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Orographic influence on the distribution of accumulated rainfall with different wind directions
Atmospheric Research 47–48 Ž1998. 615–633
Orographic influence on the distribution of accumulated rainfall with different wind directions Hermann Gysi
)
Institut fur ¨ Meteorologie und Klimaforschung, Forschungszentrum Karlsruher UniÕersitat ¨ Karlsruhe, P.O. Box 3640, D-76021 Karlsruhe, Switzerland Accepted 2 September 1997
Abstract For the region of the Upper Rhine valley with its surrounding mountains the influence of the orography on the horizontal distribution of surface rain amounts is analyzed by use of data of a C-band Doppler radar. A 30-month data sample is evaluated by accumulating rain intensities for different time intervals Žmonths, years.. The rain intensities taken into account refer to a constant height of 1.0 km AGL, i.e., to a terrain-following level. It is found that the influence of the orography on the rainfall distribution depends strongly on the direction from which clouds and rain systems move into the area under consideration. Accordingly, the data of all rain events are investigated in three different ways: Ži. for the whole period Žii. month by month regardless of wind direction and Žiii. also for the whole period but considering eight different sectors of wind directions, with each sector 458 wide. The wind direction dependent rain accumulations presented show the following features: Ž1. well-known phenomena as maxima of rainfall in the updraft region of hills or minima in the lee-side of hills, Ž2. phenomena triggered by the mesoscale flow systems such as preferred developing areas or tracks of thunderstorms as well as rain maxima in the lee-side of small hills induced by a counter current to the geostrophic wind. q 1998 Elsevier Science B.V. All rights reserved. Keywords: Radar; Rain; Accumulation; Wind direction; Orography
1. Introduction The distribution of rain at the surface generally shows a large variability in time and space. This variability occurs as well over flat terrain Žresulting from rain showers or )
Fax: q41-7247r824742; e-mail: [email protected].
0169-8095r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved. PII S 0 1 6 9 - 8 0 9 5 Ž 9 7 . 0 0 0 8 9 - 6
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convective systems. as— more pronounced— over orographically structured terrain. In both cases its evidence is difficult to substantiate ŽNickerson et al., 1986; Joss and Waldvogel, 1990; Tateya et al., 1991; Held and Joss, 1994.. This difficulty is mostly caused by the lack of highly resolved rainfall data. Usually, conventional rain gauge measurements are taken into account. However, such data are seldom reliable since the rain gauge network error of the rain distribution is rather sensitive to the relative variability of the rain field ŽSeed and Austin, 1991; Huff, 1970.. Thus, the point measurement of a single rain gauge often has to represent the rainfall intensity of an area of hundreds of square kilometers. Additionally, they often have only a time resolution of 24 h. In contrast, for investigating a wind-dependent rain distribution, data with time resolution of at least 1 h are needed. Moreover, studies about the orographic influence on the distribution of the accumulated rain within different wind directions need a very dense network of rain gauges. Corresponding experiments, however, are rather seldom
Fig. 1. Orographical structure of the region around the location of the radar Ž D . in the valley of the Rhine river Žblack solid line.. Also marked are the locations of the rain gauges 1–10 ŽREKLIP. and W ŽGerman Weather Service. and the disdrometer ŽD. used for adjustment and data correction.
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and the networks are operational only over short periods ŽHildebrand et al., 1979; Hill et al., 1981.. A different method to get rain-intensity data highly resolved in space and time consists in using radar data ŽCollier, 1972; Sauvageot, 1994.. In this study data of a C-Band radar located in the Upper Rhine valley are analyzed. The orographic structure of the region surrounding the radar is characterized by two parallel north–south orientated ridges of hills along the wide and plain Rhine valley. In Fig. 1 the location of the radar is indicated by D. Also indicated in Fig. 1 are the locations of the equipment used for adjustment of the radar measurements: ten rain gauges of the REKLIP network ŽNo. 1–10. ŽWenzel et al., 1996., one rain gauge from the German weather service ŽW. and one Disdrometer ŽD.. From climatological Ž30-year-mean. data ŽFiedler, 1995. it is shown that at the steep western slope of the Black Forest towards the Rhine valley there is a large variation in the distribution of the annual precipitation amounts. The largest values occur at the top of the Black Forest mountains and the minimal values occur in the Rhine valley east of the Vosges mountains between their easterly slopes and the city of Strasbourg. Due to the specific orographic structure of the area under consideration the appearance of many different orographic effects influencing the regional rainfall distribution is expected: Not only well-known phenomena as rainfall maxima in the updraft region or minima downstream the hills, but also phenomena triggered by mesoscale flow systems, e.g., stationary parallel rain bands ŽGysi, 1995., preferred developing regions and tracks of thunderstorms or rain maxima in the lee-side of hills can be observed. Such effects are strong enough to be statistically significant but they depend on the direction from which the clouds and rain systems move into the region of interest. Therefore they can usually not be recognized in the monthly accumulation of rain Žneither by radar nor by ground-based rain gauge measurements. which comprises a mixture of rain events with various wind directions. They only become obvious when the rain amount is accumulated over many rain events with a similar structure of the vertical wind profile.
2. Data sources and correction The data presented here are obtained by a single C-band Doppler radar located in the upper Rhine valley in the southwestern part of Germany ŽFig. 1.. The technical details of that radar are compiled in Table 1. The usual operational mode of the radar consists of two volume scans, one of radar reflectivity Ž Z . and the other of radial Doppler velocity Ž V .. For a period of 30 months ŽJanuary 1994 till May 1996. volume scans of both Z and V are available with a time resolution of 12 min which is the duration of two scans each using the following 16 elevation angles: 0.2, 1.0, 2.0, 3.0, 4.5, 6.0, 7.5, 9.0, 11.0, 13.0, 15.0, 17.5, 20.0, 23.0, 26.0 and 30.08. The maximum range chosen for Z was 120 km and for V 100 km, respectively, with a radial resolution of 0.5 km and an azimuthal resolution of 18. To remove low-frequency signals due to ground clutter in a first step the raw data have been immediately corrected during their acquisition by a high pass IIR Žinfinite
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Table 1 Main characteristics of the radar Frequency, wavelength Peak transmitted power Transmitter type Pulse duration PRF Sensitivity ŽMDS. Receiver dynamic ranges: lin Ž I,Q . log Ž Z . Antenna diameter Antenna gain y3 dB beamwidth 1. Sidelobe level Radar height ŽAGL. Žafter Jan. 1. 1996.
5.62 GHz, 5.6 cm 252 kW Ž84 dBm. Magnetron 0.85 and 2.0 m s 250–1200 Hz y104 dBm 90 dBm 101 dBm 4.2 m 44.7 dB 0.988 y28 dB 30 m 38 m
impulse response. Doppler filter selected from eight available stop- and passbands ŽPassarelli et al., 1981.. As proposed by Schmid et al. Ž1991. an intermediate filter ŽNo. 4 of 8. had been chosen. From each volume scan of Doppler-filtered reflectivity data the rain intensity is interpolated on a terrain-following layer in a height of 1.0 km AGL. The data in this height are assumed to be representative for the rain intensity at the ground. The vertical resolution in the terrain-following layer is 125 m and the horizontal resolution in each direction is 0.5 km. From the volume scans of the radial Doppler velocity vertical, profiles of wind direction and speed at the location of the radar are derived by the VVP method ŽWaldteufel and Corbin, 1979. within a range of 30 km and a vertical layer spacing of 250 m. By using a terrain-following layer the following difficulties in analyzing the rain intensity or its accumulation occurs: One problem is the vertical inhomogeneity of the rain intensity ŽJoss and Pittini, 1991. which might be interpreted as a horizontal inhomogeneity due to the varying height of the terrain-following layer above sea level. A further problem appears when the terrain-following layer crosses the bright band. In this case data from regions above the bright band where snow is present are interpreted as if the hydrometeors consist of water since a unique radar equation is applied. This leads to an underestimation of precipitation amounts. For the region considered this happened when the melting zone lies between the minimum Ž1.1 km MSL. and maximum height Ž2.2 km MSL. of the terrain-following layer. The vertical decrease of the rain intensity, the snow measurement from above the bright band as well as the attenuation of the radar beam in the bright band cause an underestimation of precipitation at the top of hills and at large distances ŽFabry et al., 1992.. The bright band problem is expected to occur mainly during the period from October to April. In order to relate the radar reflectivity Ž Z . to rain intensity Ž R ., for the whole area under consideration the following three different Z–R relations Žcf. Sauvageot, 1994. were assumed to be representative for different periods and meteorological situations.
