Estimation of Spatially Distributed Latent Energy Flux Over Complex Terrain From a Raman Lidar

Investigators

William Eichinger and Li-Chuan Chen (University of Iowa), and Daniel Cooper (Los Alamos National Laboratory).

Acknowledgment

We gratefully acknowledge the help from various individuals in the SALSA program and the Los Alamos National Laboratory lidar team of the Earth and Environmental Science Division.

Study Area

The Upper San Pedro Basin (USPB) was identified as the focal area for initial SALSA (Semi-Arid Land-Surface-Atmosphere) research during an international workshop held in 1995. The riparian system in the U.S. portion of the USPB is the first Congressionally designated Riparian National Conservation Area. The Basin embodies a variety of characteristics which make it an exceptional outdoor laboratory for addressing a large number of scientific questions in arid and semi-arid hydrology, meteorology, ecology, and the social and policy sciences. The area represents a transition between the Sonoran and Chihuahuan deserts with significant topographic and vegetation diversity, and a highly variable climate. It is an international basin spanning the Mexico-United State Border with significantly different cross border legal and land use practices. The upper and middle portions of the basin have a drainage area of 7610 km2 at the U.S. Geological Survey gaging station at Reddington, Arizona with approximately 1800 Km2 in Mexico. Elevations range from roughly 1100 to 2900 m. Major vegetation communities include desert shrub-steppe, riparian, grasslands, oak savanna, and ponderosa pine. In portions of the basin all of these vegetation types are contained within a 20 Km span. The USPB supports the second highest known number of mammal species in the word and the riparian corridor provides habitat for more than 300 bird species.

From a socio-economic perspective, great concern exists regarding the long-term viability of the San Pedro riparian system and ranching in the face of continued population growth. Groundwater sustains the riparian system in the U.S. and also much of the ranching industry in the Mexican portion of the San Pedro. The threat of excessive groundwater pumping to this riparian system has prompted the first application of international environmental law within the U.S. via the North American Free Trade Agreement.

Instrument Description

The solarblind Raman water-vapor lidar used in these experiments is based upon the Raman technique pioneered by Melfi et. al [1969] and Cooney [1970] and extended for daytime, solar-blind operation by Renault et al. [1980], and Cooney et al. [1985]. The device operates by emitting a pulsed ultraviolet laser beam into the atmosphere. Nitrogen gas and water-vapor react to this light via the Raman scattering process, causing light of longer wavelengths to be scattered back to the lidar. The system operates in the solar blind region of the spectrum using krypton fluoride as the lasing media to obtain light at 248 nm. The Raman-shifted nitrogen signal returns at 263 nm and the Raman-shifted water-vapor signal returns at 273 nm. Simultaneous measurement of the water-vapor and nitrogen returns provides a simple method for obtaining absolute measurements. Because nitrogen is the dominant atmospheric gas, dividing the Raman-shifted return signal from water-vapor by that of nitrogen normalizes each pulse and corrects for first order atmospheric transmission effects, variations in laser energy from pulse-to-pulse, and telescope field-of-view (FOV) overlap with the laser beam. The divided returns are then proportional to the absolute water-vapor content of the air. A correction is required to account for the differential atmospheric attenuation between the nitrogen and water-vapor wavelengths.

The typical horizontal range for the lidar is approximately 700 meters when scanning, with a corresponding spatial resolution of 1.5 meters in the near field. The upper scanning mirror allows three dimensional scanning in 360 degrees in azimuth and ±22 degrees in elevation. The uncertainty in the water-vapor mixing ratio is typically measured to be less than 4%.

Water-vapor Concentration Measurement From a Raman Lidar

Evapotranspiration is one of the critical variables in both water and energy balance models of hydrologic systems. These systems are driven by the soil-plant-atmosphere interface and as such involve spatially distributed processes. Traditional techniques of measuring evapotranspiration rely on point sensors to collect information which is often averaged over a region, or assumed to be representative of a far larger area. Spatially averaged data from point sensors is limited in value because of the necessarily limited number of sensors which make the measurements and because of our current inability to extend the measured values at a point (or series of points) to an understanding of the larger scale processes that are ongoing. Remotely sensed data has the potential to provide detailed data over a relatively large area. The three dimensional scanning Raman lidar built by Los Alamos National Laboratory can provide detailed maps of the water-vapor concentration with high spatial and temporal resolution. Using this information, the spatially resolved evaporative flux can be estimated over the scanned area.

A vertical scan from the lidar showing the water-vapor concentrations in a vertical plane.

Lidar Derived Flux Method

The water-vapor concentration in the vertical direction can be described using Monin-Obukov Similarity Method (MOM). With this theory, the relationships between the properties at the surface and the water-vapor concentration at some height, z, within the inner region of the boundary layer is:

where the Monin-Obukhov length, L, is defined as:

and z_0v is the roughness length for water-vapor, and Q_v is the Monin-Obukhov similarity function for water vapor, q_s and T are the surface specific humidity and temperature, q(z) is the specific humidity at height z, and u_* is the friction velocity, k is the von Karman constant, taken as 0.40, and g is the acceleration due to gravity. The roughness length is a free parameter to be calculated based upon the local conditions.

Heat and momentum fluxes are often determined from measurements of temperature, humidity, and wind speed at two or more heights. In using this method, there are often issues of fetch which lead to questions concerning the optimal heights for these measurements. While the maximum distance between the measurements leads to the greatest accuracy, measurements too close to the surface or so high that they are outside the inner region lead to erroneous values as well.

Evaporative fluxes can also be obtained from a combination of Monin-Obukhov similarity theory and vertical water-vapor profiles taken with the lidar. Rearranging (1) into linear form

where M is the slope of the fitted function ( M = LE /(L_e k u_*D) ), z' is a reduced height parameter ( z' = ln(z-d_o) - Q_v((z-d_o)/L) ), and c is a regression constant ( c = Mln(z_o) + q_s ). While the basis for the method is Monin-Obukhov theory, it is based upon a least squares fit to several hundred measurements of water-vapor concentration rather than just two.

If the vertical profile of the water-vapor concentration in the inner region is measured and a least squares line is fitted using (3), then M is determined as the slope of the fitted line and the flux is then

where u_* and L are obtained from local measurements. This approach only estimates the latent energy flux, especially over mixed terrain and canopy.

Surface Determination From Lidar

An added capability of the lidar that is useful in estimating fluxes over complex terrain is the ability to determine the location of the surface. For the case of mixed terrain and canopy, the lidar is used to find the location of the surface in the range interval under investigation. A linear least squares fit is made to determine the elevation and slope of the top of the canopy. The distance from the measured point to the surface along a line perpendicular to the measured slope and elevation is used as the corrected height above the surface. A measured value of the Monin-Obukov length is used to further adjust for atmospheric stability. However, in practice, the use of this correction results in a small (usually on the order of 3%) change in the estimated flux.