyses.

The dominant intra- and interannual composite EOFs all show that CC, CTP, and CW departures have spatially coherent links with those of SST. The second most important intra-annual functions also show coherent relations, which are about three months out of phase with those of the dominant functions. The regression analysis suggests that this phase relation may be explained by significant correlations of the cloud variables with not only SST, but also with the time derivative of SST (dSST/dt). For instance, in the tropical Pacific increased CC is accompanied by increases in SST but decreases in dSST/dt, and increased CTP is associated with decreases in SST. However, at middle and high latitudes other relationships exist, such that larger CCs may be associated with decreased SSTs, or higher CTPs may be related to higher SSTs. These diagnosed relationships have important implications for understanding cloud and cloud radiative feedbacks in weather and climate.

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Bryan C. Weare

Abstract

A new method for combining satellite and surface-based cloud observations into a self-consistent three-dimensional field is presented. This method derives the probabilities of the cloud states, which are most consistent with all of the observations and assumptions concerning the nature and relative uncertainties of the observations. It is applied to a three-layer atmosphere using monthly satellite- and surface-based cloud observations. The reconstructions of the observed fields usually lead to modifications of the surface-observed low cloud amount of less than 0.008 fractional cloud cover. Over the ocean the satellite-view low cloud amounts are usually decreased by between 0.06 and 0.12 for most of the middle latitudes and southeastern tropical Pacific. Over land the adjustments in the satellite low cloud amounts are generally smaller. The method leads to increases in satellite high cover of between 0.03 and 0.09 over most regions, and increases in middle cloud cover of up to around 0.03 over the subtropical oceans. Comparisons between derived total cloud cover and that calculated with the commonly used random and mixed overlap assumptions suggest that the mixed assumption generally better fits the results. On the whole there is overall fairly good agreement between the percent low cloud relative to total cloud cover in the reconstructed observations and a global climate model, but the model has a far larger percentage of high clouds nearly everywhere, especially in the tropical convective regions and over the Indian subcontinent.

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Bryan C. Weare

Abstract

The relationships between the patterns of monthly sea surface temperature (SST) variations and those of precipitation in the tropical Pacific Ocean region are examined. The rainfall data utilized are derived from satellite observations of outgoing longwave radiation. A composite empirical orthogonal function (EOF) analysis of the SST and precipitation indicates a dominant mode of variation linking SST variations in the eastern equatorial region with those of MNWI about 30° westward. One-point correlation analyses show that this general relationship is present for all points in the eastern and central ocean, but that no significant SST-rainfall correlations are evident for SST points wen of about the dateline. The one-point correlation analyses also suggest that during time periods outside of El Niñ's, the rainfall response to SST changes is largely confined to the areas of climatological precipitation maxima, suggesting only a minor alteration in the large-scale circulation. On the other hand, during El Niñ there is the strong suggestion that circulation changes give rise to complete shifts in rainfall zones. The possible influence of the strong spatial autocorrelations of SST on these results are also explored using the one-point correlations. It is concluded that the observed SST-rainfall teleconnections cannot be wholly explained by the large-scale nature of the SST variations.

The inferences derived from these analyses are utilized in formulating linear regression (LR) models to specify tropical precipitation anomalies based upon a knowledge of concurrent SST perturbations. Preliminary analyses suggest that while relatively large hindcast skills are evident in various LR models, the apparent skills decrease substantially when the models are applied to new data. While these results do not prove that such models can never be very useful, they do project difficulties in greatly increasing the skill, especially as long as the available data periods are relatively short

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Bryan C. Weare

Abstract

An additionally constrained multiple linear regression technique is outlined for use with the prediction or specification of fields of geophysical variables. The additional constraints are the requirement that the predictions or specifications have spatial interrelationships which are similar to the dominant empirical orthogonal functions of the dependent variables. Since the traditional multiple linear regression estimates by definition minimize the mean square errors for the data used to develop the model, the utility of the additional constraint can be evaluated only when the regression models are tested on new data. A so-called jackknife technique is used in this regard.