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Z s 300 R 1.5 Žrain only. Z s 200 R 1.6 Žfor rain. Z s 1800 R 2.2 Žfor snow.
a. May to November b. December to April
The application of different Z–R relations for rain results from previous investigations. Gysi Ž1995. has shown that in summer when rain is partly of stratiform and partly of convective type the relation Z s 300 R 1.5 leads to a better agreement between radar and rain gauge data than the relation Z s 200 R 1.6 which leads to a better agreement in winter when stratiform rain prevails. Because measurement by radar is an indirect remote sensing method it is important to adjust the estimated rain intensity with rain measurement from other sources ŽCollinge, 1991.. Long term variations of the measured reflectivity factor due to age processes of the radar-hardware Že.g., thyratron, magnetron, oxidation in the RF-wave guide, etc.. usually cause an underestimation of the reflectivity factor between 3 and 6 dBZ. With continuous and simultaneous measurements of drop spectra with a disdrometer ŽLoffler ¨ Mang et al., 1996., located 10 km south of the radar at the top of a building situated 50 m over the Rhine valley, a reflectivity correction factor F for every month has been determined to correct this underestimation. The factor has been estimated from the difference between the mean radar reflectivity factor at the location of the disdrometer and the reflectivity factor calculated from disdrometer data Žwhich have been assumed to be representative.. The corresponding radar reflectivity is the mean value for the volume by the four elevations from 1.0–4.58, the six azimuth degrees and four range bins, both centered at the location of the disdrometer. Only rain periods with homogeneous rain intensities Že.g., stratiform rain events. are considered. The rain intensity is corrected range and rain type independent in the following way: Zcorr s Zuncorr q F s 10log Ž AR B . w dBZ x
Ž 1.
and with correction factor F s 10log Ž Z DisrZ Rad . w dBZ x
Ž 2.
Zuncorr s 10log Ž AR B . y 10log Ž Z DisrZ Rad . w dBZ x
Ž 3.
and
resulting finally in Rs
10 F r10 A
1rB
10
Z un corr r10
w mmrhx
Ž 4.
Z Dis is the average monthly reflectivity factor from the disdrometer and Z Rad the respective radar average. As a further adjustment, the monthly rain accumulation data at the terrain-following layer have been compared with the monthly accumulation measurement of ten rain gauges within a distance from 6 to 70 km Žsee Fig. 1.. For radar adjustment by rain gauge data sophisticated interpolation procedures have been presented, e.g., by Creutin et al. Ž1988.. The method applied here is simpler ŽSauvageot, 1994.: A mean monthly correction factor f s ÝGirÝR i has been determined where G is the monthly rain
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amount of the different rain gauges Žindicated by subscript i . and R the corresponding rain amount by radar Žin an area of 4 km2 with the rain gauge in the center.. The correction factor applied was equal for every pixel of the terrain-following layer and equal for every rain event of a certain month. A rain event starts or ends with the beginning or ending of rainfall somewhere in the considered area. Because the ten rain gauges of the used rain gauge network have a different representativity for a comparison, the correction factor for the rain amount has been weighted with its representativity. The four stations Fr-stett, Sa, Ho-berg and Ho-ginde ŽNo. 7–10 in Fig. 1. are all within a distance of about 70 km and heights of 130, 140, 490 and 1150 m MSL. They are situated in a line parallel to the largest variation of the orographical structure Žand parallel to the largest gradient of accumulated rain.. A full consideration of these four rain gauges for radar adjustment in winter would give a large overestimation of the rain amount near the radar. Their rain amounts have therefore been weighted with a Žmonthly individually determined. factor between 0 and 1. The reasons for the poor representativity of the four rain gauges are: Ž1. due to a beam overshooting or a partial beam overshooting with shallow precipitation within this distance radar measurement is underestimated Žprincipally at the top of the hill.; Ž2. due to the large variation of rain amount the different methods of measurement become significant: a point measurement at the ground is compared with a volume integrated measurement Žthe beam width at a distance of 70 km is about 1.2 km.; and Ž3. the underestimation of precipitation beyond the bright band Žsnow. by radar. In summer the horizontal variations of the rain intensity due to local thunderstorm activity generally are very large and hence the representativity of all rain gauges for a larger area is weak. Therefore the radar measurements have only been adjusted in cases where f ) 1 and no large gradients of the accumulated rain amount on the terrain-following layer was within a radius of 5 km around the location of the rain gauge. The effect of all corrections and adjustments on the precipitation accumulation at the locations of the rain gauges is shown in Fig. 2. The period of accumulation for this
Fig. 2. Rain amount in millimeters for different locations as indicated according to rain gauge measurements ŽREKLIP. as well as corrected and uncorrected rain accumulation by radar at 1.0 km AGL over a period of 2 years.
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comparison was 2 years Žfrom January 1994 to December 1995.. The corrected rain amounts from reflectivity data show a good correspondence with those from the rain gauges ŽREKLIP. up to a range of about 50 km from the radar ŽNo. 1–6 in Fig. 1.. For the remaining four rain gauges ŽNo. 7–10 in Fig. 1. in a distance of about 70 km the agreement between the corrected radar data and the rain gauge data is poor due to the effects discussed. The difference between the rain amounts measured by the rain gauges and those obtained from radar attains a maximum of 50% at station 10 ŽHornisgrinde, top of a mountain.. As can be recognized from the rain gauge data, the accumulated rain amount increases with the location height Žsee stations 8, 9 and 10.. Within a horizontal distance of 5 km the rain amount measured by rain gauges increases by 100%. This comparison shows the importance of correcting the radar data. It also shows some difficulties of the correction procedure. 3. The method of accumulation and the frequency of the different wind directions To reveal the orographic influence on the distribution of the accumulated rain amount and its dependence on the structure of local wind system, the rain intensities on the terrain-following layer have been integrated in two different ways: Ža. monthly without respect of the wind direction and Žb. over the whole period of 30 months considering eight different sectors of the wind direction, with each sector 458 wide. Radar data have been considered whenever somewhere in the region covered by radar rainfall has been measured. Rain intensities were integrated in time with respect to a certain sector if the mean wind direction—measured above the radar between 2 and 2.5 km AGL—falls into that sector. That height interval has been chosen since it is assumed that it is the lowest layer where the wind is not disturbed by orography so that the wind direction relevant to this layer gives the direction of motion of the precipitation systems. A comparison with wind data from radiosoundings at Stuttgart Žsee Fig. 1, 70 km southeast of the radar. shows a good agreement with vertical wind profiles from radar data above 2 km AGL ŽGysi, 1995.. Table 2 shows a list of duration of accumulated rainfall for the whole period Ž30 months. for each of the eight wind sectors. Nearly 50% of the accumulated rainfall occur when the wind direction is from southwest to west and another 25% occur when the wind blows from adjacent directions, i.e., south to southwest and west to northwest. The remaining 25% of the accumulated rainfall are shared by the other five sectors. The two sectors from east to south show the smallest number of cases with rain. In comparison, the annual climatological percentage distribution of east to south wind at the mountain station Hornisgrinde ŽFiedler, 1995. is with more than 12% significantly higher than with 5.1% of the time during rain. This may be induced due to the mountains of the Black Forest and the Alpes. Since the region covered by radar measurements is in the lee-side of the Black Forest and the Alpes for these wind directions the absence of rainfall events seems to be an effect of this large-scale structure of the orography. The other two sectors with a very small number of cases with rainfall are those with wind direction from north to east. For all easterly wind directions the amount of rainfall is small Žcf. Fig. 9.. But the wind directions from southeast to south are important for the thunderstorm activity in the Rhine valley Žsee Section 4..
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Table 2 Wind direction statistics corresponding to a rainfall period of 30 months and for the two months March and May 1996 Acronym
NNE NEE ESE SES SSW SWW WNW NWN NCL Total time of rainfall WNW
Wind direction
Duration of accumulation
Number of cases
north–northeast northeast–east east–southeast southeast–south south–southwest southwest–west west–northwest northwest–north not classifiable
h 328 302 196 172 828 3540 1060 516 368 7310 252
34 35 21 22 86 297 99 55 26 675 20
strong shear
Hours of accumulation March 1996
May 1996
16 23 15 0 0 73 59 0 0 186 0
12 26 49 6 6 18 58 0 0 289 0
% 4.5 4.1 2.7 2.4 11.3 48.4 14.5 7.1 5.0 100 3.5
The acronyms are the wind directions in the center of each sector, duration is in hours and in percent; also the absolute number of cases is given. For WNW ‘strong shear’ see Section 5.
The sector WNW ‘strong shear’ is a subset of rain events with wind directions from west to northwest. It contains cases of strong wind shear in the lowest 3 km of the vertical wind profile Žsee Section 5. with easterly winds near the ground and westerly to northwesterly winds between 2 and 2.5 km AGL. It seems to result from a counter current due to a channeling effect of the specific orographical structure of the Rhine valley ŽWippermann, 1994.. For the 26 cases named NCL no unambiguous classification could be found: The wind speed in the lowest 3 km has either been too weak or a strong wind shear between a height of 2 and 3 km makes it impossible to clearly classify them or there were no Doppler data available.
