eprintid: 10553
rev_number: 16
eprint_status: archive
userid: 1305
dir: disk0/00/01/05/53
datestamp: 2018-04-12 04:13:17
lastmod: 2018-04-12 04:13:17
status_changed: 2018-04-12 04:13:17
type: book_section
metadata_visibility: show
contact_email: Library-ICRISAT@CGIAR.ORG
creators_name: Moyo, M
creators_name: Dorward, P
creators_name: Craufurd, P
icrisatcreators_name: Moyo, M
affiliation: ICRISAT (Bulawayo)
affiliation: School of Agriculture Policy and Development, University of Reading (Reading)
affiliation: International Maize and Wheat Improvement Center (CIMMYT) ICRAF House (Nairobi)
country: Zimbabwe
country: UK
country: Kenya
title: Characterizing Long Term Rainfall Data for Estimating Climate Risk in Semi-arid Zimbabwe
ispublished: pub
subjects: 570
subjects: R100
subjects: S21
subjects: s2.8
subjects: s28
subjects: s53
divisions: CRPS5
divisions: CRPS4
crps: crp1.11
full_text_status: restricted
keywords: Seasonal climate forecasts, Climate risk, Weather within climate, Semi arid regions, Rainfall, Rainfall Data, Zimbabwe, Long term rainfall
note: The authors gratefully acknowledge the funding provided to ICRISAT through the CGIAR Program on Climate Change, Agriculture and Food Security (CCAFS) for this work.
abstract: There is still a strong disconnect between the parameters and scale of information that farmers prefer and those of the seasonal climate forecasts (SCFs). There is a need to augment SCFs as they are currently presented; to make them more useful for farm decision making. The objective of this study was to use simple statistical methods of analysis to characterise long term rainfall for estimating climate risk in semi-arid Zimbabwe. This study reveals the importance of accessing long-term daily rainfall records to enable “weather-within-climate” analyses that can be tailored to the needs of farmers. The most critical point is to describe the climate in terms of events of direct relevance to farming rather than simple standard measures. Agronomically, the important rainfall events relevant to farmers in rainfed agriculture include the start, end and length of the rainy season, risks of dry spells as well as the distribution of rainfall amounts through the year. There are difficult risks in El Nino compared to Ordinary and La Nina seasons in terms of frequency and length of dry spells, number of rain days, rainfall onset and cessation dates and total rainfall amount. The chance of a dry-spell being broken is also considerably lower in El Nino years, compared to La Nina and Ordinary years. Packaging SCF with historic climate data as well as bringing in the shorter range forecasts, together with the experience of the season as it develops is a way in which value could be added to climate information dissemination. Technologies that enhance water use efficiency could also be one of the major areas of research to be integrated into the semi-arid farmers’ existing strategies to cope with climate variability and ultimately change.
date: 2017
date_type: published
series: Climate Change Management book series (CCM)
publisher: Springer
pagerange: 661-675
pages: 757
refereed: TRUE
isbn: 978-3-319-49519-4
issn: 1610-2010
book_title: Climate Change Adaptation in Africa
editors_name: Filho, W L
editors_name: Belay, S
editors_name: Kalangu, J
editors_name: Menas, W
editors_name: Munishi, P
editors_name: Musiyiwa, K
related_url_url: https://scholar.google.co.in/scholar?hl=en&as_sdt=0%2C5&q=Characterizing+Long+Term+Rainfall+Data+for+Estimating+Climate+Risk+in+Semi-arid+Zimbabwe&btnG=
related_url_type: pub
funders: CCAFS
citation:   Moyo, M and Dorward, P and Craufurd, P  (2017) Characterizing Long Term Rainfall Data for Estimating Climate Risk in Semi-arid Zimbabwe.   In:  Climate Change Adaptation in Africa.   Climate Change Management book series (CCM) .  Springer, pp. 661-675.  ISBN 978-3-319-49519-4     
document_url: http://oar.icrisat.org/10553/1/Characterizing%20Long%20Term%20Rainfall%20Data.pdf