Coastal effects on radar propagation in atmospheric ducting conditions

Transcription

1 Meteorol. Appl. 13, (2006) Coastal effects on radar propagation in atmospheric ducting conditions doi: /s B. W. Atkinson & M. Zhu Department of Geography, Queen Mary, University of London, London E1 4NS, United Kingdom Two models were used to assess the effects of coastal characteristics on radar propagation in ducting conditions in the Persian Gulf. The NCAR/Penn State MM5 model simulated atmospheric conditions at a 5-km horizontal spatial and hourly temporal resolution on a day on which observations of ducts existed. The output from this model was input to the AREPS propagation model to produce radar coverage over coastal areas. Four factors influenced radar propagation: the sea breeze; coastal configuration; orography; and ambient wind. The sea breeze alone allowed propagation to extend about 100 km inland in a layer 200 m deep. When the breeze was aided by a following ambient wind the propagation layer extended for 150 km and was 400 m deep. A coastal indentation caused differences in depth and intensity of propagation over a distance of about 30 km parallel to the coast in which the indentation occurred. Steep near-coastal orography blocked radar propagation. Keywords: radar propagation, atmospheric ducts, coastal effects, numerical modelling, propagation modelling Received September 2004, revised October Introduction Radar has many important civil and military applications. The propagation of waves from a surfacebased antenna is affected by atmospheric conditions, particularly those in the boundary layer. These effects frequently lead to anomalous propagation, when radar detection distances are significantly greater than usual. An extreme form of anomalous propagation occurs in the presence of a duct, which traps the waves in a shallow, quasi-horizontal layer (Turton et al. 1988). Duct characteristics are determined from the distribution of the modified refractivity M, which is given by M = N + z R 106 (1) where z is the height above sea level and R is the mean radius of the earth and N is the refractivity (Bean & Dutton 1968) N = 77.6 ( p e ) (2) T T in which T is the air temperature in Kelvin, p is the air pressure in hpa and e is the water vapour pressure in hpa. A ray emitted at a small angle to the ground will be bent downwards (or upwards) if the modified refractivity (M) decreases (or increases) with height. If sufficient bending towards the ground occurs, the ray may become trapped in a duct. Detailed studies of the nature and distribution of ducts using, among other tools, special aircraft observations and numerical models, have been made off the Californian coast (Burk & Thompson 1997; Haack & Burk 2001), in the Baltic Sea (Anderson et al. 1997) and the Persian Gulf (Atkinson et al. 2001; Plant & Atkinson 2002; Atkinson & Zhu 2005; Zhu & Atkinson 2004, 2005). Observations at Barcelona, later supported by output from a numerical model, outlined seasonal variation of duct occurrence over one point on the coast of north east Spain (Bech et al. 2000, 2002a, 2002b, 2004). The effects of ducts on radar coverage can be estimated by using a radar propagation model, with the atmospheric conditions (e.g. refractivity field) as input (Abdul-Jauwad et al. 1991). A frequently used assumption in early estimates was that the atmosphere in the area of interest was horizontally homogeneous. This was necessitated by the initialisation of the calculation from one vertical profile. In reality this assumption is called into question by meso-scale and smaller scale variability in duct nature and distribution. Examples of such variability are given in Zhu & Atkinson s (2005) study of the Persian Gulf region. The existence and nature of ducts are strongly determined by the character of the atmospheric boundary layer. Dry, convective boundary layers, such as are frequently found over land in daytime, inhibit ducts. In contrast, moist, stable air over the sea, the marine boundary layer (MBL), favours duct formation. Frequently such a MBL 53