4. Distribution of rainfall amount The distributions of rain amount resulting from the different ways of time integration of the rain intensity on the terrain-following layer Žmonthly and wind direction dependent accumulations. are presented and compared in this section. Before these data are discussed it is instructive to analyze a climatological map of 30 years mean annual rainfall from rain gauges Ž1931–1960; from Amt fur ¨ Wehrgeophysik, 1977. shown in Fig. 3. Typical for the distribution is the large variation of rainfall amount between the eastern slopes of the Vosges Žwest of the Rhine river. and the Black Forest Žeast of the Rhine river. with a maximum on the top of the hills of the Black Forest and a minimum southwest of Strasbourg in the lee-side of the Vosges mountains. Moreover, attention should be paid to a particular feature: In the northern part of the Black Forest a tongue of relatively small rain amount appears in north–south orientation. This phenomenon seems to be triggered by the valley of the river Murg Žsee also Fig. 1, south of the rain
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Fig. 3. Isohyets of the mean annual rainfall amount Žin mm. from rain gauges over the period of 1931–1960 Žfrom Amt fur ¨ Wehrgeophysik, 1977.. The location of the radar is marked with Ž D ..
gauge No. 6. leading from the bottom of the Rhine valley to the top of the Black Forest. It may be Ži. due to a local fohn-effect induced by southerly winds, or Žii. due to a lag of ¨ forced raise of moist air in rain events with northwesterly winds. For a comparison the whole period of 30 months of rain intensity data available have been accumulated in Fig. 4. Due to a strong beam blocking at nearby trees east of the radar the distribution of rain amount in the eastern part of the figure has been interpolated. The distribution of the 30 months rain amount is in a good correspondence with that of the 30 years annual rainfall. Compared to Fig. 3 one can see a radial decrease of the rain amount north of Mannheim and in the region near Strasbourg which seems to be reliable but too large. It is caused by the effects of the earth’s curvature, e.g., by
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Fig. 4. Distribution of the accumulated rain amount in millimeters Žas indicated by the grey scale. from January 1994 to May 1996 Ž7310 h of duration.. The solid lines are isolines of the orographical structure. The radar location is marked with a Žq..
measuring snow beyond the bright band or by radar data of rain events with very small vertical extents in winter Že.g., with a large reflectivity decrease with height in the lowest 2 km AGL.. The small rain amounts beyond the hills Žnorthwest and southeast of the radar. are due to beam blocking by the hills. But there are also differences between the distributions shown in Figs. 3 and 4. With reference to the accumulated radar data note the larger rain amount in the Rhine valley north of Strasbourg and the smaller amounts of rain east of Mannheim in the Rhine valley Žboth effects are not shown by the climatological distribution.. The larger rain amount in the Rhine valley north of Strasbourg might be induced by a blocking effect of the hills of the Pfalzerwald for southerly winds or by a blocking effect of the Black ¨ Forest for westerly winds. Due to an underestimation of rain east of Strasbourg Žas discussed in Section 2. there surely must be an extension of the maximum at the slope of the Black Forest towards south. The distributions of rain amount for individual months often show large deviations compared with the distribution for the whole period depicted in Fig. 4. As will be shown these variations are due to the different frequency of the wind direction for rain events in the different months. Note that the distribution of rain for the whole period is dominated
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Žas discussed in Section 3. by rain events with wind directions mainly from southwest to west. Two examples of monthly distributions of rain amount are shown in Fig. 5 for March 1996 and Fig. 6 for May 1996. Accumulation times as well as corresponding wind directions are integrated in Table 2. The distribution of rain in March 1996 Ž186 h. exhibit no dominant maximum. The rain amount in the hills around the radar are almost as large as those in the Rhine valley. The spot-like maxima Žin black. results from a strong single thunderstorm. In general, the distribution of rain in March is characterized by a nearly homogeneous distribution of rain over the whole area. Since no concentric rings as typical bright band structures can be recognized bright bands seem to appear most of the time at heights larger than 1.0 km AGL. The maximum rain amount in the northwestern part of the Black Forest as well as the large variation of rain amount between the eastern and the western side of the Rhine valley north of Strasbourg revealed by the long-term integration Žcf. Fig. 4. cannot clearly be seen in the March distribution. The rainfall distribution of March is typical for a month, where a specific wind direction does not prevail Žsee Table 2.. The second example of a monthly distribution of accumulated rain amount ŽMay 1996, Fig. 6. is less homogeneous than that of March 1996. It is characterized by two larger areas with higher rain amounts: one northeast of the radar at the hills of the Odenwald and one south of the radar in the Rhine valley and at the northwestern slope of the Black Forest. Both regions with larger rain amounts are in correspondence with
Fig. 5. Distribution of the accumulated rain amount in millimeters Žas indicated by the grey scale. for March 1996 Ž186 h..
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Fig. 6. Same as Fig. 5, but for May 1996 Ž289 h.. Note the difference in scale values compared to Fig. 5.
the distribution of rain amount of the whole period. Even the minimum rain in the valley of the river Murg south of the rain gauge No. 6 in Fig. 1 is recognizable. The overall structure of rain distribution in this month shows exactly the same structure in its distribution of integrated rain amount ŽGysi, 1996. as the rain accumulation of rain events from the sector WNW. As can be recognized in Table 2 rain events with wind directions from this sector have a large contribution to May. But there is a second influence on the rain distribution of May 1996: a strong thunderstorm activity leads to inhomogeneity and large horizontal variations of rain amount. The thunderstorm activity is mainly located southwest of the radar in the Rhine valley, northeast of the radar in the hills of the Odenwald and southeast of the radar near Stuttgart. It mostly results from single cell thunderstorms because no definite tracks of thunderstorms can be seen in the figure. Thunderstorm activity often occurs with wind directions according to the sectors SES ŽFig. 9. and ESE Žhaving a large contribution to the monthly integration time.. It should be noticed that in the northern part of the hills of the Pfalzerwald as well as ¨ in the area north of Mannheim only small rain amounts are detected which is atypical for that season. We now turn to the distributions of integrated rainfall amount of all rain events considering a certain sector of wind directions. Orographic effects then appear more pronounced. The distribution with the highest amount of accumulated rainfall—that one
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according to the sector SWW—has nearly the same structure as the distribution of accumulated rainfall for the whole period in Fig. 4 and is therefore not repeated here. Different from Fig. 4 and more interesting is the distribution of accumulated rainfall amount of all 86 rain events Ž3540 h. with wind directions from south to southwest ŽFig. 7.. In this case the large amount of accumulated rain in the Rhine valley, in the hills of the Pfalzerwald as well as at its southeastern slopes is characteristic. This is due to the ¨ forced raise of moist air at the hills of the Pfalzerwald accompanied with this wind ¨ direction Žsee arrow in Fig. 7, which shows the mean wind direction of the sector.. The distribution of rain amount north of the radar is rather inhomogeneous due to thunderstorm activity in this area. Thunderstorm activity is also responsible for the small areas with rain amount ) 325 mm Žin black.. It is amazing that they are still recognizable in a rain integration figure over 3540 h in Fig. 4. The characteristic maximum in the Rhine valley and at the northern slope of the Black Forest does not occur within this wind direction. Remember that the maximum mentioned is orographically induced from the Black Forest and occurs only with wind directions from southwest to north. The second example of a wind direction dependent accumulation is that concerning the sector with wind directions from northwest to north indicated by the arrow in Fig. 8. It is an accumulation over 516 h Ž55 rain events.. Here a strong orographical effect by the Black Forest appears. As expected the passive lifting of moist air combined with rain formation leads to high rain amounts at the northwestern slope of the Black Forest and
Fig. 7. Same as Fig. 6, but for the wind direction south to southwest ŽSSW, see arrow. Ž828 h..
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Fig. 8. Same as Fig. 6, but for the wind direction northwest to north ŽNWN, see arrow. Ž516 h..
in the Rhine valley. The increase of rain amount toward the Black Forest is more or less parallel to the mean wind direction of that sector. On the other hand a strong decrease of accumulated rain in the southern Rhine valley near Strasbourg can be noticed which is exactly perpendicular to the mean wind direction of the sector ŽNWN.. It seems that the Žas well as the Vosges mountains. have a strong prohibiting hills of the Pfalzerwald ¨ effect on rain in the southern Rhine valley where very small rain amounts occur. Also very small rain amounts have been measured in the hills of the Pfalzerwald itself and at ¨ its eastern and southeastern slope. But downstream immediately south of the hills of the Pfalzerwald, there is a region with larger rain amounts than in the Rhine valley further ¨ south Ži.e., west of Strasbourg.. This may result from a counter current in the Rhine valley induced by the channeling effect of the Rhine valley which turns the flow in the lowest 1.5 km AGL from northwest–north into a flow from north–northeast ŽWippermann, 1994.. Larger rain amounts then occur due to a blocking effect on the flow and a forced raise approaching the northeastern Vosges mountains and the slope of the Pfalzerwald. ¨ The last example ŽFig. 9. shows the distribution of rainfall amount according to the wind direction sector southeast to south Ž21 rain events with 196-h duration.. Larger rain amounts only appear in the Rhine valley south of the radar and in the hills of the Pfalzerwald. The distribution is very inhomogeneous indicating a considerable thunder¨ storm activity. The local maxima, e.g. northwest of the Black Forest and northwest of the radar in the Rhine valley, are due to single thunderstorm events.
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Fig. 9. Same as Fig. 6, but for the wind direction southeast to south ŽSES, see arrow. Ž172 h..
It may only be speculated if the thunderstorms form upstream at the southeasterly slope of the Black Forest Žwhich is heavily shielded for radar beams. and move over the mountain or if they form in the lee-side ŽBanta, 1990. of the Black Forest triggered by its northern and northwestern slopes. However, from the northwestern slope of the Black Forest the thunderstorms move, passing the Rhine valley, parallel to the mean wind direction of the sector Žcf. arrow in Fig. 9. towards north–northwest. As presented, the analysis of the distribution of the long time accumulations of rain according to certain wind directions reveals distinct maxima and minima of rain amounts coupled to the orographical structure of the region considered. Besides these expected results some unexpected results became obvious. So by a certain wind direction thunderstorms in the northern Black Forest may be triggered which then move through the Rhine valley as shown in Fig. 9. However, the method of considering only a certain height for determining the wind direction for the classification of rain events for accumulation is a simplification which still might obscure orographical effects on the distribution of accumulated rain due to small scale phenomena. 5. Accumulation of rain events according to a special vertical wind profile The discussion of Section 4 is based on data where only the wind direction measured in a single level, namely 2–2.5 km AGL, is considered. However, as mentioned in
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Fig. 10. Wind speed in meters per second and wind direction in degrees as a function of height ŽAGL. for the 24th of January 1996, 0605 UTC with a counter current situation due to a channeling effect of the Rhine valley. For discussion see text.
