Evaporation and energy fluxes during EFEDA: Horizontal variability and area averaging

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1 Exchange Processes at the Land Surface for a Range of Space atid Time Scales (Proceedings of the Yokohama Symposium, July 1993). IAHS Publ. no. 212, Evaporation and energy fluxes during EFEDA: Horizontal variability and area averaging A. M. JOCHUM Institut fiir Physik der Atmosphare, DLR Oberpaffenhofen, Germany Abstract Airborne measurements in the atmospheric boundary layer were conducted in the context of EFEDA to investigate the horizontal variability of near-surface fluxes of energy and evaporation as well as to derive area-averaged fluxes using several methods. Results from a one-day case study of vertial flux profiles have shown evidence for significant differences between evaporation fluxes computed for different parts of the study area. This is corroborated by results from low-level horizontal mapping flights which show a variability of near-surface evaporation fluxes on scales of the order of 4-10 kilometers but also at larger scales. Airborne lidar data show that the inhomogeneiti.es of mixed layer depth also cover scales from a few kilometers up to tens of kilometers. Area-averaged fluxes derived over different sub-areas are different from each other and from the average over the whole area. INTRODUCTION Aircraft observations play a key role in land-surface experiments such as EFEDA (European Field Experiment in a Desertification-Threatened Area) (Bolle et al., 1992) in several aspects. They represent the only means to experimentally bridge the gap between local scale point measurements at ground sites on one hand and meso- to regional-scale approaches of models and satellite data on the other hand. It was the aim of the airborne missions during the EFEDA Field Phase in June 1991 to assess the. spatial and temporal variability of near-surface evaporation and energy fluxes and other atmospheric boundary layer and land-surface parameters on scales ranging from 1 to 10 4 km 2 ; and to test and further develop observational strategies for scale-aggregation and area-averaging of fluxes. The study area (about 70 x 100 km 2 in Castilla-La Mancha, Spain) is a high plain at an average elevation of 700 m msl (above mean sea level) with quite inhomogeneous surface characteristics. Three main sites have been selected and instrumented (see Bolle et al., 1992) in areas of irrigated agricultural fields in the Southwest (Barrax), dry farmland and vineyards in the Southeast (Tomelloso), and very dry land with marginal land-use in the North (Rada de Haro/Belmonte). The terrain is hilly in the North and to a lesser extent also in the South. Aircraft measured fluxes of heat and water vapor show distinct differences over surfaces with different évapotranspiration characteristics (Michels & Jochum, 1993). To investigate these variations in more detail a mapping pattern was flown at low altitude covering the whole area. Horizontal flux maps can be derived from these data. Similar investigations during LOTREX (Jochum et al., 1991) and FIFE (Des-

2 374 A. M. Jochum jardins et al, 1992) have shown that horizontal structures are visible in these flux maps on a variety of scales. THE OBSERVATIONS The DLR Falcon - a twin engine jet instrumented for turbulence measurements (Fimpel, 1987) - was deployed at Alicante airport during the pilot experiment in June Different flight patterns were designed to obtain vertical profiles, areal averages or horizontal maps of evaporation and energy fluxes, respectively. Results from three case studies are used in this study to briefly illustrate the main points. On June 21 and 28 (one of the "golden days") a mapping pattern was flown at low level to investigate the horizontal variability of the near surface fluxes. The pattern was designed to overfly the three main sites and to be completed in approximately one hour in order to ensure quasistationarity. This results in four parallel flight legs (ML2, ML4, ML6, ML7, from South to North) of approximately 60 km each, and one leg (ML1) of 82 km to include the station of Barrax in the Southeast. The horizontal spacing is 7 km between the two southmost legs and 14 km for the remaining legs. All legs were flown in East-West direction (see Figure 4). The flights were performed shortly after noon under almost cloudfree conditions. Each flight included one ascent and one descent vertical sounding in the area, one high altitude map and one low-level mapping (Jochum et al., 1993). Data from a downward looking differential absorption lidar (Ehret et al., 1993) give vertical profiles of aerosol backscatter and of water vapor along the flight track as well as the horizontal variation of mixed layer depth. The vertical structure of the atmospheric boundary layer was inferred from aircraft, lidar (see also Figure 2) and radiosonde data. From this information it was concluded that the low-level mapping pattern was flown at about 0.2 Zi (zi = mixed layer depth). On June 23, the aircraft was flying an L-pattern at three altitudes over two legs with different surface characteristics. The aim of this mission was to investigate the vertical flux divergence over the two legs at different times of the day. The South leg was flown in East-West direction and lies in between ML1 and ML2, whereas the West leg is almost perpendicular to the legs of the mapping pattern over an area with apparently higher surface évapotranspiration than in the South (Michels, 1992; Michels & Jochum, 1993). THE VARIABILITY OF MEAN PARAMETERS A great deal of horizontal variability was observed in the individual time-series of temperature, wind, and, in particular, moisture. Figure 1 (from Michels, 1992) shows an example from the case study on June 23. The amplitudes of the specific humidity fluctuations are similar for both legs and for both altitudes. There is, however, a striking difference in horizontal structure of these fluctuations. For the South leg (Figure la), the high-amplitude fluctuations are confined to the Eastern end, which is located over the irrigated fields around Barrax, whereas they occur almost everywhere along the West leg (Figure lb), which is located over an area containing small lakes and rivers. It is interesting to note that these features are not only apparent in the lower levels but also seem to be persistent in the middle of the atmospheric boundary layer (upper panels in Figure 1).

