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Article

Electric Field Variations Caused by Low, Middle and High-Altitude Clouds over the Negev Desert, Israel

1
Exom Space, Tel Aviv 6329302, Israel
2
School of Sustainability, Reichmann University, Herzliya 4610101, Israel
*
Author to whom correspondence should be addressed.
Atmosphere 2022, 13(8), 1331; https://doi.org/10.3390/atmos13081331
Submission received: 8 August 2022 / Revised: 16 August 2022 / Accepted: 19 August 2022 / Published: 21 August 2022
(This article belongs to the Special Issue Atmospheric Electricity)

Abstract

:
Ground-based measurements of the electric field from a station located in the arid Negev region of southern Israel have been conducted continuously since 2013. We present here results of observations of the electric field (Potential Gradient, PG) variability during 22 cloudy days, with varying cloud types and cloud base heights, and compare the measured values with the mean fair-weather PG. The results show an increase of PG (~+10 to +70 V m−1) from mean fair weather values during times of low clouds. During times of mid-altitude (alto) clouds or during a superposition of low and high clouds, there were small departures in the PG values (~0 to −30 V m−1) compared to mean fair weather PG values. During times of high-altitude cirrus clouds there is a clear decrease of the PG (~−40 to −90 V m−1). The data was compared with the Israeli meteorological service cloud data and with MODIS 7 satellite cloud top height maps. In addition, AERONET aerosol optical depth values and wind speed magnitude from a local meteorological station were analyzed.

1. Introduction

The fair-weather part of the Global Electric Circuit (GEC) concept is manifested through several atmospheric observables, some of which had been monitored in various locations for over a century [1,2,3], offering a long-term record that helps in tracking global changes. The vertical component of the atmospheric electric field (Ez; sometimes referred to as the inverse of the Potential Gradient, Ez = −PG) is one of the best recorded parameters, along with the vertical current (Jz) and the ionospheric potential. The PG was shown to be affected by natural and anthropogenic processes such as pollution, dust, fog and relative humidity, as well as topographic effects and sources of ionization that depend on the local mineralogy. The well-known “Carnegie curve” shows a robust diurnal variation of the Potential Gradient at a given location with a maximum around 19 UT and a minimum around 3 UT with fair weather values ranging from +100 to +300 V m−1 (pointing downward), exhibiting a clear daily and seasonal variability [4,5,6,7].
Land-based observations of the atmospheric electric field show that local meteorology and aerosol variations, such as relative humidity, precipitation types and pollution [8,9,10,11,12,13] can lead to significant variability in the diurnal PG behavior. Aerosols are known to decrease conductivity and therefore, for maintaining a constant vertical current density in the global circuit (in accordance with Ohm’s law), they cause an increase in the PG [1,2]. With respect to clouds, Harrison [8] found that PG values during overcast conditions are slightly reduced compared to fair weather clean conditions. The reason is an increase in the columnar resistance by the cloud layer compared with that of clear air; They found that the relative contribution will vary with the depth and height of the cloud layer. Harrison and Nicoll [14] further reported that during overcast conditions, when the cloud base is above 1 km there is little associated variability in the PG data but when the cloud base is well below 1 km, the PG variability is substantial. Nicoll and Harrison [15] sampled 22 clouds by balloon-borne platforms and showed that stratiform cloud boundaries were charged asymmetrically, with the upper part charged positively +32 pC m−3 and the lower −24 pC m−3. This difference is attributed to temperature inversions at cloud top. Their results show that lower laying clouds (below 2 km) are charged more than higher clouds, and this affects cloud microphysics and lifetime. For cases when the cloud was in contact with the ground (fog) the measurement indicated an increase in the electric field [16] with patterns of pulsations, reflecting turbulent processes within the cloud layer.
This paper reports on ground-based PG measurements during overcast conditions by various types of clouds at the Wise Observatory in the Negev desert in southern Israel. We will use the conventional terminology of Potential Gradient throughout the manuscript.

