Integrated Projects Archives - climateservices.it CNR-IBE https://climateservices.it/categoria-progetti/progetti-integrati/ A CNR-IBE Initiative Mon, 17 Nov 2025 10:47:06 +0000 en-US hourly 1 https://wordpress.org/?v=6.9.1 https://climateservices.it/wp-content/uploads/2020/07/cropped-IBE_CS_FAVICON-32x32.png Integrated Projects Archives - climateservices.it CNR-IBE https://climateservices.it/categoria-progetti/progetti-integrati/ 32 32 Building Local Capacity through Cascading Agrometeorological Training in Niger A scalable model from the PRIMESA initiative https://climateservices.it/poster/building-local-capacity-through-cascading-agrometeorological-training-in-niger-a-scalable-model-from-the-primesa-initiative/ Mon, 17 Nov 2025 10:47:06 +0000 https://climateservices.it/?post_type=poster&p=16047 Within the framework of the PRIMESA initiative, funded by the Italian Agency for Development Cooperation (AICS), a structured multi-scale training program is being
implemented in Niger to enhance the use of agrometeorological information for climate-resilient agriculture. In collaboration with the National Directorate of
Meteorology (DMN) and the Ministry of Agriculture of Niger, this training scheme builds on lessons learned from the earlier ANADIA project and aims to reach farmers through a cascading training model.
The program begins at the national level, where international experts train technical staff from the DMN and the Ministry of Agriculture on key topics such as the use
of low-cost rain gauges (pluviomètres paysans), seasonal forecasts, and 10-day agrometeorological bulletins to support decision-making in agronomic crop
management. These national trainers then deliver training at the regional level to agricultural extension officers, who subsequently work directly with farmers in the
field.
The approach combines in-person sessions, practical demonstrations, printed and digital materials, and communication via rural radio and WhatsApp groups during
the growing season. Preliminary evidence shows that trained farmers not only better understand weather and climate information but also apply it more effectively
leading to improved yields.
This experience underscores the importance of co-developing training content with local actors and creating robust, multi-level partnerships to ensure that
meteorological information is not only disseminated but understood and used effectively at the community level. The model developed in Niger offers a replicable
approach for other regions facing similar challenges in agricultural adaptation and training dissemination.

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]]> From Training to Transformation: Co-Developing Forecasting Capacities for Early Warning in West Africa https://climateservices.it/poster/from-training-to-transformation-co-developing-forecasting-capacities-for-early-warning-in-west-africa/ Mon, 17 Nov 2025 10:34:04 +0000 https://climateservices.it/?post_type=poster&p=16039 In Sub-Saharan Africa, the operational implementation of regional Numerical Weather Prediction (NWP) models remains a significant challenge due to limited financial and technical resources, insufficient understanding of tropical weather systems, and the inadequate performance of global models in simulating rainfall over the region. Although recent developments—such as cloud computing and convection-permitting models—offer new opportunities, forecasting intense rainfall events, often linked to mesoscale convective systems, continues to be a major limitation for effective early warning systems.
Within the framework of the SLAPIS Sahel project, a development cooperation initiative, the Regional Training Center in Italy designed and implemented a blended and integrated training programme aimed at enhancing the capacities of the National Meteorological Services (NMSs) of Niger and Burkina Faso. The objective was to enable local forecasters, modelers, and IT personnel to operationalize regional NWP chains in support of hydrometeorological early warning systems.

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]]> Slapis Sahel Numerical Weather Prediction https://climateservices.it/progetto/slapis-sahel-numerical-weather-prediction/ Wed, 18 Jun 2025 10:19:06 +0000 https://climateservices.it/?post_type=progetto&p=15216 SLAPIS SAHELProject Numerical Weather Predictionin SLAPIS Sahel One of the key objectives of the SLAPIS Sahel project is to strengthen national capacities in Numerical Weather Prediction (NWP) as a support for hydrological early warning, particularly for flash floods and flooding events along the Sirba River and the Niger River. The national meteorological agencies of Niger […]

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SLAPIS SAHEL
Project

Numerical Weather Prediction
in SLAPIS Sahel

One of the key objectives of the SLAPIS Sahel project is to strengthen national capacities in Numerical Weather Prediction (NWP) as a support for hydrological early warning, particularly for flash floods and flooding events along the Sirba River and the Niger River.

