Gap-filled multivariate observations of global land-climate interactions

The volume of Earth system observations from space and ground has massively grown in recent decades. Despite this increasing abundance, multivariate or multi-source analyses at the interface of Atmosphere and Land are however still hampered by the sparsity of ground observations and a large number of missing values in satellite observations. In particular, there are many instances where some variables are observed at a particular time and location, while others are not available, thereby hindering robust analysis. Gap-filling is hence necessary but often done implicitly or for only single variables which can obscure physical dependencies. Here we use CLIMFILL (CLIMate data gap-FILL), a recently developed multivariate gap-filling procedure to bridge this gap. CLIMFILL combines state-of-the-art spatial interpolation with a statistical gap-filling method designed to account for the dependence across multiple gappy variables. CLIMFILL is applied to a set of remotely sensed and in-situ observations over land that are central to observing land-atmosphere feedbacks and extreme events. The resulting gridded time series spans the years 1995-2020 globally on a 0.25-degree resolution with monthly gap-free maps of nine variables including ESA CCI surface layer soil moisture, MODIS land surface temperature, diurnal temperature range, GPM precipitation, GRACE terrestrial water storage, ESA CCI burned area, ESA CCI snow cover fraction as well as two-meter temperature and precipitation from in-situ observations. Internal verification shows that this dataset can recover time series of anomalies better than state-of-the-art interpolation methods. It shows high correlations with respective variables of ERA5-Land and can help elongate and gap-fill ESA CCI surface layer soil moisture timelines for comparison with ISMN station observations. We showcase key features of the newly developed data product using three major fire seasons in California, Australia, and Europe. Their their accompanying droughts and heatwaves are well represented and can serve as a gap-free completion of an otherwise fragmented observational picture of these events. The dataset will be made freely available and can serve as a step towards the fusion of multi-source observations to create a Digital Twin of the Earth.