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  • View in gallery

    Schematic representation of the simulated domain: (a) coarse grid consisting of 4 km × 4 km grid elements, and (b) fine grid consisting of 1 km × 1 km grid elements. The hydrometeorological stations set up by Assouline and Mahrer (1996) were located at Sapir and Ein Gev. The dashed line indicates the location of the cross section used to present some of the model results. Solid lines indicate coast lines.

  • View in gallery

    NCEP–NCAR mandatory-level geopotential heights (m) and wind vectors (m s−1) over the Middle East at 500 hPa, at 0000 UTC on 23–25 Aug 1992 and 19–21 Sep 1993. Solid lines indicate coast lines.

  • View in gallery

    Soil moisture normalized by soil moisture at saturation derived from NDVI for the coarse grid illustrated in Fig. 1.

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    Simulated (solid line) and observed (dots) evolution of hydrometeorological conditions at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

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    Lake surface temperature observed at Sapir (solid line) and Ein Gev (dashed line) during the period 23–25 Aug 1992.

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    Comparison between observed and simulated hydrometeorological conditions at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

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    Same as Fig. 4, but for 19–21 Sep 1993.

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    Same as Fig. 6, but for 19–21 Sep 1993.

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    Simulated (solid line) and observed (dots) evolution of latent (E) and sensible (H) heat fluxes at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

  • View in gallery

    Comparison between observed and simulated latent (E) and sensible (H) heat fluxes at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

  • View in gallery

    Vertical cross section of the (upper row) west–east component of the wind (solid lines indicate positive, i.e., westerly, component, and dashed lines indicate negative, i.e., easterly, component; m s−1) and (lower row) potential temperature (K) on 24 Aug 1992. The location of the cross section is shown in Fig. 1.

  • View in gallery

    Horizontal cross section of (upper row) horizontal wind (m s−1) and (lower row) surface potential temperature (K) at a height of 10 m above the lake surface on 24 Aug 1992. The vertical component of the wind (m s−1) also is given at 0600 and 1200 LST.

  • View in gallery

    Same as Fig. 11, but for early afternoon.

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    Same as Fig. 12, but for early afternoon.

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    Horizontal cross section of daily mean horizontal wind speed (m s−1), potential temperature (K), latent heat flux (W m−2), and sensible heat flux (W m−2), at a height of 10 m above the lake surface on 24 Aug 1992.

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Simulations of the Summer Hydrometeorological Processes of Lake Kinneret

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  • 1 Center for Environmental Prediction, Department of Environmental Sciences, Rutgers—The State University of New Jersey, New Brunswick, New Jersey
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Abstract

Lake Kinneret is a 168-km2 lake located in northern Israel. It provides about 50% of the drinking water consumed in this arid country. To manage correctly this vital water resource, it is essential to understand the various hydrometeorological processes that affect its water budget and, in particular, its evaporation. The complexity of the terrain in this region (varying from ≈2800 m to ≈−410 m within a short distance), combined with different types of soil and ground covers surrounding the lake, results in complicated microscale and mesoscale atmospheric motions, including sea, lake, and land breezes, as well as anabatic and katabatic winds. The Regional Atmospheric Modeling System (RAMS), a state-of-the-art nonhydrostatic model with two-way interactive multigrid nesting and four-dimensional data assimilation capabilities, was used, together with observations collected near the western and eastern shores of the lake, to study these processes. It was configured with two nested grids centered in the middle of the lake: 1) a coarse grid with 4 km × 4 km grid elements representing a 264 km × 240 km domain including Mount Hermon, the Dead Sea, the Golan Heights, and the Mediterranean coast; and 2) a fine grid with 1 km × 1 km grid elements covering a 42 km × 50 km domain. Two three-day periods in the summers of 1992 and 1993, during which hydrometeorological observations were available, were simulated. To account for synoptic conditions, the National Centers for Environmental Prediction–National Center for Atmospheric Research mandatory-level reanalyses produced every 6 h for these periods were assimilated by the model. The strength and timing of the various atmospheric motions that develop in that region and their interactions significantly affect the hydrometeorological processes of the lake, which are subject to important diurnal and spatial variations of wind intensity and direction, temperature, humidity, and fluxes. Since these processes have a strong feedback on the lake hydrodynamics and thermal structure, it is concluded that the development of a coupled lake–atmosphere model is needed to provide good estimates of lake evaporation when lake water surface temperatures are not available. Here, it is demonstrated that RAMS performs properly, given the particular complexity of the Lake Kinneret system and the uncertainty inherent in observations above turbulent water.

Corresponding author address: Dr. Roni Avissar, Center for Environmental Prediction, Dept. of Environmental Sciences, Cook College, Rutgers—The State University of New Jersey, 14 College Farm Road, New Brunswick, NJ 08901-8551.

