Processes Associated with the Tropical Indian Ocean Subsurface Temperature Bias in a Coupled Model

Abstract

Subsurface temperature biases in coupled models can seriously impair their capability in generating skillful seasonal forecasts. The National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), coupled model, which is used for seasonal forecast in several countries including India, displays warm (cold) subsurface (surface) temperature bias in the tropical Indian Ocean (TIO), with deeper than observed mixed layer and thermocline. In the model, the maximum warm bias is reported between 150- and 200-m depth. Detailed analysis reveals that the enhanced vertical mixing by strong vertical shear of horizontal currents is primarily responsible for TIO subsurface warming. Weak upper-ocean stability corroborated by surface cold and subsurface warm bias further strengthens the subsurface warm bias in the model. Excess inflow of warm subsurface water from Indonesian Throughflow to the TIO region is partially contributing to the warm bias mainly over the southern TIO region. Over the north Indian Ocean, Ekman convergence and downwelling due to wind stress bias deepen the thermocline, which do favor subsurface warming. Further, upper-ocean meridional and zonal cells are deeper in CFSv2 compared to the Ocean Reanalysis System data manifesting the deeper mixing. This study outlines the need for accurate representation of vertical structure in horizontal currents and associated vertical gradients to simulate subsurface temperatures for skillful seasonal forecasts.

Representation of Bay of Bengal Upper-Ocean Salinity in General Circulation Models

“…CFSv2 displays a too-weak stability for the upper 100 m as compared to WOA13, which is clearly seen in the bias (Figure 3d). The ERM profile is consistent with that for the entire tropical Indian Ocean (Chowdary et al, 2016b) and confirms the weak stability in CFSv2 (Figure 3b,e). Though upperocean salinity is better represented in MOM5 compared to CFSv2, the stability is still too weak in the top 60 m of the water column (Figure 3d,e).…”

Effect of cloud microphysics on Indian summer monsoon precipitating clouds: A coupled climate modeling study

“…Recently, Chowdary et al . [] have demonstrated that upper ocean surface cooling in CFSv2 over tropical Indian Ocean is driven by the mixing.…”

“…It is also important to note that the oceanic component (e.g., ocean heat transport and mixing) may also be responsible for SST differences. Recently, Chowdary et al [2016] have demonstrated that upper ocean surface cooling in CFSv2 over tropical Indian Ocean is driven by the mixing.…”

Effects of a multilayer snow scheme on the global teleconnections of the Indian summer monsoon

“…; Cai and Cowan, ; Chowdary et al . ). The interactions between the biases in the monsoon and the coupled air–sea interactions over the Indian Ocean remain part of the overall bias which cannot easily be untangled in a coupled system (Li et al .…”

“…Though CFS_NSS captures the monopole mode of variability, the variability explained by this mode is lower than the dipole mode (Figure 5c,f). This bias in models is quite common due to an excessive thermocline-mixed layer interaction in the eastern equatorial Indian Ocean, which results in a Bjerknes feedback and more frequent IOD events in contrast to the observed IOD (Annamalai et al, 2003;Cai and Cowan, 2013;Chowdary et al, 2016). The interactions between the biases in the monsoon and the coupled air-sea interactions over the Indian Ocean remain part of the overall bias which cannot easily be untangled in a coupled system (Li et al, 2015;Narapusetty et al, 2016;.…”