Literary Fiction Or Ancient Astronomical and Meteorological Observations in the Work of Maria Valtorta?

religions

Article Literary Fiction or Ancient Astronomical and Meteorological Observations in the Work of Maria Valtorta?

Emilio Matricciani 1,* and Liberato De Caro 2

1 Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano, 20133 Millan, Italy 2 Istituto di Cristallograﬁa, Consiglio Nazionale delle Ricerche, 70126 Bari, Italy; [email protected] * Correspondence: [email protected]; Tel.: +39-347-7604202

Academic Editor: Christine A. James Received: 11 April 2017; Accepted: 6 June 2017; Published: 9 June 2017

Abstract: In The Gospel as revealed to me, Maria Valtorta reports a lot of information on the Holy Land at the time of Jesus: historical, archaeological, astronomical, geographical, meteorological. She states she has written what seen “in vision”. By a detailed astronomical analysis of explicit and implicit calendar information reported while she narrates detailed episodes concerning the three years of Jesus’ public life—possible because of many references to lunar phases, constellations, planets visible in the night sky in her writings—it is ascertained that every event described implies a precise date—day, month, year—without being explicitly reported by her. For example, Jesus’ cruciﬁxion should have occurred on Friday April 23 of the year 34, a date proposed by Isaac Newton. She has also recorded the occurrence of rain so that the number of rainy days reported can be compared to the current meteorological data, supposing random observations and no important changes in rainfall daily frequency in the last 2000 years, the latter issue discussed in the paper. Unexpectedly, both the annual and monthly averages of rainy days deduced from the data available from the Israel Meteorological Service and similar averages deduced from her writings agree very well.

Keywords: astronomy; Gospel; Holy Land; Jesus Christ; meteorology; rain; Roman Palestine; Valtorta Maria; mystic visions

1. An Unheard-Of Literary Work The Gospel as revealed to me (L’Evangelo come mi è stato rivelato, Valtorta 2001) is the main literary work by Maria Valtorta (1897–1961), in the following referred to as the EMV, in which she reports a very detailed life of Jesus of Nazareth. She wrote it straight off on common notebooks, while bedridden for serious health problems, mainly in the years between 1943 and 1947. To give an idea of its extension, the longest novel ever written—À la recherche du temps perdu by Marcel Proust—contains an estimated 9,609,000 characters (including spaces), whereas the EMV, printed in ten books, contains about 10,800,000 characters. The EMV describes events and characters that animate the story of Jesus’ life narrated in the Gospels, but enriched with detailed descriptions of landscapes, costumes, uses, roads, towns with their buildings (including the Temple in Jerusalem) and streets, rivers, lakes, hills, valleys, plantations, climate, even the night sky with its constellations, stars and planets. The richness of narrative elements in the EMV has allowed to pursue many studies on it because Maria Valtorta states that it is not due to her fantasy, but that she has written down everything she watched “in vision”, or was dictated to her by Jesus, as if she was really present 2000 years ago when the events narrated in the Gospels occurred. In her writings, for example, there are many narrative elements that convey chronological information like days of worship rest, references to major Jewish holy days, market days, seasons,

Religions 2017, 8, 110; doi:10.3390/rel8060110 www.mdpi.com/journal/religions Religions 2017, 8, 110 2 of 23 months related both to the Jewish lunar-solar and Julian calendars used 2000 years ago in the Holy Land under the Roman empire. No date, however, is stated explicitly with respect to the Julian calendar, except for a single case (EMV 461.16).1 However, even in this case, the year is not indicated. We find also many references to the moon in the night sky (moon phases), to planets, constellations, weather conditions, all narrative elements that enrich the events of Jesus’ life described, so detailed that they seem to be real data, as if they were recorded by a careful observer present at the scene. The astronomical and meteorological data contained in Valtorta’s work are so accurate that they have allowed pursuing several scientific investigations on them. The most obvious hypothesis is that all calendar and astronomical data contained in the EMV are the result of the Maria Valtorta’s narrative fantasy. If this is the case, any analysis of these data would not lead to a coherent chronological framework associated with the described events concerning Jesus’ life. However, in principle, there is also another possibility, a conjecture: all the astronomical and calendar data contained in the EMV are related to a well-defined chronology and, consequently, their accurate analysis would allow associating a precise date to each event of Jesus’ life described in Valtorta’s work, according to the Julian calendar. The latter result, in turn, if it were confirmed, would imply the need to explain the origin of this chronological information embedded in Valtorta’s work. Indeed, it cannot be justified by her knowledge, skills and awareness. Astronomical data, in fact, lead to establish precise dates, through complex mathematical calculations, and these exclude that Maria Valtorta was aware of the chronological information underlying her writings because we know, for certain, from her biography, that she had neither astronomical education nor the high scientific expertise needed to perform these calculations. Indeed, she was definitely hopeless at mathematics and calculations.2 Furthermore, she had never been in the Holy Land (Pisani 2010). Moreover, during the Second World War there were neither softwares nor computers to perform complex astronomical calculations. Maria Valtorta had very few books, which can be consulted visiting her house in Viareggio (Tuscany, Italy). Neither books nor tables or other astronomical material were available in her house during the Second World War, when she wrote her manuscripts as, moreover, confirmed by eyewitnesses when she was alive. In addition, of course, it is not scientifically possible to retrieve detailed chronological information belonging to a remote past by means of mystic visions. Therefore, it would seem quite obvious to expect that the intersection of many calendar and astronomical information in the long narrative of Jesus' life reported in the EMV should lead, inevitably, to many chronological contradictions. Since the 1990s the verification of this point was at the center of scientific studies on her literary work (Aulagnier 1994; Van Zandt 1994; Lavère 2012, 2014; De Caro 2014, 2015). In addition, the recent detailed analysis of her writings has demonstrated, surprisingly, that every event narrated underlies a precise date, without any contradiction. To give an idea of what has emerged from these studies, in the present paper we provide first a short example of the research work on the EMV based on the analysis of astronomical and chronological data, referring the reader to the cited bibliography for more exhaustive results (De Caro 2014, 2015). Secondly, we analyze Maria Valtorta’s literary work according to meteorology to verify the statistical plausibility of her descriptions about rainfall days.

2. From the EMV Astronomical Data the Determination of Jesus’ Cruciﬁxion Date The Jewish calendar is lunar-solar and even after thousands of years it can be reconstructed thanks to Astronomy, because of the periodicity of the motion of the Moon around the Earth and

1 In the quotations of the EMV the first number indicates the chapter, the second number the subdivision of the chapter, both established by the curator of the literary work. 2 In her biography Maria Valtorta (Valtorta 1969) writes that mathematics was her “materia paurosa” (frightful subject), p. 74, and moreover, at p. 84, “ ... la mia capacità matematica si era arenata davanti alle frazioni...Come un mulo caparbio il mio cervello si era rifiutato di proseguire nel calcolo. Non capivo nulla: le lezioni di aritmetica, geometria, computisteria erano un supplizio sterile.” ( ... my mathematical ability stopped at fractions ... As a stubborn mule my brain refused to go on in the calculations. I did not understand anything: arithmetic, geometry, book-keeping were sterile tortures). Religions 2017, 8, 110 3 of 23 of the latter around the Sun. Isaac Newton was the first who introduced the modern approach to date the crucifixion of Jesus by calculating when the crescent of the new moon was first visible from Jerusalem (Pratt 1991). He obtained Friday, April 23 of the year 34, corresponding to the 14 of Nisan of the luni-solar calendar, that is the Easter Eve. This result was published in a work after his death, in 1733 (Newton 1733; Pratt 1991). Recent studies confirm the possible historical accuracy of Newton’s crucifixion dating (De Caro 2017). Surprisingly, as we will see in the following, also the EMV data, that can be submitted to astronomical and calendar analysis, lead to the same crucifixion dating. Indeed, a detailed analysis of the explicit calendar information contained in the EMV—as references to the days of worship rest (Saturdays)—and implicit information—as references to the lunar phases, constellations, planets visible in the night sky—has given, unexpectedly, a coherent chronological framework. To every event narrated in Maria Valtorta’s literary work we can associate a specific date, determined by the intersection of many narrative elements carrying chronological constraints. This result could imply that the astronomical and calendar information contained in the EMV cannot be the result of her fantasy. It is outside the scope of this paper to answer the question of how this is possible and to check in detail how to rebuild the aforementioned chronological framework. For the latter point, see the previously cited references (De Caro 2014, 2015). To give an idea of how binding is the calendar information reported by Maria Valtorta, although in all her writings no date is ever specified, we show next how it is possible to determine univocally the date of Jesus’ crucifixion from the EMV. Valtorta’s narration of Jesus’ life explicitly states that in the year before his death, the Easter Eve—14 of Nisan of the lunar-solar calendar—was a Friday (EMV 372–375) and that Easter fell on the Sabbath (EMV 378.3). The crucifixion is also placed on a Friday, Easter Eve, according to the chronology of the events of Jesus’ death described in John’s Gospel, with the additional constraint that in both years the feast fell in April (EMV 376.1, 576.1). Moreover, also the penultimate Easter of Jesus before his death is placed in April (EMV 195.3), without indicating the day of the week. These data are extremely binding to determine the possible dates of the Julian calendar associated with these Jewish holy days. Indeed, the lunar-solar calendar year is made of 12 lunar months of 354 days, about 11 days shorter than the solar year. For this reason, about every 3 years the Jewish calendar requires 13 lunar months leading to embolismic years. In this way the calendar can be realigned with the seasons. The modern Jewish calendar has already fixed the sequence of years consisting of 13 months, but in the first century was not so, and years with 13 months were officially proclaimed by the Sanhedrin when necessary. Because of the latitude of the Holy Land and the resulting mild weather, the spring equinox, which defines astronomically the end of winter, was usually a sufficient date to ensure adequate growth of the lambs to be sacrificed for Easter, and the presence of the first ears of barley, or ripe wheat, to be offered during the liturgy of the Unleavened Bread on the 16th of Nisan. When that did not happen, because of a too harsh winter, even though it was already a date after the spring equinox, a thirteenth month was inserted to postpone Easter by 29–30 days. We do not know which years of the first century were embolismic, but Astronomy allows us to determine them, at least in terms of plausibility. In the modern version of the Jewish calendar, the beginning of the lunar months of about 29.5 days is today pre-determined according to well defined rules. Two thousand years ago, instead, a lunar month began only after direct observation of the first crescent moon at sunset, after the conjunction of the Moon with the Sun (new moon). However, by observing the sky with naked eyes it is not always possible to verify that the moon is in the crescent phase already in the first day after the conjunction and, consequently, some months were of 29 days, others of 30, never of 31 or 28, by general convention. Experience shows, in fact, that observing the sky with naked eyes, it is very difficult to see the moon in the twilight of sunset if the fraction of the lunar disk illuminated by the sun is less than 2%. This missed observation would have caused a delay of 1 day to the start of a lunar month. Also adverse weather conditions could have delayed the start of a lunar month of 1 day because, in the first day after conjunction with the Sun, the very thin crescent moon is visible in the sky only for about an hour after sunset. Religions 2017, 8, 110 4 of 23