Email: avissar@gaia.rutgers.edu

Abstract

Lake Kinneret is a 168-km2 lake located in northern Israel. It provides about 50% of the drinking water consumed in this arid country. To manage correctly this vital water resource, it is essential to understand the various hydrometeorological processes that affect its water budget and, in particular, its evaporation. The complexity of the terrain in this region (varying from ≈2800 m to ≈−410 m within a short distance), combined with different types of soil and ground covers surrounding the lake, results in complicated microscale and mesoscale atmospheric motions, including sea, lake, and land breezes, as well as anabatic and katabatic winds. The Regional Atmospheric Modeling System (RAMS), a state-of-the-art nonhydrostatic model with two-way interactive multigrid nesting and four-dimensional data assimilation capabilities, was used, together with observations collected near the western and eastern shores of the lake, to study these processes. It was configured with two nested grids centered in the middle of the lake: 1) a coarse grid with 4 km × 4 km grid elements representing a 264 km × 240 km domain including Mount Hermon, the Dead Sea, the Golan Heights, and the Mediterranean coast; and 2) a fine grid with 1 km × 1 km grid elements covering a 42 km × 50 km domain. Two three-day periods in the summers of 1992 and 1993, during which hydrometeorological observations were available, were simulated. To account for synoptic conditions, the National Centers for Environmental Prediction–National Center for Atmospheric Research mandatory-level reanalyses produced every 6 h for these periods were assimilated by the model. The strength and timing of the various atmospheric motions that develop in that region and their interactions significantly affect the hydrometeorological processes of the lake, which are subject to important diurnal and spatial variations of wind intensity and direction, temperature, humidity, and fluxes. Since these processes have a strong feedback on the lake hydrodynamics and thermal structure, it is concluded that the development of a coupled lake–atmosphere model is needed to provide good estimates of lake evaporation when lake water surface temperatures are not available. Here, it is demonstrated that RAMS performs properly, given the particular complexity of the Lake Kinneret system and the uncertainty inherent in observations above turbulent water.

Corresponding author address: Dr. Roni Avissar, Center for Environmental Prediction, Dept. of Environmental Sciences, Cook College, Rutgers—The State University of New Jersey, 14 College Farm Road, New Brunswick, NJ 08901-8551.

Email: avissar@gaia.rutgers.edu

1. Introduction

Lake Kinneret (also known as the “Sea of Galilee” or “Tiberias Lake”) is a 168-km2 lake with a maximum length, width, and depth of about 22 km, 12 km, and 44 m, respectively (Fig. 1). It is located in northern Israel, in the central part of the Jordan Valley, a corridor running from north to south, between the Galilee Hills in the west and the Golan Heights in the east. Both the Galilee Hills and the Golan Heights reach an elevation of ≈400 m above mean sea level (MSL), while the lake is ≈−210 m MSL. North of the lake is Mount Hermon, which culminates at ≈2800 m MSL. About 120 km south of it is the Dead Sea, which is ≈−410 m MSL, and about 45 km west of it is the Mediterranean Sea. This lake, which is perhaps the most precious resource in this arid country, provides more than 50% of the drinking water consumed in Israel.

The complexity of the terrain, combined with the different types of soil and ground covers that surround the lake, results in complicated atmospheric processes, including strong microscale and mesoscale atmospheric motions. For instance, the sea breeze that develops near the Mediterranean shore is adiabatically heated and dried above the Galilee Hills before penetrating the lake area in the afternoon (e.g., Serruya 1978a,b; Alpert et al. 1982; Mahrer and Assouline 1993). This hot and dry turbulent air mass drives a large amount of water out of the lake. For instance, Assouline and Mahrer (1996) observed a latent heat flux in the lake as large as 500 W m−2 during the summer. These atmospheric motions also greatly affect the lake hydrodynamics (Pan 1999).

The lake surface temperature, and the air temperature and specific humidity above the lake experience significant spatial and temporal variability, as described later. Thus, the lake hydrometeorological conditions, which are highly sensitive to these variables, are expected also to vary considerably. Among them, the lake evaporation is particularly difficult to estimate under such conditions. As a result, it is not possible to make an accurate water budget for the lake based only on a few observations. Such a budget, however, is key to proper management of the lake.

Mesoscale processes such as sea, lake, and land breezes, and mountain–valley flow have been simulated successfully many times with atmospheric models (e.g., Mahrer and Pielke 1977; McNider and Pielke 1981). Since the hydrometeorological behavior of Lake Kinneret seems to be affected by all these processes, attempts have been made to simulate it. These attempts include the two-dimensional (2D) simulations of Doron and Neuman (1977), Alpert et al. (1982), and Mahrer and Assouline (1993) and the three-dimensional (3D) simulations of Anthes and Warner (1978) and Segal et al. (1982, 1983, 1985). In general, the 2D models were capable of simulating the development of strong westerly winds over the lake in late afternoon, which result from the penetration of the Mediterranean sea breeze (MSB). These simulations, however, were unable to reproduce observed meteorological conditions, for example, wind intensity and direction, thermal structure over the lake, and time of onset of the MSB. Because of the complexity of the terrain surrounding the lake, only 3D simulations with a very high density of grid points can provide the details needed to estimate correctly the lake hydrometeorological behavior. To resolve MSB and mountain–valley flow in the lake region, a relatively large domain, about 250 km × 250 km, including Mount Hermon in the north, the Dead Sea in the south, the Golan Heights in the east, and the Mediterranean coast in the west, needs to be considered for appropriate simulations. So far, however, the computing resources needed to produce such simulations were not available, and only low-resolution 3D simulations have been produced. In these simulations, the entire lake was represented by only a few grid points. Note that there are landscape features outside of the domain selected here that may have large impacts on their local environment. For instance, the Dead Sea also generates breezes that are very important for its own hydrometeorological conditions. Because of the shape and specific location of this sea, only weak breezes develop in its northern part and they do not reach Lake Kinneret. Still, the change of topography south of the lake down to the sea may be relevant for the lake hydrometeorological processes and should be included in appropriate simulations.

