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Comments on ‘‘Does Air Pollution Really Suppress Precipitation in ?’’

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

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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 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

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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. 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 G Coast 4 10 slopes. For the cases with R , 0.80, the slopes appear to G Coast 1.4 20 A Coast 1.6 10 be completely random. Akko A1G Coast 1 20 The trend in Ro was recalculated using all the pairs 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. They further suggested that the trend of hill/ plains rainfall should be increasing, in contrast with the indications of GR04. This question is addressed here by classification of the pairs according to the distance D of observational period, Fig. 1b selects the 107 pairs with at the plains rain gauge eastward from the coastline in least 30 common years. This reduced the spread of the kilometers. values of the slopes mainly for 0.9 , R # 0.8, and in- The pairs that passed the criteria of R $ 0.90 and at creased to 78% the fraction of negative slopes. The least 30 yr (used for composing Fig. 3) were further slopes of the pairs with R , 0.8 remained random. classified according to D, as shown in Fig. 4a. This figure In summary, according to Fig. 1 the pairs with the shows that almost all of the pairs produced negative lowest correlation and measuring period replicated the trends, regardless of the value of D. However, the re- results of AHL08 and showed a random distribution quirement of R $ 0.90 left too-few pairs for a robust of trend in Ro. However, the pairs with higher corre- conclusion. The number of pairs can be seen by the lations and longer periods had smaller scatter of Ro number of dots on the lines in Figs. 1, 2, and 4. Therefore, and converged to negative slopes as found by GR04 it was necessary to relax the correlation to R $ 0.85, and GR05. shown in Fig. 4b. According to Fig. 4, especially Fig. 4b, the probability b. Reevaluating the trends in Ro over Judea for more negative trends was obtained when the hill and Samaria gauges were paired with plains gauges that were farther Figure 3 of AHL08 and Fig. 6b of GR04 present op- eastward from the coastline. This is consistent with the posite trends of Ro for the same geographic region. suggestion of AHL08 that rainfall has increased in the Which one of these figures, if any, presents the correct inner plains with respect to the coastline. However, trend? To examine this question, all of the rain gauges Fig. 5a shows that there is still a decreasing trend of used for constructing the trends of Ro in central Israel Ro even when calculated against the shore rain gauges

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TABLE 3. All possible pairs between the rain gauges used for calculating trends in orographic precipitation enhancement factor in central Israel by AHL08 flagged with A, by GR04 and GR05 only flagged with G, and by both flagged with AG. Only pairs that had at least 20 yr of paired rainfall data were retained. For each pair, the following are shown: name of the plains rain gauge, its AG flag, and its average rainfall (mm yr21), name of the hill rain gauge, its AG flag, and its average rainfall (mm yr21), the ratio Ro of the average hill/plains rainfall amounts, number of years with paired rain gauge data, correlation between the annual rainfalls, and slope of the least squares fit to the annual ratios of hill/plains rainfalls. The pairs are sorted by descending order of their correlation.

Plains gauge AG Rain plains Hill gauge AG Rain hill Ro Common years Correlation Slope Nahsonim A 567 Deir Ghassana A 657 1.159 28 0.965 0.001 34 Zora G 490 Biet Meir AG 615 1.255 48 0.964 20.003 93 Rishon Letzion G 580 Deir Ghassana A 666 1.147 29 0.951 20.001 94 Shaalavim A 533 Biet Meir AG 612 1.15 47 0.946 20.000 42 Nahshon AG 502 Biet Meir AG 613 1.221 46 0.943 20.0054 Hulda AG 528 Biet Meir AG 615 1.165 48 0.942 20.001 84 Shaalavim A 550 Jerusalem airport A 613 1.115 34 0.94 20.002 42 Zora G 515 Jerusalem airport A 613 1.191 34 0.938 20.005 56 Eyal A 625 Jinsafut A 659 1.055 34 0.938 0.000 65 Yesodot G 546 Biet Meir AG 633 1.159 44 0.936 20.003 45 Nahsonim A 559 Deir Istiya A 633 1.133 34 0.934 20.000 72 Bet Dagan AG 554 Jinsafut A 657 1.187 34 0.933 20.000 52 Zora G 490 Qiryat Anavim AG 696 1.422 48 0.933 20.005 08 Zora G 506 Bitonia G 653 1.289 35 0.933 20.006 45 M. David G 495 Biet Meir AG 599 1.209 25 0.931 20.002 52 Zerifin G 595 Deir Ghassana A 666 1.118 29 0.928 20.0029 Zora G 490 Jerusalem central A 530 1.083 48 0.927 20.001 69 Zora G 495 Zova G 660 1.332 47 0.926 20.003 18 Nahsonim A 552 Jinsafut A 651 1.179 34 0.926 20.000 66 Horeshim A 642 Jinsafut A 658 1.026 30 0.923 20.000 02 Hulda AG 528 Qiryat Anavim AG 696 1.319 48 0.922 20.002 61 Horeshim A 653 Deir Istiya A 643 0.985 29 0.922 20.000 88 Shaalavim A 533 Qiryat Anavim AG 693 1.302 47 0.921 20.001 15 Givat Brener A 591 Deir Ghassana A 666 1.127 29 0.92 20.0017 Tel Aviv Qiryat Shaul AG 578 Deir Istiya A 637 1.102 35 0.917 0.000 06 Nahshon A 502 Qiryat Anavim AG 695 1.384 46 0.917 20.006 55 Yad Hana A 652 Sebastia A 647 0.993 27 0.917 20.000 54 Jaffa port A 549 Deir Ghassana A 673 1.225 21 0.916 0.000 17 Zora G 513 Deir Ghassana A 666 1.296 29 0.916 20.0049 Nahshon AG 535 Deir Ghassana A 671 1.255 28 0.914 20.004 91 Nahshon AG 502 Jerusalem central A 528 1.052 46 0.914 20.002 84 Nahshon AG 533 Jerusalem airport A 614 1.153 33 0.914 20.005 95 Shaalavim A 553 Bitonia G 653 1.18 35 0.914 20.003 48 Rishon Letzion G 576 Deir Istiya A 637 1.105 35 0.913 20.003 43 Hulda AG 545 Jerusalem airport A 613 1.125 34 0.912 20.004 98 Bet Dagan AG 551 Deir Ghassana A 668 1.212 27 0.911 20.001 95 Rishon Letzion G 577 Jinsafut A 656 1.136 35 0.91 20.002 55 M. David G 495 Zova G 637 1.287 25 0.91 20.000 82 Eyal A 639 Deir Ghassana A 668 1.045 28 0.909 0.002 32 Nahsonim A 556 Bitonia G 647 1.162 33 0.909 20.000 35 Nahshon AG 508 Zova G 659 1.295 45 0.908 20.005 09 Shaalavim A 540 Zova G 658 1.218 46 0.908 0.000 02 Yesodot G 547 Bitonia G 652 1.192 33 0.907 20.006 22 Shaalavim A 495 Shoresh G 588 1.187 32 0.907 0.000 21 Hulda AG 528 Jerusalem central A 530 1.005 48 0.905 20.0001 Givat Brener A 576 Jerusalem airport A 613 1.064 34 0.905 20.006 43 Yesodot G 546 Qiryat Anavim AG 721 1.32 44 0.903 20.004 45 Yesodot G 546 Zova G 675 1.235 44 0.903 20.003 21 Tel Aviv Qiryat Shaul AG 582 Jinsafut A 656 1.126 35 0.902 20.001 44 Zora G 463 Shoresh G 588 1.271 32 0.902 20.000 94 Shaalavim A 569 Ramalla G 669 1.175 26 0.902 20.004 02 Shaalavim A 533 Jerusalem central A 528 0.992 47 0.902 0.001 11 Rishon Letzion G 575 Bitonia G 653 1.135 35 0.899 20.003 28 Eyal A 625 Deir Istiya A 640 1.024 34 0.899 0.0009

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TABLE 3. (Continued)