By means of specialized software3 it is now possible to determine the time of Moon rising and calculate with sufficient accuracy the percentage of its disk illuminated by the Sun, as it was visible from Jerusalem 2000 years ago. We can therefore evaluate when lunar months started relative to the Julian calendar used in the first century AD in the Roman Empire. For example, we can reconstruct the dates of the main Jewish pilgrimage holy days, such as Easter and Tabernacles. The beginning of these holy days started at the sunset of the day 14 of the first and seventh lunar month, respectively, when started the new day, the 15th of the month, within a delay of about 24–36 h relative to the actual full moon, also caused by possible adverse weather conditions which could have delayed the beginning of a lunar month of one day. For this reason, any reconstruction of lunar months of the Jewish calendar during the Roman period has to be considered always affected by an unavoidable indetermination of 1 day. After these general remarks, it is worth noting that the occurrence that Easter eve falls on the same day of the week in two consecutive years, as it can be evinced from Valtorta’s writings, represents a strong calendar constraint. In fact, because a lunar month is made of about 29.5 days, 12 lunar months amount to 354 days with a rest of few hours. However, 354 is not an integer multiple of 7, there is a rest of 4. Therefore, from this straight calculation, it is clear that after 12 lunar months Easter cannot fall on the same day of the week of the year before. Conversely, 13 lunar months amount to 384 days with a rest of few hours. Also 384 is not divisible by 7 because it gives the rest 1. However, if there was a delay of 1 day in deciding the start of Nisan, possible due to the flexibility with which in the first century AD the start of a month was proclaimed, we could find that, at the end of an embolismic year, Easter would have occurred on the same day of the week of the year before. In other words, if these two conditions were both at work-embolismic year and delay of 1 day in the start of Nisan-, two consecutive Easters could have fallen on the same day of the week. By analyzing the possible dates of Easter in the years in which Pontius Pilate was in Judea (26–36 AD), it is possible to verify that only in the years 33 and 34 the 14 of Nisan (Easter Eve) was a Friday of April, according to Maria Valtorta’s writings. There are no other possibilities, as it can be deduced from the most important astronomical studies on Jesus’ crucifixion (Fotheringham 1934; Schafer 1990; Finegan 1998; Humphreys and Waddington 1992; Bond 2013). The results of the analysis are summarized in Table1. In gray there have been shown days that fall on Saturday and, graphically, also the lunar phases. From Table1 it is clear that only in the years 33 and 34 two consecutive Easters could have fallen on Saturday, highlighted by two gray boxes in the same row, and both in April, as required by the EMV, if it is assumed that the year 34 was embolismic and its Nisan started with a delay of 1 day. If year 34 was embolismic also the year 31, most likely, was of 13 lunar months. With this calendar reconstruction, the Easter eve in the years 33 and 34 was Friday, April 3 for year 33 and April 23 for year 34. It is possible to verify that even forcing all Easters to fall in April also for years 26–28, it never happens that two Easter Eves occur on Friday (Finegan 1998). Now, according to what we have just discussed, it was not at all obvious that there was a solution that would have satisfied all the constraints imposed to the problem, as required by the calendar information contained in the EMV. Moreover, there are many other narrative elements in the writings of Maria Valtorta that contain calendar and astronomical constraints that perfectly agree with the chronological reconstruction just done. For a more comprehensive discussion we refer to the cited studies (De Caro 2014, 2015, 2017). Any belief that this agreement might be accidental is out of question.

3 In our studies we have used the free software Skychart (http://www.ap-i.net/skychart/), released under the terms of the GNU General Public License, developed by Patrick Chevalley. Religions 2017, 8, 110 5 of 23

