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MHEWS in LDCs

📈 ANALYTICAL REPORT

HAZARD MONITORING & FORECASTING IN LDCs


Insights from 2023 EW4All Rapid Assessment and Country Hydromet Diagnostics in 26 NMHSs

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Based on the 2024 report on the Status of Multi-Hazard Early Warning Systems (MHEWS) in the Least Developed Countries (LDCs), this analysis delves into the implementation capabilities and challenges of National Hydrological and Meteorological Services (NMHSs) in 26 LDCs1. It examines governance frameworks, institutional mechanisms, resource availability, technical capacities, and infrastructure support.

The findings reveal significant gaps and obstacles, offering a detailed overview of the current state of early warning systems in LDCs. They emphasize the need for coordinated support to improve the systems' effectiveness in reducing the impacts of hydrometeorological hazards.

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1. Governance and Legislative Framework
📊 Various types of legislative frameworks give NMHSs general mandates to monitor, forecast and produce warnings for the hydrometeorological hazards affecting their countries. However, many fall short of establishing clear roles and responsibilities for the institutions involved in these processes:

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Figure 1 - Extent to which MHEWS roles and responsibilities are defined in the 26 LDCs
  • While 77% of countries examined have some type of legislative instrument covering early warning systems, only 35% clearly define the roles and responsibilities of all institutions involved in national early warning systems (Figure 1).
     
  • These governance gaps often hinder coordination between national agencies, leading to competition and duplication.

 

2. Institutional Mechanisms and Operational Cooperation for MHEWS
📊 Effective monitoring of hydrometeorological hazards requires integrating meteorological, hydrological, coastal, and marine observations across multiple agencies, making operational data exchange essential:

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Figure 2 - Extent to which alerting procedures are established in the 26 LDCs
  • Most LDCs have established a high-level national DRR coordination mechanism, with 73% of NMHSs participating. However, 39% of NMHSs lack observation data from other institutions, and only 12% have formal mechanisms for data exchange to support monitoring and forecasting (Figure 2). 
     
  • Only 23% of 26 LDCs have established a national integrated MHEWS. Consequently, over 70% of NMHSs reviewed lack data on hazard vulnerability and exposure, and 69% lack standard alerting procedures, hindering effective warning dissemination.

 

3. NMHSs Operational Capacity: Hazard Monitoring and Forecasting
📊 Most NMHSs in LDCs struggle with staffing shortages, competency gaps, and non-competitive remuneration, leading to brain drain, especially among ICT professionals, and difficulty hiring qualified local staff due to inadequate higher education programs: f3

Figure 3 - Percentage of NMHS budget allocated to staffing in the 26 LCDs
  • All 26 NMHSs face funding challenges, primarily using limited budgets for staffing, severely limiting their ability to sustain operations and provide effective early warnings.
     
  • Indeed, two-thirds of the 26 NMHSs reviewed spend more than half of their budget to finance their personnel (Figure 3).

 

📊 Financial and human resource challenges severely impact NMHSs' ability to monitor and forecast effectively, exacerbated by observation gaps and high rates of inoperable stations, which hinder hazard monitoring and data quality due to maintenance capacity limitations: f4

Figure 4 - NMHSs' capacity to perform regular maintenance and calibration of their observation infrastructure networks in 26 LDCs
  • All LDCs reviewed face challenges with observation gaps in their meteorological observing network.
     
  • On average, 45% of observation stations are inoperable. Additionally, 58% of NMHSs lack capacity for necessary calibration and maintenance, with 38% partially able to address infrastructure needs (Figure 4).

 

📊 Effective monitoring systems for floods, droughts, and other hazards rely on diverse data sources beyond meteorological observations, including hydrological, marine, and historical data, as well as ancillary information like digital elevation models. However, these critical capabilities are often deficient in LDCs, as highlighted by WMO assessments (CHD, EW4All Pillar 2 Rapid Assessment): f5

Figure 5 - Maximum download speed available at the national forecasting centre in 26 LDCs
  • NMHSs use satellite data and numerical weather predictions from WIPPS2 Global and Regional Meteorological Centres for forecasting, relying on reliable, high-speed internet access crucial for their operations.
     
  • Many NMHSs in LDCs lack reliable internet access: 60% have unstable connections, and 48% face slow speeds (≤ 10 Mbps) (Figure 5).

 

📊 The Early Warning for All Initiative emphasizes using impact-based forecasting (IBF) for effective early action. However, IBF remains challenging for developing NMHSs: f6

Figure 6 - Implementation of impact-based forecasting principles and techniques for the provision of impact-based warning services by NMHSs in 26 LDCs
  • Of the 26 NMHSs, only 23% have started to implement the principles of impact-based forecasting to produce their warnings and advisories (Figure 6).
     
  • Implementing IBF poses substantial challenges for developing NMHSs due to its complex technical requirements and data integration.

 

Developing NMHSs in developing countries face challenges in IBF due to capacity gaps and resource constraints. Sustainable IBF capacity building requires strengthening NMHSs' institutional and operational capabilities across the hydromet value chain.


Conclusion

The analysis underscores the critical need for comprehensive and targeted interventions to fortify the hazard monitoring systems of NMHSs across all Earth domains in LDCs. Sustained and coordinated support is imperative to enable these institutions to not only enhance their monitoring capabilities but also to develop the capacity for providing and disseminating impact-based warnings in collaboration with pertinent national stakeholders. Moreover, establishing clear governance frameworks and fostering close operational collaboration are foundational pillars for the effective implementation of MHEWS.

Addressing the identified gaps in legislative clarity, operational cooperation, and institutional capacity is paramount to bolstering the resilience of LDCs against the disproportionate impact of natural hazards. Only through concerted efforts and strategic investments can LDCs mitigate the risks posed by these hazards and build more resilient communities for a safer and more sustainable future.


Footnotes:

  1. These are the 26 countries included in the analysis: Bangladesh, Burkina Faso, Cambodia, Chad, Comoros, Djibouti, Ethiopia, Haiti, Kiribati, Lao People’s Democratic Republic, Liberia, Madagascar, Malawi, Mali, Mozambique, Nepal, Niger, Rwanda, Senegal, Solomon Islands, Somalia, South Sudan, Sudan, Timor-Leste, Uganda, United Republic of Tanzania.

  2. The WMO Integrated Processing and Prediction System (WIPPS) is the worldwide network of centres operated by WMO Members that make available numerical weather, climate and oceanic prediction products. WIPPS is structured in a three-level system, whereby World Meteorological Centres, Regional Specialized Meteorological Centres, and National Meteorological Centres all contribute to and benefit from the system in accordance with their needs and ability (see Manual on WIPPS, WMO-No. 485, and Guide on WIPPS, WMO-No.305). The list of designated WIPPS Centres and their products are available at: WIPPS Web Portal (arcgis.com).