Plains gauge AG Rain plains Hill gauge AG Rain hill Ro Common years Correlation Slope Miqwe Israel A 539 Jinsafut A 656 1.216 35 0.898 0.000 61 Hulda AG 547 Deir Ghassana A 666 1.217 29 0.897 20.001 34 M. David G 495 Qiryat Anavim AG 693 1.399 25 0.897 20.002 86 Hulda AG 535 Zova G 660 1.234 47 0.896 20.001 87 Givat Brener A 573 Bitonia G 653 1.139 35 0.896 20.003 79 Shaalavim A 565 Deir Ghassana A 666 1.178 29 0.896 20.000 45 Tel Aviv Qiryat Shaul AG 591 Deir Ghassana A 666 1.126 29 0.895 0.000 82 Zora G 512 Jinsafut A 656 1.28 35 0.895 20.005 65 Zora G 511 Deir Istiya A 637 1.247 35 0.895 20.005 39 Miqwe Israel A 544 Deir Istiya A 637 1.171 35 0.894 0.002 63 Bat yam A 542 Deir Ghassana A 673 1.242 21 0.893 0.000 79 Zerifin G 587 Deir Istiya A 637 1.084 35 0.893 20.004 23 Nahsonim A 573 Salfit A 705 1.231 30 0.892 0.001 44 Yesodot G 558 Jerusalem airport A 624 1.118 33 0.891 20.008 03 Horeshim A 658 Deir Ghassana A 666 1.012 23 0.89 0.000 42 Nahsonim A 551 Jerusalem airport A 603 1.094 33 0.89 20.002 08 Givat Brener A 581 Deir Istiya A 637 1.096 35 0.89 20.003 05 Givat Brener A 567 Biet Meir AG 627 1.106 46 0.89 20.002 52 Hulda AG 546 Bitonia G 653 1.195 35 0.888 20.004 84 Yesodot G 546 Jerusalem central A 551 1.008 44 0.888 20.001 74 Hulda AG 493 Shoresh G 588 1.193 32 0.885 0.000 93 Zerifin G 585 Bitonia G 653 1.116 35 0.884 20.005 15 Eyal A 659 Sebastia A 645 0.979 28 0.884 0.007 79 Givat Brener A 578 Jinsafut A 656 1.134 35 0.883 20.004 19 Shaalavim A 564 Deir Istiya A 637 1.129 35 0.883 20.001 54 Shmariahu A 557 Deir Ghassana A 657 1.178 28 0.88 0.003 93 Yesodot AG 549 Deir Ghassana A 668 1.215 28 0.88 20.004 51 Zora AG 533 Sebastia A 645 1.212 28 0.879 0.004 12 Jaffa port A 528 Jinsafut A 667 1.264 29 0.875 20.0034 Nahshon AG 523 Bitonia G 656 1.256 34 0.875 20.006 77 M. David G 458 Shoresh G 583 1.273 16 0.875 0.001 32 Givat Brener A 609 Sebastia A 645 1.06 28 0.874 0.005 4 Miqwe Israel A 554 Deir Ghassana A 666 1.201 29 0.873 0.004 01 Hulda AG 575 Sebastia A 645 1.123 28 0.872 0.002 88 Bet Dagan AG 549 Bitonia G 652 1.187 33 0.871 20.001 93 Horeshim A 695 Sebastia A 658 0.947 22 0.869 0.007 99 Eyal A 634 Bitonia G 657 1.036 34 0.868 0.001 34 Bet Dagan AG 557 Salfit A 715 1.284 29 0.867 20.004 64 Zerifin G 588 Jinsafut A 656 1.115 35 0.867 20.005 44 Rishon Letzion G 579 Jerusalem airport A 614 1.06 33 0.867 20.005 36 Gaash A 536 Jinsafut A 656 1.223 35 0.866 0.006 06 Shmariahu A 542 Deir Istiya A 633 1.169 34 0.866 0.0035 Hulda AG 548 Deir Istiya A 637 1.162 35 0.866 20.003 Shmariahu A 545 Jinsafut A 651 1.195 34 0.865 0.004 22 Yad Hana A 627 Jinsafut A 656 1.046 35 0.865 20.005 59 Nir Galim A 538 Deir Ghassana A 666 1.237 29 0.864 20.003 51 Yesodot G 548 Deir Istiya A 638 1.164 34 0.863 20.005 57 Givat Brener A 574 Zova G 674 1.174 45 0.863 20.001 77 Zerifin G 567 Biet Meir AG 615 1.084 48 0.862 20.0023 Nahshon AG 551 Sebastia A 649 1.179 27 0.861 0.002 69 Jaffa port A 522 Deir Istiya A 640 1.224 27 0.86 20.002 56 Rishon Letzion G 592 Salfit A 710 1.198 31 0.86 20.002 58 Nahshon AG 530 Jinsafut A 661 1.248 34 0.86 20.0051 Nahsonim A 547 Biet Meir AG 617 1.128 45 0.86 0.000 36 Ben Gurion airport A 597 Bitonia G 662 1.109 34 0.859 20.005 36 Miqwe Israel A 540 Bitonia G 653 1.21 35 0.858 0.001 32 Bat yam A 525 Deir Istiya A 631 1.202 26 0.855 20.001 34 Shaalavim A 556 Jinsafut A 656 1.179 35 0.855 20.003 03 Zerifin G 587 Jerusalem airport A 613 1.045 34 0.854 20.008 17

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TABLE 3. (Continued)

Plains gauge AG Rain plains Hill gauge AG Rain hill Ro Common years Correlation Slope Yesodot G 576 Sebastia A 645 1.121 28 0.854 0.002 32 Zerifin G 616 Sebastia A 645 1.048 28 0.853 0.003 14 M. David G 513 Jerusalem airport A 592 1.155 17 0.853 20.005 03 Horeshim A 627 Jerusalem central A 528 0.842 41 0.853 20.000 37 Palmahim A 503 Deir Ghassana A 662 1.316 28 0.852 0.0009 Bet Dagan AG 546 Deir Istiya A 639 1.169 33 0.851 20.004 76 M. David G 515 Bitonia G 634 1.232 20 0.85 20.004 59 Nahsonim A 554 Zova G 664 1.199 44 0.85 0.001 18 Givat Brener A 567 Qiryat Anavim AG 711 1.255 46 0.85 20.003 71 Rishon Letzion G 562 Biet Meir AG 620 1.102 46 0.849 20.0018 Nahsonim A 589 Sebastia A 643 1.091 27 0.849 0.008 81 Gaash A 542 Deir Istiya A 638 1.177 34 0.848 0.005 76 Bat yam A 534 Jinsafut A 661 1.239 28 0.848 20.003 44 Yesodot G 549 Jinsafut A 658 1.199 34 0.848 20.006 81 Nahshon AG 528 Deir Istiya A 643 1.217 34 0.847 20.005 13 Nahsonim A 547 Jerusalem central A 535 0.979 45 0.847 0.0014 Shaalavim A 590 Sebastia A 645 1.094 28 0.847 0.007 25 Horeshim A 627 Qiryat Anavim AG 697 1.112 41 0.846 20.002 74 Bat yam A 531 Bitonia G 655 1.234 26 0.844 20.001 09 Nahshon AG 475 Shoresh G 588 1.237 31 0.844 20.003 18 Zora G 526 Salfit A 710 1.348 31 0.844 20.001 41 Eyal A 637 Salfit A 710 1.114 31 0.844 0.001 57 Hulda AG 548 Jinsafut A 656 1.196 35 0.843 20.003 87 Horeshim A 673 Salfit A 714 1.061 26 0.843 20.000 06 Bet Dagan AG 551 Jerusalem airport A 613 1.113 34 0.842 20.0041 Rishon Letzion G 569 Zova G 674 1.185 45 0.842 0.000 83 M. David G 495 Jerusalem central A 517 1.045 25 0.842 0.001 71 Yad Hana A 620 Deir Istiya A 638 1.029 34 0.842 20.006 98 Givat Brener A 567 Jerusalem central A 542 0.956 46 0.842 20.000 82 Nahsonim A 547 Qiryat Anavim AG 700 1.281 45 0.841 20.000 39 Horeshim A 644 Bitonia G 650 1.009 29 0.84 20.002 96 Tel Aviv Qiryat Shaul AG 580 Bitonia G 650 1.122 34 0.838 20.000 49 Horeshim A 627 Biet Meir AG 613 0.977 41 0.837 20.001 46 Ben Gurion airport AG 583 Deir Ghassana A 674 1.156 28 0.836 20.004 16 Rishon Letzion G 601 Sebastia A 645 1.073 28 0.836 0.004 05 Zerifin G 574 Zova A 660 1.15 47 0.834 20.001 77 Ben Gurion airport AG 592 Jerusalem airport A 613 1.035 34 0.832 20.005 19 Zerifin G 567 Qiryat Anavim AG 696 1.228 48 0.832 20.003 23 Ben Gurion airport AG 595 Jinsafut A 662 1.113 34 0.831 20.004 44 Tel Aviv Qiryat Shaul AG 603 Sebastia A 645 1.07 28 0.831 0.006 22 Yad Hana A 631 Deir Ghassana A 665 1.054 28 0.831 20.005 35 Nir Galim A 529 Bitonia G 653 1.234 35 0.83 20.006 06 Jaffa port A 534 Sebastia A 650 1.218 24 0.829 0.008 69 Jaffa port A 527 Bitonia G 663 1.259 27 0.829 20.001 68 Bet Dagan AG 571 Sebastia A 654 1.146 26 0.829 0.003 48 Nir Galim A 529 Deir Istiya A 637 1.204 35 0.824 20.004 49 M. David G 531 Ramalla G 659 1.242 17 0.823 20.007 92 Palmahim A 500 Bitonia G 653 1.305 35 0.822 0.001 59 Ben Gurion airport AG 609 Salfit AG 710 1.166 31 0.822 20.001 89 Zerifin G 606 Salfit AG 710 1.17 31 0.82 20.003 62 Rishon Letzion G 562 Jerusalem central A 536 0.953 46 0.82 0.000 22 Zora G 520 Ramalla G 669 1.286 26 0.82 20.009 45 Ben Gurion airport AG 588 Deir Istiya A 643 1.094 34 0.819 20.005 88 Givat Brener A 597 Salfit AG 710 1.188 31 0.818 20.001 57 Rishon Letzion G 562 Qiryat Anavim AG 703 1.25 46 0.817 20.002 34 Zerifin G 567 Jerusalem central A 530 0.935 48 0.815 20.0006 Miqwe Israel A 548 Salfit AG 710 1.295 31 0.814 0.002 36 Palmahim A 501 Jinsafut A 656 1.309 35 0.812 20.000 45 Yesodot G 517 Shoresh G 616 1.193 28 0.811 20.002 81