2 B. W. Atkinson & M. Zhu forms as air flows from warm land to cooler sea, thus becoming a marine internal boundary layer (MIBL). The nature of a MIBL and associated ducts is influenced by coastal morphology, land-sea temperature contrast, sea surface temperature, orography, the ambient wind and meso-scale structures such as the land-sea breeze circulation (Zhu & Atkinson 2004). In view of the known atmospheric meso-scale structure, later radar propagation models could be initialised with more profiles so as to capture the small-scale structure. In the absence of meteorological observations at the mesoscale, output from an atmospheric numerical model can provide the input to the radar propagation model. This study shows how meso-scale atmospheric variability affects the predicted radar coverage over coastal areas of the Persian Gulf. The approach was to use two models, a numerical atmospheric model and a radar propagation model, in a case study of one day on which detailed observations of ducts and radar propagation were available in part of the Persian Gulf (Brooks et al. 1999). The day, 28 April 1996, was a typical shamal day, shamal being the name given to strong north-westerly winds in this area, which frequently occur in both warm and cold seasons (Rao et al. 2003). The synoptic conditions showed at low levels a high pressure ridge extending from Turkey to southeast Saudi Arabia, along with a strengthening low pressure trough over Iran, a situation that generally triggered a shamal over the Gulf. Wind speeds of up to 23 m s 1 were reported at an inversion height of m (Brooks et al. 1999). Section 2 outlines the models used in the study, Section 3 the results and Section 4 is the conclusion. 2. Models used 2.1. Atmospheric model The model used for the atmospheric simulations (MM5V3) was the meso-scale model developed by the Pennsylvania State University and National Center for Atmospheric Research. This is based on the hydrostatic model introduced by Anthes & Warner (1978) and was presented in non-hydrostatic form by Dudhia (1993). Subsequent changes were succinctly described by Dudhia (1993 p. 1493): improvements have been made in the representation of the planetary boundary layer (Zhang & Anthes 1982), the surface radiation budget (Benjamin & Carlson 1986), the addition of several more cumulus parameterization schemes (e.g. Zhang & Fritsch 1986; Frank & Cohen 1987; Grell 1993), and an explicit moisture scheme (Hsie et al. 1984) with ice-phase processes (Dudhia 1989) for resolved-scale condensation. Grid nesting was also added by Zhang et al. (1986) and four-dimensional data assimilation by Stauffer & Seaman (1990). The atmospheric radiation option in the model provides a long-wave and short-wave scheme that interacts with cloud and precipitation and with the surface (Dudhia 1989). In addition to the continuous evaluation of the 54 model throughout the above development, validation for its use in studies of the atmospheric boundary layer in the Persian Gulf area, particularly for coastal areas, was presented in Zhu & Atkinson (2004). The model configuration for the simulation (Table 1) had three nested grids, the finest having a horizontal grid length of 5 km (Figure 1). This horizontal resolution was finer than that used in similar meteorological studies (e.g. Burk & Thompson 1996) and was appropriate to capture the meso-scale structures over the Gulf area. The vertical resolution used here was also shown to be adequate to capture the profiles of significant variables by comparison of simulated profiles with those observed in the US Navy Ship Antisubmarine Warfare Readiness/Effectiveness Measuring (SHAREM-115) programme (Brooks et al and pers. comm.). Tests showed that a spin-up time of 24 hours was advantageous and results from the following 24 hours were used in the analysis. The results with hourly temporal resolution from the inner, finest domain (Figure 1) are used in the study presented here. Local time (LT) is UTC plus three hours. Further validation was carried out by comparison of modelled and observed duct characteristics and associated meteorological variables, the observed values being taken from the SHAREM- 115 programme (Brooks et al and pers. comm.). Details on the resultant duct characteristics are available in Atkinson & Zhu (2005) and Zhu & Atkinson (2005) Radar propagation model The effects of the refractivity environment on radar propagation were assessed with the Advanced Refractive Effects Prediction System (AREPS) Version 3.3, (Space and Naval Warfare Systems Center 2004). The internal propagation model for AREPS is a hybrid called the Advanced Propagation Model, which solves a parabolic approximation to the wave equation through use of split-step Fourier transforms (Dockery 1988). Factors such as range-dependent refractivity environments, variable terrain, range-varying dielectric ground constants for finite conductivity and vertical polarization calculations, troposcatter and gaseous absorption are taken into account in this model. Input for the calculation includes atmospheric refractivity, terrain height, land use and surface wind. The radar modelled is an X-band radar operating at 10 GHz with the transmitter located 50 km offshore and 30 m above the surface, corresponding to the approximate characteristics of a ship-mounted search radar. The radar signal strength is represented by the one-way propagation factor F, defined by Meeks (1982) as F = 10 log E / E0 (3) where E 0 is the magnitude of the free-space field at a given point when the antenna is pointed toward the point and E is the field to be investigated at the point in question.

