Terms of Reference: Climatology Expert for Saadaal Early Warning System

Terms of Reference: Climatology Expert for Saadaal Early Warning System

Project Title: Saadaal Early Warning System

Project Location: Somalia

Project Duration: Unspecified

Date Issued: 3rd November 2024

Background
Shaqodoon Organization is a non-profit committed to economic empowerment and community development in Somalia. Our mission is to alleviate poverty and foster sustainable livelihoods through programs in entrepreneurship support, vocational training, and job creation. To further our efforts, we are finalizing the development of the Saadal Early Warning System (SEWS). To enhance the accuracy and effectiveness of SEWS, we require an expert climatology consultant to improve data reporting and ensure that the system provides accurate alerts based on reliable climate data, particularly for the Southwest State of Somalia.

Objectives
The primary objective of this consultancy is to provide expert climatology support for enhancing the accuracy of climate-related reporting in the Saadal Early Warning System. The climatology expert will enhance the accuracy of climate data used in SEWS, ensuring that indicators are integrated properly, and that alerts are based on reliable climate data. This includes ensuring that data collection methods and analysis are accurate, relevant indicators are appropriately integrated, and system outputs provide timely, precise alerts and warnings based on climate data for the Southwest State.

Scope of Work
1. Data Validation and Accuracy

·         Objective: Ensure the accuracy and reliability of climate data within the upgraded SEWS.

·         Tasks:

o   Source Validation: Confirm the accuracy of climate data sources currently in use, with emphasis on indicators like rainfall, drought index, and river flooding.

o   AI Report Validation: Review and validate AI-generated climate reports, suggesting calibration adjustments for improved accuracy in local conditions.

o   Indicator Expansion: Recommend new climate indicators, such as extreme temperature events or seasonal variability, for inclusion in SEWS to expand monitoring capabilities.

2. System Development Support

·         Objective: Address integration challenges for climate data in collaboration with the software team.

·         Tasks:

o   Development Collaboration: Work with software developers to troubleshoot issues related to climate data integration and ensure data preprocessing meets system requirements.

o   Data Source Connections: Establish partnerships with local climate authorities, meteorological agencies, and organizations like SWALIM for access to reliable, real-time climate data.

o   Real-Time Data Integration: Identify and integrate real-time climate data sources (e.g., rainfall and temperature) to enhance the system’s responsiveness to changing conditions.

3. System Enhancement and Optimization

·         Objective: Improve SEWS's climate data capabilities and address limitations.

·         Tasks:

o   Data Gap Analysis: Identify gaps in current climate data, such as incomplete or low-resolution datasets, and propose solutions, including supplementary satellite data sources.

o   Predictive Warning Enhancements: Implement updates to improve the precision of climate-related warnings by adjusting prediction models based on refined climate inputs.

4. Equipment Integration

·         Objective: Oversee the integration of new climate measurement equipment to enhance SEWS’s data collection capabilities.

·         Tasks:

o   Automatic Weather Station Setup: Assist in configuring and integrating the automatic weather station, ensuring data logger compatibility with SEWS and calibrating for multiple meteorological parameters.

o   Water Sensor Installation: Support the installation and integration of water level sensors (Types 1 and 2), ensuring data output (RS485 or 4-20mA) aligns with SEWS input requirements.

o   Data Pipeline Development: Collaborate with the development team to establish data pipelines that streamline input from new equipment into SEWS, enabling real-time updates for meteorological and hydrological data.

. Data Diversification and Interpretation

·         Objective: Expand SEWS’s climate data sources for a comprehensive environmental assessment.

·         Tasks:

o   Dataset Recommendations: Recommend additional climate datasets, such as water availability, wind patterns, soil moisture, and sea surface temperatures, to provide a broader perspective on environmental risks.

o   Integration Strategy: Outline approaches for integrating these datasets into SEWS, specifying their relevance to key system indicators and potential impact on user alerts.

6. Technical Assistance and Training

·         Objective: Provide guidance on the interpretation and application of climate data in the system.

·         Tasks:

o   Workshop Attendance and Participation: Attend workshops to present insights on climate data application within SEWS and provide hands-on guidance for stakeholders.

o   System Installation Support: Provide technical support during system installations, including setting up climate data inputs and calibrating new equipment.

o   Training and Documentation: Conduct training sessions to improve understanding of how climate data informs early warning outputs, and create comprehensive documentation on system use and data interpretation.

7. Climate Model Calibration and Advisory

·         Objective: Enhance SEWS’s predictive capacity through calibrated climate models.

·         Tasks:

o   AI Calibration: Work with the AI team to adjust model parameters for better climate predictions, considering regional environmental factors.

o   Predictive Modeling Alternatives: Recommend alternative climate forecasting techniques, such as statistical climate models or machine learning methods, to support and cross-validate AI-driven warnings.

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Interested parties are invited to submit their proposals to [email protected], which should include the following:

• Technical Approach: A detailed explanation of the proposed approach for enhancing a basic early warning system This should outline the methodology for achieving each objective, including how you will address data acquisition, system integration with new data sources, and accuracy improvements.
• Experience: Case studies or examples of relevant work, particularly in climatology, early warning systems, and integration of environmental data into digital platforms. Emphasis on experience working with data sources such as SWALIM, ICPAC, and similar entities is encouraged.

Evaluation Criteria

Proposals will be evaluated based on the following criteria:

• Technical Merit: The soundness and feasibility of the proposed approach, particularly in relation to climate data accuracy, system optimization, and integration with relevant datasets.
• Experience: Relevant experience in climatology, environmental data analysis, and integration with early warning systems. Experience working with organizations like SWALIM, FSNAU and ICPAC is highly valued.