Religions 2017, 8, 110 5 of 24 Religions 2017, 8, 110 5 of 24 TableReligions 1. Reconstruction 2017, 8, 110 of the days of Nisan for the years 29–34. Saturdays are indicated by gray boxes.5 of 24 Religions 2017, 8, 110 5 of 24 ReligionsTable 2017 1., 8 ,Reconstruction 110 of the days of Nisan for the years 29–34. Saturdays are indicated by gray5 of 24 TheReligions “E”Table indicates 2017 1., 8 ,Reconstruction 110 the embolismic of the years days of of 13 Nisan months. for the years 29–34. Saturdays are indicated by gray5 of 24 ReligionsTable 2017 1., 8 ,Reconstruction 110 of the days of Nisan for the years 29–34. Saturdays are indicated by gray5 of 24 ReligionsTableboxes. 2017 1.,The 8 ,Reconstruction 110 “E” indicates theof the embolismic days of Nisanyears offor 13 th months.e years 29–34. Saturdays are indicated by gray5 of 24 ReligionsTableboxes. 2017 1.,The 8 ,Reconstruction 110 “E” indicates theof the embolismic days of Nisanyears offor 13 th months.e years 29–34. Saturdays are indicated by gray5 of 24 Religionsboxes.Table 2017 1.,The 8 ,Reconstruction 110 “E” indicates theof the embolismic days of Nisanyears offor 13 th months.e years 29–34. Saturdays are indicated by gray5 of 24 Religionsboxes.TableNisan 2017 1.The (Days), 8 ,Reconstruction 110 “E” indicates Moon Phasetheof the embolismic days 29of Nisanyears offor 30 13 th months.e years 31 E 29–34. Saturdays 32 33are indicated 34 E by gray5 of 24 ReligionsNisanboxes.Table 2017 ,1.The(days) 8 , Reconstruction110 “E” indicates Moon Phasetheof the embolismic days of 29 Nisanyears offor 13 th 30months.e years 29–34. 31 E Saturdays 32 are indicated 33 by 34 gray E 5 of 24 ReligionsNisanTableboxes. 2017 1.,(days)The 8 ,Reconstruction 110 “E” indicates Moon Phasetheof the embolismic days of 29 Nisanyears offor 13 th 30months.e years 29–34. 31 E Saturdays 32 are indicated 33 by 34 gray E 5 of 24 ReligionsNisanTableboxes. 2017 1.,(days)The 8 ,Reconstruction 110 “E” indicates Moon Phasetheof the embolismic days of 29 Nisanyears offor 13 th 30months.e years 29–34. 31 E Saturdays 32 are indicated 33 by 34 gray E 5 of 24 ReligionsNisanTableboxes. 2017 1 11.,(days)The 8 ,Reconstruction 110 “E” indicates Moon Phasetheof the embolismic days5apr 5aprof 29 Nisanyears 25mar offor 1325mar th 30months.e years 13apr 29–34.13apr 31 E 1aprSaturdays 1apr 3221mar are 21marindicated 33 10apr by10apr 34 gray E 5 of 24 ReligionsNisanboxes.Table 20171 1.,The(days) 8 ,Reconstruction 110 “E” indicates Moon Phasetheof the embolismic days 5aprof 29 Nisanyears offor 1325mar th 30months.e years 29–34.13apr 31 E Saturdays 1apr 32 are 21marindicated 33 by10apr 34 gray E 5 of 24 Nisanboxes.Table 1 1.The(days) Reconstruction “E” indicates Moon Phasetheof the embolismic days 5aprof 29 Nisanyears offor 1325mar th 30months.e years 29–34.13apr 31 E Saturdays 1apr 32 are 21marindicated 33 by10apr 34 gray E Nisanboxes.Table 12 1.The(days) Reconstruction “E” indicates Moon Phasetheof the embolismic days 5apr6aprof 29 Nisanyears offor 1325mar26mar th 30months.e years 29–34.13apr14apr 31 E Saturdays 1apr2apr 32 are 21mar22marindicated 33 by10apr11apr 34 gray E NisanTableboxes. 21 21.The(days) Reconstruction “E” indicates Moon thePhaseof the embolismic days6apr 6apr5aprof 29 Nisanyears 26mar offor 1326mar25mar th 30months.e years14apr 29–34.14apr13apr 31 E 2aprSaturdays 2apr1apr 32 22mar are 22mar21marindicated 33 11apr by11apr10apr 34 gray E NisanTableboxes. 21 1.The(days) Reconstruction “E” indicates Moon Phasetheof the embolismic days 6apr5aprof 29 Nisanyears offor 1326mar25mar th 30months.e years 29–34.14apr13apr 31 E Saturdays 2apr1apr 32 are 22mar21marindicated 33 by11apr10apr 34 gray E NisanTableboxes. 213 1.(days)The Reconstruction “E” indicates Moon Phasetheof the embolismic days 6apr5aprof 29 Nisanyears offor 1326mar25mar27mar th 30months.e years 29–34.14apr13apr15apr 31 E Saturdays 2apr1apr3apr 32 are 22mar21mar23marindicated 33 by11apr10apr12apr 34 gray E Nisanboxes.321 3(days)The “E” indicates Moon Phasethe embolismic 5apr5apr6apr 29 years 27mar of 1327mar26mar25mar 30months. 15apr 15apr14apr13apr 31 E 3apr 3apr2apr1apr 32 23mar 23mar22mar21mar 33 12apr 12apr11apr10apr 34 E Nisanboxes.312 The(days) “E” indicates Moon Phasethe embolismic 5apr6apr 29 years of 1327mar26mar25mar 30months. 15apr14apr13apr 31 E 3apr2apr1apr 32 23mar22mar21mar 33 12apr11apr10apr 34 E Nisanboxes.3142 (days)The “E” indicates Moon Phasethe embolismic 5apr8apr6apr 29 years of 27mar25mar28mar1326mar 30months. 15apr13apr16apr14apr 31 E 3apr1apr4apr2apr 32 23mar21mar24mar22mar 33 10apr12apr13apr11apr 34 E Nisan1432 4(days) Moon Phase 8apr5apr8apr6apr 29 28mar25mar28mar27mar26mar 30 16apr13apr16apr15apr14apr 31 E 4apr 1apr4apr3apr2apr 32 24mar 24mar21mar23mar22mar 33 13apr 10apr13apr12apr11apr 34 E Nisan3124 (days) Moon Phase 5apr6apr8apr 29 27mar26mar25mar28mar 30 14apr15apr13apr16apr 31 E 2apr3apr1apr4apr 32 22mar23mar21mar24mar 33 11apr10apr12apr13apr 34 E Nisan24513 (days) Moon Phase 6apr9apr8apr5apr 29 26mar29mar28mar25mar27mar 30 14apr17apr16apr13apr15apr 31 E 2apr4apr5apr1apr3apr 32 22mar24mar25mar21mar23mar 33 11apr13apr 14apr10apr12apr 34 E Nisan25143 (days) Moon Phase 9apr6apr5apr8apr 29 29mar26mar25mar28mar27mar 30 17apr14apr13apr16apr15apr 31 E 2apr5apr1apr4apr3apr 32 22mar25mar24mar21mar23mar 33 11apr 14apr10apr13apr12apr 34 E 3512465 9apr10apr9apr5apr6apr8apr 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29apr26apr27apr28apr25apr 19apr15apr18apr16apr17apr14apr 5may8may6may7may4may 302827292626 Note:30apr30apr4may2may1may3may The backcolor 19apr23apr21apr19apr20apr22apr marks 8may Saturdays.10may11may8may9may 26apr 28apr27apr29apr26apr 15apr 17apr19apr16apr15apr18apr 5may 7may6may 5may8may 2830272629 Note:30apr2may4may1may3may The backcolor 21apr19apr23apr20apr22apr marks Saturdays.10may11may8may9may 28apr27apr26apr29apr 17apr16apr19apr15apr18apr 7may6may 5may8may 2930272826 Note:30apr3may4may1may2may The backcolor 23apr20apr22apr21apr19apr marks Saturdays.11may10may9may8may 27apr29apr28apr26apr 16apr19apr18apr17apr15apr 6may8may7may 5may 2928302727 Note:3may2may4may1may The backcolor 22apr21apr23apr20apr marks Saturdays.11may10may9may 29apr27apr28apr 18apr16apr17apr19apr 8may6may7may 29272830 Note:1may3may1may2may4may The backcolor 20apr22apr20apr21apr23apr marks 9may Saturdays.11may10may9may 27apr 29apr27apr28apr 16apr 18apr16apr17apr19apr 6may 8may6may7may This 30282927result, summarized in TableNote:4may2may3may 1may1,The is backcoloremblematic 23apr21apr22apr20apr marks to showSaturdays.10may11may9may a peculiar 28apr29apr27apr characteristic 17apr19apr18apr16apr that7may8may6may emerges This 302928result, summarized in TableNote: 4may3may2may1,The is backcoloremblematic 23apr21apr22apr marks to showSaturdays.10may11may a peculiar 28apr29apr characteristic 19apr17apr18apr that7may8may emerges This 302928result,28 summarized in TableNote:2may 4may3may2may 1,The is backcoloremblematic 21apr23apr21apr22apr marks to 10may show Saturdays.10may11may a 28aprpeculiar 28apr29apr characteristic 17apr 19apr17apr18apr 7may that7may8may emerges fromThis the 2930result,astronomical-calendar summarized in TableNote: analysis 3may4may1,The is backcoloremblematic of the23apr22apr marksEMV: to showSaturdays. 11maythe a peculiaruniqueness 29apr characteristic of19apr18apr the chronological that8may emerges fromThis the 2930result,astronomical-calendar summarized in 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EMV is withby be Asthe andhistorians,Friday, already samemany calendar proposedApril eventsevidenced, who 23analysis usuallof of byJesus’ the let I.y usofyearNewton,put life note,the the 34.narr EMV crucifixionalso,It namely atedis worththatand in theApriltheassociated either noting date canonical 23 to of thatof April the withthe all crucifixionGospels, 7year other ofthe the 34.events dates yearare This that unambiguously 30derived narratedemergesdate or to is April byrarely fromand, the 3 our attentionindirectly,astronomicalnecessarilyestablished.theconsideredof the EMV onlyyear is onwith33.by beAsthe and thehistorians,Friday,We already samemany datingcannot,calendar proposedApril eventsevidenced, who oftherefore, 23 theanalysis ofusuall of crucifixion,byJesus’ the let I. y assume usofyearNewton,put life note,the the 34.narr that byEMV crucifixionalso,It namelyated showingis Maria worththatand in theValtortaApriltheassociated eithernoting that datecanonical 23 thisto of hadthatof April the datewiththe been,all crucifixionGospels, 7year other mustofthe somehow, the 34.events dates necessarilyyearare Thisthat unambiguously 30derived narratedemergesinfluenceddate or to is be April byrarely Friday,fromand, the by 3 established.consideredofindirectly,astronomicalthe the EMV year is with33.by Asthe andhistorians,We already samemany cannot,calendar proposed eventsevidenced, who therefore, analysis usuallof byJesus’ let I. y assume usofNewton,put life note,the the narr thatEMV crucifixionalso, namelyated Maria thatand in theValtortaApriltheassociated either date canonical 23 to of hadof April the withthe been, crucifixionGospels, 7year ofthe somehow, the 34.events yearare Thisthat unambiguously 30 narratedemergesinfluenceddate or to is April rarely fromand, by 3 established.ofastronomicalindirectly,consideredthe the EMV year is with33.by Asthe andhistorians,We already samemany cannot,calendar proposed eventsevidenced, who therefore, analysis usuallof byJesus’ let I. y assume usofNewton,put life note,the the narr thatEMV crucifixionalso, namelyated Maria thatand in theValtortaApriltheassociated either date canonical 23 to of hadof April the withthe been, crucifixionGospels, 7year ofthe somehow, the 34.events yearare Thisthat unambiguously 30 narratedemergesinfluenceddate or to is April rarely fromand, by 3 April 23theofwhatindirectly,established.consideredastronomical of the theEMV she year year knewis with33.by Asthe 34. andhistorians,We already aboutsame Itmany iscannot,calendar worth it. proposed eventsevidenced, Indeed, who therefore, notinganalysis usuallof byifJesus’ itlet thatI. ywasassume usofNewton,put life note, allthethe the narr other thatcase,EMV crucifixionalso, namelyated Maria datesone thatand in should theValtortaApriltheassociated derivedeither date canonical expect23 to of hadof byApril the withthe thebeen,to crucifixionGospels, find7year astronomicalofthe somehow, the in 34.events heryearare This that writings unambiguously 30 narratedinfluencedemergesdate or and to is indirect calendarApril rarely fromand, by 3 whatindirectly,established.oftheconsidered the EMV she year knewis with33.by Asthe historians,We already aboutsamemany cannot, it. proposed eventsevidenced, Indeed, who therefore, ofusuall byifJesus’ itlet I. ywasassume usNewton,put life note, the the narr thatcase, crucifixionalso, namelyated Maria one that in should theValtortaAprilthe either date canonical expect23 to of hadof April the the been,to crucifixionGospels, find7year of somehow, thein 34. heryearare Thisthat writings unambiguously 30 emergesinfluenceddate or to isindirect April rarely from by 3 theindirectly,established.consideredofwhatreference the EMV she year knewtois with33.by Aseitherthe historians,We already aboutsamemany cannot,April it. proposed eventsevidenced, 7,Indeed, who therefore,30 or usuallof tobyifJesus’ itletApril I. yassumewas usNewton,put life note, 3,the the 33,narr thatcase, crucifixion also,and namelyated Maria one notthat in shouldto theValtortaAprilthe eitherNewton’s date canonical 23expect to of hadof April the datingthe been,to crucifixionGospels, find7year of ofsomehow, the in 34.crucifixion. heryearare This that writings unambiguously 30 emergesinfluenceddate or Moreover, to is indirect April rarely from by 3 analysisconsideredwhatreferenceestablished.theof of the theEMV she year EMV knewtois 33.by Aseitherthe historians, andWe already aboutsame Aprilcannot, associated it.proposed evidenced, 7,Indeed, who therefore,30 or usuall withtobyif itletApril I. ywasassume ustheNewton,put note, 3,the eventsthe 33, thatcase, crucifixion also,and namely Maria narratedone notthat shouldto theValtortaApril eitherNewton’s date and, expect23 to of hadof April indirectly,the datingthe been,to crucifixion find7year of ofsomehow, the in 34.crucifixion. withher year Thisthat writings many30 emergesinfluenceddate or Moreover, to iseventsindirect April rarely from by 3of consideredreferenceestablished.thewhatof the EMV she year knewtois 33.by Aseitherthe historians,We already aboutsame Aprilcannot, it.proposed evidenced, 7,Indeed, who therefore,30 or usuall tobyif itletApril I. ywasassume usNewton,put note, 3,the the 33, thatcase, crucifixion also,and namely Maria one notthat shouldto theValtortaApril eitherNewton’s date expect23 to of hadof April the datingthe been,to crucifixion find7year of ofsomehow, the in 34.crucifixion. her year Thisthat writings 30 emergesinfluenceddate or Moreover, to is indirect April rarely from by 3 ofreferenceinconsideredthewhatestablished. 1933the EMV she year there knewtois 33.by eitherAsthe was historians,We alreadyaboutsame an Aprilcannot, extraordinary it.proposed evidenced, 7,Indeed, who therefore,30 or usuall tobyif itletJubileeApril I. yassumewas usNewton,put note, 3,the proclaimedthe 33, thatcase, crucifixion also,and namely Maria one notthat by shouldto theValtortaApril eitherPiusNewton’s date XIexpect23 to of hadtoof April the celebratedatingthe been,to crucifixion find7year of ofsomehow, the in the34.crucifixion. her year 1900thThis that writings 30 influencedemergesdate oranniversary Moreover, to is indirect April rarely from by 3 Jesus’ lifeinconsideredthereferenceofwhat narrated1933the EMV she year there knewtois 33.by eitherthe in was historians,We the aboutsame an Aprilcannot, canonical extraordinary it.proposed 7,Indeed, who therefore,30 or usuall Gospels, tobyif itJubileeApril I. ywasassume Newton,put are3,the proclaimedthe 33, unambiguouslythatcase, crucifixion and namely Maria onenot by shouldto ValtortaApril eitherPiusNewton’s XI23expect established.to hadtoof April celebratedatingthe been,to find7year of ofsomehow, the in the As34.crucifixion. her year 1900th alreadyThis writings 30 influenceddate oranniversary Moreover, evidenced,to is indirect April rarely by 3 ofconsideredthewhatreferencein 1933the EMV she year there knewtois 33.by eitherthe was historians,We aboutsame an Aprilcannot, extraordinary it.proposed 7,Indeed, who therefore,30 or usuall tobyif itJubileeApril I. yassumewas Newton,put 3,the theproclaimed 33, thatcase, crucifixion and namely Maria onenot by shouldto ValtortaApril eitherPiusNewton’s expect23XI to hadtoof April celebratedatingthe been,to find7year of ofsomehow, the in the34.crucifixion. her year 1900thThis writings 30 influenceddate oranniversary Moreover, to is indirect April rarely by 3 let us note,whatinofconsideredreference 1933the also, she year there thatknewto 33.by either was thehistorians,We about an dateAprilcannot, extraordinary it. of7,Indeed, who therefore,30 the or usuall crucifixion toif itJubileeApril ywasassume put 3,the proclaimedthe 33, that thatcase, crucifixion and emerges Maria one not by shouldto Valtorta eitherPiusNewton’s from expectXI to thehadto April celebratedating EMVbeen,to find7 of of issomehow, the in the thecrucifixion. her year 1900th same writings 30 influenced oranniversary proposed Moreover, to indirect April by 3 by whatofconsideredinreference 1933the she year there knewto 33.by either was historians,We about an Aprilcannot, extraordinary it. 7,Indeed, who therefore,30 or usuall toif itJubileeApril ywasassume put 3,the theproclaimed 33, thatcase, crucifixion and Maria one not by shouldto Valtorta eitherPiusNewton’s expectXI to hadto April celebratedating been,to find7 of ofsomehow, the in thecrucifixion. her year 1900th writings 30 influenced oranniversary Moreover, to indirect April by 3 reference ofwhatinconsidered 1933the she year there knewto 33.by either was historians,We about an Aprilcannot, extraordinary it. 7,Indeed, who therefore,30 or usuall toif itJubileeApril ywasassume put 3,the proclaimedthe 33, thatcase, crucifixionand Maria onenot by shouldto Valtorta eitherPiusNewton’s expectXI to hadto April celebratedating been,to find7 of ofsomehow, the in thecrucifixion. her year 1900th writings 30 influenced oranniversary Moreover, to indirect April by 3 I. 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April 7,Indeed, 30 7or of toif the itJubileeApril was year 3,the proclaimed 33, 30 case, and or to onenot April by shouldto PiusNewton’s 3of XIexpectthe to celebratedating yearto find 33.of in thecrucifixion. We her 1900th cannot,writings anniversary Moreover, therefore,indirect inreference 1933 there to either was an April extraordinary 7, 30 or to JubileeApril 3, proclaimed 33, and not by to PiusNewton’s XI to celebratedating of thecrucifixion. 1900th anniversary Moreover, referencein 1933 there to either was an April extraordinary 7, 30 or to JubileeApril 3, proclaimed 33, and not by to PiusNewton’s XI to celebratedating of thecrucifixion. 1900th anniversary Moreover, inreference 1933 there to either was an April extraordinary 7, 30 or to JubileeApril 3, proclaimed 33, and not by to PiusNewton’s XI to celebratedating of thecrucifixion. 1900th anniversary Moreover, in 1933 there was an extraordinary Jubilee proclaimed by Pius XI to celebrate the 1900th anniversary in 1933 there was an extraordinary Jubilee proclaimed by Pius XI to celebrate the 1900th anniversary

Religions 2017, 8, 110 6 of 23 assume that Maria Valtorta had been, somehow, influenced by what she knew about it. Indeed, if it was the case, one should expect to find in her writings indirect reference to either April 7, 30 or to April 3, 33, and not to Newton’s dating of crucifixion. Moreover, in 1933 there was an extraordinary Jubilee proclaimed by Pius XI to celebrate the 1900th anniversary of the crucifixion. All the Church and, thus, also Maria Valtorta knew this anniversary which leads directly to the year 33 AD for Jesus’ death. For all Catholics this was the year of the crucifixion. Furthermore, as already noted, no date is explicitly reported in the EMV. It is only thanks to a complex and rigorous astronomical and calendar analysis of the narrative elements in Maria Valtorta’s writings that it is possible to establish an accurate chronology of every event in Jesus’ life described in the EMV. Curiously, what Maria Valtorta indicates as mystical visions and Jesus’ dictations, reported in the EMV, started on the Good Friday April 23, 1943, as if it had been an historical anniversary of Jesus’ crucifixion. Consider that before the year 1943 the Good Friday fell on April 23 only in 1886, and since 1943 it has never happened again. The next time will be Friday April 23, 2038. The fortuity, therefore, should be excluded and everything remains without a rational explanation. Indeed, if the crucifixion happened just on April 23 of the year 34 AD, then April 23, 1943, when Maria Valtorta started to write her mystic visions, was the anniversary of Jesus’s death. The date of 23 April 34 AD was not reported explicitly by Maria Valtorta. It has been obtained by a rigorous astronomical and calendar analysis of her writings. In other words, she knew nothing about it. Let us discuss two possible explanations. First, we could speculate that the strong correlation of dates is only due to a fortuitous coincidence. However, the frequency with which Good Friday coincides with the 23 of April is very low, less than once every century and, consequently, it is unlikely that it happened by chance. Secondly, we could speculate that this strong correlation is due to a fraud. However, Maria Valtorta had just elementary mathematical ability, and that, in any case, all happened during the Second World War, when people fought every day to survive. During those years her daily life was also harder than that of other people in good health because she was bedridden being paralyzed, and lived in poverty in her little house in Viareggio. Thus, it is difficult to imagine she could take the time, express the willpower and the scientific expertise, that she had not, to devise and realize such a sophisticated fraud. Secondly, in 1942 the Good Friday coincided with the 3rd of April, i.e., just the date proclaimed by Pius XI less than 10 years earlier, as previously recalled, as the historical date of crucifixion. Therefore, it is more reasonable to speculate that any probable fraud would have started everything on the 3rd of April 1942, Good Friday of that year, and would have suitably constructed all astronomical and calendar data correlated with the 3 of April of the year 33 AD, as the day of crucifixion. However, this is not the case and all her writings lead to the less-known date of Jesus’s death proposed by Isaac Newton, known only by few scholars even today. Indeed, Maria Valtorta was acquainted with the name of this scientist from her secondary school years (in Collegio Bianconi in the city of Monza, Lombardy, Italy) as the author of the three Laws of Dynamic and the Theory of Gravitation, and he was actually unknown for his biblical studies and his dating of crucifixion. Indeed, these studies were published only after his death, in Latin, and they were known only by very few scholars of that time. Only during the first half of the XX century, Newton’s work about the crucifixion dating was translated in English, a language that Maria Valtorta did not know, as she explicitly wrote on July 21 1945 (Valtorta 2006).