Fig. 11. Same as Fig. 6, but for the wind direction sector west to northwest Žsee arrow. according to the vertical wind profile of Fig. 10 Ž252 h..
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Section 4 traditional wind measurements show that under certain circumstances a strong specific flow regime is present in the Rhine valley. This feature is a counter current due to a channeling effect in the Rhine valley. It is therefore of interest to investigate such situations when the counter current is fully developed. A corresponding typical wind profile derived from the radial Doppler velocity data within a range of 50 km with the VVP method of Waldteufel and Corbin Ž1979. is given in Fig. 10. Near the ground, there is a rather strong flow from east to northeast. Between 1 and 2 km AGL it turns counterclockwise to a flow from northwest. In the height range 2–2.5 km AGL which is applied for classification of wind direction dependent rainfall the wind blows from west to northwest so that a rainfall event is counted into the sector WNW. Above a height of 3 km AGL the flow usually turns to southwestern directions under counter current conditions. Typical for rain events with this particular profile is a stationary precipitation cell southeast of the hills of the Pfalzerwald, i.e., on the lee-side ¨ of the hills considering the wind direction west–northwest in the height range 2–2.5 km AGL as moving direction of the precipitation systems. In Fig. 11 all 20 rain events showing similar wind profiles as those in Fig. 10 Ž252 h of duration within the period of 30 months. are integrated. The local maximum south of the Pfalzerwald is clearly seen ¨ in the figure. Large amounts of precipitation are also found in the Rhine valley between Strasbourg and Karlsruhe and at the northwestern slope of the Black Forest. In contrast, the large rain amounts at the slope of the Black Forest are in accordance to the expected distribution of accumulated rain events within the wind direction sector WNW. The small amount of accumulated rain in the Rhine valley northwest of the location of the radar may be a local fohn ¨ effect in the lee-side of the Pfalzerwald. ¨
6. Conclusions With the method of wind-direction-dependent time integration of rain-intensity data obtained by radar on a terrain-following surface at a height of 1 km AGL it is possible to reveal orographic effects dominating the distribution of rainfall amount. The rain distribution for the whole period Ž30 months. is determined by rain events from the wind direction sector southwest to west. It is in a good correspondence with the climatological rain distribution for the area considered. The month by month time integrations of the precipitation, however, show a weak orographic influence on the rainfall amount because they are usually a superposition of rain events from different wind directions. In contrast, the time integrations of rain events from different wind-direction sectors lead to distributions by which orographic effects clearly appear: e.g., maxima due to a blocking effect on the flow in the updraft region of hills and minima of the accumulated rain downstream the hills. Moreover, rather seldom or unexpected phenomena such as a region of thunderstorm triggering, areas of preferred thunderstorm trackways and exemplarily a maximum in the lee-side of a hill have been found. These phenomena occur statistically significant with winds blowing from a certain wind direction sector and can only be revealed by the method of the wind direction dependent accumulation of rain events.
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The wind direction in a height of 2–2.5 km AGL calculated from Doppler data seems to be a good indicator for the mean direction of motion of rain systems. If, however, local Žmeso-g scale. phenomena should be investigated it is necessary to consider not only winds in a specific height range but vertical profiles of wind and to accumulate only rain events according to those wind profiles. A comparison of accumulations of radar rain intensity data with data of a rain gauge network shows the importance to correct radar data so that the rain amount near the ground can quantitatively and reliably be measured. For ranges larger than about 80 km additional corrections are needed during the cold season when the bright band is lower than about 2 km AGL. Nevertheless, there is an advantage of using rain-intensity data by radar to determine the distribution of accumulated rain amount for climatological and hydrological applications. In summer, when thunderstorms lead to large horizontal variations of the rain intensity within only a few km, the highly resolved radar rain data are much more accurate than data interpolated from a rain gauge network. The detailed information of radar reflectivity is also necessary to investigate small scale phenomena induced by orography. The strong dependence of the rain distribution on the wind direction at a height of 2–2.5 km AGL may be useful for nowcasting Žespecially in orographically complex terrain. the local occurrence of rainfall or thunderstorms within a certain wind direction, e.g., for flood warning or for thunderstorm warning. Acknowledgements I would like to thank K.D. Beheng for his general support and helpful suggestions as well as two reviewers for their constructive comments and criticisms. Thanks also to A. Wenzel for making available the rain gauge and wind data from the REKLIP stations, to T. Garbrecht for taking care of the disdrometer and to G. Klinck for Fig. 1. The REKLIP project is supported by the ‘Ministerium fur ¨ Wissenschaft und Kunst’ of Baden-Wurt¨ temberg under contract number 1499Tit.Gr.74. References Banta, R.M., 1990. Atmospheric processes over complex terrain. Am. Meteor. Soc. 23, 45, Meteorological monographs. Collier, C.G., 1972. Applications of weather radar systems. A Guide to Users of Radar Data in Meteorology and Hydrology. Halsted Press, Chichester. Collinge, V.K., 1991. Weather radar calibration in real time: prospects for improvement. Hydrological Applications of Weather Radar. Ellis Horwood, Chichester. Creutin, J.D., Delrieu, G., Lebel, T., 1988. Rain measurement by rain gauge–radar combination: a geostatistical approach. J. Atmos. Ocean. Technol. 5, 102–115. Fabry, F., Austin, G.L., Tees, D., 1992. The accuracy of rainfall estimates by radar as a function of range. Q. J. R. Meteorol. Soc. 118, 435–453. Fiedler, F., 1995. Klimaatlas Oberrhein Mitte-Sud. ¨ Institut fur ¨ angewandte Geowissenschaften ŽIFG., Offenbach. Gysi, H., 1995. Niederschlagsmessung mit Radar in orographisch gegliedertem Gelande. PhD Thesis, Univ. ¨ Karlsruhe, Germany.
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Gysi, H., 1996. Orographic influence on the distribution of the accumulated rainfall for different wind directions. Preprints, 12th Int. Conf. on Clouds and Precipitation. Am. Meteor. Soc., pp. 649–652. Held, E., Joss, J., 1994. The influence of the orography on precipitation seen by the Swiss Radars. COST 75 Weather Radar Systems. International Seminar, Brussels, Belgium 20–23 Sept. European Commission, pp. 777–786. Hildebrand, P.H., Towery, N., Snell, M.R., 1979. Measurement of convective mean rainfall over small areas using high density rain gages and radar. J. Appl. Meteorol. 18, 1316–1326. Hill, F.F., Browning, K.A., Bader, M.J., 1981. Radar and rain gauge observations of orographic rain over south Wales. Q. J. R. Meteorol. Soc. 107, 643–670. Huff, F.A., 1970. Sampling errors in measurement of mean precipitation. J. Appl. Meteorol. 9, 35–44. Joss, J., Pittini, A., 1991. Real-time estimation of the vertical profile of radar reflectivity to improve the measurement in an alpine region. J. Meteorol. Atmos. Phys. 47, 61–72. Joss, J., Waldvogel, A., 1990. Precipitation measurement and hydrology. In: Atlas, D. ŽEd.., Radar in Meteorology. Am. Meteorol. Soc., pp. 577–606. Loffler Mang, M., Beheng, K.D., Gysi, H., 1996. Drop size distribution measurement in rain—a comparison ¨ of two sizing methods. Meteorol. Z. 4, 139–144, N.F. 5. Nickerson, E.C., Richard, E., Rosset, R., Smith, D.R., 1986. The numerical simulation of clouds, rain and airflow over the Vosges and the Black Forrest Mountains: a meso scale b model with parametrized microphysics. Mon. Wea. Rev. 114, 398–414. Passarelli, R.E., Romanik, P., Geotis, S.G., Siggia, A.D., 1981. Ground clutter rejection in the frequency domain. Preprints, 20th Conf. Radar Meteor., Am. Meteor. Soc., pp. 345–348. Sauvageot, H., 1994. Rainfall measurement by radar: a review. Atmos. Res. 35, 27–54. Schmid, W., Hogl, ¨ D., Vckovski, A., Joss, J., 1991. Test of clutter suppression techniques in the Swiss Alps. Preprints, 25th Conf. Radar Meteor., Paris, Am. Meteor. Soc., pp. 875–878. Seed, A.W., Austin, G.L., 1991. Sampling errors for rain gauge-derived mean areal daily and monthly rainfall. Hydrological Applications of Weather Radar. Ellis Horwood, Chichester. Tateya, K., Nakatsugawa, M., Yamada, T., 1991. Observations and simulation of rainfall in mountainous areas. Hydrological Applications of Weather Radar. Ellis Horwood, Chichester. Waldteufel, P., Corbin, H., 1979. On the analysis of single Doppler radar data. J. Appl. Meteorol. 18, 532–542. Wenzel, A., Kalthoff, N., Fiedler, F., 1996. On the variation of the energy-balance components with orography in the Upper Rhine valley. Theor. Appl. Climatol., in press. Wippermann, F., 1994. Air flow over and in broad valleys: channeling and counter current. Contrib. Atmos. Phys. 57 Ž1., 92–105.
