Rainwatch

Tarhule, Aondover; Saley-Bana, Zakari; Lamb, Peter

doi:10.1175/2009bams2697.1

Cited by 22 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…ACKNOWLEDGMENTS. This article is dedicated to the memory of the late Professor Peter Lamb, a great friend to Africa, our much honored and loved colleague, veritable coauthor, and founder of R AINWATCH (www.rainwatch-africa.org), who contributed so much to the understanding of African climate variability, seasonal forecasting, and to educational outreach "to help Africa to help itself " (Tarhule et al 2009). The development of The Forecasters' Handbook reported in this paper is an international joint effort arising from the international African Monsoon Multidisciplinary Analysis (AMMA) project.…”

Section: Timelinessmentioning

confidence: 99%

The First Forecasters’ Handbook for West Africa

Cornforth

Parker

Diop-Kane

et al. 2019

Bulletin of the American Meteorological Society

View full text Add to dashboard Cite

Bridging the gap between rapidly moving scientific research and specific forecasting tools, Meteorology of Tropical West Africa: The Forecasters’ Handbook gives unprecedented access to the latest science for the region’s forecasters, researchers, and students and combines this with pragmatic approaches to forecasting. It is set to change the way tropical meteorology is learned and will serve to drive demand for new forecasting tools. The Forecasters’ Handbook builds upon the legacy of the African Monsoon Multidisciplinary Analysis (AMMA) project, making the latest science applicable to forecasting in the region. By bringing together, at the outset, researchers and forecasters from across the region, and linking to applications, user communities, and decision-makers, The Forecasters’ Handbook provides a template for finding much needed solutions to critical issues such as building resilience to weather hazards and climate change in West Africa.

show abstract

Section: Timelinessmentioning

confidence: 99%

The First Forecasters’ Handbook for West Africa

Cornforth

Parker

Diop-Kane

et al. 2019

Bulletin of the American Meteorological Society

View full text Add to dashboard Cite

show abstract

“…GLAM requires daily values of precipitation, shortwave radiation, maximum temperature and minimum temperature as driving weather data with additional inputs of soil properties and planting window (Watson and Challinor, 2013). GLAM accumulates the aboveground biomass, which is a product of daily transpiration and a predetermined transpiration efficiency value, within the growing season to determine total biomass production, which is converted into yield using a harvest index (Osborne et al, 2007).…”

Section: The Glam Crop Modelmentioning

confidence: 99%

TAMSAT-ALERT v1: a new framework for agricultural decision support

et al. 2018

View full text Add to dashboard Cite

Abstract. Early warning of weather-related hazards enables farmers, policy makers and aid agencies to mitigate their exposure to risk. We present a new operational framework, Tropical Applications of Meteorology using SATellite data and ground based measurements-AgricuLtural EaRly warning sysTem (TAMSAT-ALERT), which aims to provide early warning for meteorological risk to agriculture. TAMSAT-ALERT combines information on land-surface properties, seasonal forecasts and historical weather to quantitatively assess the likelihood of adverse weather-related outcomes, such as low yield. This article describes the modular TAMSAT-ALERT framework and demonstrates its application to risk assessment for low maize yield in northern Ghana (Tamale). The modular design of TAMSAT-ALERT enables it to accommodate any impact or land-surface model driven with meteorological data. The implementation described here uses the well-established General Large Area Model (GLAM) for annual crops to provide probabilistic assessments of the meteorological hazard for maize yield in northern Ghana (Tamale) throughout the growing season. The results show that climatic risk to yield is poorly constrained in the beginning of the season, but as the season progresses, the uncertainty is rapidly reduced. Based on the assessment for the period 2002–2011, we show that TAMSAT-ALERT can estimate the meteorological risk on maize yield 6 to 8 weeks in advance of harvest. The TAMSAT-ALERT methodology implicitly weights forecast and observational inputs according to their relevance to the metric being assessed. A secondary application of TAMSAT-ALERT is thus an evaluation of the usefulness of meteorological forecast products for impact assessment. Here, we show that in northern Ghana (Tamale), the tercile seasonal forecasts of seasonal cumulative rainfall and mean temperature, which are routinely issued to farmers, are of limited value because regional and seasonal temperature and rainfall are poorly correlated with yield. This finding speaks to the pressing need for meteorological forecast products that are tailored for individual user applications.