3. Rainy Days Described in the EMV and Their Dating According to the Astronomical Analysis Astronomy is not the only science with which we can analyze the EMV. Maria Valtorta has annotated also observations about the meteorological conditions, especially the occurrence of rain, and this has suggested us to compare her data with the current meteorological data of the Holy Land. Because her observations concern only the occurrence of rain in a day, the statistical variable that we can compare is the number of rainy days. With this regard the reliability of this parameter against possible climatological changes that may have occurred in the Holy Land in the last 2000 years is also important. Of course, a statistical comparison referred to alleged meteorological conditions so remote Religions 2017, 8, 110 7 of 23 cannot be as accurate as the astronomical and calendar analysis discussed before but, nevertheless, it turns out to be very interesting, as we show in the following. The frequency of precipitation depends on the local climate of a region. The Holy Land is a geographical area of transition between regions of temperate and arid climate. The southern and eastern parts are characterized by an arid climate while the rest of the region by a Mediterranean weather. A fundamental feature of this type of climate is the large variability in the amount of rain from year to year and in different areas. Summer is very hot, it rarely rains, winter is cool and rainy, with precipitation mostly occurring from October to May. For this reason, the Israel Meteorological Service (Central Bureau of Statistics) (indicated as the IMS in the following) refers long-term precipitation (rainfall, snow, hail) data to the so-called rainy year, which starts in August and ends in July. In other words, the climate of the Holy Land is Mediterranean along the coast and semi-arid, with scarce and little frequent rainfall, in the Depression of the Dead Sea, in the Judean Desert and Jordan Valley. Thus, the weather is characterized by more abundant and frequent rainfall towards the Mediterranean Sea and the North. Today the meteorological services of many countries, such as the IMS, make freely available large data banks of precipitation of their areas. The IMS data banks allow to calculate the annual average frequency of the number of rainy days, as a function of latitude and longitude, of many localities in the Holy Land (Israel and West Bank) where meteorological stations are deployed. The climate of the Holy Land is not drastically changed in the last 2000 years because the climatological constraints that determine it (Mediterranean Sea, Depression of the Dead Sea, Judean Desert and Jordan Valley) have not changed, so that, it is reasonable to assume that the average number of annual rainy days provided by the IMS can be compared to the results deduced from the EMV, under the conjecture that Maria Valtorta wrote about what she allegedly observed in vision 2000 years ago. In this regard, it is interesting to notice that a detailed analysis of tree rings’ growth has shown that the average temperature at the beginning of the Christian era was surprisingly similar to that of the last fifty years (Esper et al. 2012). The issue of Holy Land climate changes is discussed in more detail in Section6. Now we will first focus our attention on the meteorological information deducible from the IMS analysis. Maria Valtorta never visited the Holy Land and her experience of rainfall frequency and rainy days was typical of Northern Italy—especially the Milan area, where she stayed for many years in her youth- and Tuscany—where she spent many years and died -, which is quite different of that of the Holy Land. To give an idea of the great differences that can be found, for example let us consider Alamogordo, New Mexico (32.5◦ latitude N, 106.0◦ longitude W), characterized by a semi-arid climate and rainfall mostly concentrated only in a period of the year, as in the Holy Land. In the 50 years 1951–2000, 2657 rainy days were recorded, an annual average 53.1 rainy days. In Milan (45.5◦ latitude N, 9.2◦ longitude E) with temperate-continental climate, in the 143 years 1858–2000, 15635 rainy days were recorded, with an annual average 103.3 rainy days (Matricciani 2013). To test the likelihood of the rainy days mentioned in the EMV, we have searched all references to the occurrence of rain in the period of public life of Jesus narrated by Maria Valtorta. The astronomical reconstruction of the dates associable to the narrated events has then allowed to estimate how many days of the public life, on the total of 3 years and few months, have been really described, have been “observed” as if she had been an eyewitness. This search has also allowed to establish if the reference to rain concerned single days separated by non-rainy days, or continuous sequence of rainy days. The first part of the analysis is reported in Table2, where we have listed the number of days explicitly described in the EMV and the subset of the rainy days subdivided for season and for single years of Jesus’ public life. Table3 lists the localities to which rainy days have been associated, with their geographic coordinates and dates of rainy days. The chronological reconstruction of dates associated to rainy days was determined as explained in detail in (De Caro 2014, 2015, 2017). Figure1 shows synoptically the geographical displacement of these sites, excluding the locality at the latitude of Cyprus, mentioned in Table3, because outside the Holy Land. From the analysis it follows that of the Religions 2017, 8, 110 8 of 23

1204 days of Jesus’ public life, emerged by the EMS astronomical analysis—from the 6th of Jan 31 to the 23rd of Apr 34—only about 380 have been actually described by Maria Valtorta, of which only 52 have been annotated as rainy days. From the astronomical analysis it follows that these 380 days are monthly distributed according to Table4. The latter values may be affected by small errors in the chronologicalReligions 2017 reconstruction, 8, 110 for days that fall across the end of a month and the start of the8 next.of 24

FigureFigure 1. Localities 1. Localities of the of Holythe Holy Land Land allegedly allegedly visited visited by by Jesus Jesus in in days days with with rain rain according according toto thethe EMV. Scale:EMV. 1 cm=10 Scale: km. 1 cm=10 km.

Table 2. Number of rainy days described in the years of Jesus’ public life, as they are deduced by the Table 2. Number of rainy days described in the years of Jesus’ public life, as they are deduced by the astronomical analysis of the EMV for each year and total period. Key: 75/366 means 75 days described astronomicalout of 366 analysis of Jesus’ of public the EMV life in for year each I; 9/75 year means and total9 rainy period. days out Key: of 75, 75/366 etc. The means four 75numbers days described in a out ofrow 366 reported of Jesus’ for public each year life refer in year to spring, I; 9/75 summer, means fall 9 rainy and winter, daysout respectively, of 75, etc. with The seasons four numbers starting in a row reportedconventionally for each at the year equinoxes refer to and spring, solstices. summer, fall and winter, respectively, with seasons starting conventionally at the equinoxes and solstices. Year I II III Final Months Total Period EMV 6 January 31 9 January 32 28 December 32 18 December 33 6 January 31 Year I II III Final Months Total Period 7 January 32 27 December 32 17 December 33 23 April 34 23 April 34 EMV 6 January75/366 31 9 January 115/354 32 28 December150/354 32 1840/126 December 33380/1204 6 January 31 Described Days 715 January + 30 + 20 32 + 10 27 35 December + 25 + 25 + 30 32 3517 + December 35 + 35 + 45 33 20 + 230 + April5 + 15 34 105 + 90 + 23 85 April + 100 34 75/3669/75 115/35416/115 150/35422/150 5/40 40/126 52/380 380/1204 DescribedRainy Days Days 15 + 300 + +1 20+ 7 ++ 1 10 35 + 3 25+ 3 ++ 259 + +1 30 35 3 ++ 2 35 + +7 + 35 10 + 45 4 20+ 0 ++ 0 + 1 5 + 15 10 + 105 6 + +23 90 + 13 + 85 + 100 9/75 16/115 22/150 5/40 52/380 Rainy Days If we exclude0 the + 1 +data 7 + 1correspondi 3 + 3ng + 9to + the 1 latitude 3 + 2of + Cyprus 7 + 10 (see 4Table + 0 + 3), 0 + we 1 obtain 10 an + 6 annual + 23 + 13 frequency of 51 × 365/380 = 49 rainy days. This result is compatible with that of a semi-desert climate in which rainfall is concentrated in about two consecutive seasons of the year, just as it happens in the Holy Land.

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If we exclude the data corresponding to the latitude of Cyprus (see Table3), we obtain an annual frequency of 51 × 365/380 = 49 rainy days. This result is compatible with that of a semi-desert climate in which rainfall is concentrated in about two consecutive seasons of the year, just as it happens in the Holy Land. The detailed observations that Maria Valtorta reports in the EMV are evidently due to causes other than the meteorological conditions, because the mention of rain is not instrumental to develop the narration, but it is just an incidental observation. Therefore it is legitimate to assume that: (i) the value of the annual rainy days in the EMV (49) can be compared to the frequency of annual rainy days obtained from the IMS data bank; (ii) we can refer this value also to the ancient Holy Land if we could assume that no extreme changes in the rainfall regime of this region have occurred in the last 2000 years, because of the permanence of the main geographical factors that determine the climate, previously recalled. In the next sections we will show that both these hypotheses can be justiﬁed, although our general conclusions can be considered, of course, only a conjecture about the signiﬁcance of the presence of meteorological data in the EMV.

Table 3. Locality (latitude, longitude) where rain is reported according to the EMV in the years of Jesus’ public life, divided by year of Jesus’ public life. For each locality the ﬁrst integers give the number of single or sequence of successive rainy days.

I year (6 January 31–7 January 32) 1, Nazareth (32.73, 35.27);4 2, Esdraelon (32.71, 35.13);5 1, Meron (32.99, 35.54);6 1, Clear Water (31.97, 35.73);7 3, Clear Water (31.97, 35.73); 8 1, Clear Water (31.97, 35.73).9 II year (9 January 32–27 January 32) 1, Bethsaida (32.88, 35.28);10 1, Ippo (32.78, 35.66);11 1, Sichem (32.23, 35.26);12 1, Jerusalem (31.78, 35.22);13 1, Capernaum (32.88, 35.58); 14 1, Cana-Nazareth (32.75, 35.59; 32.73, 35.27);15 1, Gennesaret (32.85, 35.52);16 4 + 1, Arbela (32.55, 35.85);17 1, Meron (32.99, 35.54);18 3, Magdala (32.84, 35.50).19 III year (28 December 32–17 December 33) 2 + 1, Nazareth and Jiphthahel (32.73, 35.27; 32.83, 35.39);20 1, Ptolemais (32.82, 35.09);21 1, Cyprus;22 1, Achziv (33.09, 35.11);23 2, Pella and Jabesh-Gilead (32.45, 35.61);24 1, Bethabara (31.84, 35.55);25 1, Bethabara (31.84, 35.55);26 3, Esdraelon (32.71, 35.13);27 1, Tiberias (32.78, 35.53);28 1, Capernaum;29 2, Nazareth-Engannim (32.73, 35.27; 32.46, 35.30);30 1, Nob;31 1, Betanhy beyond the Jordan; 32 1, Bet Horon (31.88, 35.40);33 2, Nob.34 Final months (18 December 33–23 April 34) 1, Gofena (31.96, 35.22);35 1, Doco (31.86, 35.46);36 2, Betanhy (31.78, 35.22);37 1, Jerusalem (31.78, 35.22).38 Religions 2017, 8, 110 10 of 23

Table 4. Monthly distribution of the 380 days described in the EMV.

