Demystifying the art of isotope-enabled hydrological and climate modelling
Christian Birkel, Jodie Miller, Andrew Watson, Duc Anh Trinh, Ana María Durán‐Quesada, Ricardo Sánchez‐Murillo, Chris Soulsby, Stefan Terzer‐Wassmuth, Dörthe Tetzlaff, S. Uhlenbrook, Yuliya Vystavna, Kei Yoshimura
Abstract
Over the last 20 years, we have dramatically improved hydrometeorological data including isotopes, but are we making the most of this data? Stable isotopes of oxygen and hydrogen in the water molecule (stable water isotopes – SWI) are well known tracers of the global hydrological cycle producing critical climate science. Despite this, stable water isotopes are not explicitly included in influential climate reports (e.g. Intergovernmental Panel on Climate Change, IPCC) except for paleoclimate reconstructions. Continuous developments in modelling approaches have now made isotope-enabled modelling of climate and hydrology more powerful and easier to perform, reducing prediction uncertainty and providing more robust simulations. We argue that it is time to incorporate stable water isotopes and isotope-enabled modelling into mainstream hydroclimatic forecasting with the prospect of vastly improving climate change predictions and evidence. Normalized pre- and post LAS advent (∼2007) publication metrics of “isotope-enabled” and more general “tracer-aided model” SCOPUS search words (climate and hydrology total since 1980: 733) compared to the global average land surface temperature anomaly (in red). All other published “model” papers in grey (total since 1980: 75511) and model publications concerned with “uncertainty” and with “climate change adaptation” show the overall increasing yet unquantified trend, although lagging the overall number of “model” publications with adaptation only starting in the early 2000s. • Stable water isotopes are well known tracers of the global hydrological cycle. • SWIs derived climate science not included in influential climate reports. • Isotope-enabled climate and hydrology modelling reduced prediction uncertainty. • Isotope-enabled modelling can improve climate change predictions and evidence.