2. Instrumentation, Observation Site and Data

As in previous studies, we used a CS110 electric field mill by Campbell Scientific Company that samples the vertical component of the electric field (Ez) at 1 Hz. The specific information on the Wise observatory can be found in [10,17,18] Measurements of the Ez at the Wise Observatory began in June 2013 and have been conducted almost continuously, with data saved in a data-logger and on an external USB drive. Most of the data had already been uploaded to the GloCAEM database at Reading University [19] and is available to the depository registered users. The Wise Observatory also operates a meteorological weather station which provides data of temperature, humidity, pressure and wind speed.
For cloudiness data, we used the data archive of the Israeli Meteorological Service (IMS) (https://ims.data.gov.il/ims/1 (Accessed on 15 July 2022)) that provides weather data from Israel including types of clouds, height of cloud base, amount of low, middle and high clouds and cloud amount in oktas eighths. The data is open for the public and available in Hebrew and copyrighted to the state of Israel.
The AERONET (AErosol RObotic NETwork) project is a federation of ground-based remote sensing aerosol networks established by NASA which provides globally distributed observations of spectral aerosol optical depth (AOD). The station is located in Sde-Boker, southern Israel (30.855 N, 34.782 E), approximately 20 km north from the Wise Observatory.
The MODIS (or Moderate Resolution Imaging Spectroradiometer) is a key instrument on-board NASA’s Terra and Aqua satellites. The MODIS Cloud Product combines infrared and visible techniques to determine both physical and radiative cloud properties and provides cloud top height data layer which indicates the geopotential height of the highest cloud top at a retrieved cloud top pressure. The data is obtained from the worldview open-source code app website (https://worldview.earthdata.nasa.gov/ (Accessed on 15 July 2022)) and provides interactively browse global, full-resolution satellite imagery layers and then download the underlying data.

3. Results

An analysis of 22 days was performed to investigate the relationship between the types of clouds and overcast conditions in order to identify their effect on the ground measured electric field. The measured Ez values were transformed to Potential Gradient PG ( P G = | E z | ). A summary of the results is presented in Table 1 and includes calculated average cloud-base altitude data that was retrieved from satellite images and from the Israeli Meteorological Service (IMS) archive. Data from the IMS included cloud types, cloud top and base heights as well. It should be noted that in some cases there were several layers of clouds, thus a superposition effect was considered in the analysis and an average height was considered to represent the combined effect of the cloud layers on the PG value measured at the surface. For the average height, we assumed that each cloud layer is horizontally infinite with respect to the ground station, rather than assuming a single finite cloud that approximately acts as a point charge. Thus, several layers of clouds are assumed to be acting like 2 plates with a uniform electric field.
The mean electric field (PG) data for each day was calculated from 11–17 LT and was compared to the mean PG fair-weather (FW) values taken from present and past measurements (Yaniv et al., 2016) to calculate the difference ∆PG during times of overcast skies with clouds at various altitudes. “High” and “FW” in Table 1 refer to higher or identical values compared with the values measured during fair weather conditions, respectively. In the same manner, the measured wind speed values were compared to the fair-weather criteria of wind speed in the range 1–8 m s−1 (Harrison and Nicoll 2018) and noted as “FW” or “High” values. The obtained Aeronet AOD values vs. fair weather conditions will be explained in Figure 4.
Figure 1 presents two examples for the usage of satellite images and the PG variations during daytime hours (11–17 LT). Slightly higher PG values (mean ~160 V m−1) compared with normal fair-weather values (mean ~150 V m−1) were recorded for the 4 January 2018 event, which was dominated by a low cloud layer (Figure 1 top). Substantially lower PG values (mean ~102 V m−1) relative to the normal fair-weather values (mean ~170 V m−1) were recorded for the 6 February 2018 event, which was dominated by a high cirrus cloud layer (Figure 1 bottom).
The integrated results depicting cloud effects on the mean PG values for the 22 days that were analyzed in the present study are shown in Figure 2 and Figure 3. It is clearly seen that low cloud layer corresponds to PG values that are higher than fair weather conditions in Mitzpe Ramon (Figure 2). Middle level clouds (alto) tend to result in PG values that are slightly lower than fair weather values while high cirrus cloud layers PG values effects tend to lower the PG values compared with the mean fair-weather values.
Figure 3 shows the median value as a function of the variability representing the effects of the various cloud layers. The ∆PG from fair weather values of low clouds is 26 ± 24 V m−1, middle level clouds (alto) is −10 ± 17 V m−1 and for high cirrus layers it is −56 ± 20 V m−1.
Figure 4 shows for each of the 22 days presented in Table 1 the mean value of the Aerosol Optical Depth (AOD) between 11–17 LT. For 19 days data was available. It also presents a comparison to the range of fair-weather mean AOD value (0.17–0.3 nm) derived from [10,20]. Higher aerosol concentrations were recorded on days 5, 10, 20, 22 in Table 1, but the values of PG that were recorded were lower or the same compared with fair weather conditions. This is likely due to the overcast conditions by high and mid-altitude clouds or a superposition effect of both clouds and high aerosol concentrations. During the events with the very high aerosols concentration, wind speed values were low in the range of fair-weather criteria (e.g., 1–8 m s−1) [14].
Only 3 days (1, 2, 13) out of the 22 were found with higher wind speed values that were greater than the 8 m s−1 maximum value of fair-weather condition criteria [14] (the values were 2–14 or 6–20 m s−1). Figure 5 shows the 3 case studies and the effect of the wind speed on the PG. During case study 2 (16 February 2014) and case study 13 (14 December 2016) there were transient periods of high PG values, which appear as peaks in the record. Data from the IMS and local weather stations in Sde-Boker and Mitzpe Ramon indicates that a short period of light rain (up to 4.2 mm/h) was present during case study 2 and (up to ~2 mm/h) during case study 13. Overall, the higher wind speed values did not affect the mean pattern of PG behavior. During case study 1, the PG decreased and during case studies 2 and 13, the PG mean value was quite low compared with fair weather values (~154 and ~195 V m−1 respectively) except for the short duration episode of rain. The effect of heavy rain on the Potential Gradient has been discussed by [8] and shown to decrease considerably and reverse the polarity exhibiting a large variability.

