A smart climatology of evaporation duct height and surface radar propagation in the Indian Ocean

Abstract

Surface electromagnetic propagation over the ocean is highly sensitive to near-surface atmospheric variability, particularly the height of the evaporation duct. Seasonal variation in near-surface meterological factors and sea surface temperatures impact the evaporation duct height (EDH). Present U.S. Navy EDH climatology is based on sparse ship observations over a relatively short time period and an outdated evaporation duct (ED) model. This EDH climatology does not utilize smart, or modern, climatology datasets or methods and provides only long term mean (LTM) values of EDH. We have used existing, civilian, dynamically balanced reanalysis data, for 1970 to 2006, and a state-of-the-art ED model, to produce a spatially and temporally refined EDH climatology for the Indian Ocean (IO) and nearby seas. Comparisons of the present U.S. Navy EDH climatology with our climatology show a number of differences. These differences, and the differences in the methods used to generate the two climatologies, indicate that the EDH climatology we have generated provides a more accurate depiction of EDH. The EDH climatology we have produced provides LTM EDH values. But the data and methods we used to create this climatology also allowed us to examine the impacts of climate variations on EDH. Climate variations can have major impacts on the upper ocean and overlying lower troposphere. These impacts can lead to major fluctuations in the factors that determine EDH, and can thereby alter the propagation of EM signals through the atmosphere. The IO and nearby seas are strongly affected by a number of climate variations (e.g., El NinÌ o-La NinÌ a (ENLN), Indian Ocean Zonal Mode (IOZM)). These climate variations are known to lead to large anomalies in sea surface temperature, air temperature, winds, humidity, and other variables in the IO; however, the associated impacts on EDH and EM propagation have not been identified. To assess these impacts, reanalysis data composited by season and climate variation were processed using: (1) the NPS ED model to assess the impacts of the climate variations on EDH; and (2) the Advanced Refraction Effects Prediction System (AREPS) to assess the impacts of the variations on radar propagation. Our results show significant variations in EDH and AREPS ranges associated with the climate variations that affect the IO and nearby regions. These climate variations are predictable on weekly and longer time scales. In addition, for several seasons, EDH is significantly correlated with the climate variation when EDH lags by zero, one, and two months. Thus, there appears to be potential for climate scale forecasting of EDH and radar propagation at weekly to monthly lead times. For areas of operational interest, we conducted correlation analyses of EDH with its associated factors to further our understanding of the processes that cause spatial and temporal variations of EDH. These correlation results provide insights into the spatial and temporal sensitivity of EDH to the factors. Thus, they provide guidance on how to focus research, development, and operational efforts aimed at improving analyses and forecasts of EDH. We used the EDH climatology created in this study to generate climatological sensor performance surfaces for radar propagation. These surfaces are maps of climatological surface radar propagation over the IO and nearby seas under different climatological conditions (e.g., different months, locations, climate variations, and regimes). The performance surfaces are prototypes of operational climatological products, and examples of the improved climatological products that can be developed using smart climatology data and methods. These results indicate that climatological support for military planners could be substantially improved by using a smart climatology approach (i.e., applying state-of-the-art climate datasets, analysis, and forecasting methods).