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TABLE 3. (Continued)

Plains gauge AG Rain plains Hill gauge AG Rain hill Ro Common years Correlation Slope Bat yam A 521 Salfit AG 704 1.35 25 0.81 20.0086 Horeshim A 636 Zova G 659 1.037 40 0.81 20.000 49 Gaash A 548 Deir Ghassana A 665 1.214 28 0.808 0.008 84 Nir Galim A 516 Biet Meir AG 615 1.192 48 0.808 20.003 31 Yad Hana A 627 Bitonia G 654 1.043 34 0.808 20.006 03 Horeshim A 649 Jerusalem airport A 609 0.939 30 0.807 20.004 65 Palmahim A 497 Deir Istiya A 627 1.262 34 0.806 0.000 66 Netanya A 579 Deir Istiya A 639 1.102 33 0.805 0.002 46 Miqwe Israel A 536 Jerusalem airport A 613 1.143 34 0.805 20.006 69 Shmariahu A 567 Sebastia A 643 1.133 27 0.804 0.0109 Gaash A 537 Bitonia G 654 1.218 34 0.803 0.006 48 Bat yam A 535 Sebastia A 641 1.198 23 0.798 0.008 76 Shmariahu A 544 Bitonia G 647 1.189 33 0.797 0.004 22 M. David G 532 Deir Ghassana A 635 1.194 16 0.796 0.000 66 Bet Dagan AG 538 Jerusalem central A 536 0.995 45 0.794 20.000 72 Tel Aviv Qiryat Shaul AG 582 Biet Meir AG 626 1.075 46 0.794 20.0022 Givat Brener A 581 Ramalla G 669 1.151 26 0.794 20.0071 M. David G 527 Deir Istiya A 610 1.157 21 0.792 20.001 77 Miqwe Israel A 538 Biet Meir AG 615 1.143 48 0.791 0.001 23 Nir Galim A 532 Jinsafut A 656 1.233 35 0.791 20.006 52 Nir Galim A 533 Jerusalem airport A 613 1.151 34 0.791 20.0104 Tel Aviv Qiryat Shaul AG 591 Salfit AG 710 1.201 31 0.789 0.000 19 Nahshon AG 544 Salfit AG 716 1.315 30 0.786 20.002 99 Shaalavim A 585 Salfit AG 710 1.213 31 0.783 0.000 92 Gaash A 520 Jerusalem airport A 613 1.178 34 0.782 20.000 03 Netanya A 585 Jinsafut A 657 1.123 34 0.782 0.004 21 Jaffa port A 524 Salfit AG 712 1.359 26 0.781 20.008 76 Ben Gurion airport AG 628 Sebastia A 645 1.027 28 0.777 0.004 47 Yesodot G 566 Salfit AG 710 1.253 31 0.777 20.0025 Bat yam A 527 Jerusalem airport A 596 1.132 32 0.775 20.005 61 Yad Hana A 636 Salfit AG 713 1.121 30 0.775 20.008 26 Hulda AG 566 Salfit AG 710 1.254 31 0.774 20.001 93 Tel Aviv airport A 512 Deir Istiya A 637 1.242 35 0.773 0.014 86 Hulda AG 556 Ramalla G 669 1.205 26 0.773 20.008 49 Nir Galim A 557 Sebastia A 645 1.158 28 0.77 0.002 76 Shmariahu A 550 Salfit AG 705 1.282 30 0.767 0.003 88 Miqwe Israel A 563 Sebastia A 645 1.146 28 0.767 0.009 53 M. David G 520 Jinsafut A 617 1.187 19 0.766 0.002 29 Yad Hana A 635 Jerusalem airport A 613 0.966 34 0.766 20.012 34 Gaash A 530 Biet Meir AG 615 1.159 47 0.765 0.006 49 Gaash A 540 Salfit AG 713 1.32 30 0.764 0.0057 Netanya A 604 Deir Ghassana A 668 1.106 27 0.764 0.004 14 Palmahim A 497 Jerusalem airport A 613 1.234 34 0.763 20.005 36 Bet Dagan AG 538 Biet Meir AG 617 1.147 45 0.763 20.002 71 Shaalavim A 563 Singil A 652 1.158 27 0.762 20.0016 Tel Aviv airport A 505 Jinsafut A 656 1.297 35 0.761 0.014 04 Eyal A 643 Jerusalem airport A 624 0.97 33 0.761 20.006 81 Eyal A 628 Jerusalem central A 537 0.855 45 0.76 0.001 77 Palmahim A 503 Salfit AG 707 1.406 30 0.759 0.000 62 Nir Galim A 521 Zova G 660 1.266 47 0.759 20.002 04 Miqwe Israel A 538 Qiryat Anavim AG 696 1.295 48 0.755 0.000 86 Tel Aviv Qiryat Shaul AG 582 Qiryat Anavim AG 709 1.217 46 0.753 20.002 73 Nir Galim A 516 Jerusalem central A 530 1.029 48 0.753 20.001 33 Netanya A 603 Sebastia A 654 1.084 26 0.752 0.007 07 Eyal A 628 Biet Meir AG 621 0.989 45 0.751 0.000 41 Bet Dagan AG 544 Zova G 663 1.219 44 0.75 20.001 08 Tel Aviv Qiryat Shaul AG 588 Jerusalem airport A 613 1.043 34 0.749 20.008 Nir Galim A 516 Qiryat Anavim AG 696 1.351 48 0.749 20.004 65 Tel Aviv Qiryat Shaul AG 582 Jerusalem central AG 542 0.93 46 0.748 20.000 65

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TABLE 3. (Continued)