Orographic influence on the distribution of accumulated rainfall with different wind directions Hermann Gysi
)
Institut fur ¨ Meteorologie und Klimaforschung, Forschungszentrum Karlsruher UniÕersitat ¨ Karlsruhe, P.O. Box 3640, D-76021 Karlsruhe, Switzerland Accepted 2 September 1997
Abstract For the region of the Upper Rhine valley with its surrounding mountains the influence of the orography on the horizontal distribution of surface rain amounts is analyzed by use of data of a C-band Doppler radar. A 30-month data sample is evaluated by accumulating rain intensities for different time intervals Žmonths, years.. The rain intensities taken into account refer to a constant height of 1.0 km AGL, i.e., to a terrain-following level. It is found that the influence of the orography on the rainfall distribution depends strongly on the direction from which clouds and rain systems move into the area under consideration. Accordingly, the data of all rain events are investigated in three different ways: Ži. for the whole period Žii. month by month regardless of wind direction and Žiii. also for the whole period but considering eight different sectors of wind directions, with each sector 458 wide. The wind direction dependent rain accumulations presented show the following features: Ž1. well-known phenomena as maxima of rainfall in the updraft region of hills or minima in the lee-side of hills, Ž2. phenomena triggered by the mesoscale flow systems such as preferred developing areas or tracks of thunderstorms as well as rain maxima in the lee-side of small hills induced by a counter current to the geostrophic wind. q 1998 Elsevier Science B.V. All rights reserved. Keywords: Radar; Rain; Accumulation; Wind direction; Orography
1. Introduction The distribution of rain at the surface generally shows a large variability in time and space. This variability occurs as well over flat terrain Žresulting from rain showers or )
Fax: q41-7247r824742; e-mail: [email protected].
0169-8095r98r$19.00 q 1998 Elsevier Science B.V. All rights reserved. PII S 0 1 6 9 - 8 0 9 5 Ž 9 7 . 0 0 0 8 9 - 6
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convective systems. as— more pronounced— over orographically structured terrain. In both cases its evidence is difficult to substantiate ŽNickerson et al., 1986; Joss and Waldvogel, 1990; Tateya et al., 1991; Held and Joss, 1994.. This difficulty is mostly caused by the lack of highly resolved rainfall data. Usually, conventional rain gauge measurements are taken into account. However, such data are seldom reliable since the rain gauge network error of the rain distribution is rather sensitive to the relative variability of the rain field ŽSeed and Austin, 1991; Huff, 1970.. Thus, the point measurement of a single rain gauge often has to represent the rainfall intensity of an area of hundreds of square kilometers. Additionally, they often have only a time resolution of 24 h. In contrast, for investigating a wind-dependent rain distribution, data with time resolution of at least 1 h are needed. Moreover, studies about the orographic influence on the distribution of the accumulated rain within different wind directions need a very dense network of rain gauges. Corresponding experiments, however, are rather seldom
Fig. 1. Orographical structure of the region around the location of the radar Ž D . in the valley of the Rhine river Žblack solid line.. Also marked are the locations of the rain gauges 1–10 ŽREKLIP. and W ŽGerman Weather Service. and the disdrometer ŽD. used for adjustment and data correction.
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and the networks are operational only over short periods ŽHildebrand et al., 1979; Hill et al., 1981.. A different method to get rain-intensity data highly resolved in space and time consists in using radar data ŽCollier, 1972; Sauvageot, 1994.. In this study data of a C-Band radar located in the Upper Rhine valley are analyzed. The orographic structure of the region surrounding the radar is characterized by two parallel north–south orientated ridges of hills along the wide and plain Rhine valley. In Fig. 1 the location of the radar is indicated by D. Also indicated in Fig. 1 are the locations of the equipment used for adjustment of the radar measurements: ten rain gauges of the REKLIP network ŽNo. 1–10. ŽWenzel et al., 1996., one rain gauge from the German weather service ŽW. and one Disdrometer ŽD.. From climatological Ž30-year-mean. data ŽFiedler, 1995. it is shown that at the steep western slope of the Black Forest towards the Rhine valley there is a large variation in the distribution of the annual precipitation amounts. The largest values occur at the top of the Black Forest mountains and the minimal values occur in the Rhine valley east of the Vosges mountains between their easterly slopes and the city of Strasbourg. Due to the specific orographic structure of the area under consideration the appearance of many different orographic effects influencing the regional rainfall distribution is expected: Not only well-known phenomena as rainfall maxima in the updraft region or minima downstream the hills, but also phenomena triggered by mesoscale flow systems, e.g., stationary parallel rain bands ŽGysi, 1995., preferred developing regions and tracks of thunderstorms or rain maxima in the lee-side of hills can be observed. Such effects are strong enough to be statistically significant but they depend on the direction from which the clouds and rain systems move into the region of interest. Therefore they can usually not be recognized in the monthly accumulation of rain Žneither by radar nor by ground-based rain gauge measurements. which comprises a mixture of rain events with various wind directions. They only become obvious when the rain amount is accumulated over many rain events with a similar structure of the vertical wind profile.
2. Data sources and correction The data presented here are obtained by a single C-band Doppler radar located in the upper Rhine valley in the southwestern part of Germany ŽFig. 1.. The technical details of that radar are compiled in Table 1. The usual operational mode of the radar consists of two volume scans, one of radar reflectivity Ž Z . and the other of radial Doppler velocity Ž V .. For a period of 30 months ŽJanuary 1994 till May 1996. volume scans of both Z and V are available with a time resolution of 12 min which is the duration of two scans each using the following 16 elevation angles: 0.2, 1.0, 2.0, 3.0, 4.5, 6.0, 7.5, 9.0, 11.0, 13.0, 15.0, 17.5, 20.0, 23.0, 26.0 and 30.08. The maximum range chosen for Z was 120 km and for V 100 km, respectively, with a radial resolution of 0.5 km and an azimuthal resolution of 18. To remove low-frequency signals due to ground clutter in a first step the raw data have been immediately corrected during their acquisition by a high pass IIR Žinfinite
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Table 1 Main characteristics of the radar Frequency, wavelength Peak transmitted power Transmitter type Pulse duration PRF Sensitivity ŽMDS. Receiver dynamic ranges: lin Ž I,Q . log Ž Z . Antenna diameter Antenna gain y3 dB beamwidth 1. Sidelobe level Radar height ŽAGL. Žafter Jan. 1. 1996.
5.62 GHz, 5.6 cm 252 kW Ž84 dBm. Magnetron 0.85 and 2.0 m s 250–1200 Hz y104 dBm 90 dBm 101 dBm 4.2 m 44.7 dB 0.988 y28 dB 30 m 38 m
impulse response. Doppler filter selected from eight available stop- and passbands ŽPassarelli et al., 1981.. As proposed by Schmid et al. Ž1991. an intermediate filter ŽNo. 4 of 8. had been chosen. From each volume scan of Doppler-filtered reflectivity data the rain intensity is interpolated on a terrain-following layer in a height of 1.0 km AGL. The data in this height are assumed to be representative for the rain intensity at the ground. The vertical resolution in the terrain-following layer is 125 m and the horizontal resolution in each direction is 0.5 km. From the volume scans of the radial Doppler velocity vertical, profiles of wind direction and speed at the location of the radar are derived by the VVP method ŽWaldteufel and Corbin, 1979. within a range of 30 km and a vertical layer spacing of 250 m. By using a terrain-following layer the following difficulties in analyzing the rain intensity or its accumulation occurs: One problem is the vertical inhomogeneity of the rain intensity ŽJoss and Pittini, 1991. which might be interpreted as a horizontal inhomogeneity due to the varying height of the terrain-following layer above sea level. A further problem appears when the terrain-following layer crosses the bright band. In this case data from regions above the bright band where snow is present are interpreted as if the hydrometeors consist of water since a unique radar equation is applied. This leads to an underestimation of precipitation amounts. For the region considered this happened when the melting zone lies between the minimum Ž1.1 km MSL. and maximum height Ž2.2 km MSL. of the terrain-following layer. The vertical decrease of the rain intensity, the snow measurement from above the bright band as well as the attenuation of the radar beam in the bright band cause an underestimation of precipitation at the top of hills and at large distances ŽFabry et al., 1992.. The bright band problem is expected to occur mainly during the period from October to April. In order to relate the radar reflectivity Ž Z . to rain intensity Ž R ., for the whole area under consideration the following three different Z–R relations Žcf. Sauvageot, 1994. were assumed to be representative for different periods and meteorological situations.