The major objective of the study presented here is to understand the various processes involved in the Lake Kinneret hydrometeorological behavior, and, in particular, its evaporation. For that purpose, a combination of high-resolution, 3D simulations and observations collected near the lake shore are used. The Regional Atmospheric Modeling System (RAMS) was selected for this study, mostly because it is a nonhydrostatic model that has a two-way interactive multigrid nesting capability and a four-dimensional data assimilation package. Furthermore, this state-of-the-art model has been used extensively for numerous applications and has been validated for various case studies (e.g., Pielke et al. 1992;Avissar et al. 1998).

RAMS is described in detail in Pielke et al. (1992). Thus, for brevity, only the relevant information for the processes discussed here is presented in the next section. That section also describes the numerical experiments conducted here. Section 3 provides a discussion of the Lake Kinneret complex-terrain hydrometeorological behavior and the capability of RAMS to simulate it. The potential use of such a model for water resources prediction and management is discussed in the conclusions.

2. Numerical experiment

a. The Regional Atmospheric Modeling System

RAMS consists of nonhydrostatic, compressible, dynamic equations; a thermodynamic equation; and a set of equations representing the cloud microphysics. It provides the velocity fields, temperature, mixing ratios, and pressure in a terrain-following coordinate system developed by Gal-Chen and Somerville (1975) and extended by Clark (1977). Its two-way interactive multigrid nesting capability is derived from the procedure proposed by Clark and Farley (1984). Leapfrog (in time) and second order (in space) numerical schemes are used (Tripoli and Cotton 1982). Various parameterizations are available for most physical processes, including radiation, turbulence, and land surface system. In this study, subgrid-scale turbulence is simulated with the 2.5 level of closure developed by Mellor and Yamada (1982). Horizontal diffusion is represented by a Smagorinsky-type scheme. Shortwave and longwave radiations are parameterized with the schemes developed by Mahrer and Pielke (1977). The land surface scheme developed by Avissar and Pielke (1989) was adopted here. Because there is no precipitation in northern Israel during the summer and only occasionally can clouds be seen in the region, the cloud microphysics scheme was deactivated, and atmospheric water is simulated only in the vapor phase. Different types of lateral boundary conditions are available in RAMS; zero-flux conditions were used here. A rigid lid was adopted as a top boundary condition, with a Rayleigh friction scheme applied to the five highest atmospheric layers. This type of boundary condition absorbs spurious gravity waves and considerably reduces the reflections from the upper part of the simulated domain.

b. Simulated domain and numerical grid

As discussed above, to resolve the MSB and mountain–valley flow in the lake region, a domain including Mount Hermon, the Dead Sea, the Golan Heights, and the Mediterranean coast needs to be represented. To simulate the details of the lake hydrometeorological processes, a very high resolution (not coarser than about 1 km × 1 km) is needed above and near the lake. Ideally, this very high resolution would be used to simulate the entire domain, centered in the lake. But because this approach would require more computing power than readily is available, an alternative approach, grid nesting, was adopted for the numerical experiments.

Two grids were defined: 1) a coarse grid with a gridcell size of 4 km × 4 km that covers an area of 264 km in the east–west direction and 240 km in the north–south direction; and 2) a fine grid with a gridcell size of 1 km × 1 km that covers a 42-km wide and 50-km long domain. Both grids were centered on the middle of the lake and are represented schematically in Fig. 1. These particular grids were selected based on a series of numerical experiments that simulated a 2D cross section of the domain running from the Mediterranean Sea, through the lake, and to the Golan Heights. With this nested grid configuration, the atmospheric processes simulated over the lake were very similar to those obtained with a high-resolution grid over the entire domain. In this case, however, the total number of grid points needed for a 3D simulation of this domain is reduced by a factor of ≈10, and, since the time steps of integration required for the low-resolution grid and the high-resolution grid are 24 and 8 s, respectively, the number of integrations needed for a given simulated period is reduced by a factor of ≈20. Thus, 3D simulations that use the nesting approach run about 200 times faster than they do with the high-resolution grid for the entire domain defined here.

Forty layers were used in the vertical. The first layer near the ground surface was 20-m thick, and the thickness of the other layers gradually increased away from the surface, with a growing factor of 1.2, up to a maximum thickness of 400 m. Thus, the top of the model reached an elevation of about 11 km MSL. In the land part of the domain, eight layers were used to represent the soil to a depth of 0.5 m.

c. Large-scale forcing

Stanhill and Neuman (1978) explained that during the summer Lake Kinneret is well within the subtropical high pressure belt. In this system, air in the mid- and upper troposphere sinks and is both compressed and heated as it descends to lower elevations. By contrast, in this typically cloud-free region, solar radiation heats the ground and generates strong convection. At a height of about 1 km, subsidence and convective motions meet and balance each other, a temperature inversion forms, and the upward movement of surface air is inhibited. This temperature inversion plays an important role in adjusting mesoscale circulations. For instance, the inland penetration of the sea breeze can be blocked effectively by the combination of the inland hills and this low inversion (Lu and Turco 1994). While subsidence is generated by synoptic conditions, local mesoscale activity constantly modifies the height and strength of the inversion. In addition, the airflow over the Galilee Hills is affected strongly by the thermal structure of the atmosphere, and, in turn, it can have a considerable impact on the lake hydrometeorological conditions. Thus, to simulate realistically the atmospheric processes over Lake Kinneret, it is essential to account for synoptic conditions. This necessity was confirmed by several 2D simulations that were performed to assess this sensitivity.