Plains gauge AG Rain plains Hill gauge AG Rain hill Ro Common years Correlation Slope Miqwe Israel A 544 Zova G 660 1.214 47 0.748 0.002 66 Bet Dagan AG 563 Ramalla G 662 1.175 24 0.747 20.003 36 Nir Galim A 546 Salfit AG 710 1.299 31 0.747 20.004 26 Palmahim A 490 Biet Meir AG 610 1.246 47 0.746 0.001 71 Gaash A 556 Sebastia A 647 1.164 27 0.745 0.014 21 Ben Gurion airport AG 585 Jerusalem central A 537 0.917 47 0.744 20.000 33 Jaffa port A 526 Biet Meir AG 631 1.2 34 0.742 20.007 99 Jaffa port A 525 Jerusalem airport A 603 1.148 33 0.742 20.007 24 Zerifin G 521 Shoresh G 588 1.13 32 0.742 20.001 61 Gaash A 530 Qiryat Anavim AG 696 1.313 47 0.741 0.006 76 Shmariahu A 546 Jerusalem airport A 607 1.113 32 0.741 0.000 69 Bet Dagan AG 538 Qiryat Anavim AG 702 1.304 45 0.741 20.004 44 Tel Aviv Qiryat Shaul AG 590 Zova G 674 1.143 45 0.739 20.001 87 Yesodot G 556 Ramalla G 669 1.204 26 0.739 20.010 39 Yad Hana A 619 Jerusalem central A 531 0.859 47 0.737 20.0018 Nahsonim A 562 Ramalla G 660 1.176 25 0.737 20.004 44 Shmariahu A 543 Biet Meir AG 615 1.132 45 0.734 0.003 61 Tel Aviv airport A 482 Jerusalem airport A 613 1.272 34 0.734 0.003 95 Jaffa port A 526 Qiryat Anavim AG 717 1.363 34 0.73 20.009 63 Tel Aviv airport A 508 Salfit AG 710 1.396 31 0.73 0.014 62 Givat Brener A 518 Shoresh G 599 1.156 31 0.729 20.001 64 Tel Aviv airport A 522 Deir Ghassana A 666 1.274 29 0.728 0.017 36 Nahshon AG 534 Ramalla G 669 1.254 26 0.728 20.009 52 Miqwe Israel A 538 Jerusalem central A 530 0.986 48 0.727 0.002 49 Yad Hana A 619 Biet Meir AG 615 0.993 47 0.727 20.003 66 Tel Aviv airport A 501 Biet Meir AG 615 1.227 48 0.726 0.010 26 Eyal A 628 Zova G 660 1.051 45 0.726 0.001 02 Yad Hana A 619 Qiryat Anavim AG 696 1.125 47 0.725 20.004 31 Eyal A 628 Qiryat Anavim AG 705 1.122 45 0.724 0.000 27 Shmariahu A 543 Jerusalem central A 534 0.982 45 0.723 0.004 45 Palmahim A 513 Sebastia A 644 1.256 27 0.721 0.007 96 Ben Gurion airport AG 592 Zova G 668 1.129 46 0.716 20.000 86 Jaffa port A 526 Jerusalem central A 562 1.069 34 0.713 20.010 88 Zora G 511 Singil A 652 1.275 27 0.709 20.006 42 Shmariahu A 543 Qiryat Anavim AG 700 1.288 45 0.707 0.003 66 Ben Gurion airport AG 585 Biet Meir AG 622 1.062 47 0.705 20.002 28 Hulda AG 545 Singil A 652 1.196 27 0.705 20.005 46 Tel Aviv airport A 507 Bitonia G 653 1.288 35 0.701 0.012 58 Gaash A 530 Jerusalem central A 531 1.002 47 0.7 0.0068 Palmahim A 490 Qiryat Anavim AG 689 1.408 47 0.698 0.0016 Zerifin G 579 Singil A 652 1.127 27 0.698 20.0059 Netanya A 591 Bitonia G 652 1.104 33 0.697 0.004 92 Miqwe Israel A 545 Ramalla G 669 1.229 26 0.696 20.005 15 Tel Aviv airport A 501 Qiryat Anavim AG 696 1.39 48 0.695 0.010 99 Palmahim A 490 Jerusalem central A 530 1.082 47 0.694 0.002 55 Ben Gurion airport AG 585 Qiryat Anavim AG 704 1.203 47 0.694 20.002 98 Netanya A 585 Salfit AG 715 1.222 29 0.694 20.001 97 Givat Brener A 571 Singil A 652 1.141 27 0.694 20.004 Tel Aviv airport A 506 Singil A 652 1.289 27 0.693 0.014 71 Rishon Letzion G 575 Singil A 652 1.135 27 0.692 20.0061 M. David G 527 Salfit AG 666 1.262 21 0.692 0.002 77 Bat yam A 537 Biet Meir AG 622 1.159 35 0.691 20.003 44 Rishon Letzion G 520 Shoresh G 588 1.132 31 0.691 0.000 42 M. David G 520 Sebastia A 596 1.145 17 0.688 0.008 28 Yad Hana A 626 Zova G 661 1.056 46 0.686 20.002 77 Zerifin G 584 Ramalla G 669 1.146 26 0.685 20.009 62 Gaash A 537 Zova G 661 1.231 46 0.683 0.008 09 Nahsonim A 564 Singil A 644 1.142 26 0.683 20.002 43 Bat yam A 532 Ramalla G 635 1.194 21 0.682 20.000 75

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TABLE 3. (Continued)

Plains gauge AG Rain plains Hill gauge AG Rain hill Ro Common years Correlation Slope M. David G 531 Singil A 645 1.214 19 0.68 20.005 76 Shmariahu A 550 Zova G 659 1.198 44 0.677 0.004 71 Bat yam A 537 Qiryat Anavim AG 705 1.313 35 0.676 20.004 59 Eyal A 633 Ramalla G 669 1.057 26 0.673 20.003 26 Netanya A 569 Jerusalem airport A 613 1.076 34 0.67 20.004 87 Palmahim A 495 Zova G 656 1.324 46 0.669 0.003 14 Jaffa port A 534 Zova G 688 1.288 33 0.669 20.008 42 Miqwe Israel A 539 Singil A 652 1.209 27 0.669 0.000 37 Horeshim A 652 Ramalla G 656 1.006 21 0.667 20.004 76 Rishon Letzion G 579 Ramalla G 669 1.155 26 0.666 20.008 51 Tel Aviv Qiryat Shaul AG 571 Singil A 652 1.142 27 0.659 20.001 02 Tel Aviv airport A 501 Jerusalem central A 530 1.059 48 0.657 0.010 19 Tel Aviv airport A 508 Zova G 660 1.3 47 0.652 0.011 84 Bat yam A 537 Jerusalem central A 551 1.027 35 0.652 20.006 01 Horeshim A 672 Singil A 654 0.974 21 0.651 20.007 09 Nahsonim A 495 Shoresh G 588 1.187 30 0.651 20.000 93 Yesodot G 550 Singil A 652 1.186 27 0.649 20.007 33 Gaash A 534 Singil A 651 1.218 26 0.643 0.004 63 Bet Dagan AG 504 Shoresh G 588 1.167 32 0.635 0.000 17 Bat yam A 503 Singil A 603 1.198 21 0.63 0.012 77 Netanya A 575 Biet Meir AG 613 1.065 46 0.629 0.004 35 Horeshim A 579 Shoresh G 578 0.999 28 0.624 20.000 94 Gaash A 540 Ramalla G 664 1.229 25 0.621 0.001 47 Ben Gurion airport AG 609 Ramalla G 669 1.099 26 0.613 20.006 88 Netanya A 575 Qiryat Anavim AG 695 1.209 46 0.611 0.0041 Tel Aviv airport A 524 Sebastia A 645 1.232 28 0.61 0.020 65 Nir Galim A 466 Shoresh G 588 1.263 32 0.608 20.0024 Tel Aviv airport A 513 Ramalla G 669 1.304 26 0.605 0.007 26 Gaash A 498 Shoresh G 588 1.181 32 0.604 0.0074 Jaffa port A 522 Ramalla G 647 1.238 22 0.6 20.000 74 Bat yam A 546 Zova G 677 1.24 34 0.598 20.003 77 Netanya A 575 Jerusalem central A 531 0.923 46 0.598 0.004 63 Tel Aviv airport A 472 Shoresh G 588 1.246 32 0.593 0.011 18 Miqwe Israel A 495 Shoresh G 588 1.189 32 0.592 0.000 99 Tel Aviv Qiryat Shaul AG 589 Ramalla G 669 1.136 26 0.588 20.007 45 Nir Galim A 535 Ramalla G 669 1.251 26 0.588 20.012 48 Eyal A 620 Singil A 652 1.052 27 0.583 20.000 18 Tel Aviv Qiryat Shaul AG 552 Shoresh G 604 1.093 30 0.58 20.003 68 Palmahim A 505 Ramalla G 669 1.326 26 0.572 20.003 91 Palmahim A 458 Shoresh G 588 1.283 32 0.569 0.002 69 Bet Dagan AG 543 Singil A 651 1.198 25 0.566 20.008 86 Nahshon AG 526 Singil A 652 1.241 26 0.562 20.008 84 Palmahim A 489 Singil A 637 1.304 26 0.561 0.001 05 Netanya A 583 Zova G 658 1.129 45 0.56 0.005 41 Yad Hana A 620 Ramalla G 664 1.071 25 0.558 20.011 52 Ben Gurion airport AG 542 Shoresh G 588 1.084 32 0.553 20.001 47 Ben Gurion airport AG 596 Singil A 652 1.094 27 0.547 20.006 94 Shmariahu A 533 Singil A 644 1.208 26 0.546 0.002 99 Shmariahu A 512 Shoresh G 594 1.16 29 0.543 0.0049 Nir Galim A 521 Singil A 652 1.25 27 0.538 20.007 57 Jaffa por A 502 Singil A 617 1.23 22 0.533 0.013 53 Shmariahu A 551 Ramalla G 660 1.198 25 0.522 20.001 75 Yad Hana A 608 Singil A 651 1.072 26 0.512 20.011 21 Netanya A 592 Ramalla G 662 1.117 24 0.496 20.003 54 Netanya A 575 Singil G 651 1.133 25 0.465 20.002 27 Eyal A 591 Shoresh G 601 1.017 30 0.456 0.000 38 Yad Hana A 576 Shoresh G 588 1.021 32 0.441 20.002 44 Bat yam A 482 Shoresh G 586 1.217 24 0.437 20.007 79 Jaffa port A 493 Shoresh G 601 1.221 25 0.406 20.0072 Netanya A 541 Shoresh G 588 1.087 32 0.303 0.006 72

