scholarly journals Seasonality of African Precipitation from 1996 to 2009

2012 ◽  
Vol 25 (12) ◽  
pp. 4304-4322 ◽  
Author(s):  
Brant Liebmann ◽  
Ileana Bladé ◽  
George N. Kiladis ◽  
Leila M. V. Carvalho ◽  
Gabriel B. Senay ◽  
...  
Keyword(s):  
Annual Cycle ◽  
Daily Precipitation ◽  
Warning System ◽  
Tropical Rainfall Measuring Mission ◽  
Global Precipitation Climatology Project ◽  
Horn Of Africa ◽  
Wet Season ◽  
Precipitation Climatology ◽  
Daily Data ◽  
Global Precipitation

Abstract A precipitation climatology of Africa is documented using 12 years of satellite-derived daily data from the Global Precipitation Climatology Project (GPCP). The focus is on examining spatial variations in the annual cycle and describing characteristics of the wet season(s) using a consistent, objective, and well-tested methodology. Onset is defined as occurring when daily precipitation consistently exceeds its local annual daily average and ends when precipitation systematically drops below that value. Wet season length, rate, and total are then determined. Much of Africa is characterized by a single summer wet season, with a well-defined onset and end, during which most precipitation falls. Exceptions to the single wet season regime occur mostly near the equator, where two wet periods are usually separated by a period of relatively modest precipitation. Another particularly interesting region is the semiarid to arid eastern Horn of Africa, where there are two short wet seasons separated by nearly dry periods. Chiefly, the summer monsoon spreads poleward from near the equator in both hemispheres, although in southern Africa the wet season progresses northwestward from the southeast coast. Composites relative to onset are constructed for selected points in West Africa and in the eastern Horn of Africa. In each case, onset is often preceded by the arrival of an eastward-propagating precipitation disturbance. Comparisons are made with the satellite-based Tropical Rainfall Measuring Mission (TRMM) and gauge-based Famine Early Warning System (FEWS NET) datasets. GPCP estimates are generally higher than TRMM in the wettest parts of Africa, but the timing of the annual cycle and average onset dates are largely consistent.

scholarly journals The Precipitation Characteristics of ISCCP Tropical Weather States

2013 ◽  
Vol 26 (3) ◽  
pp. 772-788 ◽  
Author(s):  
Dongmin Lee ◽  
Lazaros Oreopoulos ◽  
George J. Huffman ◽  
William B. Rossow ◽  
In-Sik Kang
Keyword(s):  
Large Scale ◽  
Tropical Rainfall Measuring Mission ◽  
Global Precipitation Climatology Project ◽  
Surface Precipitation ◽  
Daily Data ◽  
Precipitation Characteristics ◽  
Dominant State ◽  
Tropical Weather ◽  
Tropical Hydrology ◽  
Global Precipitation

Abstract The authors examine the daytime precipitation characteristics of the International Satellite Cloud Climatology Project (ISCCP) weather states in the extended tropics (35°S–35°N) for a 10-yr period. The main precipitation dataset used is the Tropical Rainfall Measuring Mission (TRMM) Multisatellite Precipitation Analysis operational product 3B42 dataset, but Global Precipitation Climatology Project daily data are also used for comparison. It is found that the most convectively active ISCCP weather state (WS1), despite an occurrence frequency below 10%, is the most dominant state with regard to surface precipitation, producing both the largest mean precipitation rates when present and the largest percent contribution to the total precipitation of the tropics; yet, even this weather state appears to not precipitate about half the time, although this may be to some extent an artifact of detection and spatiotemporal matching limitations of the precipitation dataset. WS1 exhibits a modest annual cycle of the domain-average precipitation rate, but notable seasonal shifts in its geographic distribution. The precipitation rates of the other weather states appear to be stronger when occurring before or after WS1. The precipitation rates of the various weather states are different between ocean and land, with WS1 producing higher daytime rates on average over ocean than land, likely because of the larger size and more persistent nature of oceanic WS1s. The results of this study, in addition to advancing the understanding of tropical hydrology, can serve as higher-order diagnostics for evaluating the realism of tropical precipitation distributions in large-scale models.

The Global Precipitation Climatology Project

2007 ◽  
pp. 25-35 ◽  
Author(s):  
Arnold Gruber ◽  
Bruno Rudolf ◽  
Mark M. Morrissey ◽  
Toshiyuki Kurino ◽  
John E. Janowiak ◽  
...  
Keyword(s):  
Global Precipitation Climatology Project ◽  
Precipitation Climatology ◽  
Global Precipitation

scholarly journals The Global Precipitation Climatology Project (GPCP) Combined Precipitation Dataset

1997 ◽  
Vol 78 (1) ◽  
pp. 5-20 ◽  
Author(s):  
George J. Huffman ◽  
Robert F. Adler ◽  
Philip Arkin ◽  
Alfred Chang ◽  
Ralph Ferraro ◽  
...  
Keyword(s):  
Global Precipitation Climatology Project ◽  
Precipitation Climatology ◽  
Global Precipitation

scholarly journals Spatial and Temporal Variation of Precipitation in Greece and Surrounding Regions Based on Global Precipitation Climatology Project Data

