Does Air Pollution Really Suppress Precipitation in Israel?’’
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AUGUST 2009 N O T E S A N D C O R R E S P O N D E N C E 1733 Comments on ‘‘Does Air Pollution Really Suppress Precipitation in Israel?’’ AMIR GIVATI Israeli Hydrological Service, Jerusalem, Israel DANIEL ROSENFELD The Hebrew University of Jerusalem, Jerusalem, Israel (Manuscript received 15 October 2007, in final form 20 December 2008) ABSTRACT Alpert et al. in a recent paper challenged the quantification of the suppression of orographic precipitation that was shown in two recent papers by Givati and Rosenfeld to occur in Israel. Their main claim was that the results were determined by the selection of the rain gauges. In this comment, it is demonstrated that when an objective selection of the rain gauges is applied to all of the rain gauges that were used by Alpert et al. and Givati and Rosenfeld, the outcome replicates the results of Givati and Rosenfeld and provides additional insights. At the final account, this comment further enhances the confidence that orographic precipitation has been suppressed over Israel. The direct evidence to the cause is still lacking. 1. Method by AHL08 for their Figs. 3 and 4 that indicated in- creasing tends of Ro and the gauges used by GR04 The main claim of Alpert et al. 2008 (hereinafter and GR05 for their figures that indicated decreasing AHL08) is that Givati and Rosenfeld (2004, 2005, trend of Ro. hereinafter GR04 and GR05, respectively) used rain 2) We paired all possible combinations between these gauges selectively to obtain a decreasing trend of the ratio hill and plains gauges, separately for the north and for between hilly (called ‘‘mountain’’ in AHL08) and plains the center, and retained only the pairs for which at (called ‘‘shore’’ and ‘‘inland’’ in AHL08) rain gauges. least 30 yr of data from both rain gauges are available. AHL08 used rain gauges different from those used by All of the possible pairs, their correlation, Ro, and GR04 and GR05 to show an increasing trend for central the slope of Ro are tabulated in Tables 3 and 4 for and northern Israel (in AHL08’s Figs. 3 and 4, respec- central and northern Israel, respectively. tively). AHL08 showed that using different gauge selec- 3) We classified the paired rain gauges according to the tion methods gave opposite results, and so questioned the correlation coefficient R between their annual rainfall validity of the results of GR04 and GR05. AHL08 used into three groups: R $ 0.9, 0.9 . R $ 0.8, and R , 0.8. all available records, whereas GR04 and GR05 used pairs 4) According to Fig. 2 of AHL08 the probabilities for of gauges or gauge clusters that have long enough records the trends in the orographic enhancement factor Ro and maintain a high correlation between them. To re- were random in central Israel. Recalculating the solve this selectivity question, we did the following: probabilities with the same data when applying the 1) We composed combined tables, separately for cen- objective selection criteria of correlation and dura- tral (Table 1) and northern (Table 2) Israel. Each of tion of measurements showed that decreasing slopes these combined tables include all of the gauges used of Ro dominate the highly correlated pairs of gauges that recorded data for long periods. 5) The trends between the hill and lowland rainfalls Corresponding author address: Daniel Rosenfeld, Institute of Earth Sciences, The Hebrew University of Jerusalem, Jerusalem were calculated for the three correlation classes, sep- 91904, Israel. arately for north and central Israel. Additional clas- E-mail: [email protected] sification was done as a function of distance eastward DOI: 10.1175/2009JAMC1902.1 Ó 2009 American Meteorological Society Unauthenticated | Downloaded 09/26/21 08:30 AM UTC 1734 JOURNAL OF APPLIED METEOROLOGY AND CLIMATOLOGY VOLUME 48 TABLE 1. Center Israel: station name, designation, distance from the sea, and station height. The stations that were used by AHL08 are marked as A. Those used by GR04 or GR05 are marked by G. Station name Used by Designation Distance from the sea (km) Height (m) Bat yam A Coast 1 5 Ben Gurion airport A1G Plains 15.6 50 Bet Dagan A1G Plains 9.6 30 Eyal A Plains 15.7 110 Gaash A Coast 1 50 Givat Brener A Plains 12.8 70 Horeshim A Plains 17.2 130 Hulda A1G Plains 22.3 125 Jaffa port A Coast 1 10 M. David G Plains 24.3 155 Miqwe Israel A Plains 4 20 Nahshon A1G Plains 33 200 Nahsonim A Plains 