The National Centers for Environmental Prediction–National Center for Atmospheric Research (NCEP–NCAR) mandatory-level reanalysis produced every 6 h (see Kalnay et al. 1996) was assimilated by RAMS using a procedure described by Pielke et al. (1992). This dataset includes horizontal wind components, potential temperature, and relative humidity at various pressure levels. Its horizontal resolution is 2.5° latitude and longitude. According to this procedure, the lateral boundaries of the simulated domain are “nudged” strongly to the NCEP–NCAR data. However, the internal part of the domain is affected only by the processes simulated locally and by the waves that penetrate the lateral boundaries and propagate within the region of interest, where they interact with the local processes. It is important to emphasize that, while RAMS is capable of assimilating observations anywhere in the domain that it simulates, in all cases described in this study no such assimilation was performed. All observations collected near and in Lake Kinneret were used exclusively for model evaluation.

Two different periods were considered here: 1) 23–25 August 1992, and 2) 19–21 September 1993. Wind vectors and geopotential heights at 500 hPa are depicted in Fig. 2 for these two periods. One can see that, during these two three-day sequences, synoptic-scale winds above the lake region were strong and from the west–southwest, as is typically the case during the summer in this region. On 23 August 1992, a low pressure zone is located just above the eastern Mediterranean sea, west of Lebanon and northwest of Lake Kinneret. During the next two days, this “low” moves northeastward and exits the region of interest. As a result, synoptic winds gradually and slowly decrease with time and lose their northern component. During the period of 19–21 September 1993, a low pressure system penetrates the region of interest. As a result, synoptic winds gradually intensify during that period. During both periods, hydrometeorological conditions were observed at two sites near the shore of the lake, Sapir (northwestern shore) and Ein Gev (central–eastern shore). These two sites are indicated in Fig. 1, and a complete description of the field campaign is provided in Assouline and Mahrer (1996).

d. Land and water

From May to September, there is generally no rain in the Lake Kinneret region. However, this region is exploited extensively for irrigated agriculture, and some natural vegetation also can be found there. Several 2D simulations were performed to examine the sensitivity of the lake hydrometeorological conditions to regional land use/land cover and soil moisture. These numerical experiments emphasized that, when the soil of the entire domain is initialized uniformly with a high soil moisture content, the temperature contrast between land and sea and between land and lake is small, and the lake breeze and the MSB penetrating the lake area both are weak. When the model is initialized with a low soil moisture content, the mesoscale circulations that develop in this region are very strong. The moisture content of the atmospheric boundary layer, which also affects the lake evaporation, is remarkably different in these two scenarios.

Soil moisture unfortunately is not measured systematically in this region. Because of its large potential impact on the lake hydrometeorological behavior, however, it was important to estimate it as accurately as possible. For that purpose, the normalized difference vegetation index (NDVI), which is related to the fraction of green vegetation that covers the soil surface (Gutman and Ignatov 1996; Betts et al. 1997), was used. Based on the assumption that vegetation density is related directly to soil moisture, a linear equation was used to translate NDVI into soil moisture. For simplicity, a unique soil type (viz., “sandy loam”) was considered for the entire region. The maximum NDVI observed in this region, 0.42, was translated into a soil moisture (normalized by the soil moisture at saturation) of 0.6, which corresponds to “field capacity.” For NDVI equal to 0, a minimum soil moisture of 0.05, which corresponds to “wilting point,” was considered. The resulting map of soil moisture is illustrated in Fig. 3. This estimate obviously is crude and easily could be criticized. As will be shown later, however, the model simulates properly the wind intensity and direction above the lake, and, therefore, this estimate provides reasonable results for this particular study. This satisfactory result may be because, in an arid environment, vegetation density indeed is highly correlated to soil moisture.

The Mediterranean Sea and Lake Kinneret water surface temperatures were assumed to be constant in time and space. The monthly mean temperature given by Ashbel (1955) was used for the Mediterranean Sea, and, for the lake, the observed mean surface temperatures in time and space for the periods of observation considered in this study were adopted. Soil temperature at a depth of 0.5 m was assumed to be constant in time and equal to the daily-mean observed air temperature. At initialization, soil temperature was assumed to be constant with depth, more or less reflecting real-world conditions in the middle of the night.

