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Our collective understanding of azimuthally-asymmetric features within the coherent structure of a tropical cyclone (TC) continues to improve with the availability of more detailed observations and high-resolution model outputs. However, a precise understanding of how these asymmetries impact TC intensity changes is lacking. Prior attempts at investigating the asymmetric impacts follow a mean-eddy partitioning that condenses the effect of all the asymmetries into one term and fails to highlight the differences in the role of asymmetries at different scales. In this study, we present a novel energetics-based approach to analyze the asymmetric impacts at multiple length-scales during periods of TC rapid intensity changes. Using model outputs of TCs under low and high shear, we compute the different energy pathways that enhance/suppress the growth of multi-scale asymmetries in the wavenumber (WN) domain. We then compare and contrast the energetics of the mean flow field (WN 0) with that of the persistent, coherent vortex-scale asymmetric structures (WNs 1,2) and the more local, transient, sub-vortex-scale asymmetries (WNs $\geq$ 3). We find in our case-studies that the dominant mechanisms of growth/decay of the asymmetries are the baroclinic conversion from available potential to kinetic energy at individual scales of asymmetries, and the transactions of kinetic energy between the asymmetries of various length-scales; rather than the barotropic mean-eddy transactions as is typically assumed. Our case-study analysis further shows that the growth/decay of asymmetries is largely independent of the mean. Certain aspects of eddy energetics can potentially serve as early-warning indicators of TC rapid intensity changes., Comment: 15 pages + Appendix + 12 Figures + Supplementary Material. Manuscript is under review with the Journal of the Atmospheric Sciences

Two major findings of this study are i) the presence of a robust intraseasonal oscillation (ISO) signal in the Bay of Bengal (BOB) subsurface ocean heat content (OHC) anomaly, this ISO signal propagates northward at the rate of roughly one degree latitude per day and ii) a lag of roughly 4 to 6 days between the appearance of this signal in the surface wind speed and followed by the OHC anomaly. The availability of long-term daily data sets for the OHC made it possible to examine the presence of ISO over the BOB. This study also examines the possible relationship of ISO signal in the OHC with other parameters, such as surface wind (wind speed, wind stress curl and related upwelling/downwelling), sea surface temperature (SST), net surface heat flux into the ocean and surface rain. This study confirms the finding of a robust signal for the OHC anomaly over the BoB, on the time scale of ISO, using daily data sets for a 17 years period covering each of the summer monsoon seasons. Also included is an analysis of rainfall and river runoff variability over north of the BoB. The river runoff and the precipitation data sets also show a robust ISO time scale. The mutual relationships among precipitation, SST, net heat flux and OHC are also examined in this study. This work addresses the lag relationship between the surface wind speed and the OHC, a lag of roughly 4 days relates to strong winds impacting a cooling of the ocean. The ranges of spread of all the above parameters for the total field and for the ISO time scale are expressed as percentage variability of the ISO time scale. Those show that the OHC anomaly over the Bay of Bengal is quite a robust feature. This study does not address modeling issues.

This paper addresses the forecasts of latent heat fluxes from five different formulations of the planetary boundary layer (PBL). Different formulations are deployed within the Florida State University global spectral model. Hundreds of short range forecast experiments are carried out using daily data sets for summer 2002 with each model. The primary goal of this study is to compare the performance of the diverse family of PBL algorithms for the latent heat fluxes within the PBL. Benchmark fluxes are calculated from the vertical integrals of Yanai’s formulation of the apparent moisture sink and a precipitation using Physical Initialization. This provides indirectly observed estimates of the vertical fluxes of latent heat in the PBL. This comparison reveals that no single scheme shows a global spread of improvement over other models for forecasts of latent heat fluxes in the PBL. Among these diverse models the turbulent kinetic energy based closure provides somewhat better results. The construction of a multimodel superensemble provides a synthesis of these different PBL formulations and shows improved forecasts of the surface fluxes. A single unified model utilizing weighted PBL algorithms where all the five schemes are retained within a single model shows some promise for improving a single model.

This paper deals with seasonal climate forecasting using as many as 13 coupled ocean–atmosphere models. An analysis of the individual model, multimodel ensemble, and FSU synthetic superensemble (FSUSSE) climate forecasts was performed for monthly and seasonal forecasts of precipitation, sea surface temperature (SST) and surface air temperature over the Euro-Mediterranean region including the land areas of Europe, North Africa and the Near East, during the period 1989–2001. In the FSUSSE methodology, forecasts are obtained by a weighted combination of the individual coupled ocean–atmosphere model forecasts based on a training period. The set of 13 individual climate forecast models utilized in this research is comprised of the seven models in the European suite of DEMETER models, a suite of four Florida State University models, the Australian POAMA model and the NCAR CCM3 model. The FSUSSE forecasts of seasonal precipitation anomalies were found to have the lowest root mean square (RMS) errors in comparison to the models in the multimodel ensemble, and their ensemble mean. However, the anomaly correlation (AC) coefficient results for seasonal precipitation anomaly forecasts by the FSUSSE were less impressive. The equitable threat scores for the FSUSSE forecasts of seasonal precipitation were found to be better than the various models in the multimodel ensemble, but those scores for the forecasts of positive seasonal anomalies were found to be worse than most of the models in the multimodel ensemble. The FSUSSE seasonal forecasts for SST and surface air temperature for the season considered (winter) were found to be excellent for both AC coefficients and RMS errors in the forecast anomalies.