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User manual: How to use Agvisely to generate climate service advisories for livestock in Bangladesh

T.S Amjath-Babu Timothy Joseph Krupnik (2023, [Libro])

The Agvisely digital service for livestock integrates location-specific meteorological forecasts generated by the Bangladesh Meteorological Department (BMD) with species specific biological thresholds for weather variables (Temperature, rainfall, and temperature-humidity index (THI). When a biological threshold is to be breached in next five days' forecast, the system automatically generates location-specific management advice for livestock farmers. Advisories are based on a decision tree developed by the Bangladesh Livestock Research Institute (BLRI) and CIMMYT. Agvisely is a smart phone app and web-based service developed by the International Maize and Wheat Improvement Center (CIMMYT) CIMMYT with the support of USAID, securing the Food Systems of Asian Mega- Deltas (AMD) for Climate and Livelihood Resilience and the Transforming Agrifood Systems in South Asia (TAFSSA) initiatives in collaboration with Bangladesh Dept. of Agricultural Extension (DAE) and Bangladesh Meteorological Department (BMD).

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE SERVICES LIVESTOCK DIGITAL TECHNOLOGY

Review of Nationally Determined Contributions (NCD) of Kenya from the perspective of food systems

Tek Sapkota (2023, [Documento de trabajo])

Agriculture is one of the fundamental pillars of the 2022–2027 Bottom-up Economic Transformation Plan of the Government of Kenya for tackling complex domestic and global challenges. Kenya's food system is crucial for climate change mitigation and adaptation. Kenya has prioritized aspects of agriculture, food, and land use as critical sectors for reducing emissions towards achieving Vision 2030's transformation to a low-carbon, climate-resilient development pathway. Kenya's updated NDC, as well as supporting mitigation and adaptation technical analysis reports and other policy documents, has identified an ambitious set of agroecological transformative measures to promote climate-smart agriculture, regenerative approaches, and nature-positive solutions. Kenya is committed to implementing and updating its National Climate Change Action Plans (NCCAPs) to present and achieve the greenhouse gas (GHG) emission reduction targets and resilience outcomes that it has identified.

CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE CHANGE GREENHOUSE GAS EMISSIONS FOOD SYSTEMS LAND USE CHANGE AGRICULTURE POLICIES DATA ANALYSIS FOOD WASTES

Calibrated multi-model ensemble seasonal prediction of Bangladesh summer monsoon rainfall

Nachiketa Acharya Carlo Montes Timothy Joseph Krupnik (2023, [Artículo])

Bangladesh summer monsoon rainfall (BSMR), typically from June through September (JJAS), represents the main source of water for multiple sectors. However, its high spatial and interannual variability makes the seasonal prediction of BSMR crucial for building resilience to natural disasters and for food security in a climate-risk-prone country. This study describes the development and implementation of an objective system for the seasonal forecasting of BSMR, recently adopted by the Bangladesh Meteorological Department (BMD). The approach is based on the use of a calibrated multi-model ensemble (CMME) of seven state-of-the-art general circulation models (GCMs) from the North American Multi-Model Ensemble project. The lead-1 (initial conditions of May for forecasting JJAS total rainfall) hindcasts (spanning 1982–2010) and forecasts (spanning 2011–2018) of seasonal total rainfall for the JJAS season from these seven GCMs were used. A canonical correlation analysis (CCA) regression is used to calibrate the raw GCMs outputs against observations, which are then combined with equal weight to generate final CMME predictions. Results show, compared to individual calibrated GCMs and uncalibrated MME, that the CCA-based calibration generates significant improvements over individual raw GCM in terms of the magnitude of systematic errors, Spearman's correlation coefficients, and generalised discrimination scores over most of Bangladesh areas, especially in the northern part of the country. Since October 2019, the BMD has been issuing real-time seasonal rainfall forecasts using this new forecast system.

Multi-Model Ensemble Seasonal Forecasting CIENCIAS AGROPECUARIAS Y BIOTECNOLOGÍA CLIMATE SERVICES FORECASTING MONSOONS