3. Hydrometeorological behavior of Lake Kinneret

a. Observations

The hydrometeorological variables recorded at Sapir and Ein Gev during the summers of 1992 and 1993 included wind speed and direction, air temperature and specific humidity, water temperature, and surface sensible and latent heat fluxes (Assouline and Mahrer 1996). The Sapir station was located 200 m offshore (above water), and the Ein Gev station also was sited above the water, at the end of a 50-m-long dock constructed perpendicular to the lake shore. All sensors were mounted 4 m above the lake surface.

b. Simulations versus observations

The observed hydrometeorological variables for the period of 23–25 August 1992 and the corresponding simulated variables are shown in Fig. 4. The various observed variables, including lake surface temperature (Fig. 5), depict a regular diurnal pattern. From late night until early morning, air temperature is low, relative humidity is high, and their variation across the lake is small. During this time period, winds are weak, coming from the west at Sapir and from the east–southeast at Ein Gev.

From sunrise until 1300 local standard time (LST), air temperature increases rapidly, and the relative humidity decreases correspondingly. The winds at Sapir and Ein Gev change direction by about 180°, becoming easterly and southwesterly, respectively. Also, during this period, there is an appreciable difference in air temperature between the two stations: at Sapir it can be 3°C lower than at Ein Gev, around noon. After 1300 LST, this difference reverses, as the air temperature at Sapir becomes higher and the relative humidity becomes lower. This change of tendency corresponds to a very large increase of the wind speed over the lake, an increase that first appears at Sapir with another 180° change of direction and, about 1–2 h later, appears at Ein Gev where it also becomes westerly. The maximum wind speed is about 8–9 m s−1 at Sapir and about 5 m s−1 at Ein Gev.

Clearly, Fig. 4 emphasizes that RAMS is capable of reproducing the diurnal patterns of the different hydrometeorological conditions observed at these two stations. To demonstrate its capability further, Fig. 6 presents the correlation coefficients between simulated and observed variables. In general, better correlations are obtained at Sapir than at Ein Gev. This result may be caused by the fact that the hydrometeorological conditions at Ein Gev, which is located downwind from the lake most of the day (and especially during the penetration of the MSB into the lake region), are more affected by the lake surface temperature than are the conditions at Sapir. Use of a more realistic lake surface temperature that accounts for its spatial distribution as indeed observed in the lake may improve the model performance, especially on the eastern side of the lake.

The lowest correlation coefficients (r = 0.80 and r = 0.72 at Sapir and Ein Gev, respectively) are obtained for the wind direction. This result is not surprising, given that a small variation of the wind direction near 0° (or 360°) has no important physical meaning but can affect the correlation very much. For instance, if the observed wind direction is +5° and the simulated one is −5°, the difference is small. For the calculation of the correlation coefficients, however, this 10° difference is interpreted as a difference between 5° and 355°, which is quite large. These synthetic differences could be reduced and, as a result, better correlation coefficients could be obtained by choosing a different discontinuity point on the plotting axes (perhaps using axes that vary from −180° to +180°). While such a choice would appear to improve the model performance, it in fact would not change its capability.

The high correlation obtained between these simulated and observed hydrometeorological variables and the good reproduction of their diurnal pattern by the model indicate that the model is capable of simulating this complex environment. Figures 7 and 8 indicate that this performance is not limited only to the 23–25 August 1992 period, because under different synoptic conditions RAMS’s capability again is demonstrated. Note, however, that the correlation coefficients in most cases are lower during this other period, with a particularly low value for the relative humidity at Ein Gev (r = 0.45).

Note that, over the two three-day periods depicted in Figs. 4 and 7, the diurnal variation of the various hydrometeorological conditions is superimposed on a low-frequency variation. This fact is particularly noticeable in the air temperature above the lake, which depicts an increasing tendency during the period 23–25 August 1992 and a decreasing tendency during the period 19–21 September 1993. This low-frequency signal clearly is caused by the change in synoptic conditions (see Fig. 2), which are well introduced in the simulations through RAMS’s lateral boundaries.

It also is important to point out the appreciable differences between the observations and the simulation found during the two periods considered here. For instance, the simulated relative humidity depicts a decreasing trend during both three-day sequences. Numerical tests revealed that, when the soil moisture is increased uniformly over the entire simulated domain, this trend is diminished, but the overall quality of the simulation (i.e., wind and temperature fields) degrades. More accurate representation of soil moisture could be helpful in removing this trend. Also, when winds are weak, a significant difference is found in wind direction. This result is expected for at least two reasons. First, weak winds are very sensitive to even small topographical features. Although a high-resolution grid is used in the lake region, the microtopography near the observing stations may have a significant impact on the measurements, which are not resolved or parameterized in the model. Second, the precision of the wind sensors considerably degrades at low wind speed. Assouline and Mahrer (1993) indicated that, in general, the errors associated with the measurements of wind speed and direction are about 0.5 m s−1 and 15°, respectively. This level of uncertainty is true particularly at low wind speed because of the inertia of the sensors. Last, it should be kept in mind that only first-order approximations were made for the lake surface temperature and the soil moisture content of the land surrounding the lake. A better estimate of these important variables possibly could improve the model performance.

The observed and simulated surface heat fluxes during 23–25 August 1992 are shown in Fig. 9. From late night until noontime, the observed latent and sensible heat fluxes are, at Sapir, about 100 and 20 W m−2, respectively, and, at Ein Gev, 50 and 10 W m−2, respectively. There are significant differences between the simulation and the observations. During the afternoon and evening hours, the fluxes increase significantly, especially during the MSB passage over the lake. Although the general trend of the observations is represented correctly in the simulation, the observed maximum latent heat flux is about 40% larger than the simulated one.

