Dynamics of precipitation in transition:
The water source for the Galápagos Archipelago
under climate change

Abstract:

The Galápagos Archipelago, located on the equator in the eastern Pacific, exhibits pronounced seasonal and interannual climate variability influenced primarily by the Inter-Tropical Convergence Zone and the El Niño-Southern Oscillation (ENSO). Despite its ecological significance and vulnerability to climatic changes, limited observational data has hindered long-term analyses of climate trends in the region. This study leverages the newly developed Galápagos Archipelago Refined Analysis dataset, with a 2 km × 2 km grid spacing, derived from high-resolution dynamical downscaling of ERA5 data, to comprehensively examine climatic trends across the archipelago from 1980 to 2023 using both linear regression and Mann-Kendall trend analysis. Our key finding is a positive trend in layer thickness of lower and upper troposphere driven by rising potential air temperature. While linear regression detects significant trends primarily during dry seasons, the Mann-Kendall test reveals additional monotonic warming trends during wet and transitional seasons obscured by strong interannual variability, indicating more pervasive year-round tropospheric warming than linear analysis alone suggests. This tropospheric warming signal suggests increasing atmospheric stability over the archipelago. In contrast, near-surface variables are dominated by strong interannual variability driven primarily by ENSO, and linear regression does not detect statistically significant long-term trends in air temperature, humidity, or precipitation. However, the Mann-Kendall test identifies a significant monotonic warming trend in near-surface air temperature during January–February–March, indicating a subtle wet-season surface signal that is weaker and less spatially consistent than the tropospheric warming. Notably, strong El Niño events before 2000 exhibited substantially stronger precipitation and temperature anomalies than more recent events, suggesting potential changes in ENSO characteristics affecting the region. The observed decoupling between tropospheric warming trends and boundary-layer conditions underscores the need for further investigation into vertical atmospheric dynamics and the mechanisms linking large-scale climate change to local surface conditions on the archipelago.

Abstract:

The Galápagos Islands, located in the eastern equatorial Pacific approximately 1000 km west of mainland Ecuador, are highly sensitive to the El Niño–Southern Oscillation. However, the mechanisms linking sea surface temperature (SST) variability to daily rainfall extremes remain poorly understood. Focusing on Santa Cruz Island, one of the main islands of the archipelago, we analyzed the response of daily rainfall to four El Niño events (1991–1992, 1997–1998, 2015–2016 and 2023–2024) and their relationship with SST spatial patterns. Our approach followed three steps: (1) Daily rainfall observations were classified using percentile thresholds; (2) SST spatial clusters were identified using Local Indicators of Spatial Association (LISA), which explicitly incorporates spatial autocorrelation to distinguish warm and cold SST spatial clusters; and (3) SST cluster metrics (mean temperature, spatial extent, and persistence) were extracted and related to rainfall intensification. Results show that El Niño can increase daily extreme rainfall (>P95) in frequency and in totals, with the strongest and most persistent signal during 1997–1998; in contrast, the 2015–2016 event, despite being classified as very strong by the Oceanic Niño Index (ONI), exhibited a limited and short-lived >P95 rainfall response in Santa Cruz. The link between SST clusters and extreme rainfall strengthened during El Niño (r from ~0.40 to 0.70). Correspondingly, SST clusters underwent significant spatial reorganization in their extent and persistence. Contrasts were most evident in the central–southern domain, where 1997–1998 showed strong warm incursion and persistent ≥28 °C coverage, while 2015–2016 remained more spatially constrained and less coherent. The area where clusters reached mean SST ≥ 28 °C became widespread in 1997–1998 (98.55%), whereas it remained more localized in 1991–1992 (30.28%), 2015–2016 (27.02%), and 2023–2024 (26.55%) and was absent in neutral years (0%). Persistent warm-cluster coverage increased from neutral conditions (38.53%) in 1991–1992 (47.49%), 1997–1998 (53.42%), and 2023–2024 (42.97%), but was lower in 2015–2016 (34.53%). Overall, these results provide a process-oriented link between SST cluster organization and event-to-event differences in Galápagos rainfall extremes, highlighting the value of local SST metrics beyond basin-scale ENSO indices.

Abstract:

Climate change is expected to increase the frequency and intensity of heavy rainfall events (HRE) globally. In the Galápagos Islands, HREs have caused severe impacts such as infrastructure loss and ecosystem damage, yet their occurrence remains poorly understood. This study identifies 137 HREs between 1985 and 2024 and demonstrates that local sea surface temperatures (SST) from a new regional SST index, called the Galápagos Regional Niño Index (GReNI), correlate more strongly with HREs than widely used large-scale El Niño-Southern Oscillation indices. We analyzed the rainfall and 10 m wind fields from the Galápagos Archipelago Refined Analysis data set and find that while HREs occur outside Pacific-wide El Niño events, they are generally strongest during local GReNI El Niño-like phases. These findings highlight how local SST anomalies influence mesoscale rainfall, suggesting local rather than large-scale SST are significant HRE modulators.

Abstract:

The Galápagos Archipelago exhibits a unique and high endemic biodiversity that is strongly affected by climate variability, mainly caused by the El Niño-Southern Oscillation phenomenon. However, there exist few climate datasets for the islands and a long-term climate dataset at the meso-scale is not available. We present the Galápagos Archipelago Refined analysis dataset (GAR), a dynamically downscaled dataset of 2 h temporal resolution and 2 km horizontal grid spacing for the Galápagos Archipelago, that is based on ERA5 reanalysis data. The GAR is produced by the Weather Research and Forecasting Model (WRF V.4.3.3). Sensitivity experiments focused on precipitation and air temperature led to the selection of a suitable model setup for the region, which was developed using observational data from the Darwin Measurement Network (DMN) and the Charles Darwin Research Station (CDRS). We evaluated the performance of the model by reproducing the measured daily mean values at the Cerro Crocker (CC) and Puerto Ayora (PA) stations for the period from 01 April 2022 to 31 March 2023. The results show very strong correlations (ρT,CC=0.94 and ρT,PA=0.94) for air temperatures. For daily precipitation rates, measured by rain gauges, the GAR yields medium to strong correlation (ρPg,CC=0.66 and ρPg,PA=0.44). Specific humidity very strongly correlates with the measurements (ρSH,CC=0.88 and ρSH,PA=0.97). Analysis of the spatial patterns of precipitation, specific humidity, and temperature on the meso-scale indicated a strong dependency on altitude. Precipitation for the dry season is triggered mainly by orographic lifting, while wet season precipitation is driven by thermally induced convection. The GAR fulfils the need for high spatio-temporal resolution data on the Galápagos climate and serves as a valuable source for scientific research in this area. The GAR data are publicly available, and together with the downscaling approach evaluated here, this dataset can easily be extended into the future.