4. Summary

Clouds act as resistors in the Global Electrical Circuit [3,6,21], as they increase columnar resistance due to the reduced mobility of charge carriers due to the attachment of atmospheric ions to cloud particles. Layer clouds acquire positive charge on their upper part, and negative charge at the bottom. We can expect that the overall effect of cloud layers on the measured surface electric field (Potential Gradient) will depend on the amount of charge and the height (distance) of the layer from the surface.
The Potential Gradient (PG) at ground level is affected by local conditions such as passing charged layers of clouds, transient events like wind gusts and the ambient concentration of aerosols in the air. Our results show that during times of regular fair- weather conditions, namely non-extreme aerosol concentration and wind speed values, the effect of cloud layers on the PG are altitude dependent. High cirrus layers decrease the PG that was measured on ground while lower cloud layers increase the measured PG. The impact of wind speed and aerosols concentration, that in some of the cases were slightly above the normal fair-weather conditions, was found to be negligible compared to the effect of overcast conditions. These results are consistent with the 2010 data analyzed by [8] for Reading, UK that showed decreased values of PG during broken clouds (mean 91.1 V m−1 with Inter-quartile range of 30.9 V m−1) and in overcast conditions (81.4 V m−1 and 33.1 V m−1, respectively) compared with clear sky (93.5 V m−1). It should be noted that in the total accumulated 828 h of data in that study there was no reported distinction between cloud types and their specific heights (see Table 2 there). Harrison and Nicoll [19] showed that for clouds with base height lower than 1 km the negatively charged bottom part of the cloud layer effect on the surface PG was pronounced. Their results demonstrate little sensitivity for cloud-bases above 1 km and large fluctuations in PG for cloud-base heights above 1.5 km (their Figure 4). Lucas and Deierling [22] analyzed 18 years of PG data at the Kennedy Space Center in Florida and showed that clouds reduce the PG by values of up to ~30 V m−1 in overcast conditions and ~10 V m−1 for scattered clouds compared with clear-sky conditions, however no dependence on cloud type, depth or cloud depth was reported.
In the present study we showed that the PG during overcast condition is clearly affected by the presence of clouds and that the effect is more pronounced for high clouds and is opposite in polarity but of the same magnitude for low clouds (Figure 1). While the 22 days in the present study cannot be considered to be fair-weather by the orthodox definition [14p, they are clearly not within the disturbed weather category either. Such clouds can be considered as a unique type of non-precipitation shower clouds, even though they are distinctly different from the low clouds this definition usually refers to (stratus or stratocumulus). Bearing in mind that significant parts of the planet are covered by cloudiness for prolonged periods of time, it means that a robust global record of the PG cannot be obtained without considering different cloud types and their effects on the GEC. This suggests a need for a different classification of conditions under which global fair-weather PG values are obtained.