The national meteorological agencies of Niger (DMN) and Burkina Faso (ANAM) strategically decided to develop NWP chains based on the Weather Research and Forecasting (WRF) model. WRF is a widely used regional model for both operational weather forecasting and research, developed primarily by the National Center for Atmospheric Research (NCAR) in the United States.

To this end, Niger and Burkina Faso receive support from IBE-CNR and, through it, from the LaMMA Consortium — joint initiative between CNR and the Tuscany Region, which provides regional meteorological services in Italy.

Capacity Building Timeline

In the framework of SLAPIS Sahel project, a series of capacity building actions were carried out  to build local expertise on WRF and numerical forecasting.

27 Feb – 3 Mar 2023

Niamey (Niger)

Capacity building for the staff of the Direction de la Météorologie Nationale in Numerical Weather Prediction.

Duration: 5 days — Participants: 15 (Niger)

27 Feb – 3 Mar 2023
13–16 Feb 2024

Niamey (Niger)

Action-based training: Performance and tuning of the Weather Research and Forecasting (WRF) model.

Duration: 4 days — Participants: 24 (Niger and Burkina Faso).

13–16 Feb 2024
13 Nov 2024 – 12 Nov 2025

Florence (Italy)

Long-term training on Numerical Weather Prediction for early flood warning.

Duration: 12 months — Participants: 2 (Niger and Burkina Faso)

13 Nov 2024 – 12 Nov 2025
16 April 2025

Ouagadougou (Burkina Faso)

WRF product validation workshop.

Duration: 1 day — Participants: 12 (Burkina Faso)

16 April 2025
17 April 2025

Niamey (Niger)

WRF product validation workshop.

Duration: 1 day — Participants: 18 (Niger)

17 April 2025
23 April 2025

Niamey (Niger)

Rainfall estimation merging and operational integration of WRF Workshop. Duration: 1 day — Participants: 7 (Niger)
23 April 2025
19 May 2025

Webinar

Action-oriented seminar on the MOLOCH operational model.

Duration: 1 day — Participants: 14 (Niger and Burkina Faso)

19 May 2025
11 June 2025

Webinar

Presentation of the web interface for accessing operational MOLOCH and WRF forecasts.

Duration: 1 day — Participants: 7 (Niger and Burkina Faso)

11 June 2025
Slapis Sahel - training in Florence
Slapis Sahel - training in Florence
Slapis Sahel Project - Photo of the group

Operational Forecasting Chains

The establishment of operational NWP systems in Niger and Burkina Faso stands as a concrete result of SLAPIS Sahel. Tailored to national needs, the two chains strengthen local forecasting capabilities and support early warning efforts.

Image of Table comparing model, resolution and daily runs - Niger and Burkina Faso
Flag of Niger
With support from SLAPIS Sahel, DMN Niger implemented an operational WRF chain producing two daily runs (00 and 12 UTC)with a 4 km spatial resolution. Boundary conditions are derived from the GFS global model — of the National Centre for Environmental Prediction (NCEP) at 0.25-degree resolution.
Flag of Burkina Faso

Since 2018, ANAM has been developing its WRF-based forecast chain through initiatives such as the HYDROMET Project (World Bank) and CREWS Project (WMO). Since June 2023, WRF (ARW) has been operational in Burkina Faso with two runs per day at 9 km and 3 km resolutions.

Model Evaluation & Verification

Methodology

Due to different configurations and the absence of systematic evaluation, a verification process was initiated in collaboration with LaMMA and supported through two research fellowships in Florence. 