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Z s 300 R 1.5 Žrain only. Z s 200 R 1.6 Žfor rain. Z s 1800 R 2.2 Žfor snow.
a. May to November b. December to April
The application of different Z–R relations for rain results from previous investigations. Gysi Ž1995. has shown that in summer when rain is partly of stratiform and partly of convective type the relation Z s 300 R 1.5 leads to a better agreement between radar and rain gauge data than the relation Z s 200 R 1.6 which leads to a better agreement in winter when stratiform rain prevails. Because measurement by radar is an indirect remote sensing method it is important to adjust the estimated rain intensity with rain measurement from other sources ŽCollinge, 1991.. Long term variations of the measured reflectivity factor due to age processes of the radar-hardware Že.g., thyratron, magnetron, oxidation in the RF-wave guide, etc.. usually cause an underestimation of the reflectivity factor between 3 and 6 dBZ. With continuous and simultaneous measurements of drop spectra with a disdrometer ŽLoffler ¨ Mang et al., 1996., located 10 km south of the radar at the top of a building situated 50 m over the Rhine valley, a reflectivity correction factor F for every month has been determined to correct this underestimation. The factor has been estimated from the difference between the mean radar reflectivity factor at the location of the disdrometer and the reflectivity factor calculated from disdrometer data Žwhich have been assumed to be representative.. The corresponding radar reflectivity is the mean value for the volume by the four elevations from 1.0–4.58, the six azimuth degrees and four range bins, both centered at the location of the disdrometer. Only rain periods with homogeneous rain intensities Že.g., stratiform rain events. are considered. The rain intensity is corrected range and rain type independent in the following way: Zcorr s Zuncorr q F s 10log Ž AR B . w dBZ x
Ž 1.
and with correction factor F s 10log Ž Z DisrZ Rad . w dBZ x
Ž 2.
Zuncorr s 10log Ž AR B . y 10log Ž Z DisrZ Rad . w dBZ x
Ž 3.
and
resulting finally in Rs
10 F r10 A
1rB
10
Z un corr r10
w mmrhx
Ž 4.
Z Dis is the average monthly reflectivity factor from the disdrometer and Z Rad the respective radar average. As a further adjustment, the monthly rain accumulation data at the terrain-following layer have been compared with the monthly accumulation measurement of ten rain gauges within a distance from 6 to 70 km Žsee Fig. 1.. For radar adjustment by rain gauge data sophisticated interpolation procedures have been presented, e.g., by Creutin et al. Ž1988.. The method applied here is simpler ŽSauvageot, 1994.: A mean monthly correction factor f s ÝGirÝR i has been determined where G is the monthly rain
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amount of the different rain gauges Žindicated by subscript i . and R the corresponding rain amount by radar Žin an area of 4 km2 with the rain gauge in the center.. The correction factor applied was equal for every pixel of the terrain-following layer and equal for every rain event of a certain month. A rain event starts or ends with the beginning or ending of rainfall somewhere in the considered area. Because the ten rain gauges of the used rain gauge network have a different representativity for a comparison, the correction factor for the rain amount has been weighted with its representativity. The four stations Fr-stett, Sa, Ho-berg and Ho-ginde ŽNo. 7–10 in Fig. 1. are all within a distance of about 70 km and heights of 130, 140, 490 and 1150 m MSL. They are situated in a line parallel to the largest variation of the orographical structure Žand parallel to the largest gradient of accumulated rain.. A full consideration of these four rain gauges for radar adjustment in winter would give a large overestimation of the rain amount near the radar. Their rain amounts have therefore been weighted with a Žmonthly individually determined. factor between 0 and 1. The reasons for the poor representativity of the four rain gauges are: Ž1. due to a beam overshooting or a partial beam overshooting with shallow precipitation within this distance radar measurement is underestimated Žprincipally at the top of the hill.; Ž2. due to the large variation of rain amount the different methods of measurement become significant: a point measurement at the ground is compared with a volume integrated measurement Žthe beam width at a distance of 70 km is about 1.2 km.; and Ž3. the underestimation of precipitation beyond the bright band Žsnow. by radar. In summer the horizontal variations of the rain intensity due to local thunderstorm activity generally are very large and hence the representativity of all rain gauges for a larger area is weak. Therefore the radar measurements have only been adjusted in cases where f ) 1 and no large gradients of the accumulated rain amount on the terrain-following layer was within a radius of 5 km around the location of the rain gauge. The effect of all corrections and adjustments on the precipitation accumulation at the locations of the rain gauges is shown in Fig. 2. The period of accumulation for this
Fig. 2. Rain amount in millimeters for different locations as indicated according to rain gauge measurements ŽREKLIP. as well as corrected and uncorrected rain accumulation by radar at 1.0 km AGL over a period of 2 years.
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comparison was 2 years Žfrom January 1994 to December 1995.. The corrected rain amounts from reflectivity data show a good correspondence with those from the rain gauges ŽREKLIP. up to a range of about 50 km from the radar ŽNo. 1–6 in Fig. 1.. For the remaining four rain gauges ŽNo. 7–10 in Fig. 1. in a distance of about 70 km the agreement between the corrected radar data and the rain gauge data is poor due to the effects discussed. The difference between the rain amounts measured by the rain gauges and those obtained from radar attains a maximum of 50% at station 10 ŽHornisgrinde, top of a mountain.. As can be recognized from the rain gauge data, the accumulated rain amount increases with the location height Žsee stations 8, 9 and 10.. Within a horizontal distance of 5 km the rain amount measured by rain gauges increases by 100%. This comparison shows the importance of correcting the radar data. It also shows some difficulties of the correction procedure. 3. The method of accumulation and the frequency of the different wind directions To reveal the orographic influence on the distribution of the accumulated rain amount and its dependence on the structure of local wind system, the rain intensities on the terrain-following layer have been integrated in two different ways: Ža. monthly without respect of the wind direction and Žb. over the whole period of 30 months considering eight different sectors of the wind direction, with each sector 458 wide. Radar data have been considered whenever somewhere in the region covered by radar rainfall has been measured. Rain intensities were integrated in time with respect to a certain sector if the mean wind direction—measured above the radar between 2 and 2.5 km AGL—falls into that sector. That height interval has been chosen since it is assumed that it is the lowest layer where the wind is not disturbed by orography so that the wind direction relevant to this layer gives the direction of motion of the precipitation systems. A comparison with wind data from radiosoundings at Stuttgart Žsee Fig. 1, 70 km southeast of the radar. shows a good agreement with vertical wind profiles from radar data above 2 km AGL ŽGysi, 1995.. Table 2 shows a list of duration of accumulated rainfall for the whole period Ž30 months. for each of the eight wind sectors. Nearly 50% of the accumulated rainfall occur when the wind direction is from southwest to west and another 25% occur when the wind blows from adjacent directions, i.e., south to southwest and west to northwest. The remaining 25% of the accumulated rainfall are shared by the other five sectors. The two sectors from east to south show the smallest number of cases with rain. In comparison, the annual climatological percentage distribution of east to south wind at the mountain station Hornisgrinde ŽFiedler, 1995. is with more than 12% significantly higher than with 5.1% of the time during rain. This may be induced due to the mountains of the Black Forest and the Alpes. Since the region covered by radar measurements is in the lee-side of the Black Forest and the Alpes for these wind directions the absence of rainfall events seems to be an effect of this large-scale structure of the orography. The other two sectors with a very small number of cases with rainfall are those with wind direction from north to east. For all easterly wind directions the amount of rainfall is small Žcf. Fig. 9.. But the wind directions from southeast to south are important for the thunderstorm activity in the Rhine valley Žsee Section 4..
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Table 2 Wind direction statistics corresponding to a rainfall period of 30 months and for the two months March and May 1996 Acronym
NNE NEE ESE SES SSW SWW WNW NWN NCL Total time of rainfall WNW
Wind direction
Duration of accumulation
Number of cases
north–northeast northeast–east east–southeast southeast–south south–southwest southwest–west west–northwest northwest–north not classifiable
h 328 302 196 172 828 3540 1060 516 368 7310 252
34 35 21 22 86 297 99 55 26 675 20
strong shear
Hours of accumulation March 1996
May 1996
16 23 15 0 0 73 59 0 0 186 0
12 26 49 6 6 18 58 0 0 289 0
% 4.5 4.1 2.7 2.4 11.3 48.4 14.5 7.1 5.0 100 3.5
The acronyms are the wind directions in the center of each sector, duration is in hours and in percent; also the absolute number of cases is given. For WNW ‘strong shear’ see Section 5.
The sector WNW ‘strong shear’ is a subset of rain events with wind directions from west to northwest. It contains cases of strong wind shear in the lowest 3 km of the vertical wind profile Žsee Section 5. with easterly winds near the ground and westerly to northwesterly winds between 2 and 2.5 km AGL. It seems to result from a counter current due to a channeling effect of the specific orographical structure of the Rhine valley ŽWippermann, 1994.. For the 26 cases named NCL no unambiguous classification could be found: The wind speed in the lowest 3 km has either been too weak or a strong wind shear between a height of 2 and 3 km makes it impossible to clearly classify them or there were no Doppler data available.
