Potential of long-term satellite observations and reanalysis products for characterising soil drying: trends and drought events
Notice bibliographique
Résumé
Abstract. Soil drying has multiple adverse impacts on the environment, society, and economy. Thus, it is crucial to monitor and characterise related drought events and to understand how underlying geophysical trends may affect them. Here, we compare the ability of long-term satellite observations and state-of-the-art reanalysis products to characterise soil drying. We consider the European Space Agency Climate Change Initiative (ESA CCI) remote-sensing surface soil moisture products (encompassing an ACTIVE, a PASSIVE, and a COMBINED product) as well as surface and root zone soil moisture from the ERA5, ERA5-Land, and MERRA-2 reanalysis products. In addition, we use a new root zone soil moisture dataset derived from the ESA CCI COMBINED product. We analyse global surface and root zone soil moisture trends in these products over the 2000–2022 period. Furthermore, we investigate the impact of the products' trend representation on their ability to capture major seasonal soil moisture (or agroecological) drought events as a use case. The latter is based on the analysis of 17 selected drought events documented in the scientific literature; these events are characterised by their severity (the time-accumulated standardised soil moisture anomalies), magnitude (the minimum of the standardised anomalies over time), duration, and spatial extent. The soil moisture trends are globally diverse and partly contradictory between products. ERA5, ERA5-Land, and ESA CCI COMBINED show larger fractions of drying trends, whereas ESA CCI ACTIVE and MERRA-2 display more widespread wetting trends. The differences between reanalysis products are related to a positive mean bias in the precipitation trends and regionally negative biases in surface air temperature trends in MERRA-2 compared with ground observational products, suggesting that this reanalysis underestimates drying trends. Given these biases in the MERRA-2 precipitation and temperature trends and considering available validation studies, the ESA CCI COMBINED-based products and ERA5-Land are considered more reliable and are consecutively used for a synthesis of global surface and root zone soil moisture trends. This synthesis suggests a consistent tendency towards soil drying during the last 2 decades in these products in 49.3 % of the surface and 44.5 % of the root zone layers of the covered global land area. The respective fractions of wetting trends amount to 21.1 % and 20.6 % for the surface and root zone, respectively, while areas with no trend direction consensus amount to 29.6 % and 35.0 %, respectively, reflecting the considerable uncertainties associated with global soil moisture trends. Geographically, drying is localised to parts of Europe and the Mediterranean; the Black Sea–Caspian Sea and Central Asian region; Siberia; parts of the western USA and the Canadian Prairies; and larger parts of South America, parts of southern and northern Africa, and parts of northwestern Australia. All investigated products mostly capture the considered drought events. Overall, the events tend to be least pronounced in the ACTIVE remote-sensing product across all drought metrics, particularly with respect to the magnitudes. Furthermore, MERRA-2 shows lower drought magnitudes than the other products, in both the surface layer and the root zone. The COMBINED remote-sensing products (surface and root zone soil moisture dataset) display partly stronger drought severities than the other products. In the root zone, the droughts are dampened with respect to the magnitude and smaller with respect to the spatial extent than in the surface layer, but they show a tendency toward prolonged durations and stronger severities. The product differences in the magnitude and severity of the drought events are consistent with the differences in soil moisture trends, which demonstrates that the representation of soil moisture trends plays a fundamental role in the drought-detection capacity of the different products.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».