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TABLE 4. As in Table 3, but for northern Israel.

Plains gauge AG Rain plains Hill gauge AG Hill rain Ro Common years Correlation Slope Haifa biol. A 491 Harashim A 931 1.895 4 0.957 0.031 23 Haifa biol. A 638 Sumei A 980 1.538 8 0.939 0.017 58 Regba G 579 Yehiam A 802 1.384 52 0.925 0.0016 Akko AG 590 Yirka A 701 1.188 41 0.916 20.001 65 Regba G 602 Harashim A 947 1.574 23 0.905 20.001 51 Kfar Masaryk A 619 Yehiam A 822 1.327 46 0.904 0.000 44 Akko AG 602 Makhul A 875 1.453 35 0.904 0.001 39 K. Bialik A 629 Sumei A 955 1.518 8 0.902 20.015 88 Akko AG 598 Miilya AG 797 1.334 53 0.902 20.001 65 Gesher ha ziv G 653 Sumei A 917 1.405 17 0.899 20.005 65 Akko AG 620 Sumei A 889 1.434 29 0.899 20.001 11 Nahariya G 621 Peqiin A 864 1.391 28 0.896 20.000 87 Nahariya G 620 Yirka A 701 1.131 41 0.896 0.000 25 Regba G 591 Makhul A 872 1.476 34 0.896 20.006 55 Kfar Masaryk A 632 Makhul A 875 1.385 35 0.895 20.000 96 Nahariya G 644 Sumei A 889 1.38 29 0.893 20.001 54 Regba G 560 Yirka A 700 1.249 37 0.893 20.001 11 Akko AG 593 Yehiam A 800 1.348 55 0.893 0.004 48 Akko AG 612 Fassuta A 870 1.422 41 0.892 20.003 07 Rosh-Haniqra G 631 Sumei A 885 1.403 20 0.89 20.005 88 Akko AG 586 Peqiin A 864 1.475 28 0.89 0.000 01 Qiryat Atta G 586 Harashim A 916 1.563 11 0.888 20.004 78 Kfar Masaryk A 646 Sumei A 889 1.376 29 0.888 20.003 19 Kfar Masaryk A 606 Yirka A 708 1.168 32 0.886 20.004 44 Nahariya G 627 Yehiam A 800 1.275 55 0.884 0.004 18 Regba G 610 Sumei A 897 1.472 28 0.88 20.010 66 Kfar Masaryk A 621 Kennan AG 701 1.127 44 0.88 20.004 64 Kfar Masaryk A 621 Amirim AG 743 1.198 47 0.879 20.003 92 Gesher ha ziv G 618 Yirka A 708 1.146 38 0.878 0.001 44 Akko AG 604 Meron AG 924 1.53 54 0.878 20.003 71 Qiryat Atta G 615 Sumei A 900 1.463 17 0.877 20.010 75 Kfar Masaryk A 623 Miilya AG 807 1.295 44 0.877 20.006 11 K. Bialik A 583 Kennan AG 726 1.246 25 0.876 20.001 54 Kfar Masaryk A 636 Fassuta A 870 1.369 41 0.876 20.004 73 K. Bialik A 586 Fassuta A 875 1.492 18 0.875 20.01 Haifa port AG 554 Harashim A 947 1.709 23 0.875 20.003 74 Nahariya G 630 Miilya AG 797 1.266 53 0.874 20.001 37 K. Bialik A 589 Yirka A 716 1.215 27 0.873 0.001 29 K. Bialik A 582 Peqiin A 884 1.52 20 0.87 0.007 49 Nahariya G 631 Hurfeish AG 808 1.281 35 0.868 20.003 29 Haifa biol. A 625 Peqiin A 894 1.43 14 0.867 20.006 39 Kfar Masaryk A 591 Peqiin A 888 1.503 20 0.867 20.004 56 Akko AG 593 Kennan AG 704 1.186 52 0.862 20.003 57 Kfar Masaryk A 625 Harashim A 947 1.515 23 0.859 0.005 19 Qiryat Atta G 566 Hurfeish AG 817 1.444 24 0.858 20.003 59 Akko AG 597 Malkiyya A 629 1.054 55 0.858 20.003 61 Gesher ha ziv G 627 Yehiam A 795 1.269 42 0.857 0.004 84 Qiryat Atta G 597 Fassuta A 879 1.473 30 0.857 0.000 11 Regba G 556 Peqiin A 865 1.556 25 0.857 20.001 59 Gesher ha ziv G 626 Makhul A 872 1.393 25 0.855 0.003 91 Qiryat Atta G 568 Peqiin A 876 1.542 25 0.855 0.002 28 Regba G 581 Miilya AG 797 1.372 49 0.854 20.004 64 Qiryat Atta G 580 Yehiam A 780 1.345 43 0.851 0.002 32 Nahariya G 634 Meron AG 924 1.458 54 0.851 20.003 11 Gesher ha ziv G 633 Peqiin A 894 1.412 22 0.85 20.002 86 Gesher ha ziv G 637 Fassuta A 888 1.394 29 0.85 0.003 31 K. Bialik A 589 Miilya AG 815 1.385 27 0.849 0.001 89 K. Bialik A 589 Meron AG 960 1.63 27 0.849 0.000 02 Nahariya G 646 Fassuta A 870 1.346 41 0.849 20.001 46

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TABLE 4. (Continued)

