Seasonal variability and predictability of agro-meteorological indices: Tailoring onset of rainy season estimation to meet farmers’ needs in Ghana

Talardia Gbangou*, Fulco Ludwig, Erik van Slobbe, Long Hoang, Kranjac-Berisavljevic Gordana Kranjac-Berisavljevic

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Reliable information on onset of the rainy season is important for local agriculture planning in Ghana. We examine the (i) trend and variability of onset in local observations to better understand the need for onset forecast information and (ii) performance of ECMWF System 4 seasonal climate forecast in reproducing this variability and discriminating tercile categories of onset dates across Ghana. The analyses focused on two pilots locations of interest among the fourteen synoptic stations studied, namely Ada and Tamale located in the coastal savanna and in northern Ghana. Two different onset date definitions were tested to suite with uncorrected and bias-corrected forecasts in order to test the predictability. The definitions were tailored to suit with forecast start dates, local climate data availability and cropping calendar. Results show a significant decreasing trend in historical onset dates towards more recent times (i.e 1986–2010) at Tamale station. Also, historical onset dates exhibit a significant increasing variability towards more recent time at Ada station. System 4 shows some ability for reproducing local onset variability with significant correlational relationship between forecasted and observed onset dates at some locations including Ada station. The forecasting system also has significant skill in predicting early and late onset dates categories (i.e H-K score > 0) at the pilot stations. In conclusion, the use of onset agro-meteorological index, based on System 4 as climate service in Ghana, has a potential value for decision making when considering categorical based forecasts.

Original languageEnglish
Pages (from-to)19-30
Number of pages12
JournalClimate Services
Volume14
DOIs
Publication statusPublished - 1 Apr 2019

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climate
savanna
cropping practice
decision making
index
need
station
forecast
agriculture
trend
test
services
planning

Keywords

  • Forecast categories
  • Inter-annual variability
  • Onset dates
  • Seasonal forecasts

Cite this

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title = "Seasonal variability and predictability of agro-meteorological indices: Tailoring onset of rainy season estimation to meet farmers’ needs in Ghana",
abstract = "Reliable information on onset of the rainy season is important for local agriculture planning in Ghana. We examine the (i) trend and variability of onset in local observations to better understand the need for onset forecast information and (ii) performance of ECMWF System 4 seasonal climate forecast in reproducing this variability and discriminating tercile categories of onset dates across Ghana. The analyses focused on two pilots locations of interest among the fourteen synoptic stations studied, namely Ada and Tamale located in the coastal savanna and in northern Ghana. Two different onset date definitions were tested to suite with uncorrected and bias-corrected forecasts in order to test the predictability. The definitions were tailored to suit with forecast start dates, local climate data availability and cropping calendar. Results show a significant decreasing trend in historical onset dates towards more recent times (i.e 1986–2010) at Tamale station. Also, historical onset dates exhibit a significant increasing variability towards more recent time at Ada station. System 4 shows some ability for reproducing local onset variability with significant correlational relationship between forecasted and observed onset dates at some locations including Ada station. The forecasting system also has significant skill in predicting early and late onset dates categories (i.e H-K score > 0) at the pilot stations. In conclusion, the use of onset agro-meteorological index, based on System 4 as climate service in Ghana, has a potential value for decision making when considering categorical based forecasts.",
keywords = "Forecast categories, Inter-annual variability, Onset dates, Seasonal forecasts",
author = "Talardia Gbangou and Fulco Ludwig and {van Slobbe}, Erik and Long Hoang and {Gordana Kranjac-Berisavljevic}, Kranjac-Berisavljevic",
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Seasonal variability and predictability of agro-meteorological indices: Tailoring onset of rainy season estimation to meet farmers’ needs in Ghana. / Gbangou, Talardia; Ludwig, Fulco; van Slobbe, Erik; Hoang, Long; Gordana Kranjac-Berisavljevic, Kranjac-Berisavljevic.

In: Climate Services, Vol. 14, 01.04.2019, p. 19-30.

Research output: Contribution to journalArticleAcademicpeer-review

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T1 - Seasonal variability and predictability of agro-meteorological indices: Tailoring onset of rainy season estimation to meet farmers’ needs in Ghana

AU - Gbangou, Talardia

AU - Ludwig, Fulco

AU - van Slobbe, Erik

AU - Hoang, Long

AU - Gordana Kranjac-Berisavljevic, Kranjac-Berisavljevic

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AB - Reliable information on onset of the rainy season is important for local agriculture planning in Ghana. We examine the (i) trend and variability of onset in local observations to better understand the need for onset forecast information and (ii) performance of ECMWF System 4 seasonal climate forecast in reproducing this variability and discriminating tercile categories of onset dates across Ghana. The analyses focused on two pilots locations of interest among the fourteen synoptic stations studied, namely Ada and Tamale located in the coastal savanna and in northern Ghana. Two different onset date definitions were tested to suite with uncorrected and bias-corrected forecasts in order to test the predictability. The definitions were tailored to suit with forecast start dates, local climate data availability and cropping calendar. Results show a significant decreasing trend in historical onset dates towards more recent times (i.e 1986–2010) at Tamale station. Also, historical onset dates exhibit a significant increasing variability towards more recent time at Ada station. System 4 shows some ability for reproducing local onset variability with significant correlational relationship between forecasted and observed onset dates at some locations including Ada station. The forecasting system also has significant skill in predicting early and late onset dates categories (i.e H-K score > 0) at the pilot stations. In conclusion, the use of onset agro-meteorological index, based on System 4 as climate service in Ghana, has a potential value for decision making when considering categorical based forecasts.

KW - Forecast categories

KW - Inter-annual variability

KW - Onset dates

KW - Seasonal forecasts

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