3 Evaporation and energy fluxes during EFEDA 375 (a) specific humidity (S/kg) m (b) specific humidify (g/kg) 20 g. g m 60 (KM) m m 100 (KM) Fig. 1 Variability of specific humidity along two different flight legs on 23 June 1991: (a) west leg and (b) south leg, at 1550 m a.m.s.l. (top) and 1000 m a.m.s.l. (bottom). From Michels (1992). For studies of turbulent fluxes in the atmospheric boundary layer a good assessment of the mixed layer depth is crucial. The horizontal variability of this parameter, however, makes it difficult to obtain a simple estimate. Crossections obtained from the airborne lidar demonstrate the variability over the EFEDA area on June 28. The influence of a weak coldfront passing through the area from North to South is still under discussion. Figure 2 shows a sketch of mixed layer depth derived from aerosol backscatter plots (Kiemle, personal communication) along legs ML7 (a) and the Western part of ML1 (b). The subsidence inversion, which can be clearly identified from the lidar plots, is marked by a thick dashed line. The thin dashed line in Figure 2b indicates the contours of moist thermal elements ("moistals") growing into the mixed layer. In Figure 2a it coincides with the mixed layer depth. The local terrain contour can be seen on the bottom. The variability of mixed layer depth is apparent on scales of a few kilometers in both legs, although more pronounced in the Northern leg (ML7). In addition, the mean mixed layer depth exhibits differences of several hundred meters along leg ML1 as well as - to a lesser extent - between the two legs. Leg ML1 was flown about 40 min earlier than leg ML7 thus giving the thermals and the mixed layer time to grow. This would explain the "moistals" visible at the earlier stage and the pronounced undulations of the interface, which even start to influence the capping inversion,, at the later stage. The differences of mean mixed layer depth along leg.ml1, however, seem to be due to mesoscale variations. THE VARIABILITY OF TURBULENT FLUXES For the low level mapping pattern the variability of evaporation and energy fluxes along each flight leg was investigated by partitioning the leg into segments and computing the individual averages for each segment. A sensitivity study shows that a segment length of 6 km and a spacing of 3 km (with 50% overlap) is appropriate (Jochum et al, 1993). Based on uncertainty analyses following Lenschow & Stankov (1986) it was concluded there that for these segments variations exceeding the

4 376 A. M. Jochum (a) _ E I Tw?JTjw^n7mwr~T7Hîr~ r 77rw~Tji o I 1500 «1000 ^^~^~-~~^^\_S~^/^ "A/ V ^v^/v^ wmm/////mmmmmmm/mw////////m^^^^ east-west distance, kn- Fig. 2 Variabilityof mixed layer depth along two different flight legs on 28 June 1991: (a) ML1 (south); (b) ML7 (north). Solid line: mixed layer depth; thick dashed line: subsidence inversion; thin dashed line: maximum depth of "moistals". +40% threshold around the mean are significant. Results for leg ML7 are shown in Figure 3a for sensible heat flux, and in Figure 3b for latent heat flux. A great deal of variability can be seen on scales of several kilometers as well as of tens of kilometers. There seems to be no apparent relation to the distribution of land-use underneath the flight path (shown on the bottom of Figure 3 as derived from airborne video). For comparison the results from another case study on June 21 based on the same mapping pattern are included as dashed lines. Obviously both flux patterns on the two different days are similar in some - not necessarily the same - parts of the leg. Another striking feature is the relation between areas of low and high sensible and latent heat fluxes, respectively. The partitioning of available energy into these two fluxes (attributable to different vegetation for example) seems to be different only in parts of the leg. The remaining variability seems to be due to variations in net radiation and ground heat flux. Table 1 illustrates the inter-leg variability of energy (H) and moisture (LE) fluxes (see Jochum et al., 1993). It should be noted that the terrain is higher underneath leg ML1. Thus the average height above ground is about the same for all legs (about 350 m). An uncertainty analysis similar to Lenschow & Stankov (1986) gives a maximum error of 10% for mean heat and moisture fluxes. This is mainly due to the length of the legs and the low altitude flown. The information on inter- and intra-leg variability of fluxes for the whole area is summarized in Figure 4. Jochum et al. (1993) have constructed a horizontal flux map, whereas Figure 4 gives a somewhat more detailed picture. It is assumed that each flux estimate for a 6 km segment is representative for a 6 km by 6 km "pixel". Figure 4 shows the (swath-)areas of high and low moisture flux along all transects flown in a single mapping pattern. The contrast between a region of enhanced moisture transport in the West and less "active" regions with reduced moisture transport in the East and North is most striking. A first inspection of fhe land-use distribution from maps and airborne video shows a variety of rivers and small lakes in the West which probably lead to increased évapotranspiration in that region. Also