Author Contributions

Formal analysis, R.Y.; Methodology, Y.Y.; Project administration, Y.Y.; Writing—original draft, R.Y.; Writing—review & editing, Y.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded in part by the Israeli Science Foundation grant 1848/20.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The Potential Gradient data (PG) is available through the GLOCAEM network in the University of Reading, UK https://catalogue.ceda.ac.uk/uuid/bffd0262439a4ecb8fadf0134c4a4a41. Israel Meteorology data are accessible online at: https://ims.data.gov.il/ims/1. Accessed on 15 July 2022.

Acknowledgments

This research is supported by the Israel Science Foundation (grant No. 1848/20). We thank the AeroNet Sde Boker team for letting us use their data. We thank IMS for letting us use their meteorological data. We acknowledge the use of imagery from the NASA Worldview application (https://worldview.earthdata.nasa.gov (Accessed on 1 July 2022)), part of the NASA Earth Observing System Data and Information System (EOSDIS). Thanks are due to S. Ben-Gigi of Tel-Aviv University for hosting our instruments at the Wise Observatory.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Harrison, R.G. Urban smoke concentrations at Kew, London, 1898–2004. Atmos. Environ. 2006, 40, 3327–3332. [Google Scholar] [CrossRef]
  2. Aplin, K.L. Smoke emissions from industrial western Scotland in 1859 inferred from Lord Kelvin’s atmospheric electricity measurements. Atmos. Environ. 2012, 50, 373–376. [Google Scholar] [CrossRef]
  3. Rycroft, M.J.; Nicoll, K.A.; Aplin, K.L.; Harrison, R.G. Recent advances in global electric circuit coupling between the space environment and the troposphere. J. Atmos. Sol.-Terr. Phys. 2012, 90-91, 198–211. [Google Scholar] [CrossRef] [Green Version]
  4. Torreson, O.W.; Parkinson, W.C.; Gish, O.H.; Wait, G.R. Ocean Atmospheric-Electric Results (Scientific Results of Cruise VII of the Carnegie during 1928–1929 Under Command of Captain J. P. Ault); Researches of the Department of Terrestrial Magnetism; Carnegie Institution of Washington: Washington, DC, USA, 1946; Volume 3. [Google Scholar]
  5. Israël, H. Atmospheric Electricity; Israel Program for Scientific Translations: Jerusalem, Israel, 1970; Volume 29. [Google Scholar]
  6. Rycroft, M.J.; Harrison, R.G.; Nicoll, K.A.; Mareev, E.A. An overview of Earth’s global electric circuit and atmospheric conductivity. Sp. Sci. Rev. 2008, 137, 83–105. [Google Scholar] [CrossRef]
  7. Harrison, R.G. The Carnegie Curve. Surv. Geophys. 2013, 34, 209–232. [Google Scholar] [CrossRef] [Green Version]
  8. Harrison, R.G. Fair weather atmospheric electricity. J. Phys. Conf. Ser. 2011, 301, 012001. [Google Scholar] [CrossRef]
  9. Kourtidis, K.; Szabóné André, K.; Karagioras, A.; Nita, I.A.; Sátori, G.; Bór, J.; Kastelis, N. The influence of circulation weather types on the exposure of the biosphere to atmospheric electric fields. Int. J. Biometeorol. 2021, 65, 93–105. [Google Scholar] [CrossRef] [PubMed]
  10. Yaniv, R.; Yair, Y.; Price, C.; Katz, S. Local and global impacts on the fair-weather electric field in Israel. Atmos. Res. 2016, 172, 119–125. [Google Scholar] [CrossRef]
  11. Yaniv, R.; Yair, Y.; Price, C.; Mkrtchyan, H.; Lynn, B.; Reymers, A. Ground-based measurements of the vertical E-field in mountainous regions and the “Austausch” effect. Atmos. Res. 2017, 189, 127–133. [Google Scholar] [CrossRef]
  12. Karagioras, A.; Kourtidis, K. A Study of the Effects of Rain, Snow and Hail on the Atmospheric Electric Field near Ground. Atmosphere 2021, 12, 996. [Google Scholar] [CrossRef]
  13. Afreen, S.; Victor, N.J.; Nazir, S.; Siingh, D.; Bashir, G.; Ahmad, N.; Ahmad, S.J.; Singh, R.P. Fair-weather atmospheric electric field measurements at Gulmarg, India. J. Earth Syst. Sci. 2022, 131, 7. [Google Scholar] [CrossRef]