2008 ◽  
Vol 21 (6) ◽  
pp. 1349-1370 ◽  
Author(s):  
N. Hatzianastassiou ◽  
B. Katsoulis ◽  
J. Pnevmatikos ◽  
V. Antakis
Keyword(s):  
Large Scale ◽  
Precipitation Amount ◽  
Global Precipitation Climatology Project ◽  
Spatial And Temporal Variation ◽  
Mean Annual Precipitation ◽  
Study Region ◽  
Precipitation Climatology ◽  
Spatial Coverage ◽  
Precipitation Decrease ◽  
Global Precipitation

Abstract In this study, the spatial and temporal distribution of precipitation in the broader Greek area is investigated for the 26-yr period 1979–2004 by using monthly mean satellite-based data, with complete spatial coverage, taken from the Global Precipitation Climatology Project (GPCP). The results show that there exists a clear contrast between the more rainy western Greek area (rainside) and the drier eastern one (rainshadow), whereas there is little precipitation over the islands, particularly in the southern parts. The computed long-term areal mean annual precipitation amount averaged for the study area is equal to P = 639.8 ± 44.8 mm yr−1, showing a decreasing trend of −2.32 mm yr−1 or −60.3 mm over the 26-yr study period, which corresponds to −9.4%. This decrease of precipitation, arising primarily in winter and secondarily in spring, is the result of a decreasing trend from 1979 through the 1980s, against an increase during the 1990s through the early 2000s, followed again by a decrease up to the year 2004. The performed analysis reveals an increasing trend of precipitation in the central and northern parts of the study region, contrary to an identified decreasing trend in the southern parts, which is indicative of threatening desertification processes in those areas in the context of climatic changes in the climatically sensitive Mediterranean basin. In addition, the analysis shows that the precipitation decrease is due to a corresponding decrease of maximum precipitation against rather unchanged minimum precipitation amounts. The analysis indicates that the changing precipitation patterns in the region during winter are significantly anticorrelated with the North Atlantic Oscillation (NAO) index values, against a positive correlation during summer, highlighting thus the role of large-scale circulation patterns for regional climates. The GPCP precipitation data are satisfactorily correlated with instrumental measurements from 36 stations uniformly distributed over the study area (correlation coefficient R = 0.74 for all stations; R = 0.63–0.91 for individual stations).

scholarly journals Estimating Climatological Bias Errors for the Global Precipitation Climatology Project (GPCP)

2012 ◽  
Vol 51 (1) ◽  
pp. 84-99 ◽  
Author(s):  
Robert F. Adler ◽  
Guojun Gu ◽  
George J. Huffman
Keyword(s):  
Error Estimate ◽  
Error Estimates ◽  
Relative Error ◽  
Absolute Magnitude ◽  
Global Precipitation Climatology Project ◽  
Bias Error ◽  
Precipitation Climatology ◽  
The Mean ◽  
The Tropics ◽  
Global Precipitation

AbstractA procedure is described to estimate bias errors for mean precipitation by using multiple estimates from different algorithms, satellite sources, and merged products. The Global Precipitation Climatology Project (GPCP) monthly product is used as a base precipitation estimate, with other input products included when they are within ±50% of the GPCP estimates on a zonal-mean basis (ocean and land separately). The standard deviation σ of the included products is then taken to be the estimated systematic, or bias, error. The results allow one to examine monthly climatologies and the annual climatology, producing maps of estimated bias errors, zonal-mean errors, and estimated errors over large areas such as ocean and land for both the tropics and the globe. For ocean areas, where there is the largest question as to absolute magnitude of precipitation, the analysis shows spatial variations in the estimated bias errors, indicating areas where one should have more or less confidence in the mean precipitation estimates. In the tropics, relative bias error estimates (σ/μ, where μ is the mean precipitation) over the eastern Pacific Ocean are as large as 20%, as compared with 10%–15% in the western Pacific part of the ITCZ. An examination of latitudinal differences over ocean clearly shows an increase in estimated bias error at higher latitudes, reaching up to 50%. Over land, the error estimates also locate regions of potential problems in the tropics and larger cold-season errors at high latitudes that are due to snow. An empirical technique to area average the gridded errors (σ) is described that allows one to make error estimates for arbitrary areas and for the tropics and the globe (land and ocean separately, and combined). Over the tropics this calculation leads to a relative error estimate for tropical land and ocean combined of 7%, which is considered to be an upper bound because of the lack of sign-of-the-error canceling when integrating over different areas with a different number of input products. For the globe the calculated relative error estimate from this study is about 9%, which is also probably a slight overestimate. These tropical and global estimated bias errors provide one estimate of the current state of knowledge of the planet’s mean precipitation.

scholarly journals Comparação dos dados de precipitação gerados Pelo gpcp vs observados para o estado do rio grande do sul