15.2 100 Netanya A Coast 1 35 Nir Galim A Coast 5 20 Palmahim A Coast 1 20 Rishon Letzion (Nahalat Jehoda) G Coast 6 50 Shaalavim A Plains 29.9 180 Shmariahu A Coast 3 30 Tel Aviv airport A Coast 1 4 Tel Aviv Qiryat Shaul A Coast 4 40 Yad Hana A Plains 15 60 Yesodot G Plains 21.3 70 Zerifin G Plains 12 50 Zora G Plains 33.9 340 Biet Meir G Hill 39 530 Bitonia G Hill 45 810 Deir Ghassana A Hill 37 460 Deir Istiya A Hill 34 432 Jerusalem airport A Hill 52 740 Jerusalem central A Hill 58 815 Jinsafut A Hill 31 430 Qiryat Anavim A1G Hill 46 700 Ramalla G Hill 49 870 Salfit A1G Hill 39 520 Sebastia A Hill 34 335 Shoresh G Hill 41 680 Singil A Hill 49 775 Zova G Hill 47 730 from the coastline, to account for the decay of the of rain gauges require that they will be well correlated convectiveness of the clouds with distance from the and also comeasured for a sufficiently long period. sea inland or for other possible factors that may AHL08 did not apply any such test. However, where depend on the distance from the sea. The distribu- should we put the threshold for correlation between the tions of the trends from all of the paired gauges are pairs of gauges and for the number of years that they displayed the same way as in AHL08’s Fig. 2. cover? To avoid an arbitrary cutoff, a range of these thresholds was applied for the trends of Ro, as shown The results obtained by this analysis make it unneces- in Fig. 1. sary to address the remaining claims of AHL08. Figure 1a is composed of 181 pairs of gauges that had 2. Results for central Israel at least 20 yr of common measurements. According to Fig. 1a, 94% of the pairs with correlations R . 0.90 a. Is the probability for trends in Ro over Judea had negative slopes of the correlation of Ro with time. and Samaria random? For 0.9 , R # 0.8, 62% of the slopes were negative. For Figure 2b of AHL08 suggests a random probability R , 0.80, this number falls to 52%, which means prac- for Ro when all gauges are paired. However, valid pairs tically a random sign for the slopes. To test the impact of Unauthenticated | Downloaded 09/26/21 08:30 AM UTC AUGUST 2009 N O T E S A N D C O R R E S P O N D E N C E 1735 TABLE 2. Northern Israel: station name, designation, distance from by both AHL08 and GR04 were combined into Table 3. the sea and station height. These pairs of rain gauges were analyzed and displayed Distance in Figs. 2a,b the same way as was done for Fig. 1. from the Height Figure 2 shows the accumulated probabilities of all Station name Used by Designation sea (km) (m) trends from the most negative slope upward, for pairs of K. Bialik A Coast 3.1 20 stations used by AHL08 and GR04 in central Israel. Haifa port A1G Coast 0.5 5 There were in all 350 pairs, out of which 342 and 222 Haifa biol. A Coast 3.3 300 pairs exceeded 20 and 30 common measurement years, K. Galim A Coast 2 10 respectively. As in Fig. 1, it can be seen that negative Atlit A Coast 2.3 10 Rosh-Haniqra G Coast 1 30 trends occur for 90% of the hilly–plains pairs with cor- Gesher ha ziv G Coast 3 20 relation of R $ 0.90 and common measuring period of Ramat-Yohanan A Coast 9 58 at least 30 yr. Upon lowering the correlation range to Qiryat Atta G Coast 8.8 35 0.90 . R $ 0.80, only 75% of the pairs have decreasing Nahariya G Coast 4 10 slopes. For the cases with R , 0.80, the slopes appear to Regba G Coast 1.4 20 Kfar Masaryk A Coast 1.6 10 be completely random. Akko A1G Coast 1 20 The trend in Ro was recalculated using all the pairs Yehiam A Hill 13 380 that had R $ 0.90 and period $30 yr. The Ro for each Yirka A Hill 13.4 430 year was calculated as the sum of the hill rainfall divided Miilya AG Hill 15 500 by the sum of the plains rainfall, taken from all pairs Harashim A Hill 17.2 823 Fassuta A Hill 19.2 650 that passed the selection criteria. The result is presented Peqiin A Hill 22 650 in Fig. 3, which replicates the indicated decreasing trend Makhul A Hill 21.4 480 in Ro as reported by GR04. Sumei A Hill 21 580 Hurfeish A1G Hill 23.8 630 c. The role of distance of the plains gauges from Baram A Hill 29.8 750 the coastline Yiron A1G Hill 32.6 690 Meron A1G Hill 33.5 680 AHL08 suggested that any indicated decreasing trend Amirim A1G Hill 35.5 600 in Ro would be an artifact due to a relative increase of Rihaniya A Hill 36.5 660 the rainfall in the inner plains in comparison with the Malkiyya A Hill 37.5 690 coastline, possibly caused by effects of the coastal ur- Kennan A1G Hill 39.3 934 Yiftah A Hill 41.5 475 banization.