The major discrepancy between the simulation and the observations is for the latent heat flux, especially at the Sapir site. This discrepancy is because this flux is sensitive to several parameters. In particular, a small discrepancy in lake surface temperature results in a relatively large error in this flux. Moreover, the measurement of the latent heat flux probably is the least reliable of all observations, especially in the specific case of the Sapir site where the instruments are located offshore above the water. Indeed, the krypton hygrometer that was used for the eddy correlation in this experiment is very sensitive to water droplets. Therefore, it is possible that the highly turbulent MSB that penetrates the lake increases the number of droplets transported above the lake and affects the measurement. This conclusion is supported by the fact that the discrepancy in the absolute value of the sensible heat flux is much smaller than that seen in the latent heat flux, and that, unlike the model, which is based on an energy balance at the lake surface, observations of the various fluxes do not close the energy budget very well (Assouline and Mahrer 1996). These discrepancies are well reflected by the relatively low correlation coefficients obtained between observed and simulated surface heat fluxes that are presented in Fig. 10.

It should be noted that the simulated sensible heat flux at Ein Gev is correlated poorly with observations (r = 0.22). However, one needs to realize that the absolute magnitude of this flux is very small in comparison with the energy fluxes into and out of the lake, and that it is very sensitive to the lake surface temperature, which is assumed to be constant in the simulation. Given that a small fluctuation of the lake surface temperature, the air temperature above the lake, and the surface wind speed can have considerable effects on the surface sensible heat flux, this low correlation is not alarming and should not overshadow the overall quality of the simulation.

To understand better the hydrometeorological conditions near and above the lake, the cross sections (x–z plane) of the eastern wind component u and potential temperature θ are shown in Fig. 11, and the surface horizontal wind and surface potential temperature fields are given in Fig. 12. The data presented in both figures are obtained from the simulation for 24 August 1992.

In the early morning (0600 LST), the winds converge toward the lake in the lower part of the atmosphere, but a strong westerly wind exists above ≈1 km MSL (Fig. 11). Figure 12 shows that the air in the entire valley surrounding the lake is cool and stable. The air is slightly cooler near the northwestern shore. To emphasize better the zone and magnitude of the flow convergence that occurs over the lake, the vertical velocity in the atmospheric surface layer also is provided in this figure. At that time, the air motions in the valley are controlled by katabatic downslope winds from the surrounding high topographical features and by the land breezes generated by the temperature difference between the warm lake surface and the cool land. The cool, high-density air mass residing over the lake acts as a barrier for the strong westerly wind flowing high above the valley, which is warmer and has a lower density.

At noon, a strong westerly wind is found above the Galilee Hills, west of the lake valley, and a moderate westerly wind exists above the Golan Heights, east of this valley (Fig. 11). A well-developed atmospheric mixing layer is seen in the valley, and a pocket of stable air still is found above the lake. Figure 12 indicates that the surface winds diverge over the lake, completely reversing the surface wind pattern seen at 0600. The air temperature above the lake has increased by about 6 K, but its spatial distribution has remained more or less the same. Note that neither u nor θ at an elevation higher than ≈2000 m above the lake valley have been affected noticeably by these significant low-level changes, emphasizing a clear decoupling between synoptic-scale motions and the mesoscale circulations, which have developed locally.

After sunrise, considerable horizontal temperature gradients develop between the land (which strongly warms up as a result of the absorption of solar radiation at the ground surface), the Mediterranean Sea, and Lake Kinneret (whose temperatures are much less affected by the absorption of solar radiation). As a result, sea and lake breezes develop in this region. Simultaneously, anabatic upslope winds are induced along the hills around the lake. The sea and lake breezes, combined with these anabatic flows, enhance the local circulations. For instance, the strong westerly wind found above the Galilee Hills at noon is the result of the upslope flow that develops on the western side of the Galilee Hills, enhanced by the MSB. The lake breeze, combined with the upslope flow that develops on the eastern side of the Galilee Hills, opposes the penetration of this strong westerly wind toward the lake. In addition, the cool, high-density air pocket above the lake surface also contributes to this resistance.

One can notice in Fig. 12 that, at noon, the easterly surface wind above the lake is stronger than the westerly wind. This difference is due to the larger temperature gradient between the lake surface and the land on the western flank of the valley, which is exposed much better to the morning sun than is the eastern flank. Also, the western flank of the lake valley is more arid than its eastern flank, resulting in a higher temperature there, even with the same amount of solar radiation absorbed at the ground surface on both sides of the valley. Furthermore, the relatively strong large-scale westerly wind passing over the Galilee Hills creates a low pressure zone in the lee of the hills (on the western flank of the lake valley), which facilitates the development of the lake breeze and the thermally induced upslope wind. In fact, the importance of this mechanism was confirmed by producing a simulation identical to the one discussed here except that the synoptic-scale (background) wind was directed in the opposite direction (i.e., it was changed to an easterly wind). In that case, the westerly surface wind above the lake became stronger than the easterly wind.