  14. Harrison, R.G.; Nicoll, K.A. Fair weather criteria for atmospheric electricity measurements. J. Atmos. Sol.-Terr. Phys. 2018, 179, 239–250. [Google Scholar] [CrossRef]
  15. Nicoll, K.A.; Harrison, R.G. Stratiform cloud electrification: Comparison of theory with multiple in-cloud measurements. Q. J. R. Meteorol. Soc. 2016, 142, 2679–2691. [Google Scholar] [CrossRef] [Green Version]
  16. Anisimov, S.V.; Mareev, E.A.; Shikhova, N.M.; Sorokin, A.E.; Dimktriev, E.M. On the electro-dynamical characteristics of the fog. Atmos Res. 2005, 76, 16–28. [Google Scholar] [CrossRef]
  17. Elhalel, G.; Yair, Y.; Nicoll, K.; Price, C.; Reuveni, Y.; Harrison, R.G. Influence of short-term solar disturb-ances on the fair-weather conduction current. J. Space. Weath. Space Clim. 2014, 4, A26. [Google Scholar] [CrossRef] [Green Version]
  18. Greenberg, E.; Price, C.; Yair, Y.; Haldoupis, C.; Chanrion, O.A.; Neubert, T. ELF/VLF signatures of sprite-producing lightning discharges observed during the 2005 EuroSprite campaign. J. Atmos. Sol.-Terr. Phys. 2009, 71, 1254–1266. [Google Scholar] [CrossRef]
  19. Nicoll, K.; Harrison, R.; Barta, V.; Bor, J.; Brugge, R.; Chillingarian, A.; Chum, J.; Georgoulias, A.; Guha, A.; Kourtidis, K.; et al. A global atmospheric electricity monitoring network for climate and geophysical research. J. Atmos. Sol.-Terr. Phys. 2019, 184, 18–29. [Google Scholar] [CrossRef]
  20. Yair, Y.; Katz, S.; Yaniv, R.; Ziv, B.; Price, C. An electrified dust storm over the Negev desert, Israel. Atmos. Res. 2016, 181, 63–71. [Google Scholar] [CrossRef]
  21. Baumgaertner, A.J.G.; Lucas, G.M.; Thayer, J.P.; Mallios, S.A. On the role of clouds in the fair weather part of the global electric circuit. Atmos. Chem. Phys. 2014, 14, 8599–8610. [Google Scholar] [CrossRef] [Green Version]
  22. Lucas, G.M.; Thayer, J.P.; Deierling, W. Statistical analysis of spatial and temporal variations in atmospheric electric fields from a regional array of field mills. J. Geophys. Res. Atmos. 2017, 122, 1158–1174. [Google Scholar] [CrossRef]
Figure 1. Data for two case studies: 4 January 2018 (top) and 6 February 2018 (Bottom). In each row: (left) Satellite image of clouds above Israel in visible light. (center) Measured cloud top height by Terra MODIS with colors indicating approximate height. (right) Observed PG values at ground level in Mitzpe Ramon.
Figure 1. Data for two case studies: 4 January 2018 (top) and 6 February 2018 (Bottom). In each row: (left) Satellite image of clouds above Israel in visible light. (center) Measured cloud top height by Terra MODIS with colors indicating approximate height. (right) Observed PG values at ground level in Mitzpe Ramon.
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Figure 2. The height of clouds and their effect on the measured ground level PG. Circles are single layer of clouds while the triangles are a superposition of two or three types of clouds and are the average height. (for example, a presence of a ~10 km high cirrus cloud together with a ~1500 m stratus layer is indicated as a single combined height of 5750 m).
Figure 2. The height of clouds and their effect on the measured ground level PG. Circles are single layer of clouds while the triangles are a superposition of two or three types of clouds and are the average height. (for example, a presence of a ~10 km high cirrus cloud together with a ~1500 m stratus layer is indicated as a single combined height of 5750 m).
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Figure 3. The variability of PG for different types of clouds at Mitzpe Ramon. Variability is expressed in terms of the Inter-Quartile Range and is scaled to one standard deviation for a normal distribution.