5 Evaporation and energy fluxes during EFEDA east-west distance, km Fig. 3 Variability of (a) sensible and (b) latent heat fluxes along leg ML7 on 28 June (solid line) and 21 June (dashed line). Symbols represent averages over segments of 6 km length with horizontal spacing of 3 km. Land-use information is given at the bottom of the figure (1 cm in the vertical direction represents 100% cover). Shaded: fields; dotted: forest and bushes; white: villages; wavy lines: rivers and lakes. the irrigated fields near Barrax in the Southeast corner seem to induce enhanced latent heat flux. A similar picture emerges from the results of Michels (1992) and Michels & Jochum (1993) obtained from the L-shaped flight pattern on June 23, Table 2 (adopted from Michels, 1992) gives an overview of the vertical profiles of mean parameters and fluxes for the noon and evening flight. Both flights show that the Table 1 Mean values of sensible (H) and latent (LE) heat fluxes for five different flight legs ML1-ML7 (from south to north) at 0.2z, on 28 June Quantity (unit) ML1 ML2 ML4 ML6 ML7 average (all legs) standard deviation z (m msl) leg length (km) H {Wm~ 2 ) LE (Win- 2 )

6 378 A. M. Jochum Fig. 4 Areas of high and low evaporation flux along five transects of the mapping pattern flown on 28 June Dashed (white) areas represent latent heat flux larger (smaller) than arithmetic mean average +40% ( 40%). The three supersites are circled by double lines. Scale: 1 cm = 3.8 km. moisture flux is enhanced over the West leg (coinciding with areas of high moisture flux in Figure 4). A SYNOPSIS OF DIFFERENT OBSERVATIONS In order to obtain surface values from airborne flux measurements at 0.2 z, the flux divergence has to be estimated and the flux profiles have to be assumed linear. Available aircraft data suggest values around 1.5 1CT 3 Wm^ktrf 1 for sensible heat flux and negligible values for latent heat flux convergence, respectively. Surface fluxes obtained from a variety of methods and data sources have been compiled in Figure 5. The range of observations at each main site was determined from measurements of different groups at individual towers (Bolle et al, 1992, and Moene, personal communication) within each site. Data for 13:00-14:00 UTC on June 28 were used. Considering the fact that some of these data are still preliminary, there is a high degree of uncertainty in these estimates (for example, the surface energy budget has not yet been closed in all cases). Arithmetic means were computed over all sites, and over all aircraft legs (columns 4 and 5 in Figure 5). The values given in Figure 5 are partly different from those shown in Table 2 of Jochum et al. (1993) since more recent data have become available. Bastiaansen and Roebeling (1993) have estimated surface fluxes from TMS data. Their results are shown in columns 6 and 7 of Figure 5. Airborne latent heat flux estimates apparently fall well within the range of surface observations and remote sensing estimates, with their lower value slightly larger than the minimum of the arithmetic average of the surface observations, and the upper value around 50% of the corresponding maximum. Airborne sensible heat flux estimates are also within the range of surface and remote