Plains gauge AG Rain plains Hill gauge AG Hill rain Ro Common years Correlation Slope Kfar Masaryk A 626 Meron AG 931 1.486 46 0.849 20.008 84 Akko AG 594 Harashim A 947 1.595 23 0.849 0.008 12 K. Bialik A 587 Malkiyya A 671 1.142 26 0.848 0.003 68 Haifa port AG 567 Sumei A 889 1.569 29 0.847 20.008 49 Akko AG 596 Baram A 740 1.243 37 0.847 0.001 27 Qiryat Atta G 581 Miilya AG 801 1.38 44 0.846 20.0022 K. Bialik A 589 Yehiam A 779 1.323 27 0.845 0.005 13 K. Bialik A 596 Hurfeish AG 855 1.435 19 0.845 0.000 65 Gesher ha ziv G 627 Miilya AG 808 1.289 42 0.845 20.000 03 Akko AG 603 Yiftah A 561 0.929 54 0.842 20.001 46 Nahariya G 638 Makhul A 875 1.372 35 0.841 0.002 09 K. Galim A 594 Sumei A 908 1.53 26 0.84 20.008 32 Akko AG 591 Hurfeish AG 808 1.367 35 0.84 20.003 65 Rosh-Haniqra G 585 Yirka A 701 1.198 41 0.839 20.002 74 Gesher ha ziv G 633 Hurfeish AG 826 1.305 24 0.839 20.004 53 Qiryat Atta G 601 Makhul A 869 1.445 24 0.839 20.000 65 Regba G 598 Fassuta A 871 1.458 38 0.839 20.010 04 Nahariya G 635 Yiftah A 561 0.884 54 0.838 20.001 02 Gesher ha ziv G 626 Meron AG 937 1.498 41 0.837 20.003 92 Nahariya G 629 Kennan AG 704 1.119 52 0.837 20.002 51 Kfar Masaryk A 621 Hurfeish AG 816 1.315 27 0.835 20.007 48 Kfar Masaryk A 619 Baram A 776 1.254 28 0.835 20.004 54 Akko AG 608 Amirim AG 758 1.247 50 0.835 20.002 85 Ramat-Yohanan A 547 Yirka A 688 1.258 37 0.833 20.000 28 Nahariya G 641 Amirim AG 758 1.183 50 0.83 20.001 98 Regba G 580 Hurfeish AG 806 1.39 34 0.83 20.006 29 Regba G 580 Kennan AG 705 1.216 49 0.83 20.0061 Kfar Masaryk A 621 Malkiyya A 634 1.022 47 0.829 20.007 47 K. Bialik A 574 Makhul A 875 1.524 14 0.826 0.004 62 Regba G 585 Meron AG 928 1.586 50 0.825 20.007 57 Rosh-Haniqra G 595 Yehiam A 783 1.316 46 0.824 0.000 24 Rosh-Haniqra G 616 Fassuta A 864 1.404 33 0.824 20.002 31 Kfar Masaryk A 630 Yiftah A 570 0.904 45 0.824 20.004 65 Gesher ha ziv G 629 Kennan AG 719 1.142 38 0.823 20.001 85 Qiryat Atta G 579 Kennan AG 710 1.227 40 0.823 20.0055 K. Galim A 578 Harashim A 962 1.665 22 0.822 0.002 28 Rosh-Haniqra G 613 Makhul A 863 1.408 26 0.822 20.0017 Rosh-Haniqra G 597 Miilya AG 801 1.343 45 0.821 20.004 19 Akko AG 604 Yiron AG 763 1.264 54 0.82 20.003 Haifa biol. A 611 Hurfeish AG 841 1.376 15 0.819 20.001 27 Regba G 583 Baram A 744 1.276 33 0.819 20.002 14 Qiryat Atta G 591 Amirim AG 767 1.298 38 0.815 20.006 51 Rosh-Haniqra G 593 Peqiin A 870 1.467 27 0.814 20.005 51 Nahariya G 626 Malkiyya A 629 1.004 55 0.814 20.003 48 Haifa biol. A 595 Meron AG 950 1.597 25 0.812 0.002 37 Rosh-Haniqra G 597 Yiftah A 556 0.932 46 0.81 20.003 54 Ramat-Yohanan A 537 Peqiin A 845 1.574 23 0.81 20.002 03 Atlit A 507 Harashim A 919 1.813 15 0.807 20.018 56 Regba G 584 Yiftah A 560 0.958 51 0.807 20.003 44 Qiryat Atta G 584 Yiftah A 559 0.957 43 0.805 20.002 41 Qiryat Atta G 582 Meron AG 926 1.59 43 0.803 20.006 44 Qiryat Atta G 574 Yirka A 701 1.221 41 0.803 20.001 86 Nahariya G 632 Baram A 740 1.171 37 0.803 0.001 38 Haifa port AG 556 Makhul A 875 1.574 35 0.798 20.003 34 Gesher ha ziv G 602 Harashim A 921 1.53 12 0.797 20.041 09 Gesher ha ziv G 626 Malkiyya A 652 1.041 41 0.797 20.001 43 Gesher ha ziv G 627 Yiftah A 565 0.901 42 0.797 20.000 81 Kfar Masaryk A 626 Yiron AG 772 1.233 46 0.797 20.008 05 Nahariya G 634 Yiron AG 763 1.204 54 0.796 20.002 53

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TABLE 4. (Continued)

Plains gauge AG Rain plains Hill gauge AG Hill rain Ro Common years Correlation Slope Nahariya G 623 Harashim A 947 1.521 23 0.795 0.003 89 K. Bialik A 589 Yiron AG 800 1.359 27 0.794 0.002 99 Qiryat Atta G 579 Malkiyya A 645 1.114 43 0.794 20.003 48 Haifa port AG 543 Yehiam A 804 1.481 52 0.793 0.003 17 Haifa port AG 545 Kennan AG 705 1.293 50 0.791 20.005 01 Haifa biol. A 595 Yirka A 720 1.21 25 0.79 0.008 17 K. Bialik A 602 Amirim AG 797 1.324 24 0.788 20.003 45 Gesher ha ziv G 640 Amirim AG 776 1.213 37 0.788 20.002 39 Qiryat Atta G 582 Yiron AG 773 1.328 43 0.788 20.0024 K. Bialik A 595 Yiftah A 588 0.988 26 0.786 0.003 27 Akko AG 591 Rihaniya A 687 1.162 38 0.786 20.004 72 Atlit A 543 Sumei A 904 1.664 20 0.785 20.009 09 Rosh-Haniqra G 589 Harashim A 911 1.548 14 0.784 20.0172 Regba G 592 Amirim AG 762 1.288 47 0.784 20.006 91 Rosh-Haniqra G 597 Malkiyya A 636 1.065 46 0.781 20.0052 Rosh-Haniqra G 596 Meron AG 919 1.541 46 0.78 20.008 63 Haifa port AG 547 Amirim AG 754 1.379 49 0.779 20.006 48 K. Bialik A 582 Baram A 743 1.276 24 0.778 0.006 46 Haifa port AG 533 Yirka A 704 1.321 39 0.778 20.000 13 Haifa biol. A 590 Yehiam A 787 1.334 24 0.778 0.010 91 Ramat-Yohanan A 563 Yehiam A 801 1.424 51 0.778 0.0031 Gesher ha ziv G 635 Baram A 741 1.166 27 0.777 0.002 97 Regba G 580 Malkiyya A 630 1.086 51 0.777 20.006 54 Haifa port AG 547 Miilya AG 800 1.463 51 0.773 20.003 81 Rosh-Haniqra G 586 Hurfeish AG 799 1.363 28 0.77 20.010 11 Haifa biol. A 603 Amirim AG 765 1.269 24 0.768 0.0118 Rosh-Haniqra G 594 Kennan AG 704 1.186 43 0.768 20.007 44 Haifa biol. A 590 Rihaniya A 698 1.183 24 0.766 20.003 98 K. Galim A 575 Yehiam A 825 1.434 46 0.766 0.002 54 Gesher ha ziv G 626 Yiron AG 782 1.251 41 0.764 20.001 39 Haifa biol. A 591 Kennan AG 720 1.219 24 0.762 0.002 74 Regba G 585 Yiron AG 767 1.311 50 0.762 20.006 32 Haifa port AG 558 Fassuta AG 870 1.559 41 0.761 20.006 85 Nahariya G 624 Rihaniya A 687 1.1 38 0.76 20.003 61 Haifa port AG 550 Meron AG 924 1.68 52 0.757 20.006 17 Haifa biol. A 595 Malkiyya A 669.5 1.126 25 0.754 0.007 47 Ramat-Yohanan A 569 Amirim AG 743.2 1.306 46 0.753 20.0027 Atlit A 522 Yehiam A 793.5 1.519 44 0.752 0.0086 Rosh-Haniqra G 593 Baram A 726.5 1.225 31 0.751 20.001 65 Ramat-Yohanan A 559 Kennan AG 691.8 1.237 48 0.75 20.003 84 Haifa port AG 532 Peqiin A 875.7 1.645 25 0.743 20.004 34 Gesher ha ziv G 621 Rihaniya A 698.4 1.125 36 0.743 20.003 04 Rosh-Haniqra G 609 Amirim AG 762.1 1.252 41 0.74 20.005 76 Regba G 564 Rihaniya A 693 1.228 35 0.738 20.0052 Haifa biol. A 595 Yiftah A 573 0.963 25 0.737 0.006 55 K. Galim A 577 Kennan AG 708.5 1.228 44 0.735 20.003 33 K. Bialik A 586 Rihaniya A 714.6 1.22 26 0.734 20.000 53 K. Galim A 571 Amirim AG 761.2 1.333 44 0.734 20.005 94 Haifa port AG 551 Hurfeish A 812.5 1.475 33 0.732 20.005 69 Rosh-Haniqra G 596 Yiron AG 761.1 1.277 46 0.731 20.005 85 Ramat-Yohanan A 583 Sumei A 889 1.526 29 0.731 20.004 91 Atlit A 522 Miilya AG 801.4 1.534 44 0.728 0.002 62 Haifa biol. A 615 Baram A 753 1.224 18 0.727 0.001 93 Atlit A 533 Fassuta A 894.5 1.677 31 0.725 0.003 89 Ramat-Yohanan A 564 Miilya AG 787.9 1.396 49 0.721 20.0025 Qiryat Atta G 575 Baram A 728.3 1.268 30 0.721 0.002 68 Haifa port AG 552 Yiftah A 565.4 1.024 52 0.718 20.003 24 Haifa port AG 545 Malkiyya A 633.8 1.164 53 0.717 20.006 46 Rosh-Haniqra G 586 Rihaniya A 686.7 1.172 38 0.717 20.006 47

