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John E. Janowiak

Abstract

Interannual variations in African rainfall are examined using rotated principal component analysis (PCA) applied to anomalies from the annual mean as well as seasonal anomalies. The rotated PCA loading patterns suggest several “preferred” continental-scale rainfall anomaly patterns. The dominant features of year-to-year variations in African rainfall appear to be the high spatial coherence of rainfall anomalies over large portions of the continent. In addition, several dipole regions, that is, adjacent regions which tend to experience rainfall anomalies of opposite sign, are found and discussed. One dipole region, the sub-Saharan region, appears to have a relationship with a characteristic Atlantic sea surface temperature anomaly pattern during boreal summer. During austral summer, the tendency for a large-scale dipole pattern in southeast Africa is apparent, as is an association of this pattern with the warm and cold phases of the El Niñ/Southern Oscillation (ENSO) phenomenon.

Normalized rainfall departures over areas determined from the PCA loading patterns are used as an index from which composites are formed. Patterns of rainfall anomalies, based on composites of high and low values of these indices, are produced to quantify the year-to-year variation in rainfall in the areas of study. During the austral summer of warm episode ENSO years, rainfall tends to be 10%–25% above normal east of 20°E between the equator and 10°S and correspondingly lower than normal east of 20°E, between 15° and 30°S. The opposite anomaly pattern tends to be observed during cold phases of ENSO in this region. Anomaly dipoles of similar magnitude (when expressed as percentages) tend to be found in sub-Saharan Africa during boreal summer.

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John E. Janowiak

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John E. Janowiak

Abstract

Quantitative estimates of rainfall, as derived from satellite observations of cloud-top temperature, have been produced for each 2.5° lat-long location from 30°N to 30°S for the period 1986–89. These remotely sensed estimates are a preliminary product of the Global Precipitation Climatology Project (GPCP), which is charged with the development of a global rainfall dataset during the period 1986–95, using all available in situ data supplemented with satellite-derived estimates of precipitation. Four-year means (1986–89) of monthly satellite-derived rainfall estimates were compared to the climatological rainfall datasets compiled by Jaeger and Legates and Willmott in the tropics, to assess the performance of the satellite estimates in the context of existing state-of-the-art global precipitation datasets. It is shown that the satellite estimates and the climatologies are in reasonable agreement both in temporal and spatial variation, although some large regional differences were found. A more quantitative assessment of these estimates is also presented by comparing them with ground-based observations from a high-density radar-raingage network over Japan.

Short-range forecasts of precipitation from the National Meteorological Center (NMC) Medium-Range Forecast (MRF) and the European Centre for Medium Range Weather Forecasts (ECMWF) models are also compared with the satellite estimates in the tropics. The motivation for this comparison is to assess the utility of the model precipitation forecasts as a “first guess” of the global tropical precipitation field for use in an objective analysis scheme to integrate the satellite-derived estimates and in situ data for the GPCP. The results show that the distribution and magnitude of mean tropical rainfall agree reasonably well among the estimates and model forecasts during the 9-month study period (March–November 1989). However, temporal correlations between the satellite estimates and the model precipitation predictions reveal that the models currently do not represent the time variations of rainfall in much of the tropics, particularly 30–60-day oscillations, that are apparent in the satellite estimates.

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John E. Janowiak

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John E. Janowiak

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John E. Janowiak and Pingping Xie

Abstract

A method has been developed to produce real-time rain gauge–satellite merged analyses of global monthly precipitation. A dataset of these analyses spans the period from January 1979 to the present, which is sufficiently long to allow the computation of reasonably stable base period means from which departures from “normal” can be computed. The dataset is used routinely for global precipitation monitoring purposes at the National Oceanic and Atmospheric Administration/National Weather Service/National Centers for Environmental Prediction/Climate Prediction Center, is updated monthly, and is available via the Internet.

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John E. Janowiak and Pingping Xie

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A pentad version of the Global Precipitation Climatology Project global precipitation dataset is used to document the annual and interannual variations in precipitation over monsoon regions around the globe. An algorithm is described that determines objectively wet season onset and withdrawal for individual years, and this tool is used to examine the behavior of various characteristics of the major monsoon systems. The definition of onset and withdrawal are determined by examining the ramp-up and diminution of rainfall within the context of the climatological rainfall at each location. Also examined are interannual variations in onset and withdrawal and their relationship to rainy season precipitation accumulations. Changes in the distribution of “heavy” and “light” precipitation events are examined for years in which “abundant” and “poor” wet seasons are observed, and associations with variations in large-scale atmospheric general circulation features are also examined. In particular, some regions of the world have strong associations between wet season rainfall and global-scale patterns of 200-hPa streamfunction anomalies.

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Mark L. Morrissey and John E. Janowiak

Abstract

The effect of temporal sampling error in satellite estimates of climate-scale rainfall is to produce a “conditional” bias where the algorithm overestimates high rainfall and underestimates low rainfall. Thus, the bias is conditional on the value of the estimate. This paper illustrates the problem using satellite infrared rainfall estimates together with a well-known satellite algorithm and shows it to be a function of the averaging scale, the sampling rate, and the temporal autocorrelation structure of the satellite estimates. Using realistic sampling rates, it is shown that significant biases exist in satellite rainfall estimates if polar-orbiting data are used in their construction. A simple correction for this bias based upon the estimated autocorrelation structure is given.

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Gerald D. Bell and John E. Janowiak

This paper presents an observational analysis of the large-scale atmospheric circulation prior to and during the Midwest floods of June–July 1993. The floods developed and persisted in association with three major circulation features, none of which alone would likely have produced such intense and prolonged flooding. First, a persistent, positive phase of the North Pacific teleconnection pattern was observed throughout the Pacific sector for four months prior to the onset of the floods. This anomalous circulation was associated with much above-normal cyclone activity over the middle latitudes of the North Pacific and with below-normal cyclone activity over the western and central United States. Second, a major change in this pattern occurred over the western United States in late May, which established very strong zonal flow from the western Pacific to the eastern United States. This flow provided a “duct” for the intense cyclones to propagate directly into the Midwest throughout the month of June. These storms triggered a series of intense convective complexes over the Midwest, resulting in major flooding. Third, during July a persistent wave pattern with highly amplified southwesterly flow became established over the western and central United States. This circulation, in conjunction with a quasi-stationary frontal boundary and sustained moisture transport into the central United States, was associated with a continuation of excessive rainfall and flooding in the Midwest.

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Phillip A. Arkin and John E. Janowiak

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