7 Evaporation and energy fluxes during EFEDA 379 (a) (b) M M 1,1,1,1 E g 5 Î5 ES?._ > Il II m ta Fig. 5 Comparison of surface fluxes of (a) latent and (b) sensible heat obtained from different methods. Data from the flux towers by courtesy of A. Moene; estimates from TMS data from Bastiaansen & Roebeling (1993). For surface observations minimum and maximum values of all stations at each site are given. For aircraft and TMS estimates mean + standard deviations are shown. c en ç ro sensing estimates, although being closer to their lower limit. Kelly et al. (1992) find that for FIFE the aircraft measurements underestimate the surface observations of sensible heat flux by 30%, and of latent heat flux by 10%. The difference is attributed mainly to the short legs flown across the FIFE area of 15 km by 15 km. From Figure 4 and Figure 5 it is obvious that the simple straightforward way to derive area-averaged fluxes from arithmetically averaging a subset of observations (sometimes using weighted averages) will not generally work for the EFEDA area. Depending on the subset or sub-area selected the results will be different. A more physically based approach using the integral balance method to estimate regional averages from observations of the individual terms in the budget equations (Jochum, 1993) is being tested. Most probably a combination of observational methods and mesoscale modeling (like André et al, 1990, did for HAPEX-MOBILHY) is needed. Table 2 Mean values for specific humidity, potential temperature, sensible and latent heat fluxes on 23 June Quantity (unit) q (gkg->) Height (km msl) West leg noon South leg noon West leg evening South leg evening Q ( C) H (Wm~ 2 ) LE (Wm- 2 )

8 380 A. M. Jochum CONCLUSIONS Results from mapping flights show a variability of near-surface evaporation and energy flux on scales of the order of several kilometers, and again on scales of some tens of kilometers. The mesoscale variations seem to correspond to different evaporation characteristics of the underlying terrain. Area-averaging for different sub-areas gives different results. Acknowledgement This work was partly funded by CEC. It would not have been possible without the efforts of the crews of the DLR Falcon and of the Meteorological Office at Alicante Airport. The contributions of B. Michels, N. Entstrasser and J. Schuster during data analysis of the Falcon data and of Ch. Kiemle in providing the lidar data are gladly acknowledged. I also thank A. Moene for making available the lists of surface flux observations which he compiled from data of all contributing groups. REFERENCES André, J.-C, P. Bougeault, and J.-P. Goutorbe, 1990: Regional estimates of heal and evaporation fluxes over non-homogeneous terrain. Examples from the HAPEX-MOBILHY programme. Boundary-Layer Meteorol-, 50, Bastiaanssen, W.G.M., and R.A. Roebeling, 1993: Analysis of land surface exchange processes in two agricultural regions in Spain using Thematic Mapper Simulator data (These proceedings) Bolle, H.J., et al., 1992: EFEDA: European field experiment in a desertification-threatened area. Ann. Geophysicae, in press. Desjardins, R.L., P.H. Schuepp, J.I. MacPherson, and D.J. Buckley, 1992: Spatial and temporal variations of the fluxes of carbon dioxide and sensible and latent heat over the FIFE site. J. Geophys. Res., 97, 18,467-18,476. Ehret, G., C. Kiemle, W. Renger, and G. Simmel, 1993: Airborne remote sensing of tropospheric water vapor using a near infrared DIAL system. Appl. Optics, in press. Fimpel, H.P., 1987: The DFVLR meteorological research aircraft Falcon-E; instrumentation and examples of measured data. Sixth Symposium on Meteorological Observations and Instrumentation, American Meteorological Society, Boston, Jochum, A.M., 1993: Estimation of area-averaged fluxes from aircraft measurements using different observational techniques. Eighth Symposium on Meteorological Observations and Instrumentation. American Meteorological Society, Jochum, A.M., H. Willeke, N. Entstrasser, A. Klebelsberg, 1991: Measurements in the inhomogeneous atmospheric boundary layer using three powered gliders. DLR-FB 91-30, Jochum, A.M., B.I. Michels, N. Entstrasser, 1993: Regional and local variations of evaporation fluxes during EFEDA. Conference on Hydroclimatology, American Meteorological Society, Kelly, R.D., E.A. Smith, J.I. MacPherson, 1992: A comparison of surface sensible and latent heat fluxes from aircraft and surface measurements in FIFE J. Geophys. Res., 97, 18,445-18,454. Lenschow, D.H., and B.B. Stankov, 1986: Length scales in the convective boundary layer. J. Atmos. ScL, 43, Michels, B.I., 1992: Fluxes of heat and water vapour in a convective mixed layer during EFEDA. DLR-FB 92-21, 77p. Michels, B.I., and A.M. Jochum, 1993: Heat and moisture flux divergence in a region with inhomogeneous surface evaporation. Submitted to J. Hydro!..