The performance of Earth System Models in simulating droughts
P.P. den Blaauwen (TU Delft - Civil Engineering & Geosciences)
F. van Oorschot – Mentor (TU Delft - Civil Engineering & Geosciences)
R.J. van der Ent – Mentor (TU Delft - Civil Engineering & Geosciences)
R.W. Hut – Mentor (TU Delft - Civil Engineering & Geosciences)
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Abstract
This research evaluated the performance of Land Surface Models (LSMs) in simulating droughts, examining Land-Hist offline simulations from the Land Surface, Snow and Soil Moisture Intercomparison Project (LS3MIP). It is well known that LSMs possess uncertainties and biases due to oversimplifications or the absence of certain physical processes (e.g., groundwater interactions and lateral connectivity). Therefore, the objective of this research was to identify the strengths and weaknesses of various LSMs and how this relates to the performance in simulating soil moisture droughts.
To address this objective, eight LSMs were evaluated: CESM2, CMCC-ESM2, E3SM-1-1, EC-Earth3-Veg, HadGEM3-GC31-LL, IPSL-CM6A-LR, MIROC6, and UKESM1-0-LL. Two reference evaporation datasets (DOLCE V3 and an ensemble of FLUXCOM-RS, BESS and PML) and a reference soil moisture dataset (SoMo.ml) were utilized for the evaluation. After a global analysis of LSM evaporation characteristics, six climatically diverse study areas were selected for further investigation.
A long-term analysis was performed by examining the water balance and implementing the LSMs into the Budyko framework. Subsequently, soil moisture deficits were calculated for the driest periods in time, and the resulting accumulated deficits were compared with the reference evaporation data. The timing and progression of the deficits were evaluated using the reference soil moisture data. Finally, the sensitivity of the models was evaluated by examining the response of evaporation anomalies to precipitation anomalies and comparing this with the reference evaporation data.
The results showed that there was a large spread in output and performance among the LSMs across all parts of the evaluation. The greatest contrasts among the LSMs were found in the dry-to-wet transition zones within the tropics. In this latitudinal range, the worst-performing LSMs overestimated the accumulation of soil moisture deficits and the severity of droughts, while the opposite was found for the extratropical regions. Additionally, the models showed, in general, that they were overly sensitive to precipitation anomalies.
When ranking the implemented model bases in the LSMs based on their performance during droughts, the findings showed that the Community Land Model (implemented in CMCC-ESM2, E3SM-1-1 and CESM2) was predominantly the best performing, followed by ORCHIDEE (IPSL-CM6A-LR) and HTESSEL (EC-Earth3-Veg). MATSIRO (MIROC6) and JULES (HadGEM3-GC31-LL and UKESM1-0-LL) were the least performing model bases.
From a hydrological perspective, the findings of this research could be linked to some known limitations of LSMs. Oversimplified soil and vegetation dynamics could contribute to LSMs being overly sensitive to precipitation anomalies, while the contrasts between tropical and extratropical regions could be attributed to the representation of soil moisture–evaporation coupling, which plays a greater role in the tropical study areas.
Ultimately, this research could contribute to LS3MIP and the land surface modeling community, as the results highlight the strengths and weaknesses of LSMs in simulating soil moisture droughts. From there, this research could contribute to improving LSMs, understanding drought mechanisms, and addressing climate change impacts, especially in drought-prone regions.