January February March April May June July August September October November December 21 32 43 62 33 18 37 19 26 30 35 24

38 “This stormy day” (EMV 608.10): Friday 23 April 34. 37 “Here is the rain” (EMV 581.8): Thursday 15 April 34; “It has stopped raining” (EMV 583.18): Fri 16 Apr 34; the latitude and longitude are those of Jerusalem. 36 “Rain must have drizzled during the night” (EMV 576.1): spring of year 34; the latitude and longitude are those of Jericho. 35 “The sound of the wind is joined by the fall of rain that patters” (EMV 561): winter of year 33; the latitude and longitude are those of Jifna. 34 “After a Sabbath and two wet days” (EMV 530.3): 22–23 November 33. 33 “Because it has rained” (EMV 514.1): Friday 6 November 33. 32 “It is raining” (EMV 504.2): Tuesday 27 October 33. 31 “A real tornado under a frightening sky” (EMV 489.7): Sunday 4 October 33; the latitude and longitude are those of Jerusalem. 30 “The country which is wet after the shower. It must have rained only recently” (EMV 478.1): Thursday 24 September 33 at Nazareth; “it is going to rain” (EMV 480.3): Friday 25 September 33; “Don’t you see how wet and tired He is?” (EMV 481.3): Friday 25 September 33 at Engannim; the latitude and longitude are those of Jenin, two consecutive rainy days. 29 “Jesus goes outside, heedless of the storm” (EMV 459.2): Friday 11 September 33. 28 “Jesus arrives at Tiberias with His apostles on a stormy morning” (EMV 445.1): Wednesday 2 September 33. 27 “A deluge of rain and hailstones falls upon the area” (EMV 42.68): Thursday 18 June 33; “It must have continued to rain all the previous day and during the night” (EMV 429.1): Friday 19 June 33; “the branches still dripping, as is usual after a storm” (EMV 430.1): Saturday 20 June 33; thus, there have been three consecutive rainy days. 26 “They walk all night in changeable weather, in fitful showers.” (EMV 361.10): Sunday 22 March 33. 25 “Who foresaw all this rain?” (EMV 360.2): Thursday 19 March 33. 24 “The first drops of rain fall” (EMV 358.10): Monday 16 March 33 at Pella; “The elm-tree is slippery because of the rain” (EMV 359.2): Tuesday 17 March 33 at Jabesh-Gilead. 23 “The recent hailstorms have destroyed strips of the country” (EMV 332.5): Sunday 25 January 33; the latitude and longitude are those of Rosh Hanikra. 22 “Never seen a storm like this” (EMV 320.2): Saturday 3 January 33; this data has not considered in the statistical analysis since Cyprus does not belong to The Holy Land. 21 “It’s beginning to rain” (EMV 318.4): Thursday 1 January 33. 20 “It is a wet winter morning” (EMV 312.1): Sunday 28 December 32; “in the ice-cold rain of a winter night” (EMV 314.9): Mon 29 December 32; “tormented by cold wet weather” (EMV 316.1): Wednesday 31 December 32. Two consecutive rainy days separated by another one by a day without rain (cf. EMV 315). The latitude and longitude are those of Nazareth and Iblin. 19 “Rain, rain, rain ... ” (EMV 302.1): Friday 28 November 32; “in search of the warm sun after the stormy days” (EMV 305.1): Friday 5 December 32; Maria Valtorta indicates “stormy days”; we can assume at least three consecutive rainy days. 18 “a dull wet day” (EMV 298.1): Sunday 16 November32. 17 “Long live the rain! It helped also to keep You in my house for five days” (EMV 296.1): from Friday 7 to Tuesday 11 November 32; “He has been coming for three days to this place with the donkeys, always in the rain” (EMV 296.6): from Monday 10 to Wednesday 12 November 32; rainy days: Friday; Sunday, Monday, Tuesday, Wednesday; the Saturday has not been described in the literacy work; therefore we cannot know if it has been a rainy day. Thus the consecutive rainy days are at least four. The latitude and longitude are those of Irbid. 16 “it is preparing a storm” (EMV 274.2): Monday 15 September 32. The latitude and longitude are those of Ginosar. 15 “the recent storm has washed them” (EMV 244.1): 17–18 July 32. 14 “the rain starts” (EMV 238.1): Friday 11 July 32. 13 “It is raining” (EMV 195.1): Friday 4 April 32. 12 “A heavy shower during the night has made the road somewhat muddy” (EMV 193.1): Wednesday 2 April 32. 11 “The storm rages more and more furiously” (EMV 185.3): 23–24 March 32. 10 “Because of the storm of a few days ago” (EMV 180.7): 10–12 March 32. 9 “It is a rainy day” (EMV 137.1): Sunday 6 January 32. 8 “in a heavy shower of rain which is getting heavier” (EMV 123.2): third decade of November 31; “It is raining in torrents” (EMV 124.1): second consecutive rainy day; “it is still raining ” (EMV 125.1): third consecutive rainy day. 7 “Jesus’ voice resounds in the large room crowded with people; it is in fact raining” (EMV 120.1): third decade of November 31. The latitude and longitude are those of Niran. 6 “It’s raining, Master” (EMV 110.4): Friday 12 October 31. The considered latitude and longitude are those of Hatzor. 5 “It must have rained during the night, one of the first rains of the dreary winter months” (EMV 109.1) ... “Towards evening, a military Roman wagon catches up with them. ... The two soldiers stop; from under the cover pulled over the wagon, as it has started raining” (EMV 109.13): 4–5 October 31. The latitude and longitude are those of Kyriat Tivon. 4 “It is a stormy day and a storm is impending” (EMV 92.1): Thursday 2 August 31; “Jesus goes into the kitchen garden, which looks as if it has been washed by the storm of the previous evening” (EMV 93.1) ... “Peter says: «This is Friday... Master, tomorrow is the Sabbath»” (EMV 93.3): Friday 3 August 31. Religions 2017, 8, 110 11 of 24

Table 4. Monthly distribution of the 380 days described in the EMV.

January February March April May June July August September October November December

21 32 43 62 33 18 37 19 26 30 35 24

4. A Meteorological Picture Statistically Coherent with the Current Data of the Holy Land As already observed, in the Holy Land the rainy days are mostly concentrated in the fall and winter months. Relative to the period 1990–2015 and for 184 localities, almost all with rainfall data collected for 26 years by the IMS, Figure 2 shows the length of the average annual rainy period, as a function of the longitude and latitude, defined as in the following. For each year we have first calculated the duration of the continuous interval of time between the last rainy day before summer and the first rainy day after summer and have then subtracted it from 365 or 366 (leap years). The final result shown in Figure 2 for each locality is the average for the all period. It is confirmed that Religionsthe2017 rainy, 8, 110 period is about half of the year, longer in the more rainy North-East region and shorter11 in of 23 the South-East region. Figure 3 shows the annual average value of rainy days versus longitude (higher panel) and 4. A Meteorological Picture Statistically Coherent with the Current Data of the Holy Land latitude (lower panel) for the same localities of Figure 2. Squares give the value found in the EMV As(49), already triangles observed, give the in average the Holy value Land of 159 the locali rainyties days with are latitude mostly > 31.5° concentrated (about the in latitude the fall of and winterJerusalem), months. Relative that is the to minimum the period latitude 1990–2015 reported and in Figure for 184 1 localities,for the localities almost with all rainfall with rainfalldescribed data collectedin the for EMV. 26 years The value by the obtained IMS, Figurefrom the2 IMSshows data the bank length is 50.6 of rainy the days average per year, annual practically rainy as period, the value of the EMV, 49. Figure 3 shows also the values at ±1 standard deviation of the longitude and as a function of the longitude and latitude, defined as in the following. For each year we have first latitude found in the 159 localities with latitude > 31.5°, and in the EMV localities. In longitude the calculated the duration of the continuous interval of time between the last rainy day before summer displacement of the IMS and EMV sets is justified by the fact that some of the localities mentioned in and thethe first EMV rainy are daynow afterin Jordan, summer and the and corresponding have then subtracted meteorological it from statistical 365 or data 366 are (leap not years).recorded The final resultin the shown IMS databank. in Figure Conversely,2 for each locality in latitude is the the average two sets for almost the all coincide period. because It is confirmed the latitude that of the rainy periodJordan isis aboutabout the half same of the of year,that of longer Israel inand the We morest Bank. rainy Notice North-East that in both region cases, and however, shorter the in the South-Eastaverage region. values and the standard deviations are almost coincident.

Religions 2017, 8, 110 12 of 24

Figure 2.FigureAnnual 2. Annual average average value value of the of rainythe rainy period period for for 184 184 localities localities of ofthe the Holy Land Land versus versus longitude longitude (a) and(a) latitude and latitude (b), from (b), 1990from 1990 to 2015, to 2015, according according to to the the IMS. IMS. Explicitly Explicitly indicatedindicated are are the the values values of of JerusalemJerusalem (J), Tel (J), Aviv Tel (T), Aviv Haifa (T), Haifa University University (HU), (HU), Nazareth Nazareth (N), (N), Malkiya Malkiya (M), (M), KalyaKalya (K).

Figure3 shows the annual average value of rainy days versus longitude (higher panel) and latitude (lower panel) for the same localities of Figure2. Squares give the value found in the EMV (49), triangles give the average value of 159 localities with latitude > 31.5◦ (about the latitude of Jerusalem), that is the minimum latitude reported in Figure1 for the localities with rainfall described in the EMV. The value obtained from the IMS data bank is 50.6 rainy days per year, practically as the value of the

Religions 2017, 8, 110 12 of 24

Religions 2017, 8, 110 12 of 23

EMV, 49. Figure3 shows also the values at ±1 standard deviation of the longitude and latitude found in the 159 localities with latitude > 31.5◦, and in the EMV localities. In longitude the displacement of the IMS and EMV sets is justiﬁed by the fact that some of the localities mentioned in the EMV are now in Jordan, and the corresponding meteorological statistical data are not recorded in the IMS databank. Conversely,Figure in latitude 2. Annual the average two sets value almost of the coinciderainy period because for 184 localities the latitude of the Holy of Jordan Land versus is about longitude the same of that of Israel(a) and and West latitude Bank. (b), from Notice 1990 that to 2015, in both according cases, to however,the IMS. Explicitly the average indicated values are the and values the standardof deviations areJerusalem almost (J), coincident. Tel Aviv (T), Haifa University (HU), Nazareth (N), Malkiya (M), Kalya (K).

Figure 3. Annual average value of rainy days for 184 localities of the Holy Land versus longitude (a) and latitude (b) from 1990 to 2015, according to the IMS. Triangles refer to the average value versus the average longitude or latitude and ±1 standard deviation of these parameters. Squares refer to the value obtained from the EMV (49) for the average longitude or latitude and ±1 standard deviation of these parameters for the 159 localities with latitude > 31.5◦ (minimum latitude of the localities of Table3). Explicitly indicated are the values of Jerusalem (J), Tel Aviv (T), Haifa University (HU), Nazareth (N), Malkiya (M), Kalya (K).

Besides the number of rainy days, another interesting statistical variable for current applications is the number of couples of rainy days, as established by the mathematical theory of de-integration of the quantity of water (rainfall) collected in 1 day (Matricciani 2013). The theory needs very few input data locally measured and two of them are just the number of rainy days and the number of couples of rainy days. The rainy days are those directly recorded by the meteorological services, such as the IMS, while the number of couples of rainy days is determined by examining a sequence of non-overlapping Religions 2017, 8, 110 13 of 24

Figure 3. Annual average value of rainy days for 184 localities of the Holy Land versus longitude (a) and latitude (b) from 1990 to 2015, according to the IMS. Triangles refer to the average value versus the average longitude or latitude and ±1 standard deviation of these parameters. Squares refer to the value obtained from the EMV (49) for the average longitude or latitude and ±1 standard deviation of these parameters for the 159 localities with latitude > 31.5° (minimum latitude of the localities of Table 3). Explicitly indicated are the values of Jerusalem (J), Tel Aviv (T), Haifa University (HU), Nazareth (N), Malkiya (M), Kalya (K).