Historical forecasts (hindcasts) were generated for July–August–September 2023 and 2024, comparing WRF-Niger, WRF-Burkina, and GFS.

Simulations were run on an 8-node Intel Xeon Gold 6130 cluster (256 cores total) with the latest WRF version. The simulation domain covered Niger, Burkina Faso, extended southward to the Gulf of Guinea and eastward to Chad. Initialization data were sourced from the GFS global model, and 36-hour simulations were launched from 18 UTC. The initial 6-hour spin-up period was excluded from the analysis. Comparisons were performed using both satellite estimates (00h–00h accumulation) and station data (06h–06h accumulation).

Results

Deterministic Metrics (ME, MAE, Correlation)

Deterministic metrics — including Mean Error (ME), Mean Absolute Error (MAE), and correlation — indicate that WRF-Niger tended to perform better for low rainfall (≤5 mm/day), while WRF-Burkina showed higher scores for heavier precipitation.
Deterministic Scores - Project Slapis Sahel
Infograph WRF Model performance by rainfall intensity

Fraction Skill Score (FSS)

Fractional Skill Score (FSS): WRF-Burkina showed better skill in producing significant forecasts at smaller spatial scales for high rainfall accumulations. (Figure 2)
Fractional Skill Scores - Project Slapis Sahel
Fractional Skill Scores - Project Slapis Sahel

Case Study Analysis

The verification included specific case studies — such as the events of 20 and 30 August 2024 — to illustrate how the models performed under particular meteorological conditions. These cases (Figure 3) were used to assess the models’ ability to capture the spatial and temporal characteristics of precipitation, with a focus on convective rainfall.

Precipitation comparison 20/08/2024 - Project Slapis Sahel

General Comparison

Overall, both WRF models (Burkina Faso and Niger) demonstrated better performance than the global GFS model.

Future Perspectives

As a perspective for improvement, future tests will aim to run both WRF models using open-access data from the European Centre for Medium-Range Weather Forecasts (ECMWF).

Parallel Backup Chain and MOLOCH

In order to ensure a backup forecasting chain in case of outages affecting the operational systems of Niger and Burkina Faso during the rainy season, a parallel WRF chain was implemented on LaMMA’s cluster, using the same configuration adopted by DMN.

screenshot of the operational chain - Slapis Sahel project

What is Moloch?

Model Overview

MOLOCH (MOdel LOCal H-coordinates) is a non-hydrostatic, convection-resolving numerical weather prediction model developed by the Institute of Atmospheric Sciences and Climate (CNR-ISAC) and used by the LaMMA Consortium. It features an Arakawa C-grid, a hybrid terrain-following coordinate system, and updated radiation and soil schemes. The microphysics scheme includes five hydrometeors and does not use graupel parametrization, unlike some WRF schemes.

– CORE: Non-hydrostatic, fully compressible, convection-resolving
– GRID: Arakawa C-grid, latitude-longitude, hybrid terrain-following
– RADIATION: ECMWF scheme (updated 2024)
– TURBULENCE: E–L Kinetic Energy, 1.5-order closure
– SOIL: 6-level DROPA scheme
– CUMULUS SCHEME: Kain-Fritsch

MOLOCH is widely used for temperature and precipitation forecasts in Italy, Spain, and Greece. The latest version is available on GitLab:
🔗 https://gitlab.com/isac-meteo/globo-bolam-moloch

In addition, an operational MOLOCH chain (what is MOLOCH? see box above) was also deployed to provide numerical forecasts for West Africa.  As a dedicated test comparing MOLOCH and WRF in the region showed that MOLOCH is two to three times faster than WRF.

Moloch as Innovative Solution

The deployment of MOLOCH in the Sahel is one of the innovative aspects of this study: the model has traditionally been used in mid-latitude regions (Davolio et al., 2020), and very few attempts had previously been made to run it in tropical environments using explicit convection schemes.

