Improved SST‐Precipitation Intraseasonal Relationships in the ECMWF Coupled Climate Reanalysis

Abstract

The European Centre for Medium‐range Weather Forecasts (ECMWF) has produced the ocean‐atmosphere coupled reanalysis for the twentieth century, CERA‐20C, following on from the similar but atmosphere‐only reanalysis ERA‐20C. Here we demonstrate the capability of CERA‐20C in producing more physically consistent ocean and atmosphere boundary conditions, by focusing on sea surface temperature (SST)‐precipitation intraseasonal relationships. CERA‐20C reproduces well the observed SST‐precipitation correlations, while these relationships are poorly represented in ERA‐20C, with the greatest discrepancies in the early 1900s. The improved relationships in CERA‐20C are due to intraseasonal improvements in SST that are not present in the external HadISST2 product. In CERA‐20C, SST‐precipitation relationships are slightly weaker in the 1900s than in the 2000s, mainly due to differences in the assimilated observation density. We also find that the coupled model initialized from CERA‐20C in the 2000s realistically simulates these relationships, while relaxing SST toward HadISST2 tends to damp these relationships. CERA‐20C has improved mean and variance in precipitation over ERA‐20C, but these are mostly due to improvements in the atmospheric model and not due to coupled feedbacks.

The effect of atmosphere–ocean coupling on the prediction of 2016 western North Pacific tropical cyclones

“…This effect becomes less distinguishable if it is superimposed with other longer‐time air–sea coupling effects, such as the seasonal cycle or El Niño/La Niña events. Coupled data assimilation, which provides dynamically consistent SST and atmospheric initial conditions (Feng et al, ), might benefit TC predictions by reducing such atmosphere–ocean imbalances in coupled forecasts, which, at the moment, are initialized separately in the ocean and atmosphere.…”

“…A passing TC induces a cold wake in the upper ocean, due to the upwelling of cooler subsurface water and increased evaporation, forced by the strong surface wind (Chen et al, ). TCs can also cool the ocean surface through increased cloud cover with reduced downward shortwave radiation, similar to other atmospheric convective events such as equatorial waves and the MJO (e.g., Feng et al, ). These negative feedbacks change the local thermodynamic structure of the TCs through reduced upward surface heat fluxes, to discourage rapid TC intensification.…”

Variability in vertical structure of precipitation with sea surface temperature over the Arabian Sea and the Bay of Bengal as inferred by Tropical Rainfall Measuring Mission precipitation radar measurements

“…The Indian summer monsoon (ISM; June through September) is one of the most complex weather phenomena, involving coupling between the atmosphere, land, and ocean. At the boundary of the ocean and atmosphere, air-sea interactions play a key role in the coupled Earth system (Wu and Kirtman, 2005;Feng et al, 2018). The relations between sea surface temperature (SST) and precipitation are the important measures for the air-sea interactions on different temporal scales (Woolnough et al, 2000;Rajendran et al, 2012).…”

“…The relations between sea surface temperature (SST) and precipitation are the important measures for the air-sea interactions on different temporal scales (Woolnough et al, 2000;Rajendran et al, 2012). Recent studies (Wang et al, 2005;Rajeevan et al, 2012;Chaudhari et al, 2013Chaudhari et al, , 2016Weller et al, 2016;Feng et al, 2018) have shown that the simulation of the ISM can be improved with the exact representation of the SST-precipitation relationship. SST modulates the meteorological factors that influence the formation and evolution of different kinds of precipitating systems over tropical oceans (Gadgil et al, 1984;Schumacher and Houze, 2003;Takayabu et al, 2010;Oueslati and Bellon, 2015).…”

Ocean Reanalyses: Recent Advances and Unsolved Challenges

“…Recent years have seen the pioneering production of Earth system reanalyses that simultaneously produce a dynamically consistent reconstruction of the atmosphere, ocean, land and seaice, although with varying complexity in the data assimilation coupling (e.g., Penny et al, 2017). These products are preliminary but provide promising results (e.g., Feng et al, 2018) and will likely be developed much further in the coming decade. Earth system reanalyses can potentially improve the representation of budgets (Mayer et al, 2017), although propagation and amplification of coupled biases and errors may occur (Zhang et al, 2013).…”