Besides the number of rainy days, another interesting statistical variable for current applications Religions 2017,is8 ,the 110 number of couples of rainy days, as established by the mathematical theory of de-integration13 of 23 of the quantity of water (rainfall) collected in 1 day (Matricciani 2013). The theory needs very few input data locally measured and two of them are just the number of rainy days and the number of couples ofcouples days and of rainy by declaringdays. The rainy rainy days a are couple those ofdirectly days recorded in which by the it rainsmeteorological in the ﬁrst services, day, such or in the second day,as or the in IMS, both. while The the numbernumber of of couples couples of rainy of rainy days is days determined is another by examining parameter, a sequence as the of number non- of overlapping couples of days and by declaring rainy a couple of days in which it rains in the first day, rainy days, typical of a certain geographical area. The two variables are enough correlated. or in the second day, or in both. The number of couples of rainy days is another parameter, as the Figurenumber4 shows of rainy the days, annual typical average of a certain value geographical of the area. couples The two of variables rainy daysare enough versus correlated. longitude (higher panel)Figure and latitude 4 shows the (lower annual panel) average for value the of localities the couples of of Figure rainy days1. The versus number longitude of (higher couples of rainy dayspanel) deducible and latitude from the(lower EMV, panel) based for the on localities the chronology of Figure 1. reassumed The number in of Tablecouples3, of gives rainy 41 days couples and, if we excludededucible thefrom value the EMV, relative based toon thethe chronology latitude of reassumed Cyprus, in for Table comparing 3, gives 41 againcouples this and, result if we with exclude the value relative to the latitude of Cyprus, for comparing again this result with that obtained that obtained from the IMS, in a year we ﬁnd 40 × 365 ×380 = 38.4 couples. This result agrees very from the IMS, in a year we find 40 × 365 ×380 = 38.4 couples. This result agrees very well with the ◦ well with thevalue value 36.0 deduced 36.0 deduced from the from IMS data the bank IMS for data the bank159 localities for the with 159 latitude localities > 31.5°. with Once latitude more, we > 31.5 . Once more,can we notice, can notice,in Figure in 4, Figure a surprising4, a surprising correlation between correlation the average between values the deduced average from values the EMV deduced from the EMV(squares) (squares) and from and the from IMS (triangles). the IMS (triangles).

Religions 2017, 8, 110 14 of 24

Figure 4. AnnualFigure 4. average Annual valueaverage of value rainy of couplesrainy couples of 184 of 184 localities localities of of the the Holy Holy Land versus versus longitude longitude (a) and latitude(a) (b) and from latitude 1990 (b) from to 2015, 1990 to according 2015, according to the to IMS.the IMS. Triangles Triangles referrefer to to the the average average value value versus versus the average longitude or latitude and ± 1 standard deviation of these parameters. Squares refer to the the average longitude or latitude and ± 1 standard deviation of these parameters. Squares refer to the value obtained from the EMV (38.4) for the average longitude or latitude and ± 1 standard deviation value obtainedof these from parameters the EMV for (38.4) the 159 for localities the average with lati longitudetude > 31.5° or (minimum latitude latitude and ± of1 standardthe localities deviation of ◦ of these parametersTable 3). Explicitly for the indicated 159 localities are the withvalues latitudeof Jerusalem > 31.5 (J), Tel(minimum Aviv (T), Haifa latitude University of the (HU), localities of Table3).Nazareth Explicitly (N), indicated Malkiya (M), are Kalya the values(K). of Jerusalem (J), Tel Aviv (T), Haifa University (HU), Nazareth (N), Malkiya (M), Kalya (K). 5. Monthly Frequency of Rainy Days Let us observe the meteorological data with a finer temporal detail. Figure 5 shows, for each month of the year, the average value relative to 26 years, and the ± 1 standard deviation values of the rainy days for the 184 localities. Notice that the annual cycle is repeated for showing continuity. We can clearly see the strong seasonal pattern of the rainy days in the Holy Land, according to the IMS data bank. From these data we can calculate the average value and standard deviation expected for the distribution of days described in the EMV, by taking into account the number of days listed in Table 4, and the fact that these partial data refer to about 3 years, from August to July of every year, because the first rainy day in the EMV is August 3, 31 (Nazareth) and the last one is April 23, 34 (Jerusalem), according to Table 3, and that after April rainy days are extremely rare (Figure 5).

Religions 2017, 8, 110 14 of 23

5. Monthly Frequency of Rainy Days Let us observe the meteorological data with a ﬁner temporal detail. Figure5 shows, for each month of the year, the average value relative to 26 years, and the ± 1 standard deviation values of the rainy days for the 184 localities. Notice that the annual cycle is repeated for showing continuity. We can clearly see the strong seasonal pattern of the rainy days in the Holy Land, according to the IMS data bank. From these data we can calculate the average value and standard deviation expected for the distribution of days described in the EMV, by taking into account the number of days listed in Table4, and the fact that these partial data refer to about 3 years, from August to July of every year, because the ﬁrst rainy day in the EMV is August 3, 31 (Nazareth) and the last one is April 23, 34 (Jerusalem), accordingReligions 2017 to Table, 8, 1103 , and that after April rainy days are extremely rare (Figure5). 15 of 24

FigureFigure 5. 5.(a): (a): average average value value and and± ± 1 standard deviatio deviationn of of the the monthly monthly rainy rainy days days concerning concerning 184 184localities localities of of the the Holy Holy Land inin thethe yearsyears1990–2015, 1990–2015, from from January January (1) (1) to to December December (12). (12). (b): (b): standard standard deviation.deviation. Notice Notice that that each each annual annual cycle cycle is repeatedis repeated twice twice for for showing showing continuity. continuity.

LetLetmi and andsi be the be average the average value value and the and standard the standard deviation, deviation, respectively, respectively, of the rainy of the days rainy of the days i-thof month the i-th of themonth year, ofi =the1, year, 2, ... 12=1,2,…12, according, toaccording the IMS (Figureto the 5IMS), δ i(Figurethe number 5), of the days number described of days in thedescribed month i-th in according the month to i the-th according EMV (Table to4 ),thed iEMVthe number (Table of4), days the for number each month of days (31 forfor ieach= 1 etc.month). The(31 average for =1 value etc.). of The the rainyaverage days value for eachof the month rainy days found for from each the month IMS found data bank from (Figure the IMS5) data can bebank rescaled(Figure to 5) the can values be rescaled that have to beenthe values found accordingthat have tobeen the found number according of days describedto the number in the EMVof days (Tabledescribed4), thus in ﬁnding the EMV the (Table average 4), valuethus finding concerning the average the 380 daysvalue described concerning by the Maria 380 Valtorta:days described by Maria Valtorta: δi µi = m i (1) 3=di (1) 3 For example, for January, i = 1, the scaling factor that multiplies, mi is given by 21/(3 × 31). For example, for January, =1, the scaling factor that multiplies, is given by 21/(3 × 31). The The annual number of rainy days is thus given by: annual number of rainy days is thus given by: 12 G = µ = 17.2 (2) =∑ i = 17.2 (2) i=1 The total given by (2) is smaller than the long-term average value, namely 47.8 for the 184 localities considered in the IMS data bank, or 50.6 for the 159 localities with latitude > 31.5° because,

obviously, the partial number of monthly days observed in 3 years in the EMV () is smaller than the number of total monthly days observable in 3 years (3). On the other hand, going from 26 to 3 years and supposing that the observations are uncorrelated from month to month and from year to

year (hypothesis physically well grounded), the average monthly value can be considered as a random variable with average value given by Equation (1) and standard deviation given by:

=26/3 (3) Expression (3) is derived as follows. If is the number of uncorrelated occurrences (as we can assume for the monthly average of rainy days of successive years), then the standard deviation of the random variable “average value” is proportional to 1/√ (Papoulis 1990). Therefore going from =26 to =3 the standard deviation scales according to (3).

If now we consider the value at +1 standard deviation , we get the average value:

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The total given by (2) is smaller than the long-term average value, namely 47.8 for the 184 localities considered in the IMS data bank, or 50.6 for the 159 localities with latitude > 31.5◦ because, obviously, the partial number of monthly days observed in 3 years in the EMV (δi) is smaller than the number of total monthly days observable in 3 years (3di). On the other hand, going from 26 to 3 years and supposing that the observations are uncorrelated from month to month and from year to year (hypothesis physically well grounded), the average monthly value µi can be considered as a random variable with average value given by Equation (1) and standard deviation given by: √ σi = si 26/3 (3)

Expression (3) is derived as follows. If N is the number of uncorrelated occurrences (as we can assume for the monthly average of rainy days of successive√ years), then the standard deviation of the random variable “average value” is proportional to 1/ N (Papoulis 1990). Therefore going from N = 26 to N = 3 the standard deviation scales according to (3). If now we consider the value at +1 standard deviation σi, we get the average value: √ + δi µi = mi + si 26/3 (4) 3di

And from (4) a total number of annual rainy days given by:

12 + G = ∑ µi = 51.2 (5) i=1 which agrees very well with the long-term value 47.8 for the 184 localities, or even better with 50.6 for the 159 localities with latitude > 31.5◦ (Figure3). In other words, the experimental data state that the value given by the combination of Equations (4) and (5) is a more precise estimate of the average monthly rainy days for a period of 3 years randomly observed (for rainfall) for only 380 days, as reported in Table4, compared to the long-term period (26 years). Notice that if the value given by (2) is directly scaled to 3 years, we get about the same value given by (5), namely 17.2 × 3 × 365/380 = 49.6. Let us apply the same reasoning to the rainy days described in the EMV. It is found:

380 µ = δ (6) i,EMV 3 × 365 i

12 GEMV = ∑ µi,EMV = 17.7 (7) i=1

The average value at +1 standard deviation σi is given by:

380 √ µ+ = δ + s 26/3 (8) i,EMV 3 × 365 i i

Therefore, the total number of rainy days in 380 days is estimated as:

12 + = + = GEMV ∑ µi,EMV 51.6 (9) i=1 a value which is very close to that deduced from the IMS (51.2). From it we get an average annual value 51.6 × 365/380 = 49.6, again very close to the annual number of rainy days (49.0) described in the EMV. If (7) is directly scaled to 3 years we get 17.7 × 3 × 365/380 = 51.0, a result which conﬁrms (8) and (9). Religions 2017, 8, 110 16 of 23

Figure6 reassumes all these results and clearly shows the very good agreement just discussed. We have drawn the monthly average value of the rainy days relative to 184 localities of the Holy Land (curve IMS, circles), or for 3 years and only 380 days (according to Table4, curve IMS EMV, diamonds), as given by Equation (4) from the IMS data bank. The curve labeled EMV (squares) shows the number of monthly days obtained from the EMV, Equation (8). The agreement is very good. In other words, the estimate of the number of rainy days from the monthly distribution (8) seems to be statistically Religions 2017, 8, 110 17 of 24 very reliable.

Monthly Rainy Days EMV

IMS 10 IMS EMV EMV

5 Rainy Days Rainy

0 2 4 6 8 10 12 14 16 18 20 22 24 Month Figure 6. Monthly average value of the rainy days for about 26 years (1990–2015) relative to 184 localities Figure 6. Monthly average value of the rainy days for about 26 years (1990–2015) relative to 184 of the Holy Land (curve IMS, circles), or for 3 years and only 380 days (according to Table4) (curve IMS localities of the Holy Land (curve IMS, circles), or for 3 years and only 380 days (according to Table EMV, diamonds), Equation (4), from the IMS data bank. The curve labeled EMV (squares) shows 4) (curve IMS EMV, diamonds), Equation (4), from the IMS data bank. The curve labeled EMV the number of monthly days obtained from the EMV, Equation (8). Notice that each annual cycle is (squares) shows the number of monthly days obtained from the EMV, Equation (8). Notice that each repeated twice for showing continuity. annual cycle is repeated twice for showing continuity.

