Ocean Salinity and the Global Water Cycle

Ocean salinity as a tool to understand and predict rainfall variability on land

Li et al. (2016a) provides evidence that springtime SSS in the subtropical North Atlantic can be used as a predictor of terrestrial precipitation during the subsequent summer monsoon in Africa. Specifically, increased springtime SSS in the subtropical North Atlantic tends to be followed by enhanced monsoon-season precipitation in the African Sahel. In the spring, high SSS is associated with stronger moisture flux divergence from the subtropical oceans, which converges over the African Sahel and elevates local soil moisture. From spring to summer, the initial water cycling signal is preserved, amplified, and manifests in excessive precipitation. Because of the physical connection between salinity, ocean-to-land moisture transport, and local soil moisture feedback, seasonal forecasts of Sahel precipitation can be improved by incorporating SSS into prediction models. Thus, expanded monitoring of ocean salinity should contribute to more skillful predictions of precipitation in vulnerable subtropical regions, such as the Sahel.

Moisture originating from the subtropical North Atlantic feeds precipitation throughout the Western Hemisphere. This ocean-to-land moisture transport leaves its imprint on SSS, enabling SSS over the subtropical oceans to be used as an indicator of terrestrial precipitation. Li et al. (2016b) demonstrates that springtime SSS over the northwestern portion of the subtropical North Atlantic significantly correlates with summertime precipitation over the U.S. Midwest. The linkage between springtime SSS and the Midwest summer precipitation is established through ocean-to-land moisture transport followed by a soil moisture feedback over the southern U.S. In the spring, high SSS over the northwestern subtropical Atlantic coincides with a local increase in moisture flux divergence. The moisture flux is then directed toward and converges over the southern U.S., which experiences increased precipitation and soil moisture. The increased soil moisture influences the regional water cycle both thermodynamically and dynamically, leading to excessive summer precipitation in the Midwest, as detailed in the study. Owing to these robust physical linkages, the springtime SSS outweighs the leading SST modes in predicting the Midwest summer precipitation and significantly improves rainfall prediction in this region.

The role of the oceanic water cycle in the record-breaking 2015 warm-season precipitation in the U.S. is analyzed in Li et al. (2018). The extreme precipitation started in the southern U.S. in the spring and propagated northward to the Midwest in the summer of 2015. This seasonal evolution of precipitation anomalies represents a typical mode of variability of U.S. warm-season precipitation and is linked to moisture export from the subtropical North Atlantic. The North Atlantic moisture flux interacts with local soil moisture which enables enhanced moisture to be drawn in from the Gulf of Mexico in the summer. Further analysis shows that the relationship between Midwest U.S. rainfall and the North Atlantic has become more significant in recent decades, indicating an increased likelihood of extremes like the 2015 case. Indeed, two record-high warm-season precipitation events (i.e., 1993 and 2008) both occurred in the more recent decades of the 66 year analysis period. The export of water from the North Atlantic leaves a marked surface salinity signature. The SSS signature appeared in the spring preceding all three extreme precipitation events, i.e. a saltier-than-normal subtropical North Atlantic in spring followed by extreme Midwest precipitation in summer. Thus, our study suggests that pre-season salinity patterns can be used for improved seasonal prediction of extreme precipitation in the U.S. Midwest, as is further demonstrated in Li et al. (2022): combined with soil moisture feedbacks bridging the springtime North Atlantic salinity, the SSS-based statistical prediction model improves U.S. Midwest heavy rainfall forecasts by 92%, complementing existing sea surface temperature-based frameworks.

For Australia, Rathore et al. (2020) demonstrates that SSS variability can also be used as a measure of terrestrial precipitation on interseasonal to interannual time scales and for determining moisture sources. Seasonal composites during El Niño-Southern Oscillation/Indian Ocean Dipole (ENSO/IOD) events are used to understand the variations of moisture transport and precipitation over Australia, and their association with SSS variability. During co-occurring La Niña and negative IOD events, salty anomalies around the Maritime Continent indicate freshwater export and are associated with a significant moisture transport that converges over Australia to create anomalous wet conditions. The significant pattern correlation between the moisture flux divergence and SSS anomaly during the ENSO/IOD events highlights the associated ocean-atmosphere coupling. A case study of the 2010/11 Brisbane flood demonstrates that changes in SSS occur before the peak of ENSO/IOD events. This raises the prospect that tracking of SSS variability could aid Australian rainfall predictions. As such, Rathore et al. (2021) uses SSS as an additional precursor for improving the prediction of austral summer rainfall over northeastern Australia. Using random-forest regression analysis, it is shown that local soil moisture, ENSO, and Indo-Pacific warm pool SSS are the most important precursors for northeast Australian rainfall. The improved Australian rainfall prediction when including SSS from the prior season suggests that sustained observations of SSS can aid with anticipating water cycle variations in Australia.