4. Distribution of rainfall amount The distributions of rain amount resulting from the different ways of time integration of the rain intensity on the terrain-following layer Žmonthly and wind direction dependent accumulations. are presented and compared in this section. Before these data are discussed it is instructive to analyze a climatological map of 30 years mean annual rainfall from rain gauges Ž1931–1960; from Amt fur ¨ Wehrgeophysik, 1977. shown in Fig. 3. Typical for the distribution is the large variation of rainfall amount between the eastern slopes of the Vosges Žwest of the Rhine river. and the Black Forest Žeast of the Rhine river. with a maximum on the top of the hills of the Black Forest and a minimum southwest of Strasbourg in the lee-side of the Vosges mountains. Moreover, attention should be paid to a particular feature: In the northern part of the Black Forest a tongue of relatively small rain amount appears in north–south orientation. This phenomenon seems to be triggered by the valley of the river Murg Žsee also Fig. 1, south of the rain
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Fig. 3. Isohyets of the mean annual rainfall amount Žin mm. from rain gauges over the period of 1931–1960 Žfrom Amt fur ¨ Wehrgeophysik, 1977.. The location of the radar is marked with Ž D ..
gauge No. 6. leading from the bottom of the Rhine valley to the top of the Black Forest. It may be Ži. due to a local fohn-effect induced by southerly winds, or Žii. due to a lag of ¨ forced raise of moist air in rain events with northwesterly winds. For a comparison the whole period of 30 months of rain intensity data available have been accumulated in Fig. 4. Due to a strong beam blocking at nearby trees east of the radar the distribution of rain amount in the eastern part of the figure has been interpolated. The distribution of the 30 months rain amount is in a good correspondence with that of the 30 years annual rainfall. Compared to Fig. 3 one can see a radial decrease of the rain amount north of Mannheim and in the region near Strasbourg which seems to be reliable but too large. It is caused by the effects of the earth’s curvature, e.g., by
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Fig. 4. Distribution of the accumulated rain amount in millimeters Žas indicated by the grey scale. from January 1994 to May 1996 Ž7310 h of duration.. The solid lines are isolines of the orographical structure. The radar location is marked with a Žq..
measuring snow beyond the bright band or by radar data of rain events with very small vertical extents in winter Že.g., with a large reflectivity decrease with height in the lowest 2 km AGL.. The small rain amounts beyond the hills Žnorthwest and southeast of the radar. are due to beam blocking by the hills. But there are also differences between the distributions shown in Figs. 3 and 4. With reference to the accumulated radar data note the larger rain amount in the Rhine valley north of Strasbourg and the smaller amounts of rain east of Mannheim in the Rhine valley Žboth effects are not shown by the climatological distribution.. The larger rain amount in the Rhine valley north of Strasbourg might be induced by a blocking effect of the hills of the Pfalzerwald for southerly winds or by a blocking effect of the Black ¨ Forest for westerly winds. Due to an underestimation of rain east of Strasbourg Žas discussed in Section 2. there surely must be an extension of the maximum at the slope of the Black Forest towards south. The distributions of rain amount for individual months often show large deviations compared with the distribution for the whole period depicted in Fig. 4. As will be shown these variations are due to the different frequency of the wind direction for rain events in the different months. Note that the distribution of rain for the whole period is dominated
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Žas discussed in Section 3. by rain events with wind directions mainly from southwest to west. Two examples of monthly distributions of rain amount are shown in Fig. 5 for March 1996 and Fig. 6 for May 1996. Accumulation times as well as corresponding wind directions are integrated in Table 2. The distribution of rain in March 1996 Ž186 h. exhibit no dominant maximum. The rain amount in the hills around the radar are almost as large as those in the Rhine valley. The spot-like maxima Žin black. results from a strong single thunderstorm. In general, the distribution of rain in March is characterized by a nearly homogeneous distribution of rain over the whole area. Since no concentric rings as typical bright band structures can be recognized bright bands seem to appear most of the time at heights larger than 1.0 km AGL. The maximum rain amount in the northwestern part of the Black Forest as well as the large variation of rain amount between the eastern and the western side of the Rhine valley north of Strasbourg revealed by the long-term integration Žcf. Fig. 4. cannot clearly be seen in the March distribution. The rainfall distribution of March is typical for a month, where a specific wind direction does not prevail Žsee Table 2.. The second example of a monthly distribution of accumulated rain amount ŽMay 1996, Fig. 6. is less homogeneous than that of March 1996. It is characterized by two larger areas with higher rain amounts: one northeast of the radar at the hills of the Odenwald and one south of the radar in the Rhine valley and at the northwestern slope of the Black Forest. Both regions with larger rain amounts are in correspondence with
Fig. 5. Distribution of the accumulated rain amount in millimeters Žas indicated by the grey scale. for March 1996 Ž186 h..
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Fig. 6. Same as Fig. 5, but for May 1996 Ž289 h.. Note the difference in scale values compared to Fig. 5.
the distribution of rain amount of the whole period. Even the minimum rain in the valley of the river Murg south of the rain gauge No. 6 in Fig. 1 is recognizable. The overall structure of rain distribution in this month shows exactly the same structure in its distribution of integrated rain amount ŽGysi, 1996. as the rain accumulation of rain events from the sector WNW. As can be recognized in Table 2 rain events with wind directions from this sector have a large contribution to May. But there is a second influence on the rain distribution of May 1996: a strong thunderstorm activity leads to inhomogeneity and large horizontal variations of rain amount. The thunderstorm activity is mainly located southwest of the radar in the Rhine valley, northeast of the radar in the hills of the Odenwald and southeast of the radar near Stuttgart. It mostly results from single cell thunderstorms because no definite tracks of thunderstorms can be seen in the figure. Thunderstorm activity often occurs with wind directions according to the sectors SES ŽFig. 9. and ESE Žhaving a large contribution to the monthly integration time.. It should be noticed that in the northern part of the hills of the Pfalzerwald as well as ¨ in the area north of Mannheim only small rain amounts are detected which is atypical for that season. We now turn to the distributions of integrated rainfall amount of all rain events considering a certain sector of wind directions. Orographic effects then appear more pronounced. The distribution with the highest amount of accumulated rainfall—that one
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according to the sector SWW—has nearly the same structure as the distribution of accumulated rainfall for the whole period in Fig. 4 and is therefore not repeated here. Different from Fig. 4 and more interesting is the distribution of accumulated rainfall amount of all 86 rain events Ž3540 h. with wind directions from south to southwest ŽFig. 7.. In this case the large amount of accumulated rain in the Rhine valley, in the hills of the Pfalzerwald as well as at its southeastern slopes is characteristic. This is due to the ¨ forced raise of moist air at the hills of the Pfalzerwald accompanied with this wind ¨ direction Žsee arrow in Fig. 7, which shows the mean wind direction of the sector.. The distribution of rain amount north of the radar is rather inhomogeneous due to thunderstorm activity in this area. Thunderstorm activity is also responsible for the small areas with rain amount ) 325 mm Žin black.. It is amazing that they are still recognizable in a rain integration figure over 3540 h in Fig. 4. The characteristic maximum in the Rhine valley and at the northern slope of the Black Forest does not occur within this wind direction. Remember that the maximum mentioned is orographically induced from the Black Forest and occurs only with wind directions from southwest to north. The second example of a wind direction dependent accumulation is that concerning the sector with wind directions from northwest to north indicated by the arrow in Fig. 8. It is an accumulation over 516 h Ž55 rain events.. Here a strong orographical effect by the Black Forest appears. As expected the passive lifting of moist air combined with rain formation leads to high rain amounts at the northwestern slope of the Black Forest and
Fig. 7. Same as Fig. 6, but for the wind direction south to southwest ŽSSW, see arrow. Ž828 h..
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Fig. 8. Same as Fig. 6, but for the wind direction northwest to north ŽNWN, see arrow. Ž516 h..
in the Rhine valley. The increase of rain amount toward the Black Forest is more or less parallel to the mean wind direction of that sector. On the other hand a strong decrease of accumulated rain in the southern Rhine valley near Strasbourg can be noticed which is exactly perpendicular to the mean wind direction of the sector ŽNWN.. It seems that the Žas well as the Vosges mountains. have a strong prohibiting hills of the Pfalzerwald ¨ effect on rain in the southern Rhine valley where very small rain amounts occur. Also very small rain amounts have been measured in the hills of the Pfalzerwald itself and at ¨ its eastern and southeastern slope. But downstream immediately south of the hills of the Pfalzerwald, there is a region with larger rain amounts than in the Rhine valley further ¨ south Ži.e., west of Strasbourg.. This may result from a counter current in the Rhine valley induced by the channeling effect of the Rhine valley which turns the flow in the lowest 1.5 km AGL from northwest–north into a flow from north–northeast ŽWippermann, 1994.. Larger rain amounts then occur due to a blocking effect on the flow and a forced raise approaching the northeastern Vosges mountains and the slope of the Pfalzerwald. ¨ The last example ŽFig. 9. shows the distribution of rainfall amount according to the wind direction sector southeast to south Ž21 rain events with 196-h duration.. Larger rain amounts only appear in the Rhine valley south of the radar and in the hills of the Pfalzerwald. The distribution is very inhomogeneous indicating a considerable thunder¨ storm activity. The local maxima, e.g. northwest of the Black Forest and northwest of the radar in the Rhine valley, are due to single thunderstorm events.
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Fig. 9. Same as Fig. 6, but for the wind direction southeast to south ŽSES, see arrow. Ž172 h..
It may only be speculated if the thunderstorms form upstream at the southeasterly slope of the Black Forest Žwhich is heavily shielded for radar beams. and move over the mountain or if they form in the lee-side ŽBanta, 1990. of the Black Forest triggered by its northern and northwestern slopes. However, from the northwestern slope of the Black Forest the thunderstorms move, passing the Rhine valley, parallel to the mean wind direction of the sector Žcf. arrow in Fig. 9. towards north–northwest. As presented, the analysis of the distribution of the long time accumulations of rain according to certain wind directions reveals distinct maxima and minima of rain amounts coupled to the orographical structure of the region considered. Besides these expected results some unexpected results became obvious. So by a certain wind direction thunderstorms in the northern Black Forest may be triggered which then move through the Rhine valley as shown in Fig. 9. However, the method of considering only a certain height for determining the wind direction for the classification of rain events for accumulation is a simplification which still might obscure orographical effects on the distribution of accumulated rain due to small scale phenomena. 5. Accumulation of rain events according to a special vertical wind profile The discussion of Section 4 is based on data where only the wind direction measured in a single level, namely 2–2.5 km AGL, is considered. However, as mentioned in
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Fig. 10. Wind speed in meters per second and wind direction in degrees as a function of height ŽAGL. for the 24th of January 1996, 0605 UTC with a counter current situation due to a channeling effect of the Rhine valley. For discussion see text.