InIn conclusion, also also the the finer finer analysis on the mo monthlynthly frequency of rainy days indicates that the observation of of rainfall reported in the EMV cannot be attributed to the literary invention of Maria Valtorta, but it seems as if she had been a witness of real rain in the Holy Land 2000 years ago. As we have mentioned in Section 22,, MariaMaria ValtortaValtorta hadhad nono significantsignificant mathematicalmathematical abilityability toto inventinvent suchsuch coherent data, moreovermoreover consideringconsidering thethe years years of of war war and and the the bombing bombing of of Viareggio Viareggio that that caused caused her her to tomove move in in another another smaller smaller village, village, in in her her fragile fragile conditions. conditions. Frankly Frankly speaking,speaking, thethe statementstatement that she has invented everything is not defensible, also be becausecause the probability of randomly generated such a coherent picturepicture isis low,low, 2% 2% for for the the year, year, between between 2% 2% and and 15% 15% for thefor singlethe single months months for the for single the single rainy rainydays anddays even and smallereven smaller (0.45%) (0.45%) for the for yearly the yearly rainy rainy couples couples with bothwith daysboth rainydays rainy (see Appendix (see AppendixA). A). Now we have to discuss the second issue, namely whether the climate of the Holy Land has changedNow in we the have last to 2000 discuss years the and, second in case issue, of positivenamely whether answer, ifthe these climate changes of the could Holy hinder Land has the changedpossibility in to the compare last 2000 statistically years and, EMS in rainycase of days positive data with answer, the IMSif these data changes bank values. could hinder the possibility to compare statistically EMS rainy days data with the IMS data bank values. 6. Is the Holy Land Climate Changed in the Last 2000 Years? 6. Is theToday Holy the Land Holy Climate Land seems Changed more in arid the andLast less2000 rainy Years? that 2000 years ago. According to these authors,Today the the change Holy seems Land to seems have occurredmore arid because and less of rainy many that causes, 2000 both years climatic ago. According (climate cycles) to these and authors,due to human the change activities seems (wars, to have destructions, occurred giving becaus upe agriculture)of many causes, (Huntington both climatic 1908, part(climate I pp. 513–22,cycles) andpart due II pp. to 577–86,human activities part III pp. (wars, 641–52). destructions, In the last gi decadesving up agriculture) in the Mediterranean (Huntington Sea 1908, there part has I been pp. 513–22,a general part tendency II pp. 577–86, to a reduction part III pp. of 641–52). the quantity In the of last rainfall decades and, in atthe the Mediterranean same time, an Sea increase there has in beenthe peak a general values tendency of precipitation to a reduction (maxima), of the with quantity more rigid of rainfall winters and, and at hotter the same summers. time, an In increase the East inMediterranean the peak values there of hasprecipitation been a conflicting (maxima), tendency with more in the rigid years winters 1951–1990 and hotter as, an summers. exception In to the Eastgeneral Mediterranean tendency, in there the geographical has been a conflicting area that includes tendency Negev in the and years the center-south1951–1990 as, of an the exception Holy Land, to thethe general quantity tendency, of total precipitation in the geographical is increased area that (Alpert includes et al. Negev 2004), and likely the because center-south of a different of the Holy use Land,of the the land quantity (agriculture of total activity) precipitation (Abert etis al.increase 2008).d Besides (Abert et the al. tree 2004), rings’ likely study because already of mentioneda different use(Esper of etthe al. land2012 ),(agriculture another interesting activity) result (Abert that et refers al. 2008). directly Besides to the Holythe tree Land rings’ climate study at the already time of mentionedJesus and to (Esper that of et today al. 2012), is the another level of interesting the Dead Sea,result which that refers shows directly a peak dueto the to Holy wetter Land climate climate just at the time of Jesus and to that of today is the level of the Dead Sea, which shows a peak due to wetter climate just 2000 years ago (McCormick et al. 2012, see their Figure 7) with the level estimated in 394 m below the Mediterranean sea, close to the level peak found in the 1950’s (390 m). In our analysis we have compared to the current values the only meteorological variable that is possible to examine quantitatively in Maria Valtorta’s writings, namely the number of rainy days observed in the EMV, under the hypothesis that this random variable has not drastically changed in the last 2000 years. This seems to be indeed the case because this random variable is stable in long intervals, as Figure 7 shows, as an example, for Jerusalem in the years 1862–2014. The smoother curves have been obtained by filtering the original time series with a numerical kernel that filters out

Religions 2017, 8, 110 17 of 23

2000 years ago (McCormick et al. 2012, see their Figure 7) with the level estimated in 394 m below the Mediterranean sea, close to the level peak found in the 1950’s (390 m). In our analysis we have compared to the current values the only meteorological variable that is possible to examine quantitatively in Maria Valtorta’s writings, namely the number of rainy days observed in the EMV, under the hypothesis that this random variable has not drastically changed in the last 2000 years. This seems to be indeed the case because this random variable is stable in long intervals,Religions 2017 as, 8 Figure, 110 7 shows, as an example, for Jerusalem in the years 1862–2014. The smoother curves18 of 24 have been obtained by filtering the original time series with a numerical kernel that filters out the the sinusoidal components with period shorter than 10 years to reduce the short-term fluctuations. sinusoidal components with period shorter than 10 years to reduce the short-term fluctuations. Besides Besides the short-term fluctuations, typical of any meteorological variable, it is evident the large the short-term fluctuations, typical of any meteorological variable, it is evident the large stability of stability of this variable for more than a century, with average value 52.7 days and standard deviation this variable for more than a century, with average value 52.7 days and standard deviation 11.9 days. 11.9 days. If Maria Valtorta had had the recent rainy days data of Jerusalem and filtered the data, she If Maria Valtorta had had the recent rainy days data of Jerusalem and filtered the data, she would have would have seen, before 1943, a time series of increasing number of rainy days in the years 1930 to seen, before 1943, a time series of increasing number of rainy days in the years 1930 to 1943. Of course, 1943. Of course, it is unlikely that a science and mathematics illiterate, as she was, could model the it is unlikely that a science and mathematics illiterate, as she was, could model the raw data shown raw data shown in Figure 7 or averaged them. In other words, she could not invent the average results in Figure7 or averaged them. In other words, she could not invent the average results found in her found in her writings, very similar to the long term values found in the Holy Land. writings, very similar to the long term values found in the Holy Land.

Annual Rainy Days Jerusalem 1862-2014 100

Days 40

0 1860 1880 1900 1920 1940 1960 1980 2000 Year

Figure 7. Time series of the number of the rainy days occurred in Jerusalem in the month of December, Figure 7. Time series of the number of the rainy days occurred in Jerusalem in the month of December, from 1862 to 2014 (153 years). The smoother (red) curve is the result of ﬁltering the original time series from 1862 to 2014 (153 years). The smoother (red) curve is the result of filtering the original time series by cancelling the components with period less than 10 years. For rainy days the average value is by cancelling the components with period less than 10 years. For rainy days the average value is 52.7 52.7 days, the standard deviation is 11.9 days. days, the standard deviation is 11.9 days.

ToTo further clarify clarify this this point point Figu Figurere 8 8shows shows the the time time series series of th ofe number the number of rainy of days rainy (higher days (higherpanel) and panel) the and quantity the quantity of water of precipitated water precipitated and ac andcumulated accumulated in the insame the sameday (lower day (lower panel) panel) in each in eachmonth month of December of December in the in theyears years 1862–2014 1862–2014 (153 (153 year years)s) in in Jerusalem. Jerusalem. The The average average number number of rainy daysdays isis 9.5,9.5, thethe standardstandard deviationdeviation 3.83.8 days,days, thethe averageaverage quantityquantity ofof waterwater isis 10.810.8 cmcm withwith standardstandard deviationdeviation 7.87.8 cm,cm, i.e.,i.e., 72%72% ofof thethe average.average. FigureFigure9 9 shows shows the the scatterplot scatterplot between between the the two two variables variables concerningconcerning the same same year. year. The The correlation correlation is is0.670.67 ±± 0.060.0600 forfor the the original original data, data, and and 0.570.57 ± 0.06± 0.0677 for forthe thefiltered filtered data. data. The Thelatter, latter, without without short-term short-term fluctuations, fluctuations, are more are moreadapt adapt to evidence to evidence the long- the long-termterm temporal temporal relationship. relationship. We Wecan can notice notice that that by by calculating calculating the the coefficient coefficient of of determination determination only 100100× ×0.67 0.672==45% 45%of of the the variance variance of of the the water water precipitated precipitated is explained,is explained, or itor can it can be predicted,be predicted, by the by numberthe number of rainy of rainy days days in the in raw the data,raw data, and onlyand only100 × 1000.57 ×2 = 0.5732% =in 32% the filtered in the filtered data. In data. other In words, other thewords, two the variables two variables are loosely are correlated loosely correlated and this isand more this evident is more in evident the filtered in the data. filtered It is possible data. It tois findpossible months to find with months the same withnumber the same of rainy number days of but rainy with days very butdifferent with veryquantity different of water quantity precipitated. of water precipitated.

Religions 20172017,, 88,, 110110 1819 of 2324 Religions 2017, 8, 110 19 of 24

Figure 8. Time series of the number of the rainy days (a) and total quantity of precipitated water (b) FigureFigure 8. Time8. Time series series of of the the number number of of the the rainy rainy days days (a) (a) and and total totalquantity quantity ofof precipitatedprecipitated water (b) (b)expressed expressed in cm in cmof height of height for fora surface a surface of 1 of m 12 m, in2, Jerusalem in Jerusalem in the in the month month of December, of December, from from 1862 1862 to expressed in cm of height for a surface of 1 m2, in Jerusalem in the month of December, from 1862 to to2014 2014 (153 (153 years). years). The The smoother smoother (red) (red) cu curvesrves are are the the results results of of filterin ﬁlteringg the the original original time series by 2014 (153 years). The smoother (red) curves are the results of filtering the original time series by cancelling thethe components withwith periodperiod lessless thanthan 10 years. For rainy da daysys the average value is 9.5 days, cancelling the components with period less than 10 years. For rainy days the average value is 9.5 days, the standard deviation deviation is is 3.8 3.8 days. days. For For water, water, the the av averageerage value value is is10.8 10.8 cm cm with with standard standard deviation deviation 7.8 the standard deviation is 3.8 days. For water, the average value is 10.8 cm with standard deviation 7.8 7.8cm, cm, i.e.,i.e., 72% 72% of the of theaverage. average. cm, i.e., 72% of the average.

December,December, Jerusalem Jerusalem 1862-2014 1862-2014 40 40

35 35

30 30

25 25

20 20

Water (cm) Water 15

10 10

5 5

0 0 0 5 10 15 20 0 5 10 15 20 RainyRainy Days Days

Figure 9. Scatterplot between the number of rainy days and the total quantity of precipitated water FigureFigure 9. Scatterplot 9. Scatterplot between between the the number number of rainyof rainy days days and and the the total total quantity quantity ofprecipitated of precipitated water water expressed in cm of height for a surface of 1 m22, in Jerusalem in the month of December, from 1862 to expressedexpressed in cm in cm of height of height for afor surface a surface of 1 of m 1 ,m in2, Jerusalem in Jerusalem in the in the month month of December, of December, from from 1862 1862 to to 2014 (153 years). The average number of rainy days is 9.5, the standard deviation 3.8 days; the average 20142014 (153 (153 years). years). The The average average number number of rainy of rainy days days is 9.5, is 9.5, the the standard standard deviation deviation 3.8 days;3.8 days; the the average average quantity of water is 10.8 cm with standard deviation 7.8 cm, i.e., 72% of the average. The correlation quantityquantity of water of water is 10.8 is 10.8 cm cm with with standard standard deviation deviatio 7.8n cm,7.8 cm, i.e., i.e., 72% 72% of the of the average. average. The The correlation correlation coefficient is 0.67. coefﬁcientcoefficient is 0.67. is 0.67.