The additional cross sections provided in Figs. 13 and 14 emphasize the dramatic change of hydrometeorological conditions that occurs over the lake during the afternoon hours. As the sun appears in the west, the amount of radiation received on the eastern side of the Galilee Hills (i.e., the western side of the lake valley) is reduced considerably because of the strong slope of the terrain. As a result, the energy input, which sustained the temperature gradient between the lake and the land west of the lake, is rapidly discontinued. This decrease greatly weakens the easterly flow, which opposed the strong penetration of the MSB. Furthermore, the western side of the Galilee Hills is now well exposed to solar radiation, and this exposure gives an additional boost to the already strong westerly upslope wind enhanced by the MSB.

As the intensity of the solar radiation decreases during the afternoon hours, the turbulence above the ground surface weakens and allows cool air from the Mediterranean Sea to propagate inland more rapidly (Anthes 1978). Also, since the inversion layer is not very high above the Galilee Hills, when the MSB passes there, its magnitude increases because of a channeling effect (Long 1954; Durran 1986; Durran and Klemp 1987).

As a result of these various processes, in early afternoon a strong westerly wind penetrates the lake from its western shore and, within less than two hours, reaches the eastern shore. As this wind descends the Galilee Hills toward the lake, it warms adiabatically and pushes the stable atmospheric layer that had built up above the lake. When this forcing happens, a convective boundary layer capped by an inversion layer at about 1000 m (MSL) is obtained over the lake. Stanhill and Neuman (1978) observed such an inversion layer at that height.

As pointed out by Lu and Turco (1994), when the air over a mountaintop is fairly stable, the inland penetration of the sea breeze can be blocked by that mountain. Because there is a lower terrain and a shorter distance between the northern part of the lake and the Mediterranean Sea, the strong westerly wind arrives first at the northwestern shore of the lake. This phenomenon was observed by Bitan (1981), who reported that the penetration of the MSB to the southwestern shore was felt one or two hours later than on the northwestern shore.

The rapidity of this meteorological event is illustrated clearly in Figs. 13 and 14. As the MSB penetrates the lake region, it initially is deflected north and south toward low-topography channels (see Fig. 1), and it also combines with the anabatic upslope flow, which develops on the Golan Heights east of the lake valley. At 1800 LST, the MSB has penetrated into the entire lake valley (Figs. 11 and 12) and is stronger on the western shore than it is on the eastern shore of the lake. This difference of wind intensity across the lake probably also is related to the lee effect of the synoptic-scale westerly wind passing over the Galilee Hills and the Golan Heights, which creates a high pressure zone on the eastern side of the lake valley and blocks the airmass movement there.

The Coriolis force has almost no effect on the near-surface winds in the lake area. This effect was assessed by producing a simulation similar to the one described here but with the Coriolis term set to zero. Only minor differences were found in the wind field between these two simulations.

The warm and dry air mass descending the Galilee Hills and penetrating the lake area promotes evaporation from the lake and is cooled by the water surface, which is at a lower temperature. Because this cooling is proportional to the time that the air mass spends over the water, the air temperature is, in general, higher near the northwestern shore of the lake and cooler near its southeastern shore.

At night, the solar energy that fueled the anabatic wind and the sea and lake breezes disappears. As a result, these atmospheric motions dissipate. At the same time, cooling by longwave radiative emission takes place over the land. Because the lake surface temperature is kept constant, this cooling creates a lake–land thermal gradient, which triggers land breezes that converge over the lake. Note that, in reality, because of convection and the high heat capacity of water, the lake surface does not cool as much as the surrounding land does. Thus, the constant lake temperature imposed in our simulations does not introduce a large error. In Fig. 12, these breezes mostly are noticeable at 0600 LST.

The land cooling around the lake has at least two additional effects: 1) it induces the development of a stable atmospheric layer (as clearly illustrated by the cross sections of potential temperature presented in Fig. 11), and 2) it generates katabatic flows of cool, high-density air, which converge toward the low-elevation lake valley from all the high-topographical features that surround it. The combination of katabatic winds and land breezes results in relatively strong, nocturnal flows of cold air, which converge over the lake and stagnate there until the MSB redevelops the following day.

4. Discussion and conclusions

Observations collected near the western and eastern shores of Lake Kinneret were used to demonstrate the capability of RAMS to simulate the diurnal variation of the hydrometeorological conditions on the lake. The combination of complex topography around the lake (varying from ≈2800 m to ≈−410 m MSL), the proximity of the Mediterranean Sea, and the arid land surrounding the lake induces the development of a complex system of mesoscale and microscale circulations, including sea, lake, and land breezes, as well as anabatic and katabatic winds. The strength and timing of these circulations and their interactions greatly affect the hydrometeorological conditions of the lake, which are subject to important diurnal variations of wind intensity and direction, temperature, humidity, and fluxes.

Although Lake Kinneret is only about 12 km wide and 22 km long, these hydrometeorological conditions have large spatial variability. Even when averaged on a daily basis, a large spatial variability is found over the lake. This variability is well illustrated in Fig. 15, which emphasizes a surface wind speed variability of more than 100%, a latent heat variability of about 100%, and a sensible heat variability of about 400% across the lake.