Thanks to its faster runtime, MOLOCH was able to simulate a wider domain covering all of West Africa at a spatial resolution of 3 km.

Image comparing two models Moloch and WRF

click the image to enlarge

Forecast Products & Visualization Tools

A web interface was developed to visualize outputs from both WRF and MOLOCH. This tool is available to DMN and ANAM forecasters to support daily operations and gather feedback on content and format improvements.

  1. Model Output Viewer
    This section provides access to the outputs of the WRF and MOLOCH models.
    Currently, both models are initialised using data from the GFS (Global Forecast System). Two forecast runs are available per day: one at 00 UTC and one at 12 UTC. 
    In the near future, additional forecast chains based on ECMWF Open Data are planned to be implemented.
  2. Archive Access
    Archived model outputs are available both as images and in GRIB format. These resources are intended to support daily bulletins as well as verification analyses and retrospective studies.
  3. Model Evaluation
    This section will collect performance assessments of WRF and MOLOCH, comparing model outputs with observed data from in-situ stations or satellite sources.

At the bottom of the page, a table summarises key characteristics of the two models, including resolution, microphysics schemes, convection treatment, domain, and input data sources.

Screenshot of the application developed in the project Slapis Sahel - Precipitation map Screenshot of the application developed in the project Slapis Sahel - Wind map

Preview of the Moloch model - Hourly precipitation and Hourly Mean Temperature

MOLOCH model hourly precipitation mm (6 km resolution), initialized with ECMWF IFS data

MOLOCH model hourly mean 2 meters temperature °C (6 km resolution), initialized with ECMWF IFS data

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]]> DEM Generation from Multi-View Satellite Images in Sub-Sahel Region https://climateservices.it/publication/dem-generation-from-multi-view-satellite-images-in-sub-sahel-region/ Fri, 13 Jun 2025 07:37:12 +0000 https://climateservices.it/?post_type=publication&p=15194 Floods are causing a significant loss of human lives and valuable resources in West Africa. In particular, Niger and Burkina Faso were highly affected areas in past years. In order to predict flood, an accurate Digital elevation model (DEM) is required for flood mapping. At the studied area in Niger, up to this date, the […]

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]]> Floods are causing a significant loss of human lives and valuable resources in West Africa. In particular, Niger and Burkina Faso were highly affected areas in past years. In order to predict flood, an accurate Digital elevation model (DEM) is required for flood mapping. At the studied area in Niger, up to this date, the LiDAR DEMs are scarcely available, and the only available DEMs are global DEMs like global SRTM DEMs with a resolution of 10m. These global DEMs are not accurate enough to be used for flood mapping. So, in this context, this study investigates the potential of multidate, multi-view stereo pairs PlanetScope images for the generation of DEM. Three DEMs were generated from images with slightly different view angles to see the effect of view angles of images on 3D modelling. One of the DEM generated by PlanetScope images was compared with DEM generated by high-resolution drone imagery and shows the normalized Median of Absolute Deviation (NMAD) of the elevation differences of 10m. Results show that planetScope images are useful assets for generating multiple DEMs due to their high temporal resolution. Such DEMs could be extremely useful for studying dynamic phenomena or monitoring disaster events like floods.

Keywords: Remote Sensing, DEM Generation, Cubesat Satellites, Stereo-Modelling, 3D Modelling

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]]> Bridging the communication gap in agrometeorological services: Enhancing the uptake and effectiveness for users in developing countries https://climateservices.it/publication/bridging-the-communication-gap-in-agrometeorological-services-enhancing-the-uptake-and-effectiveness-for-users-in-developing-countries/ Wed, 04 Jun 2025 14:50:50 +0000 https://climateservices.it/?post_type=publication&p=15116 Over the past decades, advancements in agrometeorological monitoring and forecasting have been driven by technology, infrastructure, and capacity building. Literature highlights that agrometeorological services support agricultural decision-making, boosting farmers’ resilience and income globally. However, challenges in communication and dissemination limit their effectiveness, particularly for smallholder farmers in remote areas. The problem extends beyond media type […]