This additionally constrained multiple linear regression technique is tested on two examples of the specification of monthly values using independent data for the same month. The first is the specification of North Pacific sector 700-mb geopotential heights using the time coefficients of the first two empirical orthogonal functions of Pacific sea surface temperature. The second is the specification of monthly precipitation totals at 36 stations in the western United States using 700-mb heights. Use of the additional constraint leads to average increases in observed-predicted correlations of between 5 and 30% when used with new data. These improvements are quite evenly distributed over nearly all of the points of the fields of the dependent variable.

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Bryan C. Weare

Abstract

The spatial and temporal character of El Niño is explored with analyses of tropical Pacific Ocean surface temperatures for the period 1957–76. The data are derived from approximately 5×106 marine weather reports. Maps are illustrated which portray the initiation, maturation and decay of an “average” El Niño event. Empirical orthogonal functions of nonseasonal departures are displayed. The time coefficients of the dominant empirical functions are derived together with average departures for 18 regions which are usually 10° of latitude and 40–50° of longitude in size. Lag correlation and coherence-spectral analysts are carried out on all of the time series. The pattern of El Niño which is portrayed is that of a basinwide phenomenon with a time evolution lasting more than 24 months. During this evolution sea temperatures in the western Pacific tend to have departures of opposite sign to those in the cast. Variations in the eastern equatorial region are shown to precede those in the central equatorial and northeastern tropical Pacific by 1–4 months. On the other hand, changes in the central and eastern Pacific near 25°S tend to precede those in the equatorial region by a few months.

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Bryan C. Weare

Abstract

Centered composite analysis is described and applied to gain a better understanding of the initial phases of the Madden–Julian oscillation (MJO). Centered composite analysis identifies the dates and central locations of key events. The elements of the composite means are centered on these central locations before averages are calculated. In this way much of the spatial fuzziness, which is inherent in traditional composite analysis, is removed. The results for the MJO, based on MJO-filtered outgoing longwave radiation for the reference data and 40-yr ECMWF Re-Analysis (ERA-40) and NCEP–NCAR reanalysis products for the composites, show highly significant composites of unfiltered data for not only zero lag, but also lags back to 20 days before the target events. These composites identify propagating patterns of surface pressure, upper- and lower-troposphere zonal winds, surface temperature, and 850-hPa specific humidity associated with MJO convective events in the Indian Ocean. The propagation characteristics of important features, especially surface pressure, differ substantially for MJO convective anomalies centered over the Indian or western Pacific Oceans. This suggests that distinctly different mechanisms may be dominant in these two regions, and that many earlier analyses may be mixing properties of the two.

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Bryan C. Weare

Abstract

Multilag singular value decomposition (MLSVD) analysis is developed and applied to diagnosing the impact of interannual variations of outgoing longwave radiation (OLR) on tropical stratospheric temperature changes. MLSVD is designed to analyze simultaneously variations at multiple levels and for a large number of temporal lags and leads. The two dominant MLSVDs are strongly related to El Niño–Southern Oscillation (ENSO). The associated patterns of tropical OLR are similar to the canonical ENSO SST patterns with strong negative sign regions stretching along the equator in the eastern and central Pacific. These dominant modes are strongly linked to temperature perturbations at a wide range of lags. At the lowest analyzed level (200 hPa) and zero lag positive temperatures anomalies are in the region of low OLR. In the lower stratosphere near 100 hPa, strong negative temperature perturbations replace the positive values of the lowest level. Higher in the stratosphere near 20 hPa, equatorial temperature perturbations are again positive, but with a more zonally elongated spatial pattern. Overall, the equatorial temperature anomalies propagate slowly to the east, at a speed strongly related to ocean–atmosphere coupling of less than 1 m s−1, and vertically and westward into the stratosphere by Rossby waves with a speed in the range of 30 m s−1.

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