Of particular interest, as depicted in Fig. 15, the spatial distribution of latent heat flux appears to be controlled largely by wind speed. Because the lake evaporation is a crucial component of its water budget, a few sensitivity tests aimed at evaluating the importance of the lake surface temperature also were performed. The results, together with the observations collected at Sapir and Ein Gev, are presented in Table 1. Clearly, and not surprisingly, it appears that evaporation is very sensitive to lake surface temperature. For example, the use of mean lake surface temperatures that are 3 K lower or higher than those observed results in daily evaporations, averaged over the lake, of 2.8 and 9.9 mm, which are 53% lower and 65% higher, respectively, than that obtained with the mean observed lake surface temperature. This sensitivity analysis also emphasizes that the feedback from the lake temperature on the air temperature and the wind speed and direction is weak. Thus, for meteorological purposes (except for the lake surface fluxes), it seems that the feedback from the lake dynamics that affects the lake surface temperature is not really important. For that purpose, the daily, spatial mean lake surface temperature is sufficient.

As demonstrated by Pan (1999), the magnitude and spatial variability of the wind and heat fluxes over the lake have very important impacts on the lake hydrodynamics and thermal structure. In return, as demonstrated by this simple sensitivity analysis, the lake surface temperature, which is strongly affected by the lake dynamics and the energy balance of the lake, has a crucial impact on the surface heat fluxes. Given this sensitivity and the fact that the lake temperature is not known a priori, it appears that the development of a coupled lake–atmosphere model is needed to provide good estimates of lake evaporation. Such a model currently is being developed and tested and will be described in a future paper. Here, it was shown that the atmospheric component of such a coupled model performs well, given the particular complexity of the Lake Kinneret system and the uncertainty inherent in observations above turbulent water. Since Pan (1999) emphasized that the lake hydrodynamics and thermal structure also can be simulated accurately, a successful coupling is expected to provide a very powerful tool for lake water resource management.

Acknowledgments

The authors wish to thank Y. Mahrer and S. Assouline for providing the hydrometeorological observations that they collected at Lake Kinneret during the summers of 1992 and 1993. Their contribution to this study is greatly appreciated. This research was funded partly by the United States–Israel Binational Science Foundation (BSF) under Grant 92-00359. Computing facilities were provided by the Rutgers University Center for Environmental Prediction. The second author was a graduate student supported by the Rutgers University Institute of Marine and Coastal Sciences. This financial support is appreciated.

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Fig. 1.
Fig. 1.

Schematic representation of the simulated domain: (a) coarse grid consisting of 4 km × 4 km grid elements, and (b) fine grid consisting of 1 km × 1 km grid elements. The hydrometeorological stations set up by Assouline and Mahrer (1996) were located at Sapir and Ein Gev. The dashed line indicates the location of the cross section used to present some of the model results. Solid lines indicate coast lines.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 2.
Fig. 2.

NCEP–NCAR mandatory-level geopotential heights (m) and wind vectors (m s−1) over the Middle East at 500 hPa, at 0000 UTC on 23–25 Aug 1992 and 19–21 Sep 1993. Solid lines indicate coast lines.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 3.
Fig. 3.

Soil moisture normalized by soil moisture at saturation derived from NDVI for the coarse grid illustrated in Fig. 1.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 4.
Fig. 4.

Simulated (solid line) and observed (dots) evolution of hydrometeorological conditions at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 5.
Fig. 5.

Lake surface temperature observed at Sapir (solid line) and Ein Gev (dashed line) during the period 23–25 Aug 1992.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 6.
Fig. 6.

Comparison between observed and simulated hydrometeorological conditions at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 7.
Fig. 7.

Same as Fig. 4, but for 19–21 Sep 1993.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 8.
Fig. 8.

Same as Fig. 6, but for 19–21 Sep 1993.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 9.
Fig. 9.

Simulated (solid line) and observed (dots) evolution of latent (E) and sensible (H) heat fluxes at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 10.
Fig. 10.

Comparison between observed and simulated latent (E) and sensible (H) heat fluxes at Sapir (left column) and Ein Gev (right column) during the period 23–25 Aug 1992. Observations were made by Assouline and Mahrer (1996).

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 11.
Fig. 11.

Vertical cross section of the (upper row) west–east component of the wind (solid lines indicate positive, i.e., westerly, component, and dashed lines indicate negative, i.e., easterly, component; m s−1) and (lower row) potential temperature (K) on 24 Aug 1992. The location of the cross section is shown in Fig. 1.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 12.
Fig. 12.

Horizontal cross section of (upper row) horizontal wind (m s−1) and (lower row) surface potential temperature (K) at a height of 10 m above the lake surface on 24 Aug 1992. The vertical component of the wind (m s−1) also is given at 0600 and 1200 LST.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 13.
Fig. 13.

Same as Fig. 11, but for early afternoon.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 14.
Fig. 14.

Same as Fig. 12, but for early afternoon.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Fig. 15.
Fig. 15.

Horizontal cross section of daily mean horizontal wind speed (m s−1), potential temperature (K), latent heat flux (W m−2), and sensible heat flux (W m−2), at a height of 10 m above the lake surface on 24 Aug 1992.

Citation: Journal of Hydrometeorology 1, 1; 10.1175/1525-7541(2000)001<0095:SOTSHP>2.0.CO;2

Table 1.

The effects of lake surface temperature (Tl) on Lake Kinneret evaporation (mm day−1) on 24 Aug 1992. Note that the observed mean lake surface temperature was Tl = 28.75°C.

Table 1.
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