3 Coastal effects on radar propagation Table 1. Atmospheric model configuration. MM5V3 1. Domain 1 83(x) 83(y) 33(z) 9. Stephens s (1984) radiation scheme Domain 2 136(x) 106(y) 33(z) Domain 3 256(x) 223(y) 33(z) 2. Domain 1 centre 26.0 N, 52.0 E 10. Dudhia s (1989) explicit precipitation scheme Domain 2 centre 27.3 N, 52.6 E Domain 3 centre 27.3 N, 51.9 E 3. Domain 1 horizontal grid length ds = 45 km 11. Grell s (1993) convective precipitation scheme Domain 2 horizontal grid length ds = 15 km Domain 3 horizontal grid length ds = 5km 4. σ = , 0.996, 0.993, 0.991, 0.988, 0.984, 12. Surface temperature derived by force-restore method 0.979, 0.974, 0.969, 0.963, 0.958, 0.953, 0.948, 0.943, 0.938, 0.932, 0.922, 0.904, 0.888, 0.850, 0.816, 0.783, 0.746, 0.704, 0.664, 0,622, 0.576, 0.513, 0.436, 0.337, 0.225, 0.136, The equivalent heights to these σ levels for a point over the Persian Gulf are, in metres 11, 30, 50, 69, 88, 118, 157, 196, 239, 282, 321, 360, 400, 440, 480, 528, 608, 760, 959, 1210, 1506, 1803, 2152, 2552, 2953, 3400, 3910, 4650, 5642, 7140, 9138, 11142, Domain 1 time step dt = 90 s 13. Orography included Domain 2 time step dt = 30 s Domain 3 time step dt = 10 s 6. Integration time 48 hr 14. Land use includes only desert and water 7. Non-hydrostatic dynamics 8. Blackadar s (1979) high resolution PBL scheme 15. Initial fields for all domains at 00 UTC 27 April 1996 and lateral boundary conditions for the coarsest domain at 12-hr intervals were based on 40-year ECMWF Reanalysis data. The lateral boundary conditions for the fine domains were provided by their mother domains at every time step Figure 1. Area covered by the finest of the three grids and locations of cross-sections used in the study. 55

4 B. W. Atkinson & M. Zhu Figure 2. Cross-sections along line AB (see Figure 1 for location), 28 April 1996 of simulated elements. (a) mixing ratio (g kg 1 ) at 0900 hr UTC (1200 hr LT); (b) potential temperature ( C) at 0900 hr UTC (1200 hr LT); (c) modified refractivity (M-units) at 0900 hr UTC (1200 hr LT); (d) mixing ratio (g kg 1 ) at 1800 hr UTC (2100 hr LT). 3. Results Four cases of modelled radar propagation are presented. They show the effect on the propagation of a sea breeze, coastal configuration, orography and an ambient wind Sea breeze On 28 April 1996 a sea-breeze circulation developed over the west coast of the Gulf (see Zhu & Atkinson 2004, 2005). Such circulations have a clear diurnal pattern of behaviour, being non-existent or very weak in the morning and being best developed in the late afternoon. Figure 2 shows conditions along section AB (see Figure 1 for location) at 0900 hr UTC (1200 hr LT). Moist sea air remained largely over the sea, giving a duct with top height of m (Figure 2a). Over the land the dry, convective boundary layer prevented the formation of a duct (Figure 2b). The small magnitude of the difference in M ( M) across the layer with negative vertical gradient (the trapping layer) suggests that the duct was weak (Figure 2c). In contrast, by 1800 hr UTC (2100 hr LT) moist air had been carried about 90 km inland by the sea breeze, taking with it the duct, its depth of 200 m reflecting that of the layer of moist air (Figure 2d). Between 90 and 115 km from the coast no duct existed but beyond 115 km a shallow surface 56 duct had formed. The radar propagation showed a clear response to this variation in the atmospheric conditions. At 0900 hr UTC (1200 hr LT) the duct over the sea had no effect on the propagation and areas over land at low levels were beyond detection distance (Figure 3a). By 1800 hr UTC (2100 hr LT) (Figure 3b), energy propagated for a distance of 90 km inland, due to the presence of duct associated with the moist air brought in by the sea breeze Coastal configuration A sea breeze also developed near the north coast but, because of the opposing northwest ambient wind, the sea breeze front (SBF) remained offshore, parallel to the coastline. The front was breached by a tongue of sinking, warm, dry air from the north, which was associated with an indentation of the coastline (see line CD in Figure 1). Figure 4 shows that the warm, dry air in the tongue restricted the depths of the MIBL and the associated duct to less than 100 m over a distance of 100 km offshore. Further south, outside the tongue, the MIBL and duct height increased to over 300 m with M of about 10 M-units. Only a few tens of kilometres to the west, outside the tongue, the north coast sea-breeze circulation had a pronounced effect on the development of the MIBL and duct height. The interplay of MIBL