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TABLE 4. (Continued)

Plains gauge AG Rain plains Hill gauge AG Hill rain Ro Common years Correlation Slope Ramat-Yohanan A 562 Malkiyya A 624.7 1.112 52 0.717 20.004 82 Ramat-Yohanan A 568 Meron AG 911.2 1.606 50 0.716 20.004 53 Atlit A 530 Makhul A 870.8 1.643 28 0.715 0.004 81 Haifa biol. A 595 Yiron AG 803.8 1.351 25 0.714 0.011 09 Ramat-Yohanan A 570 Yiftah A 556.8 0.977 50 0.706 20.001 85 Haifa biol. A 595 Miilya AG 815.2 1.371 25 0.705 0.009 59 Haifa biol. A 608 Fassuta A 896.9 1.475 21 0.702 0.024 34 Ramat-Yohanan A 580 Makhul A 874.8 1.509 35 0.702 0.000 97 K. Galim A 578 Miilya AG 805.8 1.395 44 0.701 20.002 96 Atlit A 521 Kennan AG 708.7 1.36 42 0.699 20.001 08 Atlit A 527 Meron AG 927.7 1.759 42 0.696 20.001 14 K. Galim A 578 Meron AG 936.3 1.619 45 0.693 20.006 22 Atlit A 525 Amirim AG 770.4 1.469 38 0.689 20.0049 Ramat-Yohanan A 580 Fassuta A 869.1 1.5 40 0.689 20.005 06 K. Galim A 585 Makhul A 886.4 1.517 34 0.688 20.001 42 K. Galim A 583 Hurfeish AG 808.9 1.388 30 0.687 20.0034 Atlit A 522 Malkiyya A 634.8 1.216 43 0.687 20.000 96 Atlit A 531 Hurfeish AG 828.7 1.56 25 0.685 0.000 14 Haifa port AG 550 Yiron A 768.5 1.397 52 0.684 20.005 99 K. Galim A 585 Fassuta A 880.1 1.504 37 0.681 20.0065 Atlit A 527 Yiftah A 561.7 1.066 43 0.68 0.000 79 Ramat-Yohanan A 568 Yiron AG 755.5 1.331 50 0.68 20.004 13 Kfar Masaryk A 612 Rihaniya A 714.3 1.168 30 0.671 20.020 65 K. Galim A 551 Peqiin A 874.8 1.589 19 0.668 20.000 31 Ramat-Yohanan A 553 Rihaniya A 684.9 1.24 36 0.668 20.007 06 Haifa port AG 552 Baram A 750.5 1.36 35 0.665 20.002 46 K. Galim A 572 Malkiyya A 635.7 1.111 46 0.665 20.006 03 Atlit A 530 Peqiin A 874.7 1.65 21 0.662 0.0028 Atlit A 516 Yirka A 704.1 1.365 37 0.655 0.003 58 K. Galim A 579 Yiftah A 568.2 0.982 46 0.653 20.002 63 Qiryat Atta G 576 Rihaniya A 686.7 1.192 38 0.653 20.005 74 K. Galim A 564 Yirka A 710.2 1.258 32 0.65 0.001 45 K. Galim A 578 Yiron AG 771.8 1.335 45 0.629 20.005 38 Atlit A 527 Yiron AG 775.9 1.471 42 0.622 0.000 33 Ramat-Yohanan A 564 Hurfeish AG 793.2 1.407 32 0.61 20.003 68 Haifa biol. A 567 Makhul A 872.9 1.54 18 0.6 0.025 91 Ramat-Yohanan A 575 Harashim A 947 1.646 23 0.59 0.010 99 K. Galim A 578 Baram A 755 1.307 29 0.569 20.000 73 Atlit A 530 Baram A 729.4 1.377 27 0.566 0.007 48 Ramat-Yohanan A 564 Baram A 736.4 1.306 33 0.557 20.000 17 Haifa port AG 532 Rihaniya A 694.4 1.305 36 0.53 20.007 87 Atlit A 521 Rihaniya A 681.4 1.309 35 0.527 0.000 25 K. Galim A 570 Rihaniya A 701.4 1.232 31 0.409 20.007 87 alone (i.e., for the class of D , 10 km in Fig. 4b). This are the same as specified in the legend of Fig. 4 of trend (Fig. 5a) is half of its magnitude when Ro is com- AHL08. All of the possible pairs between plains and puted with respect to the rain gauges at D . 20 km from hill gauges are shown in Table 4. As for central Israel, the coastline (Fig. 5c). we selected also for the north only pairs with measure- ments of the same years for at least 30 yr. According to Fig. 6a more than 80% of the pairs had negative trends 3. Results for northern Israel of Ro. a. Is the probability for trends in Ro over the upper random? b. The meteorological significance of distance from the coastline The method that was applied to central Israel was applied also to the rain gauge pairs that were used by According to AHL08, a major issue in central Israel was AHL08 and GR05 for northern Israel. The rain gauges the possible changes in the plains rainfall with distance

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FIG. 2. As in Fig. 1, but for all pairs of rain gauges used by AHL08 and GR04 for their calculations of trends in Ro in central FIG. 1. The cumulative probabilities of trends in Ro exceeding Israel. The individual values are provided in Table 3. Note the the value in the abscissa, for all pairs of Judea and Samaria rain decreasing random scatter and focusing on negative values for gauges with the plains gauges, for the gauges used to compose greater R and the longer measuring period. Fig. 2 of AHL08. The gauges are classified according to three groups according to their correlation coefficient R, as indicated in the legend. Shown are the results for pairs of gauges with co- measured rainfall for at least (a) 20 and (b) 30 yr. were at D , 10 km from the coastline. Instead, the short inland from the coastline, due to possible anthropogenic- distance of part of the hill rain gauges to the coastline induced changes in the convective clouds that moved (five pairs were at D , 20 km) presented another issue inland from the sea. This could not be an issue in of convective clouds that formed over the sea contrib- northern Israel, because all of the plains rain gauges uting significantly to the hill rainfall. This was not as

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FIG. 3. The trend of Ro for the Judean and Samaria hills, based on the pairs of rain gauges that had correlation of R . 0.90 and at least 30 yr of paired rainfall data, from Table 3. The inset P value is the probability that the slope of the regression line is not different from zero. The decreasing linear trend is statistically significant at P 5 0.001 using the Kendall nonparametric two-tail test.