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]]> Over the past decades, advancements in agrometeorological monitoring and forecasting have been driven by technology, infrastructure, and capacity building. Literature highlights that agrometeorological services support agricultural decision-making, boosting farmers’ resilience and income globally. However, challenges in communication and dissemination limit their effectiveness, particularly for smallholder farmers in remote areas. The problem extends beyond media type and format to issues of accessibility, comprehensibility, and users’ trust. While technology has enabled faster dissemination, there is a risk of new services being technology-centered rather than user-focused. This non-systematic literature review delves into effective communication strategies for agrometeorological information in developing countries, reviewing existing knowledge and presenting case studies. It addresses how to ensure access to information, identify efficient communication channels, use inclusive technologies, enhance users’ understanding, make information actionable, and gather feedback on information effectiveness. Stakeholders’ engagement methods include a variety of participatory approaches and iterative monitoring, evaluation and learning processes. The choice of communication channels significantly affects information reach. Despite the rise of ICT, challenges in access and understanding persist, especially for marginalized groups, making simple communication technologies like rural radios still crucial for last-mile dissemination. The review emphasizes that no single communication approach fits all situations. Key principles of coproduction and user engagement in climate services are essential for effective agrometeorological communication. Future directions include enhancing the legitimacy and salience of services by integrating local knowledge, expanding scope to include herders and off-farm stakeholders, building capacity among intermediaries and users, soliciting feedback, and fostering public–private partnerships for scaling and sustainability.

Keywords: Agricultural Meteorology; Communication; Climate Services; Co-production; Stakeholders engagement; Best practices

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]]> Flood risk assessment of agricultural areas along the Niger river upstream Niamey https://climateservices.it/publication/flood-risk-assessment-of-agricultural-areas-along-the-niger-river-upstream-niamey/ Wed, 30 Apr 2025 13:24:37 +0000 https://climateservices.it/?post_type=publication&p=15069 Much of the food supplied to the city of Niamey (1.5 million inhabitants), the capital of Niger, comes from 150 large commercial horticultural sites and 10 vast irrigated perimeters distributed along the Niger River upstream of the city. These areas are threatened by floods, such as the one that devastated paddy fields and horticultural areas […]

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]]> Much of the food supplied to the city of Niamey (1.5 million inhabitants), the capital of Niger, comes from 150 large commercial horticultural sites and 10 vast irrigated perimeters distributed along the Niger River upstream of the city. These areas are threatened by floods, such as the one that devastated paddy fields and horticultural areas in August 2024. To address this problem, a detailed assessment of the river flood risk, expressed in monetary terms, is urgently needed to complement the early flood warning system.

This activity is part of the SLAPIS Sahel project, which aims to develop a more general framework for flood risk management applied to the transboundary Sirba river basin and the nearby Niger river, with the active participation of the water authorities of Burkina Faso and Niger. In this context, this work focuses on the flood risk analysis of the Niger River upstream of the city of Niamey in a multidisciplinary way. To this aim, a hydrological study of the basin was carried out, taking into account the two types of floods that affect the area: floods due to the local rainy season, and dry season events caused by floods upstream in the Guinea-Conakry basin. A hydraulic model was then used to map the extent of flooding, allowing to study the impact and expected damage to the target areas. Daily satellite imagery was used to assess the extent of recent floods and the characteristics of the exposed areas. All these activities were repeated for both the wet and dry seasons, as agricultural production changes and the impacts are different.

This analysis supports the cost-benefit assessment of possible defense structures.