Moreover,Moreover, let letus usnow now consider consider the the geographical geographical dispersion dispersion of theseof these data data by bycalculating calculating the the monthlymonthly averages averages relative relative to theto the 184 184 localities localities in thein the years years from from 1990 1990 to 2015.to 2015. Figure Figure 10 10shows shows the the scatterplotscatterplot between between the the number number of theof the monthly monthly average average quantity quantity of waterof water ( ,( in, cmin cm of heightof height for fora a

Religions 2017, 8, 110 19 of 23

Moreover, let us now consider the geographical dispersion of these data by calculating the monthly averages relative to the 184 localities in the years from 1990 to 2015. Figure 10 shows the scatterplotReligions 2017, between 8, 110 the number of the monthly average quantity of water (w, in cm of height20 for of 24 a 2 surface of 1 m ) and the average number of monthly rainy days (dR). The regression function that surface of 1 m2) and the average number of monthly rainy days ( ). The regression function that minimizes the mean squared error between data and model is given by the parabola: minimizes the mean squared error between data and model is given by the parabola: = × + × 2 w =0.530 0.530 ×d R +0.058 0.058 ×d R (10)(10)

FigureFigure 11 11 shows, shows, in in the the upper upper panel, panel, the scatterplotthe scatterplot of the of difference the difference between between the monthly the monthly average quantityaverage ofquantity precipitated of precipitated water of Figure water 10of andFigure the 10 regression and the curveregression Equation curve (10), Equation named (10), delta named water, anddelta the water, average and number the average of monthly number rainy of monthly days, relative rainy thedays, 184 relative localities the of 184 the localities Holy Land, of the for Holy each monthLand, for in theeach years month from in 1990 the years to 2015. from In the1990 lower to 2015. panel In the the scatterplot lower panel between the scatterplot the same between quantities the is shown,same quantities but with theis shown, difference but givenwith the in percentdifference (%) given of the in value percent of the (%) regression of the value curve. of the We regression can notice that,curve. according We can notice to the averagethat, according relationship to the (10), average the average relationship quantity (10), of the monthly average water quantity accumulated of monthly can changewater accumulated∓60% for the can same change number ∓60% of average for the rainy same days number of the of month. average Notice rainy that days this of geographical the month. spreadNotice isthat numerically this geographical close to the spread temporal is numericall spread (72%)y close obtained to the intemporal the years spread 1862–2014 (72%) for obtained the month in ofthe December years 1862–2014 in Jerusalem for the (Figure month8 ).of Therefore December long-term in Jerusalem changes (Figure in the8). Therefore random variable long-termw arechanges very likelyin the maskedrandom byvariable the spread are found very likely in the masked region. Inby other the spread words, found the possible in the region. climatic In changesother words, that afterthe possible 2000 years climatic might havechanges affected that the after quantity 2000 ofye waterars might accumulated have affected daily in the the quantity Holy Land of shouldwater haveaccumulated affected daily the number in the Holy of rainy Land days should very have loosely. affected the number of rainy days very loosely.

FigureFigure 10.10. Scatterplot between the number of thethe monthlymonthly averageaverage quantityquantity ofof precipitatedprecipitated waterwater expressedexpressed inin cmcm ofof heightheight forfor aa surfacesurface ofof 11 mm22 andand thethe averageaverage numbernumber ofof monthlymonthly rainyrainy daysdays concerningconcerning 184184 localities localities of theof the Holy Holy Land, Land, for each for montheach month in the yearsin the from years 1990 from to 2015. 1990 The to regression2015. The lineregression is the parabola line is the given parabola by (10). given by (10).

TheseThese resultsresults conﬁrmconfirm thatthat thethe numbernumber ofof rainyrainy daysdays isis aa randomrandom variablevariable quitequite independentindependent ofof somesome climateclimate changeschanges thatthat maymay havehave occurredoccurred inin thethe HolyHoly LandLand inin thethe lastlast 20002000 yearsyears and,and, forfor thisthis reason,reason, itit allows allows a a reliable reliable statistical statistical comparison comparison between between the meteorologicalthe meteorological information information derived derived from thefrom EMS the analysisEMS analysis and the and current the current data derived data derived from thefrom IMS. the IMS.

Religions 2017, 8, 110 20 of 23 Religions 2017, 8, 110 21 of 24

FigureFigure 11. 11.(a): (a): scatterplot scatterplot of theof the difference difference between between the the monthly monthly average average quantity quantity of precipitated of precipitated water ofwater Figure of 10 Figure and the 10 regressionand the regression curve (10), curve named (10), Deltanamed Water, Delta andWater, the and average the average number number of monthly of rainymonthly days rainy concerning days concerning 184 localities 184 oflocalities the Holy of th Land,e Holy for Land, each for month each month in the yearsin the fromyears 1990from to1990 2015. (b):to scatterplot 2015. (b): scatterplot of the same of the quantities same quantities but with but the wi differenceth the difference given given in percent in percent (%) of (%) the of value the value of the parabolicof the parabolic regression regression curve (10). curve (10).

7. Conclusions7. Conclusions TheThe richness richness of of narrative narrative elements elements containedcontained in The Gospel Gospel as as revealed revealed to to me me byby Maria Maria Valtorta Valtorta has has allowedallowed to to pursue pursue both both astronomical astronomical and and meteorologicalmeteorological studies, suited suited to to verify verify as as much much as aspossible possible whatwhat she she states. states. Indeed, Indeed, Maria Maria Valtorta Valtorta afﬁrmedaffirmed to have witnessed witnessed in in mystic mystic visions visions the the life life of ofJesus, Jesus, andand in particularin particular his threehis three years years of public of public life, reporting life, reporting detailed detailed descriptions descriptions of landscapes, of landscapes, costumes, uses,costumes, roads, townsuses, roads, with theirtowns buildings with their (including buildings the(including Temple the in Jerusalem)Temple in Jerusalem) and streets, and rivers, streets, lakes, hills,rivers, valleys, lakes, plantations, hills, valleys, climate plantations, and rainfall climate rainy days,and rainfall night sky rainy with days, its constellations, night sky with stars its and constellations, stars and planets in the Holy Land, all information that should belong to a period of planets in the Holy Land, all information that should belong to a period of 2000 years ago. This is 2000 years ago. This is not possible from a rational point of view, but from this study a surprising not possible from a rational point of view, but from this study a surprising and unexpected result and unexpected result emerges: Maria Valtorta narration seems to be not a fruit of her fantasy. In emerges: Maria Valtorta narration seems to be not a fruit of her fantasy. In fact, thanks to a complex and

Religions 2017, 8, 110 21 of 23 rigorous astronomical analysis of the narrative elements present in her writings, it has been possible to determine a precise chronology of every event of Jesus’ life that she tells us, even if no explicit calendar date is reported in her writings. In particular, this study has led to dating the crucifixion of Jesus in Friday, April 23 of the year 34, a date already proposed by da I. Newton. Maria Valtorta has also recorded in the EMV the presence of rain and this has suggested to compare her observations with the current meteorological data concerning the number of rainy days in the Holy Land, as recorded by the Israel Meteorological Service (IMS), because this random variable, as shown, seems to be quite independent by the limited climatic changes that have characterized the Holy Land in the last 2000 years. What has emerged is, once more, surprising and unexpected because the annual and even the monthly frequencies of rainy days found in the EMV correspond to what we find today in the IMS data bank. It seems that she has written down observations and facts really happened at the time of Jesus’ life, as a real witness of them would have done. The question arises, unsolved from a point of view exclusively rational, how all this is possible because what Maria Valtorta writes down cannot, in any way, be traced back to her fantasy or to her astronomical and meteorological knowledge. In conclusion, if from one hand the scientific inquire has evidenced all the surprising and unexpected results reported and discussed in this paper, on the other hand our actual scientific knowledge cannot readily explain how these results are possible.

Acknowledgments: We wish to thank the Israel Meteorological Service for the raw data bank freely available on their web site https://ims.data.gov.il. Author Contributions: Liberato De Caro performed the astronomical analysis to obtain calendar dates. Emilio Matricciani performed the meteorological analysis. Both authors discussed and interpreted the obtained results, and wrote the paper. Conﬂicts of Interest: The authors declare no conﬂict of interest.

Appendix A Could the observed strong correlations, between meteorological data extracted by the EMV and those of the IMS data bank, be the result of a fortuitous coincidence, due to randomly generated rainy days? To verify this point, let us consider that the Binomial distribution originates in an experiment with independent repeated trials and it allows to estimate the probability of ﬁnding k rainy days in observing n days. In our case, according to the IMS data bank, the annual probability of ﬁnding x = k rainy days is given:

! ( 2 ) 380 n k n−k ∼ 380 1 (k − np) P{x = k} = p (1 − p) = p exp − p (A1) 1204 k 1204 2πnp(1 − p) 2 np(1 − p)

The scaling factor 380/1204 takes care of the reduced observation period, and in (A1) k = 51, n = 365, p = 51/365. The Gaussian approximation in the right member is the limit of the Binomial distribution for large integers (see Papoulis 1990, p. 108), as is the case in (A1). Since we compute (A1) at the average value k = np, we get: ! 380 n k n−k ∼ 380 1 P{x = k} = p (1 − p) = p = 0.0191 = 1.91% (A2) 1204 k 1204 2πnp(1 − p)

Likewise, we can calculate the probability of couples of rainy days at the average value, now with k = 38.4, n = 365/2, p = 2 × 38.4/365

∼ 380 1 P{x = 38.4} = p = 0.0229 = 2.29% (A3) 1204 2πnp(1 − p) Religions 2017, 8, 110 22 of 23

For the subset of couples of days both rainy, the probability is even smaller. In the IMS data bank there are 50.6 single rainy days/year and 36 rainy couples/year, therefore the number of rainy couples with both days rainy is approximately (50.6 − 36)/2 =∼ 7 and thus the probability of this event is given 7 by 36 × 2.29 = 0.45%. In the EMV, in 380 days of observation, we have counted 51 single rainy daysReligions and 2017 40, 8 rainy, 110 couples (this latter count may be imprecise of few units because of the day chosen23 of 24 for starting the count, while in the IMS data bank it is precise by assuming January 1 as the starting day),40)/2 therefore ≅ 6. The thenumber number found of rainyin 380 couples days of with observation both days is 8, rainy close is to approximately the yearly average(51 − of40 )the/2 IMS=∼ 6. Thedata. number found in 380 days of observation is 8, close to the yearly average of the IMS data. Let us consider consider the the monthly monthly rainy rainy days. days. Because Because of ofthe the smaller smaller integer integer values values in this in thiscase, case, the theBinomial Binomial distribution distribution can can be used be used directly directly.. For For example, example, the the probability probability of of finding ﬁnding ==11x = k = 11 rainy days (the monthly averageaverage valuesvalues areare approximatedapproximated toto thethe nearestnearest integer)integer) inin JanuaryJanuary isis givengiven by:by:

21 31 !11 11 11 31−11 =11 = 21 31( 11)(1 − 11) = 0.0334 = 3.34% (A4) P{x = 11} = 3×31 11 31( ) (1 −31 ) = 0.0334 = 3.34% (A4) 3 × 31 11 31 31 Figure A1 shows the probability for each month. We can see that it never exceeds about 15%. Figure A1 shows the probability for each month. We can see that it never exceeds about 15%. Not to mention the couples of days both rainy, if Maria Valtorta had randomly described rainy days Not to mention the couples of days both rainy, if Maria Valtorta had randomly described rainy days in each month, she would have had the above probabilities of correctly guessing the number of the in each month, she would have had the above probabilities of correctly guessing the number of the average rainy days per month which, as we have shown, in the EMV are found to closely follow the average rainy days per month which, as we have shown, in the EMV are found to closely follow the IMS data (Figure 6). Therefore, her observations are very unlikely the result of a fortuitous IMS data (Figure6). Therefore, her observations are very unlikely the result of a fortuitous coincidence. coincidence. Random extraction of average rainy days 20

5 Probability (%) 0 2 4 6 8 10 12 14 16 18 20 22 24 Month

Figure A1. Probability of randomly ﬁnding the average number of rainy days for each month, according Figure A1. Probability of randomly finding the average number of rainy days for each month, to the IMS daily rainfall data bank in the years from 1990 to 2015, concerning 184 localities of the Holy according to the IMS daily rainfall data bank in the years from 1990 to 2015, concerning 184 localities Land. Notice that each annual cycle is repeated twice for showing continuity. of the Holy Land. Notice that each annual cycle is repeated twice for showing continuity.

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