much an issue for the hill gauges in central Israel, be- cause D was larger than 30 km for all of them. The distance of the hill gauges from the coastline matters because the convective clouds of the winter rainstorms in Israel are energized by the heat flux from the sea surface to the colder air mass arriving from Europe (Shay-El and Alpert 1991). The convective clouds mature when they move inland and lose their energy source. This is evident by the rain intensities decreasing from the coastline inland, along a distance of about 30 km eastward from the coastline (Sharon and Kutiel 1986). The frequency of thunderstorms also be- haves similarly (Yair and Levin 1994). Rosenfeld (1986) showed that the radar-detected echo-top heights aver- FIG. 4. As in Fig. 1, but for the data from Table 3 that passed the criteria of at least 30 yr and (a) R $ 0.9 or (b) R $ 0.85. age, in Israel, about 5 km MSL. The top heights de- The rain gauge pairs are further classified according to the dis- crease from 5.4 km over the sea by about 400 m when tance D of the plains rain gauge eastward from the coastline, in moving from sea to the coastal plains and decrease by an kilometers. additional 400 m over the hills. Such deep convective clouds have smaller susceptibility to aerosol effects on rainfall amounts than do the shallower orographic tive clouds whose response to changing meteorological clouds (Phillips et al. 2002) that form when the air as- and aerosol conditions is different from that of the oro- cends over the hills inland. graphic clouds, for which the rainfall is more significant The western parts of the hilly areas, which are close to over the farther inland hills. Therefore, the stratification the sea, are likely rained over by the maturing convec- of the effects by distance from coastline is important for

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FIG. 5. The trend of Ro for the Judean and Samaria hills, based on the pairs of rain gauges that had correlation of R $ 0.85 and at least 30 yr of paired rainfall data (the same as used for Fig. 4b). The pairs are partitioned by the distance of the plains rain gauge eastward from the coastline: (a) D , 10 km, (b) 10 # D , 20 km, and (c) D $ 20 km. The Kendall two-tail nonparametric P value for (c) is 0.002.

gaining insights to the possible causes of the indicated The results show a slight, statistically insignificant in- trends. crease in Ro for the hills at D # 15 km from the sea, a similar decreasing trend in Ro for 15 , D # 30, and a significant decreasing trend for D . 30 km. GR05 c. The dependence of trends on distance from showed that farther east of the , in the the coastline northern Valley where the precipitation is not There were only four pairs of gauges in Table 3 with orographic, Ro no longer decreases. R . 0.90 that had a record of at least 30 yr. Relaxing R to 0.85 still left too-few pairs for additional classifica- tion by distance of the hill gauge eastward from the 4. Discussion and conclusions coastline. According to Fig. 6b, the number of pairs that survived the selection criteria was 15 for D # 15, 7 for Reanalysis of the trends in Ro using an objective 15 , D # 30, and 6 for D . 30. Relaxing the threshold selection method of the pairs of rain gauges showed further to R . 0.80 allowed 22, 13, and 29 pairs to enter that the probabilities of trends in Ro are not random, in the three D classes, respectively. Comparing Figs. 6b contrast to the assertion in Fig. 2 of AHL08, but rather and 6c shows that the relaxation of R was at the expense are clearly negative over the hills in both central and of increasing scatter of the probabilities of Ro. Using northern Israel. A complicating factor is the weak trend either threshold did not change the essence of the re- of increased rainfall some distance from the sea inland, sults, and therefore we used the lower threshold for regardless of the topography. However, beyond the making them representative for the larger number of range of that effect, at D . 30 km inland, Ro decreased gauges. with respect to the plains rain gauges, in both cen- The pairs of rain gauges were combined for the three tral and northern Israel. The trends in the orographic D intervals, as was done for the center, shown in Fig. 7. precipitation over the hills at D , 30 km from the

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FIG. 6. As in Fig. 1, but for the proba- bilities of trends in Ro in northern Israel, based on the data from Table 4 for gauge pairs that had at least 30 yr of coincident rainfall data. (a) Pairs classified by their correlation coefficients R; (b) all pairs with R . 0.85 classified according to the distance of the hill gauges eastward from the coast- line. (c) As in (b), but for R . 0.80.

coastline are partially masked by the convective clouds that are typical Israeli winter storms decreases their that move inland from the sea. At greater distance, the rainfall amounts and delays their peak intensity by decreasing trend in Ro is evident even when comparing about 20 min. According to their Fig. 4, this redistrib- with the coastal rain gauges (D , 10 km from the shore utes the rainfall and causes a large enhancement of the line), especially in the north. The strong decreasing rainfall a distance of about 20 min downwind. Khain trend of Ro at the eastern half of the upper Galilee et al. (1999) simulated the effects of added CCN aero- is tied to the hills and disappears farther east in the sols on clouds near the coastline of Israel. Their simu- Jordan Valley. lations showed that the main cause of the convection is AHL08 ascribed the trend of increased rainfall some the contrast between the cold air and the warm sea- distance from the sea inland to the hypothesis of an water. They showed that the added aerosols delayed urban heat island effect. However, there is greater the rainfall and redistributed it from the sea to a few support for the hypothesis that a trend of increasing tens of kilometers inland. aerosols that are imported from eastern Europe with A likely cause of the decreasing trend of orographic the rain-bearing air mass has caused the convective precipitation in Israel remains the aerosols, as specu- clouds over sea to delay their precipitation and redis- lated by GR04 and GR05. However, the possible im- tribute it farther eastward of the coastline. Teller and pacts of other meteorological factors, such as changes Levin (2006), based on their cloud simulations, showed in the instability profiles, cannot be excluded. This im- that adding cloud condensation nuclei (CCN) to clouds portant question should be investigated further.

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FIG. 7. The trend of Ro for the Galilee hills, based on the pairs of rain gauges that had correlation of R $ 0.80 and at least 30 yr of paired rainfall data (the same as used for Fig. 6c). The pairs are partitioned by the distance of the hill rain gauge eastward from the coastline: (a) D # 15 km, (b) 15 , D # 30 km, and (c) D . 30 km. The Kendall two- tail nonparametric P value for (c) is 0.006.

Acknowledgments. This study was partially funded by Phillips, V. T. J., T. W. Choularton, and A. M. Blyth, 2002: CIRCE (Climate Change and Impact Research: The The influence of aerosol concentrations on the glaciation and Mediterranean Environment) of the Commission of the precipitation of a cumulus cloud. Quart. J. Roy. Meteor. Soc., 128, 951–971. European Union (http://www.circeproject.eu/). Rosenfeld, D., 1986: The dynamic characteristics of cumuliform clouds and cloud systems and their effect on the rainfall pre- REFERENCES cipitated by them. Ph.D. thesis, The Hebrew University of Jerusalem, 142 pp. Alpert, P., N. Halfon, and Z. Levin, 2008: Does air pollution really Sharon, D., and H. Kutiel, 1986: The distribution of rainfall in- suppress precipitation in Israel? J. Appl. Meteor. Climatol., 47, tensity in Israel, its regional and seasonal variations and its 933–943. climatological evaluation. Int. J. Climatol., 6, 277–291. Givati, A., and D. Rosenfeld, 2004: Quantifying precipitation Shay-El, Y., and P. Alpert, 1991: A diagnostic study of winter di- suppression due to air pollution. J. Appl. Meteor., 43, 1038– abatic heating in the Mediterranean in relation to cyclones. 1056. Quart. J. Roy. Meteor. Soc., 117, 715–747. ——, and ——, 2005: Separation between cloud-seeding and air- Teller, A., and Z. Levin, 2006: The effects of aerosols on pre- pollution effects. J. Appl. Meteor., 44, 1298–1315. cipitation and dimensions of subtropical clouds; a sensitivity Khain, A. P., A. Pokrovsky, and I. Sednev, 1999: Effects of study using a numerical cloud model. Atmos. Chem. Phys., 6, cloud-aerosol interaction on cloud microphysics, precipitation 67–80. formation and size distribution of atmospheric aerosol parti- Yair, Y., and Z. Levin, 1994: Lightning disintegration in clouds cles: Numerical experiments with a spectral microphysics cloud and into the ground in thunderstorms in Israel. Meteor. Isr., model. Atmos. Res., 52, 195–220. 3, 20–28.

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