5 Coastal effects on radar propagation Figure 3. Range-height distribution of one-way propagation factor (db) derived from AREPS 3.3 along line AB (see Figure 1 for location), 28 April Antenna located 30 m above the surface at point A. (a) 0900 hr UTC (1200 hr LT); (b) 1800 hr UTC (2100 hr LT). and sea breeze has been examined by Plant & Atkinson (2002). In this case the SBF lay about 25 km offshore (Figure 5a). The uplift associated with it led to a plume of moist air (Figure 5b) that, in turn, led to duct top heights of 200 m. Seaward of the SBF, subsidence inhibited the growth of the MIBL so that its depth, and that of the associated duct, remained at less than 100 m over the rest of the section. M within the MIBL was over 30 M-units (Figure 5c). The distribution of radar propagation reflected the different atmospheric states described above. The deep but relatively weak duct south of the tongue trapped energy below about 100 m (Figure 6a), but this layer 57

6 B. W. Atkinson & M. Zhu Figure 4. Cross-sections along line CD (see Figure 1 for location) at 1300 hr UTC (1600 hr LT), 28 April 1996, of simulated elements. (a) vertical velocity (cm s 1 ); (b) potential temperature ( C);(c)mixingratio(gkg 1 ); (d) modified refractivity (M-units). Figure 5. Cross-sections along line EF (see Figure 1 for location) at 1300 hr UTC (1600 hr LT), 28 April 1996, of simulated elements. (a) vertical velocity (cm s 1 ); (b) mixing ratio (g kg 1 ); (c) modified refractivity (M-units). 58

7 Coastal effects on radar propagation Figure 6. Range-height distribution of one-way propagation factor (db) derived from AREPS 3.3 at 1300 hr UTC (1600 hr LT), 28 April Antenna located 30 m above the surface at points C and E. (a) along line CD; (b) along line EF. (See Figure 1 for locations.) became much shallower (about m) within the tongue itself, before disappearing over the land. Outside the tongue, where the surface duct was shallower but stronger, more energy was trapped (Figure 6b) in a layer of almost constant depth ( 40 m). The local increase in depth at km probably reflected the SBF. The clear difference in duct characteristics and radar propagation within and without the tongue revealed sensitivity to the coastal configuration Orography To the east of the Gulf the mountains of Iran reach heights of about 900 m within about 25 km of the coast. This means that an upslope breeze was added to the sea breeze over that coast, giving a MBL that increased in depth above sea level from west to east (Figure 7a). The associated duct-top height above sea level increased from 300 to 600 m. M was about 30 M-units in the 59

8 B. W. Atkinson & M. Zhu Figure 7. Cross-sections along line GH (see Figure 1 for location) at 1500 hr UTC (1800 hr LT), 28 April 1996, of simulated elements. (a) mixing ratio (g kg 1 ); (b) modified refractivity (M-units). Figure 8. Range-height distribution of one-way propagation factor (db) derived from AREPS 3.3 along line GH (see Figure 1 for location) 1500 hr UTC (1800 hr LT,) 28 April Antenna located 30 m above the surface at point G. west over the Gulf and reduced to zero over the land (Figure 7b). Radar energy was trapped by the duct and blocked by the orography (Figure 8). Beam blockage corrections are available but, as shown by Bech et al. (2001, 2003), their standard forms can be inadequate in duct conditions Ambient wind Astride the south coast, moist air was about 400 m deep and penetrated inland for at least 150 km (Figure 9a). This was due to two factors. First, the MIBL over the Gulf increased in depth from northwest to southeast, thus being at its deepest over the southern coast. Second, the south coast sea breeze s formation in a following ambient wind, in sharp contrast to the situation over the north coast, favoured large penetration inland. The 60 duct was about 400 m deep with M about 30 M-units in its upper layers over the sea, but less than 5 M-units at 100 km inland (Figure 9b). This deep, extensive duct led to a concentration of propagation below 400 m over the sea and for 100 km inland (Figure 10). Further inland the very weak duct allowed escape of energy to higher levels. The strong trapping at heights of 200 to 400 m just inland from the coast was associated with very weak propagation near the surface at the coast, similar to that shown in Figure 3a. 4. Conclusion This study has two main conclusions. First, it has shown the feasibility of coupling a meso-scale and a radar propagation model to estimate radar coverage over coastal areas. Secondly, it has demonstrated the

