Analysis of ocean surface heat fluxes in a NOGAPS climate simulation: Influences from convection, clouds and dynamical processes

Abstract

Abstract. This study examines the simulation quality of the surface heat flux fields produced during a climate simulation of the Navy Operational Global Atmospheric Prediction System, version 3.4, with a reduced spectral truncation of T63 and 18 levels (herineafter referred to as NOGAPS-CL). Comparisons are made between a 17-year NOGAPS-CL simulation using monthly sea surface temperatures as surface boundary conditions and a number of validating data sets consisting of ship, satellite, and/or reanalysis-based surface heat fluxes, precipitation, top of the atmosphere radiation budget, water vapor, cloud frequency, surface wind stress, and tropospheric winds. In this extended, long-range integration, NOGAPS-CL underpredicts the net surface shortwave flux in much of the subtropical oceans and overpredicts the net shortwave flux in the western Pacific warm pool and the midlatitude oceans, when compared to several satellite-derived climatological data sets. In addition, NOGAPS-CL over predicts the latent heat flux in much of the subtropics and under predicts the latent heat flux over the northern ocean western boundary currents and under the storm track regions that extend eastward from them. These shortwave and evaporation biases combine to produce errors in the surface net heat flux, with too little heat entering the subtropical/tropical oceans and too much heat loss in the midlatitudes oceans. Examination of related quantities indicates that the tropical climate biases are coupled to shortcomings in the convective cloud and/or boundary layer parameterizations which leads to the premature release of moist instability from the boundary layer in regions just outside the deep convective zones. This leads to enhanced climatological cloudiness, rainfall, and surface evaporation, as well as to a reduction in the surface shortwave flux and outgoing longwave radiation (OLR), in the subtropical regions. Furthermore, because of this early release of the moist static energy, there is a reduction in clouds, rainfall and water vapor content, as well as enhanced surface shortwave flux and outgoing longwave radiation, in the deep convective zones. The reduction in rainfall and enhanced OLR reduces the strength of the tropical large-scale circulation, which in turn reduces the strength of the subsidence in the subtropical regions which normally acts to suppress the convection processes in these regions. The implications of these results are discussed in terms of the relationship among the forecast model climatological surface fluxes, convection, clouds, and the dynamical processes, as well as their similarities to other climate models and their possible impact on the simulation of transient systems.

Analysis of Observed and Modeled Surface Fluxes, Cloud Forcing, and Convective Processes for Improving the Meteorological and Oceanographic Modeling and Prediction Systems

“…The results pertaining to Part 1) of the APPROACH were described in previous reports and can now be found in Waliser and Hogan (2000).…”

“…The results from the NOGAPS analysis (Waliser and Hogan, 2000) point to the convective parameterization as the major shortcoming underlying the model biases in the surface heat fluxes, and indicate how it also negatively impacts the large-scale circulation, the rainfall, surface wind, and cloud fields, and possibly even the simulation of intraseasonal variability. Remedying these shortcomings will: 1) improve NOGAPS physical representation of the atmosphere and extend the skill of its medium range weather predictions, and 2) improve the skill of the oceanographic predictions via the improved simulation and prediction of the surface fluxes.…”

Dynamic predictability of intraseasonal variability associated with the Asian summer monsoon

“…This is due to the generally poor representation of the ISO in most AGCMs, except for a few research-oriented models (e.g. Slingo et al 1996;Waliser et al 1999b;Waliser and Hogan 2000;Waliser et al 2003b). However, if the ISO could be better represented in operational weather forecast models, particularly in terms of stronger amplitudes and more coherent structures, the above results imply that extended-range tropical forecasts in the regions directly impacted by the ISO (e.g.…”

Lower Tropospheric Processes: A Control on the Global Mean Precipitation Rate

“…Our investigation begins by recognizing that the global mean precipitation in climate models can be analyzed through a surface evaporation framework (Richter & Xie, 2008; Siler et al., 2019). For example, Waliser and Hogan (2000) noted in their surface flux analysis of a climate model that biases in surface evaporation were partly due to dry air mixing down into the boundary layer over regions where evaporation rates are higher than precipitation rates. This highlights that processes occurring in non‐precipitating regions can control the global mean precipitation rate.…”