Paper Harvest Report
Date range: June 12, 2026
2 top-tier papers selected out of 90 total publications
Today’s Highlights
Convection-permitting simulations of Burkina Faso’s catastrophic September 2009 flood show that removing both Tropical Disturbances and Equatorial Rossby waves eliminates the extreme precipitation event in Ouagadougou entirely, underscoring how sensitive Sahelian flood forecasting is to large-scale wave dynamics. Separately, a new tendency-correction scheme applied jointly to the atmosphere and ocean components of CanESM5 meaningfully improves seasonal prediction skill — including for precipitation — a useful step for the seasonal outlooks that underpin drought and water-resources planning.
Table of Contents
Top-Tier Journal Papers
Exploring the Influence of Equatorial Waves on a Record‐Breaking Extreme Precipitation Event in Central Sahel: Insights From Convection Permitting Simulations
Authors: Moussa Diakhaté, Philippe Peyrillé, Jean‐Pierre Chaboureau, Florent Beucher, Fleur Couvreux
Journal: Geophysical Research Letters · DOI: 10.1029/2026gl122000
Matched topics: river, flood
The floods of 01 September 2009 in Ouagadougou, Burkina Faso, were among the most severe in the Central Sahel’s history, highlighting the region’s persistent flood risk. This extreme precipitation event (EPE) was influenced by various atmospheric drivers, including Convectively Coupled Equatorial Waves (CCEWs). This study uses the Meso‐NH numerical model to assess the individual impacts of CCEWs on the 2009 EPE. Results indicate that Tropical Disturbances (TDs) and Equatorial Rossby waves (ERs) significantly affect the system’s propagation and intensity, with TD removal causing a northward shift and ER removal reducing precipitation due to upstream drying. Removing both TDs and ERs eliminates the EPE entirely in Ouagadougou, while other waves have minimal impact. These findings emphasize the crucial role of TD and ER interactions in triggering EPEs in the Central Sahel and highlight the importance of accurately representing these waves in forecasting models.
Atmosphere‐Ocean Tendency Corrections Improve Seasonal Prediction Skill of CanESM5
Authors: W. J. Merryfield, V. V. Kharin, W.‐S. Lee, J. F. Scinocca, J. Velletta
Journal: Geophysical Research Letters · DOI: 10.1029/2026gl121919
Matched topics: seasonal, earth system model
This study examines impacts on prediction skill of empirically‐derived tendency corrections (TC) to climatological seasonal cycle biases in retrospective seasonal forecasts from the Canadian Earth System Model version 5 (CanESM5). A novel aspect is that TC are applied simultaneously in the modeled atmosphere and ocean, rather than to either independently. As in previous studies, climatological seasonal cycle biases and associated model drift are substantially reduced in variables to which TC are applied. In addition, the skill of the predictions is appreciably improved, both on average globally and in particular regions such as the far western equatorial Pacific. These improvements extend to variables for which TC is not directly applied such as precipitation, and are in contrast to some previous studies in which TC resulted in at best minor improvements to skill.
Statistics
| Metric | Count |
|---|---|
| Journals searched | 11 |
| Total papers fetched | 90 |
| Passed deterministic filter | 5 |
| After LLM relevance filtering | 2 |
| Rejected (not relevant) | 3 |
| AI for Science items picked | 0 |
Papers by journal
| Journal | Papers |
|---|---|
| Geophysical Research Letters | 2 |
Filtering Criteria
Topics: hydrology, hydrologic model, river, runoff, streamflow, reservoir, water management, flood, drought, seasonal, land surface model, climate change, hydropower, surface water, irrigation, earth system model, estuary, coastal, freshwater discharge, river plume, ocean biogeochemistry, marine heatwave, paleohydrology, paleoclimate, Quaternary, Holocene, Pleistocene, fluvial geomorphology, river terrace, loess, drainage network, river capture, landscape evolution, luminescence dating
Fields: engineering, environmental science, computer science, geology, geography