9 Coastal effects on radar propagation Figure 9. Cross-sections along line IJ (see Figure 1 for location) at 1500 hr UTC (1800 hr LT), 28 April 1996, of simulated elements. (a) mixing ratio (g kg 1 ); (b) modified refractivity (M-units). Figure 10. Range-height distribution of one-way propagation factor (db) derived from AREPS 3.3 along line IJ (see Figure 1 for location) 1500 hr UTC (1800 hr LT), 28 April Antenna located 30 m above the surface at point I. effects of coastal meso-scale atmospheric structure in a desert environment, largely through their effect on ducts, on the radar coverage across the coast. The sea breeze alone led to trapping of radar waves in a layer about 100 m deep penetrating about 100 km inland. When the sea breeze lay in an ambient wind and a welldeveloped MIBL, these dimensions increased to 400 m and 150 km respectively. Coastal orography also led to a deepening and increased penetration of the layer of high radar propagation over the coastal slope but further inland the radar beam was blocked by the orography. Coastal configuration led to a break in the SBF off the north coast, giving quite different radar coverage across the coast along two parallel lines only 30 km apart. Acknowledgement We are grateful to the Defence, Science and Technology Laboratory, Ministry of Defence for supporting this work. References Abdul-Jauwad, S. H., Khan, P. Z. & Halawani, T. O. (1991) Prediction of radar coverage under anomalous propagation condition for a typical coastal site: a case study. Radio Sci. 26: Anderson, T., Alberoni, P. P., Mezzalsama, P., Michelson, D. & Nanni, S. (1997) Anomalous propagation identification from terrain and sea waves using vertical reflectivity profile 61

