19 Jan 2022
19 Jan 2022
Status: a revised version of this preprint is currently under review for the journal HESS.

Characterizing natural variability in complex hydrological systems using Passive Microwave based Climate Data Records: a case study for the Okavango Delta

Robin van der Schalie1, Mendy van der Vliet1, Clément Albergel2, Wouter Dorigo3, Piotr Wolski4, and Richard de Jeu1 Robin van der Schalie et al.
  • 1VanderSat B.V., Water and Climate Unit, Haarlem, Netherlands
  • 2European Space Agency Climate Office, ECSAT, Harwell Campus, Didcot, Oxfordshire, UK
  • 3CLIMERS, TU Wien, Department of Geodesy and Geoinformation, Vienna, Austria
  • 4Climate System Analysis Group, University of Cape Town, Cape Town, South Africa

Abstract. The Okavango river system in southern Africa is known for its strong interannual variability of hydrological conditions. Here we present how this is exposed in surface soil moisture, land surface temperature, and vegetation optical depth as derived from the Land Parameter Retrieval Model using an inter-calibrated, long term, multi-sensor passive microwave satellite data record (1998–2020). We also investigate how these interannual variations relate to state-of-the-art climate reanalysis data from ERA5-Land. We analyzed both the upstream river catchment and the Okavango Delta, supported by independent data records of discharge measurements, precipitation and vegetation dynamics observed by optical satellites. The seasonal vegetation optical depth anomalies have a strong correspondence with MODIS Leaf Area Index (correlation catchment: 0.74, Delta: 0.88). Land surface temperature anomalies derived from passive microwave observations match best with those of ERA5-Land (catchment: 0.88, Delta: 0.81), as compared to MODIS nighttime LST (catchment: 0.70, Delta: 0.65). Although surface soil moisture anomalies from passive microwave observations and ERA5-Land correlate reasonably well (catchment: 0.72, Delta: 0.69), an in-depth evaluation over the Delta uncovered situations where passive microwave satellites record strong fluctuations, while ERA5-Land does not. This is further analyzed using information on inundated area, river discharge and precipitation. The passive microwave soil moisture signal demonstrates a response to both the inundated area and precipitation. ERA5-Land however, which by default does not account for any lateral influx from rivers, only shows a response to the precipitation information that is used as forcing. This also causes the reanalysis model to miss record low land surface temperature values as it underestimates the latent heat flux in certain years. These findings demonstrate the complexity of this hydrological system and suggest that future land surface model generations should also include lateral land surface exchange. Also, our study highlights the importance of maintaining and improving climate data records of soil moisture, vegetation and land surface temperature from passive microwave observations and other observation systems.

Robin van der Schalie et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on hess-2021-637', Anonymous Referee #1, 15 Feb 2022
    • AC1: 'Reply on RC1', Robin van der Schalie, 14 Apr 2022
  • RC2: 'Comment on hess-2021-637', Anonymous Referee #2, 24 Mar 2022
    • AC2: 'Reply on RC2', Robin van der Schalie, 14 Apr 2022

Robin van der Schalie et al.

Robin van der Schalie et al.


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Short summary
Climate Data Records of surface soil moisture, vegetation optical depth and land surface temperature are derived from Passive Microwave Observations. The ability of these datasets to properly detect anomalies and extremes is very valuable in climate research, and can especially help to improve our insight in complex regions where the current climate reanalysis datasets reach their limitations. Here we present a case study over the Okavango Delta, where we focus on inter-annual variability.