 

 

Link to EGU presentation EGU25_PICO_SLAPIS

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]]> Flood Damage Risk Mapping Along the River Niger: Ten Benefits of a Participated Approach https://climateservices.it/publication/flood-damage-risk-mapping-along-the-river-niger-ten-benefits-of-a-participated-approach/ Wed, 30 Apr 2025 13:17:14 +0000 https://climateservices.it/?post_type=publication&p=15067 Flood risk mapping is spreading in the Global South due to the availability of high-resolution/high-frequency satellite imagery, volunteered geographic information, and hydraulic models. However, these maps are increasingly generated without the participation of exposed communities, contrary to the Sendai Framework for Disaster Risk Reduction 2015–2030 priorities. As a result, the understanding of risk is limited. […]

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]]> Flood risk mapping is spreading in the Global South due to the availability of high-resolution/high-frequency satellite imagery, volunteered geographic information, and hydraulic models. However, these maps are increasingly generated without the participation of exposed communities, contrary to the Sendai Framework for Disaster Risk Reduction 2015–2030 priorities. As a result, the understanding of risk is limited. This study aims to map flood risk with citizen science complemented by hydrology, geomatics, and spatial planning. The Niger River floods of 2024–2025 on a 113 km2 area upstream of Niamey are investigated. The novelty of the work is the integration of local and technical knowledge in the micro-mapping of risk in a large area. We consider risk the product of a hazard and damage in monetary terms. Focus groups in flooded municipalities, interviews with irrigation perimeter managers, and statistical river flow and rainfall analysis identified the hazard. The flood plain was extracted from Sentinel-2 images using MNDWI and validated with ground control points. Six classes of assets were identified by visual photo interpretation of very high-resolution satellite imagery. Damage was ascertained through interviews with a sample of farmers. The floods of 2024–2025 may occur again in the next 12–19 years. Farmers cannot crop safer sites, raising significant environmental justice issues. Damage depends on the strength of the levees, the crop, and the season. From January to February, horticulture is at a higher risk. Flooding does not bring benefits. Risk maps highlight hot spots, are validated, and can be linked to observed flood levels.

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]]> Compound-event analysis in non-stationary hydrological hazards: a case study of the Niger River in Niamey https://climateservices.it/publication/compound-event-analysis-in-non-stationary-hydrological-hazards-a-case-study-of-the-niger-river-in-niamey/ Thu, 05 Dec 2024 12:49:56 +0000 https://climateservices.it/?post_type=publication&p=14959 This study examines compound hydrological hazards in a non-stationary context, specifically focusing on the Niger River in Niamey. The hazard results from the confluence of local Sahelian and more remote Guinean tributaries, displaying seasonal floods. The study first investigates whether Niamey’s annual flood hazard is a compound result of Sahelian and Guinean flows, and then […]

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]]> This study examines compound hydrological hazards in a non-stationary context, specifically focusing on the Niger River in Niamey. The hazard results from the confluence of local Sahelian and more remote Guinean tributaries, displaying seasonal floods. The study first investigates whether Niamey’s annual flood hazard is a compound result of Sahelian and Guinean flows, and then assesses the value of a compound hazard approach versus traditional flood analyses in this region. Analyzing discharge data from 1950 to 2020, the study disentangles Sahelian and Guinean flow impacts. It compares flood return level estimations from three statistical models of varying complexity. Findings confirm Niamey’s hazard as compound, stressing the need to consider both tributaries separately. Incorporating non-stationarity in statistical modeling is crucial, yet fully integrating the compound nature of hazards doesn’t significantly change the quantitative estimation of the hazard in Niamey.

