Skip to main content

Dataverse

Looking for the numbers behind our science? Browse through our datasets, or search by key terms.

Providing decision-makers with timely, accurate information on climate and weather variations helps inform decisions that enhance agriculture production and mitigate or avoid harvest loss. This improves food security, lifts agriculture incomes, and increases farmers’ resilience to future shocks. While innovative approaches to generating and communicating climate information show promise, evidence gaps exist in understanding their effectiveness. The Learning Agenda on Climate Services in Sub-Saharan Africa encompassed two related efforts featured below that sought to generate and analyze new information, evidence, and learning on the effective and sustainable production, delivery, and use of climate information to improve decision-making and outcomes for rural agricultural livelihoods. This learning agenda brought together a wide range of partners to examine climate information systems from the production of national level information, to the use of tailored products by farmers and others in the agriculture sector.
Featured Dataverses

In order to use this feature you must have at least one published dataverse.

Publish Dataverse

Are you sure you want to publish your dataverse? Once you do so it must remain published.

Publish Dataverse

This dataverse cannot be published because the dataverse it is in has not been published.

Delete Dataverse

Are you sure you want to delete your dataverse? You cannot undelete this dataverse.

Find Advanced Search

21 to 30 of 50 Results
Tab-Delimited - 1.3 MB - MD5: d27579e764192350ef0222621be7ff30
Data
Aug 3, 2021 - Panel Data Dataverse
Chiputwa, Brian; Makui, Parmutia, 2021, "Climate Information Services Research Initiative (CISRI) Evaluation in Senegal: Panel Data", https://doi.org/10.34725/DVN/WUUURU, World Agroforestry - Research Data Repository, V1, UNF:6:4+WF58IyyGAzlcXHJD/ckg== [fileUNF]
Combined panel data for the baseline and end line surveys
Tab-Delimited - 1.7 MB - MD5: 5207a51a03be449c51e65d21be9ee50e
Data
Combined indicators data file
Aug 2, 2021 - Baseline Survey Dataverse
Chiputwa, Brian; Wainaina, Priscilla; Nakelse, Tebila; Makui, Parmutia; Zougmoré, Robert; Ndiaye, Ousmane; Minang, Peter, 2021, "Replication Data for: Transforming climate science into usable services: The effectiveness of co-production in promoting uptake of climate information by smallholder farmers in Senegal", https://doi.org/10.34725/DVN/JTF31N, World Agroforestry - Research Data Repository, V1, UNF:6:q9HPu4S77ND3/NtEI/2wPw== [fileUNF]
Does the provision of weather and climate information services (WCIS) enhance farmer’s use of forecasts in informing farm decisions? This paper assesses the effectiveness of the Multi-disciplinary Working Group (MWG) – a WCIS co-production initiative in Senegal in influencing far...
Aug 2, 2021 - Baseline Survey Dataverse
Chiputwa, Brian; Wainaina, Priscilla; Makui, Parmutia; Nakelse, Tebila; Zougmoré, Robert; Ndiaye, Ousmane, 2021, "Replication Data for: Evaluating the Impact of the Multidisciplinary Working Group Model on Farmers’ Use of Climate Information Services in Senegal", https://doi.org/10.34725/DVN/KPIS4B, World Agroforestry - Research Data Repository, V1, UNF:6:q9HPu4S77ND3/NtEI/2wPw== [fileUNF]
Climate variability and change have been identified as major threats to important sectors that drive economic growth and sustainable development in Africa. The provision of tailor-made climate information services is increasingly gaining importance. It has been widely touted as a...
Add Data

Sign up or log in to create a dataverse or add a dataset.

Share Dataverse

Share this dataverse on your favorite social media networks.

Link Dataverse
Reset Modifications

Are you sure you want to reset the selected metadata fields? If you do this, any customizations (hidden, required, optional) you have done will no longer appear.

Contact World Agroforestry (ICRAF) Support

World Agroforestry (ICRAF) Support

Please fill this out to prove you are not a robot.

+ =