Figure 3. The variability of PG for different types of clouds at Mitzpe Ramon. Variability is expressed in terms of the Inter-Quartile Range and is scaled to one standard deviation for a normal distribution.
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Figure 4. Mean Aerosol Optical Depth values [nm] for 19 out of 22 days and the 0.17–0.3 range of AOD mean fair weather values from previous studies [10,20].
Figure 4. Mean Aerosol Optical Depth values [nm] for 19 out of 22 days and the 0.17–0.3 range of AOD mean fair weather values from previous studies [10,20].
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Figure 5. The vertical electric field (top) and wind speed results (bottom) for 3 events. 15 February 2014 (left), 16 February 2014 (middle) and 14 December 2016 (right). High values were recorded during short periods of light rain.
Figure 5. The vertical electric field (top) and wind speed results (bottom) for 3 events. 15 February 2014 (left), 16 February 2014 (middle) and 14 December 2016 (right). High values were recorded during short periods of light rain.
Atmosphere 13 01331 g005aAtmosphere 13 01331 g005b
Table 1. 22 case studies on the effect of clouds on measured PG. * This refers to cases when more than one cloud layer was present.
Table 1. 22 case studies on the effect of clouds on measured PG. * This refers to cases when more than one cloud layer was present.
#DateCloud TypeMean Cloud Height [m]Mean FW PG (V m−1)Mean PG Diurnal (V m−1)∆PG from FW Values to Diurnal Mean (V m−1)Comments
* Superposition
Effect (SP)
Aeronet
Value vs. FW
Wind
Speed
vs. FW
115/02/2014Cumulus & Cirrostratus8600165158.96−6SP—low and high cloudsFWHigh
216/02/2014Cumulus & altocumulus3400165154.82−10.2SP—low and mid cloudsFWHigh
309/03/2014Stratocumulus & alto cumulus3250169151.51−17.5SP—low and mid cloudsN/AFW
413/04/2014Altostratus & cirrostratus7750175155.18−19.8SP—mid and high cloudsFWFW
515/04/2014Altocumulus7200175140.96−34 HighFW
605/05/2014Altocumulus9900183137.61−45.4 HighFW
713/05/2014Cumulus humilis & Cirrus fibratus5900183132.26−47.7SP—low and high cloudsFWFW
820/07/2014Stratocumulus1600180190.6510.7 FWFW
919/11/2016Cirrus8000182112.44−69.6 HighFW
1022/11/2016Cirrocumulus11,400182129.85−52.5 HighFW
1129/11/2016Cirrus8400182121.76−60.2 FWFW
1230/11/2016Cirrocumulus & alto cumulus900018285.52−96.5SP—mid and high cloudsFWFW
1314/12/2016Cumulus & alto cumulus1000170195.6925.7SP—low and mid cloudsHighHigh
1423/12/2016Cumulus800170240.670.6 N/AFW
1501/01/2018Stratocumulus500150200.450.4 N/AFW
1604/01/2018Stratocumulus & alto cumulus3500150159.049.04SP—low and mid cloudsFWFW
1717/01/2018Stratocumulus1000155162.237.23 FWFW
1821/01/2018Cirrus12,500160130.15−29.9 HighFW
1929/01/2018Altocumulus4000160159.29−0.7 FWFW
2006/02/2018Cirrostratus11,700170102.26−67.7 HighFW
2110/02/2018Cirrostratus11,600170134.88−35.1 HighFW
2212/02/2018Cirrus fibratus & stratus fractus5750170171.691.7SP—low and high cloudsHighFW
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Yaniv, R.; Yair, Y. Electric Field Variations Caused by Low, Middle and High-Altitude Clouds over the Negev Desert, Israel. Atmosphere 2022, 13, 1331. https://doi.org/10.3390/atmos13081331

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Yaniv R, Yair Y. Electric Field Variations Caused by Low, Middle and High-Altitude Clouds over the Negev Desert, Israel. Atmosphere. 2022; 13(8):1331. https://doi.org/10.3390/atmos13081331

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Yaniv, Roy, and Yoav Yair. 2022. "Electric Field Variations Caused by Low, Middle and High-Altitude Clouds over the Negev Desert, Israel" Atmosphere 13, no. 8: 1331. https://doi.org/10.3390/atmos13081331

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