CLIMATIC PATTERN ANALYSIS OF RAINFALL AND DRY SPELLS DURING THE AGRICULTURAL SEASON IN MALAWI
The study identified the basic structural characteristics of dry spells, seasonal, and extreme rainfall events to offer localized information which in data-scarce regions is typically extrapolated from syntheses of regional or satellite climate data. Utilizing observed daily station rainfall dataset...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
AcademicPres
2024-08-01
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| Series: | Agricultura |
| Subjects: | |
| Online Access: | https://journals.usamvcluj.ro/index.php/agricultura/article/view/14792 |
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| Summary: | The study identified the basic structural characteristics of dry spells, seasonal, and extreme rainfall events to offer localized information which in data-scarce regions is typically extrapolated from syntheses of regional or satellite climate data. Utilizing observed daily station rainfall datasets from the rainy season (November to April) spanning the years 1961 to 2007, a set of indices including percentile, absolute, threshold, and duration measures, was derived for locations at low (Balaka), medium (Bunda, Chitedze, KIA), and high (Dedza) altitudes in Malawi. For each site, a separate analysis was conducted in which the indices were subjected to principal component analysis, followed by composite analysis and K-means clustering of the extracted principal components. Climatic patterns at Bunda and KIA were predominantly characterised by wet events, whereas Dedza, Chitedze, and Balaka exhibited patterns defined by growing season characteristics coupled with dry events. Notably, in Balaka, wet events were of equal significance indicating a location prone to compound events. Key indices defining climatic patterns included wet days and pentads, maximum one-day rainfall, extreme intensity, extreme percent, 6 to 10 and ≥ 15 days dy spells, length, and end date of the growing season. The results highlight that climatic frameworks for analysing rainfall and dry events must consider multi-index analyses and cannot be uniformly applied across geographically diverse areas or assumed to be homogeneous within regions. |
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| ISSN: | 1221-5317 |