show abstract

Section: Satellite Data and Ground Based Measurements-agricultural Eamentioning

confidence: 99%

“…The Rainwatch-AfClix early warning system (RWX), for example, provides time 35 series of cumulative rainfall, which are compared against historical time years. Users value the facility to compare the current season against past years, finding that it enables them to intuitively gauge risk (Tarhule et al, 2009) There have been several attempts to forecast yield using crop models, driven by seasonal forecasts (Hansen and Indeje, 2004;Semenov and Doblas-Reyes, 2007). Mismatches between the scales of the input agronomical and climate data, and lack of skill of the seasonal forecasts proved challenging for these early systems (Hansen and Indeje, 2004).…”

mentioning

confidence: 99%

TAMSAT-ALERT v1: A new framework for agricultural decision support

Asfaw¹,

Black²,

Brown³

et al. 2018

Preprint

View full text Add to dashboard Cite

Abstract. Early warning of weather related hazards enables farmers, policy makers and aid agencies to mitigate their exposure to risk. We present a new operational framework, Tropical Applications of Meteorology using SATellite data and ground based measurements-AgricuLtural EaRly warning sysTem (TAMSAT-ALERT), which facilitates monitoring of meteorological risk to agriculture. TAMSAT-ALERT combines information on land surface properties, seasonal forecasts and historical weather into quantitative assessments of the likelihood of adverse weather-related outcomes, such as low yield. This 15 article describes the TAMSAT-ALERT framework and demonstrates its application to risk assessment for low maize yield in Northern Ghana. The modular design of TAMSAT-ALERT enables it to accommodate any impact/land surface model driven with meteorological data, and hence to enhance rather than displace existing operational systems. The implementation described here uses the well-established General Large Area Model for annual crops (GLAM) to provide probabilistic assessments of the meteorological hazard to maize yield in northern Ghana throughout the growing season. The results show 20 that climatic risk to yield is poorly constrained at the beginning of the season, but as the season progresses, the uncertainty rapidly reduces. The TAMSAT-ALERT methodology implicitly weights forecast and observational inputs according to their relevance to the metric being assessed. TAMSAT-ALERT can thus be used as a test-bed for the value of probabilistic seasonal forecast information. Here, we show that in northern Ghana, the regional tercile seasonal forecasts of cumulative rainfall and mean temperature, which are routinely issued to farmers, are of limited value for decision making. 25 IntroductionMany African people depend on rain-fed agriculture, and are thus vulnerable to drought, and other weather-related hazards.Anticipation of hazard enables farmers and aid agencies to plan ahead, averting disaster (Boyd et al., 2013). Here, we present a new framework for early warning of high meteorological risk to agriculture, the Tropical Applications of Meteorology using SATellite data and ground based measurements-AgricuLtural EaRly warning sysTem (TAMSAT-ALERT). TAMSAT-30 ALERT integrates assessment of climatological weather-related risk, with forecasts and real-time monitoring of environmental conditions. The framework is intended to be a decision support system, which when combined with socio-economic assessments, can be used by governmental agencies and NGOs to help farmers manage agricultural risk.The need for timely information on agricultural risk has motivated the development of a number of drought early warning systems and decision support platforms. The Rainwatch-AfClix early warning system (RWX), for example, provides time 35 series of cumulative rainfall, which are compared against historical time years. Users value the facility to compare the current season against past years, finding that it enables them to intuitively gauge risk (Ta...

show abstract

Rainwatch

Cited by 22 publications

References 4 publications

The First Forecasters’ Handbook for West Africa

The First Forecasters’ Handbook for West Africa

TAMSAT-ALERT v1: a new framework for agricultural decision support

TAMSAT-ALERT v1: A new framework for agricultural decision support

Contact Info

Product

Resources

About