2015 ◽  
Vol 30 (4) ◽  
pp. 415-422 ◽  
Author(s):  
Claudinéia Brazil Saldanha ◽  
Bernadete Radin ◽  
Maria Angélica Gonçalves Cardoso ◽  
Matheus Lara Rippel ◽  
Ludmila Losada da Fonseca ◽  
...  
Keyword(s):  
Rio Grande ◽  
Global Precipitation Climatology Project ◽  
Rio Grande Do Sul ◽  
Precipitation Climatology ◽  
Global Precipitation

RESUMO Fontes alternativas de dados de precipitação têm se tornado cada vez mais usuais, possibilitando também uma avaliação de áreas com ausência de série longa e/ou continua de dados meteorológicos ou com baixa densidade de estações meteorológicas. O objetivo deste trabalho foi avaliar o desempenho das séries de dados do Global Precipitation Climatology Project (GPCP) para o Estado do Rio Grande do Sul e verificar a sua possível utilização na ausência de dados observados de precipitação. Nesse trabalho utilizaram-se séries mensais de precipitação do GPCP fornecidas pela National Oceanic and Atmospheric Administration (NOAA) com uma resolução de 0,5° x 0,5° latitude-longitude, para o período de 1979 a 2010. As análises foram realizadas a partir da comparação com dados de precipitação de 22 estações meteorológicas localizadas no estado do Rio Grande do Sul. A partir dos resultados das análises estatísticas, observa-se que o GPCP apresentou um bom desempenho na região de estudo, com o coeficiente de correlação em torno de 0,81. Com isso, infere-se que os dados do GPCP podem ser utilizados como fonte alternativa de dados de precipitação, quando as séries temporais possuem períodos de falhas.

scholarly journals PLANETARY-SCALE CLIMATIC INDICES AND RELATIONSHIP BETWEEN DECADAL VARIABILITY OF RAINFALL IN NORTHEASTERN AND SOUTHERN BRAZIL

2013 ◽  
Vol 31 (1) ◽  
pp. 31 ◽  
Author(s):  
Luciana Figueiredo Prado ◽  
Ilana Wainer
Keyword(s):  
Decadal Variability ◽  
Southern Oscillation ◽  
Global Precipitation Climatology Project ◽  
Tropical Atlantic ◽  
Climatic Index ◽  
Climatic Indices ◽  
Atmospheric Research ◽  
Precipitation Climatology ◽  
Environmental Prediction ◽  
Global Precipitation

This work analyzes the relationship between climatic index and rainfall in the Northeastern (NE) and Southern (S) Brazil, in decadal timescale. The climatic indices were obtained from the reanalysis data from NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research) between 1948 and 2008. Subsequently, (indices and rainfall correlation coefficients derived from the GPCP (Global Precipitation Climatology Project) dataset were calculated using filtered and non-filtered time series, within the decadal frequency). The results show that ElNi ˜no Southern Oscillation (ENSO) is the main phenomenon influencing NE rainfall due to related changes in tropical circulation while the Intertropical Convergence Zone (ITCZ) annual cycle also affects rainfall in the NE to a lesser extent. Meanwhile, in the Southern region, the most important phenomenon is the Southern Annular Mode (SAM) which controls cyclones activity in mid-latitudes. The Tropical Atlantic dipole index (ADI) also influences the rainfall in the Southern, and this might be related to moisture being transported from the ocean to the continent, which is then carried to the South by the Low Level Jet. It is also suggested that the decadal variability of the Tropical Atlantic Ocean and its influence on the precipitation in NE andS regions of Brazil are episodic because no significant correlations were obtained at decadal frequency. Finally, the spectral analysis revealed that the interannual timescale is the main frequency of variability in both studied regions, affecting differently each one of them. RESUMO: Este trabalho analisa as relações entre índices climáticos e a precipitação no Nordeste (NE) e Sul (S) do Brasil, em escala decadal. Os índices climáticos foram obtidos a partir de dados da reanálise do NCEP/NCAR (National Center for Environmental Prediction/National Center for Atmospheric Research), para o período de 1948 a 2008. Posteriormente, foram obtidos os coeficientes de correlação entre os índices e as anomalias de precipitação advindas do banco de dados do GPCP (Global Precipitation Climatology Project) nestas regiões, utilizando séries não filtradas e séries filtradas na frequência decadal. Os resultados sugerem que o principal fenômeno que modula a precipitação no NE é o El Ni˜no-Oscilação Sul (ENOS), devido às alterações na circulação tropical, e também o ciclo anual da Zona de Convergência Intertropical (ZCIT), que modula a estação chuvosa do NE. Na região S, o fenômeno que mais influencia a precipitação em escala decadal é o Modo Anular Sul (SAM),por modular a atividade ciclogenética em latitudes médias, além do índice do dipolo do Atlântico Tropical (DA), que pode estar ligado ao aporte de umidade oceânica para o continente, e levada ao S pelo jato de baixos níveis. Também se sugere que a variabilidade decadal do Atlântico tropical e sua influência na precipitação no NE sejam episódicas, e não periódica, já que não foram obtidas correlações importantes para este índice, na frequência estudada. Finalmente, a análise espectral revelouque a escala interanual é a principal frequência de variabilidade temporal em ambas as regiões, com efeitos diversos em cada uma delas.Palavras-chave: precipitação, ENOS, Atlântico, SAM. 

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