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]]> Geospatial Capacity Building for Flood Resilience in the Sahel: the SLAPIS project case study https://climateservices.it/publication/geospatial-capacity-building-for-flood-resilience-in-the-sahel-the-slapis-project-case-study/ Thu, 05 Dec 2024 12:47:45 +0000 https://climateservices.it/?post_type=publication&p=14957 This study focuses on the development of a people-centred early warning system (EWS) against floods in the Sirba River basin between Niger and Burkina Faso. This densely populated area has witnessed an increase in extreme flooding events in recent years. Several flood forecasting systems in the Sahel exist, although there is no EWS that integrates […]

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]]> This study focuses on the development of a people-centred early warning system (EWS) against floods in the Sirba River basin between Niger and Burkina Faso. This densely populated area has witnessed an increase in extreme flooding events in recent years. Several flood forecasting systems in the Sahel exist, although there is no EWS that integrates the four components of people-centred EWSs, namely risk knowledge, monitoring and warning service, dissemination and communication, and response capacity. The proposed EWS, named SLAPIS, includes a risk knowledge component that involves defining four levels of vigilance. Its monitoring and alert component involves a user-friendly web application containing real-time data collected through automatic stations. The EWS communicate seamlessly with the national alert system. The response capacity is strengthened through the creation of a flood zone atlas. In this framework, the EWS integrates significant geoinformatics in preparation of local risk reduction plans and the awareness of local communities. In the SLAPIS case study, multi-temporal classifications were conducted using Sentinel-2 data and high-resolution images (approximately 10 cm) generated through Structure from Motion (SfM) techniques. Digital Terrain Model (DTM) creation for hydraulic model calibration employed a multiscale approach, incorporating GNSS survey data processed via Precise Point Positioning (PPP), HydroSHEDS (approximately 100m resolution), and commercial 10m resolution data. All information was calibrated, harmonised, and integrated into the EWS model, which is accessible via a web platform. Capacity building encompassed direct training and field implementation to streamline the primary EWS generation steps.

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]]> Comparative Trend Analysis of Precipitation Indices in Several Towns of the Sirba River Catchment (Burkina Faso) from CHIRPS and TAMSAT Rainfall Estimates https://climateservices.it/publication/comparative-trend-analysis-of-precipitation-indices-in-several-towns-of-the-sirba-river-catchment-burkina-faso-from-chirps-and-tamsat-rainfall-estimates/ Thu, 05 Dec 2024 12:44:42 +0000 https://climateservices.it/?post_type=publication&p=14955 The increasingly frequent pluvial flood of West African urban settlements indicates the need to investigate the drivers of local rainfall changes. However, meteorological stations are few, unevenly distributed, and work irregularly. Daily satellite rainfall datasets can be used. Nevertheless, these products often need to be more accurate due to sensor errors and limitations in retrieval […]

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]]> The increasingly frequent pluvial flood of West African urban settlements indicates the need to investigate the drivers of local rainfall changes. However, meteorological stations are few, unevenly distributed, and work irregularly. Daily satellite rainfall datasets can be used. Nevertheless, these products often need to be more accurate due to sensor errors and limitations in retrieval algorithms. The problem is, therefore, how to characterize rainfall where there is a need for ground-based rainfall records or incomplete series. This study aims to characterize urban rainfall using two satellite datasets. The analysis was carried out in the Sirba river catchment, Burkina Faso, using the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and the Tropical Applications of Meteorology using SATellite and ground-based data (TAMSAT) datasets. Ten indices from the Expert Team on Climate Change Detection and Indices (ETCCDI) of precipitation were calculated, and their statistical trends were evaluated from 1983 to 2023. The study introduces two key innovations: a comparative analysis of precipitation trends using two satellite datasets and applying this analysis to towns within a previously understudied 39,138 km2 catchment area that is frequently flooded. Both datasets agree on the increase of (i) annual cumulative rainfall over all towns, (ii) five-day maximum rainfall over the town of Manni, (iii) rainfall due to very wet days in Gayéri, (iv) days of heavy rainfall in Bogandé, Manni and Yalgho, and (v) days of very heavy rainfall in Yalgho. These findings suggest the need for targeted pluvial flood prevention measures in towns with increasing trends in heavy rainfall.

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