Fig. 11. Same as Fig. 6, but for the wind direction sector west to northwest Žsee arrow. according to the vertical wind profile of Fig. 10 Ž252 h..
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Section 4 traditional wind measurements show that under certain circumstances a strong specific flow regime is present in the Rhine valley. This feature is a counter current due to a channeling effect in the Rhine valley. It is therefore of interest to investigate such situations when the counter current is fully developed. A corresponding typical wind profile derived from the radial Doppler velocity data within a range of 50 km with the VVP method of Waldteufel and Corbin Ž1979. is given in Fig. 10. Near the ground, there is a rather strong flow from east to northeast. Between 1 and 2 km AGL it turns counterclockwise to a flow from northwest. In the height range 2–2.5 km AGL which is applied for classification of wind direction dependent rainfall the wind blows from west to northwest so that a rainfall event is counted into the sector WNW. Above a height of 3 km AGL the flow usually turns to southwestern directions under counter current conditions. Typical for rain events with this particular profile is a stationary precipitation cell southeast of the hills of the Pfalzerwald, i.e., on the lee-side ¨ of the hills considering the wind direction west–northwest in the height range 2–2.5 km AGL as moving direction of the precipitation systems. In Fig. 11 all 20 rain events showing similar wind profiles as those in Fig. 10 Ž252 h of duration within the period of 30 months. are integrated. The local maximum south of the Pfalzerwald is clearly seen ¨ in the figure. Large amounts of precipitation are also found in the Rhine valley between Strasbourg and Karlsruhe and at the northwestern slope of the Black Forest. In contrast, the large rain amounts at the slope of the Black Forest are in accordance to the expected distribution of accumulated rain events within the wind direction sector WNW. The small amount of accumulated rain in the Rhine valley northwest of the location of the radar may be a local fohn ¨ effect in the lee-side of the Pfalzerwald. ¨
6. Conclusions With the method of wind-direction-dependent time integration of rain-intensity data obtained by radar on a terrain-following surface at a height of 1 km AGL it is possible to reveal orographic effects dominating the distribution of rainfall amount. The rain distribution for the whole period Ž30 months. is determined by rain events from the wind direction sector southwest to west. It is in a good correspondence with the climatological rain distribution for the area considered. The month by month time integrations of the precipitation, however, show a weak orographic influence on the rainfall amount because they are usually a superposition of rain events from different wind directions. In contrast, the time integrations of rain events from different wind-direction sectors lead to distributions by which orographic effects clearly appear: e.g., maxima due to a blocking effect on the flow in the updraft region of hills and minima of the accumulated rain downstream the hills. Moreover, rather seldom or unexpected phenomena such as a region of thunderstorm triggering, areas of preferred thunderstorm trackways and exemplarily a maximum in the lee-side of a hill have been found. These phenomena occur statistically significant with winds blowing from a certain wind direction sector and can only be revealed by the method of the wind direction dependent accumulation of rain events.
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The wind direction in a height of 2–2.5 km AGL calculated from Doppler data seems to be a good indicator for the mean direction of motion of rain systems. If, however, local Žmeso-g scale. phenomena should be investigated it is necessary to consider not only winds in a specific height range but vertical profiles of wind and to accumulate only rain events according to those wind profiles. A comparison of accumulations of radar rain intensity data with data of a rain gauge network shows the importance to correct radar data so that the rain amount near the ground can quantitatively and reliably be measured. For ranges larger than about 80 km additional corrections are needed during the cold season when the bright band is lower than about 2 km AGL. Nevertheless, there is an advantage of using rain-intensity data by radar to determine the distribution of accumulated rain amount for climatological and hydrological applications. In summer, when thunderstorms lead to large horizontal variations of the rain intensity within only a few km, the highly resolved radar rain data are much more accurate than data interpolated from a rain gauge network. The detailed information of radar reflectivity is also necessary to investigate small scale phenomena induced by orography. The strong dependence of the rain distribution on the wind direction at a height of 2–2.5 km AGL may be useful for nowcasting Žespecially in orographically complex terrain. the local occurrence of rainfall or thunderstorms within a certain wind direction, e.g., for flood warning or for thunderstorm warning. Acknowledgements I would like to thank K.D. Beheng for his general support and helpful suggestions as well as two reviewers for their constructive comments and criticisms. Thanks also to A. Wenzel for making available the rain gauge and wind data from the REKLIP stations, to T. Garbrecht for taking care of the disdrometer and to G. Klinck for Fig. 1. The REKLIP project is supported by the ‘Ministerium fur ¨ Wissenschaft und Kunst’ of Baden-Wurt¨ temberg under contract number 1499Tit.Gr.74. References Banta, R.M., 1990. Atmospheric processes over complex terrain. Am. Meteor. Soc. 23, 45, Meteorological monographs. Collier, C.G., 1972. Applications of weather radar systems. A Guide to Users of Radar Data in Meteorology and Hydrology. Halsted Press, Chichester. Collinge, V.K., 1991. Weather radar calibration in real time: prospects for improvement. Hydrological Applications of Weather Radar. Ellis Horwood, Chichester. Creutin, J.D., Delrieu, G., Lebel, T., 1988. Rain measurement by rain gauge–radar combination: a geostatistical approach. J. Atmos. Ocean. Technol. 5, 102–115. Fabry, F., Austin, G.L., Tees, D., 1992. The accuracy of rainfall estimates by radar as a function of range. Q. J. R. Meteorol. Soc. 118, 435–453. Fiedler, F., 1995. Klimaatlas Oberrhein Mitte-Sud. ¨ Institut fur ¨ angewandte Geowissenschaften ŽIFG., Offenbach. Gysi, H., 1995. Niederschlagsmessung mit Radar in orographisch gegliedertem Gelande. PhD Thesis, Univ. ¨ Karlsruhe, Germany.
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Gysi, H., 1996. Orographic influence on the distribution of the accumulated rainfall for different wind directions. Preprints, 12th Int. Conf. on Clouds and Precipitation. Am. Meteor. Soc., pp. 649–652. Held, E., Joss, J., 1994. The influence of the orography on precipitation seen by the Swiss Radars. COST 75 Weather Radar Systems. International Seminar, Brussels, Belgium 20–23 Sept. European Commission, pp. 777–786. Hildebrand, P.H., Towery, N., Snell, M.R., 1979. Measurement of convective mean rainfall over small areas using high density rain gages and radar. J. Appl. Meteorol. 18, 1316–1326. Hill, F.F., Browning, K.A., Bader, M.J., 1981. Radar and rain gauge observations of orographic rain over south Wales. Q. J. R. Meteorol. Soc. 107, 643–670. Huff, F.A., 1970. Sampling errors in measurement of mean precipitation. J. Appl. Meteorol. 9, 35–44. Joss, J., Pittini, A., 1991. Real-time estimation of the vertical profile of radar reflectivity to improve the measurement in an alpine region. J. Meteorol. Atmos. Phys. 47, 61–72. Joss, J., Waldvogel, A., 1990. Precipitation measurement and hydrology. In: Atlas, D. ŽEd.., Radar in Meteorology. Am. Meteorol. Soc., pp. 577–606. Loffler Mang, M., Beheng, K.D., Gysi, H., 1996. Drop size distribution measurement in rain—a comparison ¨ of two sizing methods. Meteorol. Z. 4, 139–144, N.F. 5. Nickerson, E.C., Richard, E., Rosset, R., Smith, D.R., 1986. The numerical simulation of clouds, rain and airflow over the Vosges and the Black Forrest Mountains: a meso scale b model with parametrized microphysics. Mon. Wea. Rev. 114, 398–414. Passarelli, R.E., Romanik, P., Geotis, S.G., Siggia, A.D., 1981. Ground clutter rejection in the frequency domain. Preprints, 20th Conf. Radar Meteor., Am. Meteor. Soc., pp. 345–348. Sauvageot, H., 1994. Rainfall measurement by radar: a review. Atmos. Res. 35, 27–54. Schmid, W., Hogl, ¨ D., Vckovski, A., Joss, J., 1991. Test of clutter suppression techniques in the Swiss Alps. Preprints, 25th Conf. Radar Meteor., Paris, Am. Meteor. Soc., pp. 875–878. Seed, A.W., Austin, G.L., 1991. Sampling errors for rain gauge-derived mean areal daily and monthly rainfall. Hydrological Applications of Weather Radar. Ellis Horwood, Chichester. Tateya, K., Nakatsugawa, M., Yamada, T., 1991. Observations and simulation of rainfall in mountainous areas. Hydrological Applications of Weather Radar. Ellis Horwood, Chichester. Waldteufel, P., Corbin, H., 1979. On the analysis of single Doppler radar data. J. Appl. Meteorol. 18, 532–542. Wenzel, A., Kalthoff, N., Fiedler, F., 1996. On the variation of the energy-balance components with orography in the Upper Rhine valley. Theor. Appl. Climatol., in press. Wippermann, F., 1994. Air flow over and in broad valleys: channeling and counter current. Contrib. Atmos. Phys. 57 Ž1., 92–105.