10 B. W. Atkinson & M. Zhu analysis. Proc. 28th International Conf. Radar Meteorol., Am. Meteorol. Soc., Austin, Texas: Anthes, R. A. & Warner, T. T. (1978) Development of hydro-dynamic models suitable for air pollution and other mesometeorological studies. Mon. Wea. Rev. 106: Atkinson, B. W., Li, J.-G. & Plant, R. S. (2001) Numerical modelling of the propagation environment in the atmospheric boundary layer over the Persian Gulf. J. Appl. Meteorol. 40: Atkinson, B. W. & Zhu, M. (2005) Radar-duct and boundarylayer characteristics over The Gulf area Q. J. R. Meteorol. Soc. 131: Bean, B. R. & Dutton, E. J. (1968) Radio Meteorology. Dover Publications, 435 pp. Bech, J., Sairouni, A., Codina, B., Lorente, J. & Bebbington, D. (2000) Weather radar anaprop conditions at a Mediterranean coastal site. Phys. Chem. Earth (B) 25: Bech, J., Codina, B., Lorente, J. & Bebbington, D. (2001) Anomalous propagation effects on weather radar beam blockage corrections. Proc. 30th International Conf. Radar Meteorol., Am. Meteorol. Soc., Munich, Germany: P7.3. Bech, J., Codina, B., Lorente, J. & Bebbington, D. (2002a) Seasonal variations of radar anomalous propagation conditions in a coastal area. URSI Commision-F Open Symposium on Radiowave Propagation and Remote Sensing, Institut fur Hochfrequenztechnik, Deutsches Zentrum fur Luftund Raumfahrt, D-82234, Wessling, Germany. 3 pp. Bech, J., Codina, B., Lorente, J. & Bebbington, D. (2002b) Monthly and daily variations of radar anomalous propagation conditions: How normal is normal propagation? Proc. ERAD (2002), Delft, Netherlands: Bech, J., Codina, B., Lorente, J. & Bebbington, D. (2003) The sensitivity of single polarization weather radar beam blockage correction to variability in the vertical refractivity gradient. J. Atmos. Ocean Technol. 20: Bech, J., Toda, J., Codina, B., Lorente, J. & Bebbington, D. (2004) Using mesoscale NWP model data to identify radar anomalous propagation events. Proc. ERAD (2004), Visby, Island of Gotland, Sweden: Benjamin, S. G. &. Carlson, T. N (1986) Some effects of surface heating and topography on the regional severe storm environment. Part I: Three-dimensional simulations. Mon. Wea. Rev. 114: Blackadar, A. K. (1979) High-resolution models of the planetary boundary layer. In: J. Pfaffin & E. Ziegler (eds.), Advances in Environmental Science and Engineering 1, no. 1, Gordon and Beach, Brooks, I. M., Goroch, A. K. & Rogers, D. P. (1999) Observations of strong surface radar ducts over the Persian Gulf. J. Appl. Meteorol. 38: Burk, S. D. & Thompson, W. T. (1996) The summertime lowlevel jet and marine boundary layer structure along the California coast. Mon. Wea. Rev. 124: Burk, S. D. & Thompson, W. T. (1997) Meso-scale modelling of summertime refractive conditions in the southern California Bight. J. Appl. Meteorol. 36: Dockery, G. D. (1988) Modelling electromagnetic wave propagation in the troposphere using the parabolic equation. IEEE Trans. Antennas Propag. 36: Dudhia, J. (1989) Numerical study of convection observed during the Winter Monsoon Experiment using a mesoscale two-dimensional model. J. Atmos. Sci. 46: Dudhia, J. (1993) A nonhydrostatic version of the Penn State- NCAR mesoscale model: validation tests and simulation of an Atlantic cyclone and cold front. Mon. Wea. Rev. 121: Frank, W. M. & Cohen, C. (1987) Simulation of tropical convective systems. Part I: A cumulus parameterization. J. Atmos. Sci. 46: Grell, G. A. (1993) Prognostic evaluation of assumptions used in cumulus parameterizations. Mon. Wea. Rev. 121: Haack, T. & Burk, S. D. (2001) Summertime marine refractivity conditions along coastal California. J. Appl. Meteorol. 40: Hsie, E.-Y., Anthes, R. A. & Keyser, D. (1984) Numerical simulation of frontogenesis in a moist atmosphere. J. Atmos. Sci. 41: Meeks, M. L. (1982) Radar Propagation at Low Altitudes. Artech House Inc., 105 pp. Plant, R. S. & Atkinson, B. W. (2002) Sea-breeze modification of the growth of a marine internal boundary layer. Bound.- Layer Meteor. 104: Rao, P. G., Hatwar, H. R., Al-Sulaiti, M. H. & Al-Mulla, A. H. (2003) Summer shamals over the Arabian Gulf. Weather 58: Space and Naval Warfare Systems Center (2004) Statement of functionality for Advanced Refractive Effects Prediction System, Space and Naval Warfare Systems Command, San Diego, 208 pp. Stauffer, D. R. & Seaman, N. L. (1990) Use of fourdimensional data assimilation in a limited-area mesoscale model. Part I: Experiments with synoptic scale data. Mon. Wea. Rev. 118: Stephens, G. L. (1984) The parameterization of radiation for weather prediction and climate models. Mon. Wea. Rev. 112: Turton, J. D., Bennetts, D. A. & Farmer, S. F. G. (1988) An introduction to radio ducting. Meteorol. Mag. 117: Zhang, D.-L. & Anthes, R. A. (1982) A high-resolution model of the planetary boundary layer sensitivity tests and comparisons with SESAME-79 data. J. Appl. Meteorol. 21: Zhang, D.-L. & Fritsch, J. M. (1986) Numerical simulations of the meso-β scale structure and evolution of the 1977 Johnstown flood. Part I: Model description and verification. J. Atmos. Sci. 43: Zhu, M. & Atkinson, B. W. (2004) Observed and modelled climatology of the land-sea breeze circulation over the Persian Gulf. Int. J. Climatol. 24: Zhu, M. & Atkinson, B. W. (2005) Simulated climatology of atmospheric ducts over the Persian Gulf area. Bound.-Layer Meteor. 115: