Responses of CIPS/AIM Noctilucent Clouds to the Interplanetary Magnetic Field

. This study investigates the link between the interplanetary magnetic field (IMF) B y component and the Noctilucent clouds (NLCs) measured by the Cloud Imaging and Particle Size (CIPS) experiment onboard the Aeronomy of ICE in the Mesosphere (AIM) satellite. The mean ice particle radius in NLCs is found to be positively/negatively correlated with IMF B y in the Southern/Northern Hemisphere (SH/NH), respectively, on a day-to-day time scale in most of the 20-summer seasons during the 2007-2017 period with a near 0-day lag time, and the response in the SH is stronger than that in the NH. 15 Moreover, the albedo, ice water content, and frequency of occurrence of NLCs present positive correlation with IMF B y in SH but no significant correlation in NH. The superposed epoch analysis (SEA) further indicates the r m on average changes by about 0.73 nm after IMF B y reversals, which is significant at 90% confidence level in Monte Carlo sensitivity tests. Our results suggest an IMF B y -driven pathway: the influence of the solar wind on the polar ionospheric electric potential affects the nucleation processes in NLCs, and consequently the ice particle radius and NLC brightness.


NLCs
The Noctilucent clouds (NLCs), also known as polar mesospheric clouds (PMCs), are the highest and coldest clouds in the terrestrial atmosphere, forming in the high latitude summer mesosphere at ~83 km altitude, where the temperature can drop to ~140 K or lower. The long-term trends in NLCs are thought to be associated with global climate change. NLCs are 25 susceptible to perturbations from lower atmospheric activities such as gravity waves (Gao et al., 2018) and planetary waves (France et al., 2018). NLCs are strongly influenced by both solar and lunar tides, with diurnal and semidiurnal variations observed in the NLC properties (Fiedler & Baumgarten, 2018;Stevens et al., 2017;von Savigny et al., 2017). NLCs also can be affected by solar activities on various time scales, including solar proton events (Bardeen et al., 2016;Winkler et al., 2012), the 27-day solar rotation (Robert et al., 2010;Thomas et al., 2015;Thurairajah et al., 2017), and the 11-year solar 30 cycle (Dalin et al., 2018;DeLand and Thomas, 2019;Hervig et al., 2019). To distinguish the contribution of solar activity to polar mesospheric clouds from that of climate change, it is important to clarify the mechanisms of the solar influence on NLCs. Based on the observed modest anti-correlation in NLCs with the 27-day and 11-year solar variations, both photodissociation and dynamic origins have been proposed in which the solar ultraviolet irradiance as characterized by the Lyman alpha (Ly-α) index is supposed to play a key role by altering the water vapor and temperature in the NLCs region 35 (Dalin et al., 2018;Thomas et al., 2015), while in general the exact mechanism is still unclear. In this paper, the IMF By rather than the Ly-α is applied as the solar activity index to explore the solar wind-NLC link, and a new hypotheses will be discussed in the next section.

IMF By-related mechanisms for NLC-Solar link
The main IMF By-related process is the change of ionospheric potential in polar cap regions, which determines the flow of 40 the regional downward ionosphere-earth current density JZ. The current flow is part of the global atmospheric electric circuit (GEC), with ionospheric potential being ~250 kV positive relative to Earth's surface, maintained by the global thunderstorms and electrified clouds (Slyunyaev et al., 2019;Williams and Mareev, 2014). The Earth experiences a Lorentz electric field applied by the cross product of solar wind magnetic field and velocity, which is mainly northward/southward for positive/negative (duskward/dawnward) IMF By, and observations have shown that the IMF By-dependent daily-averaged 45 perturbation of ionospheric potential ranges from -30 to 30 kV at high geomagnetic latitudes and is opposite in the SH/NH (Tinsley and Heelis, 1993).
A possible link may exist between the solar wind By variations and polar surface meteorology through the ionospheric potential, which has been supported by a variety of observations, in term of polar surface pressure (Lam et al., 2013), geopotential height (Lam et al., 2014), temperature (Freeman and Lam, 2019;Lam et al., 2018), and below-cloud irradiance 50 (Frederick et al., 2019;Frederick and Tinsley, 2018;Tinsley et al., 2021). It should be noted that these observations are characterized by two features: the responses in SH and NH are opposite, in line with the opposite IMF By-induced ionospheric potential in SH and NH; the delay time is short, lasting only a few days or less. A hypothesis has been proposed to explain the above observations: firstly, solar wind By induces changes in the ionospheric electric potential, as well as the downward current density JZ in the GEC; second, the microphysical processes inside clouds are sufficiently sensitive to 55 space charge generated by JZ so that the cloud properties such as infrared opacity and albedo will consequently be affected.
Finally, polar surface meteorology will be influenced by cloud radiative forcing (Lam and Tinsley, 2016). The invoked cloud microphysical changes have been detailed for individual aerosol-droplet collisions (Zhang et al., , 2019Tinsley, 2017, 2018), but direct measurements in clouds and modelling are required to test this hypothesis.
In comparison with the tropospheric clouds within which many factors are involved, the polar mesospheric clouds 60 provide a relatively pure scenario to study the role played by electric charges in the microphysical process of clouds. By extending the above 'solar -GEC -cloud microphysics -tropospheric meteorology' hypothesis, it is straightforward to propose the 'IMF By -Ionospheric potential -NLC Microphysics -NLC brightness' hypothesis for the polar mesospheric clouds: IMF By induces changes in polar ionospheric potential, which will modulate the charge distribution on meteoric smoke particles (MSPs) with major implications for the nucleation rate and ice particle formation processes in NLCs, and 65 ultimately affect the macroscopic properties of NLCs.

Nucleation processes in NLCs
The formation of ice particles in NLCs is still not well understood, as a variety of factors are involved in the microphysical process, among which the nucleate rate and number density of ice nuclei contribute the most important uncertainties (Rapp and Thomas, 2006). Although the homogeneous nucleation has been considered feasible (Murry and Jensen, 2010), the 70 extreme conditions required make the homogeneous nucleation unlikely to occur at the typical mesospheric supersaturation level (Tanaka et al., 2022). The heterogeneous nucleation instead is thought to be more effective by providing a pre-existing ice nuclei, for which candidates such as ion clusters, soot, sulphate aerosols, meteoric smoke particles have been proposed (Rapp and Thomas, 2006). MSPs are abundant in the mesosphere and considered to be most likely, evidence that ice particles contain small amounts of MSPs has been provided by observations (Hervig et al., 2012). The exact nucleation 75 process of MSPs is still poorly known, due to the lack of laboratory measurements at the mesospheric condition.
The MSPs are generated by meteor ablation at the upper mesosphere and lower thermosphere, with the radius ranging from sub-nanometre to nanometre size. The 2-D simulations involving the middle atmospheric circulation revealed that the MSPs will move upward along with the strong updrafts in the summer mesosphere, and are then transported to winter mesosphere by the meridional winds, and finally sink down into the stratosphere by the downwelling (Megner et al., 2008a(Megner et al., , 80 2008b. The global mass re-distribution of MSPs results in a pronounced reduction of MSPs concentration and lifetime at summer mesosphere, and thus the conventional idea of nucleation on MSPs is challenged. The above dilemma can be resolved when the charged MSPs are taken into consideration, because the MSPs charge can effectively reduce the critical radius of ice nuclei at low temperature, allowing the charged MSPs to act as ice nuclei (Gumbel and Megner, 2009;Megner and Gumbel, 2009). It should be noted that the galactic cosmic rays can generate 85 continuous ions throughout the atmosphere, and the charged molecular clusters are found to grow much faster than neutral clusters. The so-called ion-mediated nucleation (IMN) is of great important for the formation of cloud condensation nuclei in atmosphere and has been studies for decades (Yu and Turco, 2000;Yu et al., 2008). The distribution of charges on MSPs becomes important with regards to the above assumption, while the efficiency of MSPs collecting electrons at the mesosphere is still unclear. Due to the mobility of electrons is much larger than that of positive ions, negatively charging is 90 supposed to be dominant in the upper mesosphere, and rocket-borne measurements show that about 10% of MSPs are negatively charged (Plane et al., 2014;Robertson et al., 2014). The NLCs locate in the D-region ionosphere where the electric environment is sensitive to disturbances from solar winds. This provides a possible way through which solar activity may impact the NLCs through an electric-related mechanism.
The CIPS/AIM began observing the NLCs in 2007 and 20-summer-season data in SH and NH from 2007 to 2017 are 95 available now. Therefore, we investigated the hypothetical IMF By-driven solar-NLC link in this study. The paper is structured as follows: Section 2 provides a brief description of the CIPS data and solar wind data. Section 3 presents the results of NLC correlation with IMF By during the 20 NLC seasons on the day-to-day scale, as well as the superposed epoch analysis for NLCs response to IMF By reversals. Section 4 discusses the results and Section 5 summarizes our main conclusions. 100 2 Data

CIPS/AIM data
The aeronomy of ICE in the Mesosphere (AIM) satellite was launched on 25 April 2007 to a sun-synchronous polar orbit whose local time is mainly midday-midnight at high latitude regions. The Cloud Imaging and Particle Size (CIPS) experiment onboard AIM comprises a panoramic UV nadir imager, consisting of four cameras operating at 265 nm, with a 105 field of view of 120°×80° and a horizontal spatial resolution of 5×5 km. This platform observes the scattered radiance from NLCs, and images the NLCs of ~40°-85° latitude zone for the summer hemisphere ~15 times per day. The CIPS has provided NLC data from the 2007 summer season until now, in terms of ice particle radius, albedo, and ice water content (IWC), and detailed descriptions of the CIPS data products, calibration, retrieval algorithms, and retrieval uncertainties have been published (Carstens et al., 2013;Lumpe et al., 2013). The CIPS level 2 orbit data provide rectangular images of NLC 110 properties for each of the 15 orbit strips per day, in which a single pixel represents a 25 km2 (5×5 km) area anywhere on the globe and a 5800×1000 km strip region is covered, thus the cloud cover as well as the frequency of occurrence (FO) of

Solar wind data
The solar wind By data in GSM format were downloaded online from the GSFC/ SPDF OMNI Web interface (https://omniweb.gsfc.nasa.gov/form/dx1.html). In the geocentric solar magnetospheric (GSM) coordinate system, the origin locates at the center of the Earth, X points towards the sun, Z lies in the plane of the X and geomagnetic dipole and is perpendicular to X (roughly northward), Y completes the righthanded coordinate system, stretching toward the dusk. The 120 solar wind structures are fairly complex, varying from 2-sector to 4-sector and sometimes irregularly, therefore, during a 27day solar rotation period, the IMF By can reverse 2 or 4 or more times, unlike other solar indexes such as Ly-α or F10.7 which show regular 27-day period. In order to apply the widely used SEA method, the key days of By reversals are listed in Table 1, which have been selected to ensure that during the 5-day period before and after the key day there is no NLCs data missed and that the direction of IMF By is relatively stable. The IMF By changing from positive to negative (from negative to 125 positive) is denoted by p2n (n2p). Four groups of dates during 2007 and 2017 are listed in Table 1, corresponding to the n2p (28 cases) and p2n (29 cases) reversals during NH summer, and the n2p (23 cases) and p2n (18 cases) reversals during SH summer, respectively. Figure 1 shows the variations of the daily-averaged solar wind magnetic field and NLC properties during the NLC seasons from 2007 through 2017. The daily-averaged IMF By varies between -5 nT and 5 nT, as shown in Fig. 1(a-b), and the periods of IMF By variations are complex, as noted above. Fig. 1(c-h) show the intensity of NLCs in terms of mean ice particle radius (rm), mean albedo (Albm), and mean ice water content (IWCm), while Fig. 1(i-j) show the cloud cover of NLCs, as calculated by counting of pixels, and is linearly proportional to FO. In order to diminish noise, the NLC data in the latitude 135 bands 65°-85° are used because the NLCs are rarely observed by CIPS below 65° latitude, and an albedo threshold of 5×10 -6 sr -1 was applied. The intensity and coverage of NLC peak ~20 days after the solstice, and show strong seasonal variations, with the exception of the mean ice particle radius, rm. the period of 10 days before and 50 days after the solstice day are used (Fig. 1). The link between the anomalous mean ice particle radius rm with IMF By is conspicuous, with positive correlation coefficients in all of the SH summer seasons and negative correlations in most of the NH summer seasons (Fig. 3a). These opposite responses in the SH and NH are consistent with the opposite ionospheric potential changes in SH and NH caused by IMF By. Further, the response was stronger in the SH, with the correlation coefficient being about twice of that in NH. In NLCs, the larger the ice particle size is, the greater 150 the albedo and IWC are, namely, the mean ice particle radius is normally positively correlated with the albedo and IWC (Lumpe et al., 2013), the 20-seasonal CIPS data show a correlation coefficient of ~0.52 between rm and Albm and of ~0.35 for rm and IWCm. Conversely, the cloud cover of NLCs will also change in pace with the formation and growth process of ice particle radius, and the 20-seasonal CIPS data also show a correlation coefficient of ~0.48 between rm and FO. It is thus reasonable to speculate that the albedo, IWC, and FO will respond to IMF By in concert with ice particle radius, and Fig. 3( b-155 d) show the correlation coefficients between the anomaly of Albm, IWCm, and FO with IMF By are pronounced in SH, but not in NH.

Correlation analysis of day-to-day responses of NLCs to IMF By 130
We have also tried to roughly estimated the column number density of ice particles, Nice, based on the CIPS data of IWC and ice particle radius r. Assuming the mass of ice particle mice to be ρ ice 4πr 3 /3, where ρ ice = 0.92 / 3 , then the ice particle concentration Nice will be approximately equal to the ice water content divided by the mass of ice particle, IWC/mice. 160 It is of great interest to study the correlation of ice particle concentration with IMF By, since it can reveal the microphysical process during the NLCs responses to solar wind magnetic fields. The results show that the correlation coefficient between ice particle concentration with IMF By is -0.14±0.06 in SH and 0.09±0.04 in NH, which are surprisingly opposite from that of rm and IWCm shown in Fig. 3. In the dry NLC region, ice particles compete for the limited water vapor, resulting in an anticorrelation between the ice particle concentration and ice particle radius, which have been verified by observation and 165 simulation (Hervig et al., 2009;Wilms et al., 2016). Our above results support this anticorrelation again, implying that the solar wind may firstly increase/decrease the nucleate rate and ice particle number density in NLCs, then decrease/increase the ice particle radius.
NLCs are dominantly influenced by the solar tides with the diurnal variation, and the NLCs occurrences are usually more frequent at the local time of morning (Fiedler & Baumgarten, 2018;Stevens et al., 2017). In addition, the NLCs can 170 also be affected by the lunar tides, and the longitudinal variations in NLCs attributed to the non-migrating lunar tides have been found (Liu et al., 2016;von Savigny et al., 2017). To check whether the local time differences between the descending and ascending branches of the AIM satellite will affect the results in Fig. 3, we separate the CIPS data of the descending and ascending branches into two groups. Similarly, in order to check the longitudinal variations, the CIPS data are divided into two groups in term of the longitude ranges of (-180°,0°) and (0°,180°). The correlation coefficients for the above two 175 scenarios have been calculated and listed in Table 2, and the results for all of them are consistent with the results shown in Furthermore, Figure 4 shows the mean correlation coefficients for time lags varying from -7 to 7 days. The error bars illustrate the standard deviation of the mean, which are calculated from the 10 seasonal correlation coefficients and are also 180 given in Fig. 3 at 0-day lag time. A very short delay time was observed (Fig. 4), with the maximum correlations occurring near zero day, implying a microphysical response in NLCs to IMF By similar to the short delay time that has also been observed in the solar-troposphere studies. In previous studies of the link between Ly-α and NLCs, the proposed mechanisms involving photodissociation, heating, or circulation all required longer time. The photodissociation process accounts for a negatively correlation for the H2O at the mesosphere and the 27-day solar irradiance variations, with a phase lag of about 6-7 185 days, which can be attributed to the lifetime of H2O at that altitudes (Shapiro et al., 2012). Satellite observations showed the time lag for the water response to solar 27-day rotation of about 0-3 days and for the temperature response of about 0-8 days, depending on altitudes; and the time lag between NLC properties variations and solar Ly-α ranges from 0 to 3 days in the NH and from 6 to 7 days in the SH, depending on instruments and properties (Thomas et al., 2015;Thurairajah et al., 2017). In contrast, the IMF By-related processes of ionospheric potential changes respond quickly to solar wind magnetic field 190 reversals. In summary, the nearly zero lag-time of NLC properties responding to IMF By variations implies a mechanism of electro-dynamic origin rather than thermal-dynamic origin.
In order to further verify the response of NLCs to solar wind at different latitudes, the approaches in Fig. 3 were repeated for the five latitude bands of 80°-85°, 75°-80°, 70°-75°, 65°-70°, 60°-65°, respectively. The correlation coefficients of the anomaly of NLC properties with IMF By are shown in Figure 5, and the slope of the anomaly of NLC properties to 195 IMF By are given in Figure 6. Fig. 5(a) and 6(a) show that in SH, the correlation and sensitivity of ice particle radius rm to IMF By are both greater at higher latitudes, in agreement with the ionospheric potential perturbations caused by IMF By changes, while in NH the correlation and sensitivity are just about half of that in SH but still significant in latitude higher than 65°. For the 60°-65° latitude region, the results are not significant, this may because at lower latitudes the IMF Byinduced processes are too weak and because the rare NLC occurrences at lower latitudes entail weaker signal/noise. NH for FO, and in consideration of the ~5 nT amplitude of IMF By variation during solar wind reversals, the responses of NLC intensity and coverage to IMF By are not negligible. The correlation coefficient of ice particle column number density Nice with IMF By with can also be obtain for different latitudes varying from 85° to 60°: -0.14±0.06, -0.13±0.05, -0.09±0.03, -0.03±0.04, -0.004±0.07 in SH; and 0.06±0.05, 0.09±0.05, 0.12±0.04, 0.04±0.04, 0.01±0.04 in NH. Again, the correlation coefficient of ice particle concentration with solar wind magnetic field is opposite from that of mean ice particle radius and 210 ice water content. However, it should be noted that due to the detection threshold of CIPS instrument for ice particles with radii greater than 10-15 nm, the variation of the invisible smaller ice particles' concentration is unknown.
In addition, other solar wind parameters such as IMF Bz, Ap index and Ly-α irradiance have also been examined by the same processes; however, no correlations were found for them at 0-day lag time. The solar wind magnetic field line has an Archimedes spiral pattern, i.e., IMF Bx is negatively proportional to IMF By and a correlation coefficient of about -0.67 215 between them was obtained during the period of 2007 to 2017, thus similar correlations also exist between IMF Bx and NLC properties, but with the opposite sign. The IMF Bz corresponds to a dawn-dusk solar wind electric field, and thus can generate a dawn-dusk ionospheric potential drop for both hemispheres, while the sun-synchronous orbit of AIM is designed to be midday-midnight with rare opportunity to pass the dawn-dusk regions, thus the zero correlations observed for NLCs with IMF Bz are just as expected. 220

Superposed epochs for NLCs response to IMF By reversals
The superposed epoch analysis is frequently applied in the studies of atmospheric responses to short-term solar variations, in which solar signals are more obvious and easier to be extracted than for decadal or longer-term variations. Although the NLCs only occur in summer, during the 20-season period of CIPS data enough IMF By reversal cases have been accumulated, as listed in Table 1, allowing the SEA method to be used to explore the NLCs responses. In the SEA method, the ice particle 225 radius distribution is denoted by f(r), where the distribution is of the values of r over the array of pixels on a given day. The averages of f(r) during 3 days before and 3 days after the key day are denoted by f3-pre and f3-aft respectively, then the changes of ice particle radius distribution δf during IMF By reversals are given by δf = f3-aft -f3-pre. The results of δf for the n2p and p2n IMF By reversals in SH given in Table 1 are illustrated in Figure 7, with an albedo threshold of 5×10 -6 sr -1 . The mean ice particle radius rm can be calculated by integrating the product of radius and its distribution, rm=∑rf(r), thus the changes of rm 230 during IMF By reversals are obtained by δrm = rm,3_aft -rm,3_pre =∑rδf, and the values of δrm are given in each panel of Fig. 7.
For n2p/p2n IMF By reversals, the polar ionospheric electric potential will increase/decrease in the SH, and the rm increases/decreases by about 0.88/1.07 nm in SH as shown in Fig. 7. Similarly, the results of NH are illustrated in Figure 8, for n2p/p2n IMF By reversals, the polar ionospheric electric potential will decrease/increase in the NH, the rm decreases/increases by about 0.25/0.71 nm in NH as shown in Fig. 8. Generally, the ice particle average radius changes by 235 about 0.73 nm during IMF By reversals, and the responses in SH is stronger than that in NH. The results in Fig. 7-8 were subject to Monte Carlo sensitive tests, in which the same number of key days in Table 1 were randomly generated and δrm can be calculated by SEA, by repeating this process for one thousand times, the distribution of δrm are obtained, showing the results in Fig. 7-8 are significant at 90% confidence level.
In addition, we also investigate the responses of NLCs to IMF By reversals for different brightness of noctilucent 240 clouds. The NLCs was ranged into five groups by albedo: 5-10×10 -6 sr -1 , 10-15×10 -6 sr -1 , 15-20×10 -6 sr -1 , 20-25×10 -6 sr -1 , 25-30×10 -6 sr -1 respectively. It should be noted that the NLCs with albedo less than 5×10 -6 sr -1 are viewed as noise, and the proportion of NLCs with albedo greater than 30×10 -6 sr -1 are negligible. Figure 9 shows that for varying NLCs albedos the particle radius rm changes during IMF By reversals are consistent to the result in Fig. 7 and 8, verifying that both the dark and the light NLCs are sensitive to IMF By reversals. On the other hand, the NLCs with greater albedo usually have greater mean 245 ice particle radius, thus the results in Fig. 9 also indicate that both the small and large ice particle sensitive to IMF By reversals. In addition, the results in Fig. 9 also support that the responses of NLCs to IMF By is stronger in SH than that in NH.

Discussion
Our results support the existence of a link between NLCs and solar wind magnetic fields, characterized by the two features 250 of opposite responses in SH and NH in conjunction with a short lag time of 1-day at most, similar to the previously introduced solar-troposphere link. The 'IMF By -ionospheric potential -NLCs microphysics -NLCs brightness' hypothesis can be applied to explain the IMF By-driven solar-NLCs link: IMF By will firstly change the ionospheric potential as well as the downward electric current JZ at polar regions, subsequently change the fraction of negatively charged MSPs and the nucleation processes in NLCs, finally the ice particle radius, ice particle concentration, IWC, as well as albedo will be 255 affected.
As introduced in the section 1.2, the increase of IMF By will cause the ionospheric potential as well as the ionosphereearth current density JZ in the polar cap to increases/decrease in SH/NH. The downward atmospheric current density JZ is of great interest in the studies of tropospheric clouds, since positive/negative space charges can be induced at the cloud top/bottom boundaries, which has been verified by in-situ observations (Nicoll and Harrison, 2016). As the electric current 260 flows through cloud boundaries, due to the changes of conductivity, gradients of electric field are created, requiring the formation of space charges according to Gauss's Law (Zhou and Tinsley, 2007;. The NLCs locate at the D-region ionosphere, where the ionization and conductivity are caused by solar radiation and thus increase with altitudes. Similarly, net positive space charges will be accumulated in the NLCs region as the downward current JZ flows through. Moreover, as the ionization varies nearly exponentially with altitudes in the D-region ionosphere, the gradient of electric field is larger at 265 lower altitudes. As a result, the amount of net space charges accumulated in the bottom of NLCs or lower will be larger than in the upper region of NLCs. Given the ionization rate of the D-region ionosphere depends on solar radiation, the effect of IMF By on the ionization rate as well as positive ions concentration should be negligible, thus the net positive space charges are mainly generated by the reduction of electrons. The MSPs are dominatingly negatively charged because electrons are easier to collect by MSPs as compared to positive 270 ions, consistent with rocket-borne measurements (Plane et al., 2014;Robertson et al, 2014). In consideration of that the net positive space charges induced by the downward current JZ will reduce the concentration of elections, then a reduction of negatively charged MSPs is also required. And due to the exponentially changes of conductivity, the amount of negatively charged MSPs in the bottom of NLCs or lower will decreases more significantly than that in the upper region of NLCs.
Upward vertical winds are dominant in the summer mesosphere, able to carry the MSPs at the bottom of NLCs or lower to 275 pass through the supersaturation region. As mentioned above, the reduction of negatively charged MSPs at lower altitudes are larger than that at higher altitudes, the effect of current JZ on the nucleation processes of NLCs through the negatively charged MSPs may be further amplified by the upward winds.
As introduced in section 1.3, the critical radius of ice nuclei for the negatively charged MSPs is smaller than that for the neutral MSPs, and will decrease to nearly zero at extreme low temperature. Based on the assumption that the charged MSPs 280 are more efficient than neutral MSPs to form ice nuclei, the concentration of negatively charged MSPs will play an important role on the nucleation rate in NLCs. In addition, studies show that the decrease of nucleation rate will reduce the ice particle concentration, and given the limited amount of water vapor, larger ice particles will be yielded, and brighter NLC will be observed (Wilms et al., 2016).
Our results can be explained in the following pathway: when the IMF By increases, the ionospheric potential and the 285 downward current JZ will increase in SH, the net positive space charges increase, requiring a reduction in the number density of negatively charged MSPs in the NLCs region. Therefore, the nucleation rate dominated by the negatively charged MSPs will decrease, less ice particles will be formed. Due to the limited of water vapor, the mean particle radius will be larger, and characters such as the albedo, IWC, and cloud occurrence will increase. Conversely, the response of the downward current JZ to IMF By in the NH is opposite from that of SH, thus the NLCs in NH changes in an opposite way with that of SH. 290 Polar mesosphere summer echoes (PMSE) are very strong radar echoes scattered by the electron number density irregularities at the polar summer mesopause altitudes of about 75-100 km, and the electron structures are thought to be caused by the neutral air turbulence in combination with the charged ice aerosol particles in the NLCs (Rapp and Lübken, 2004). Note that the NLCs are absent in the winter hemisphere, whereas polar mesosphere winter echoes (PMWE) were still observed at much lower altitudes of 55-85 km. PMWE are suggested to be caused by the neutral air turbulence together with 295 the charged MSPs (Strelnikov et al., 2021). A possible link is expected to exist between PMSE/PMWE with IMF By for two reasons: First, the PMSE is sensitive to ice particle radius and concentration, due to the ice particle can affect the diffusion of electrons (Rapp and Lübken, 2004). Our results show that the ice particle radius is sensitive to solar wind, thus it is necessary to check whether this response has further influence on the PMSE. Second, as mentioned in the above microphysical process, the IMF By is supposed to have a major effect on the charging process of the MSPs, and the latter plays a more direct role in 300 PMSE/PMWE. In brief, to investigate the response of PMSE/PMWE to IMF By will be helpful for understanding the link between solar wind and mesosphere, while the relevant work is beyond the scope of this paper.
In conclusion, our results suggest a new possible way for the link between solar activity and NLCs. The IMF By-related mechanisms are concerned more about the microphysical process of ice nuclei formation, namely, the charging of MSPs and its influence on nucleation rate. While the Ly-α related mechanism focuses more on the photodissociation, heat, and dynamic 305 processes, which will affect IWC on a longer time lag. Unlike the Ly-α irradiance which has a regular 27-day period as well as an 11-year period, the IMF By varies in a more complex way, thus its effect on NLCs, as in the correlations, are not just the 27-day period. To better understand the effect of solar activity on NLCs at different lags, periods, and latitudes, the IMF By and Ly-α should both be considered in future works.

Conclusion 310
The responses of NLCs to solar wind magnetic fields were investigated using the CIPS/AIM data. Our findings suggest that such a solar-NLC link exists. The mean ice particle radius in NLCs was positively/negatively correlated with the IMF By in SH/NH on the day-to-day time scale in the majority of NLC seasons during the period of 2007-2017, with a short lag time of 1 day at most. The correlation and sensitivity of rm versus IMF By were stronger in the SH, about twice as that in the NH, and more conspicuous in higher latitudes. Similar responses of albedo, IWC and FO in NLCs with IMF By were also noticeable 315 in the SH but not obvious in the NH. The superposed epoch analysis provides further insights into the mean ice particle radius responses during n2p and p2n IMF By reversals in SH and NH, and results show the rm averagely changes by about 0.73 nm following IMF By reversals, which is significant at 90% confidence level in the Monte Carlo sensitivity tests. The solar-NLC links are interpreted from the perspective of an IMF By-driven mechanisms: opposite ionospheric electric potential changes in SH and NH are induced by the IMF By, which will change the downward current density JZ flowing 320 through the NLCs region and thus influence the charging of MSPs. Given the negatively charged MSPs play an important role on the nucleation processes in NLCs, then the ice particle radius as well as the brightness of NLCs will be affected.
However, it is necessary to further understand the underlying processes of NLCs proposed in above mechanism, and to implement and verify them in polar mesospheric clouds modelling.   Figure 1. Daily-averaged IMF By, mean ice particle radius (rm), mean albedo (Albm), mean ice water content (IWCm), and cloud cover observed by CIPS for NH (left) and SH (right) for each of the NLC seasons from 2007 through 2017. 490 Figure 2. The left panels show the relationships of the daily IMF By (red curves) with the anomaly of mean ice particle radius (rm), mean albedo (Albm), mean ice water content (IWCm), and cloud cover in the 2008/2009 NLCs season for SH. The anomaly of NLCs data are obtained by removing the 40-day running mean. The right panels present the correlation 495 coefficients between the daily IMF By and the anomaly of NLCs characters.  . Correlation coefficients between the anomaly of rm, Albm, IWCm and IMF By for time lags varying from -7 to 7 days, with red/blue lines representing the mean correlation coefficients and error bars illustrating the standard deviation of the mean for the SH and NH respectively. 505 Figure 5. Correlation coefficients between the anomaly of rm, Albm, IWCm and IMF By at different latitude bands, with red/blue lines representing the mean correlation coefficients and error bars illustrating the standard deviation of the mean for the SH and NH respectively. 510 Figure 6. Slope of the anomaly of rm, Albm, IWCm versus IMF By at different latitude bands, with red/blue lines representing the mean slope and error bars illustrating the standard deviation of the mean for the SH and NH respectively. Figure 7. Changes of ice particle radius distribution δf(r) during n2p and p2n IMF By reversals in the southern hemisphere. The distributions of r over all pixels on three days before/after the key days are indicated by the gray/red bars, and the changes between them are shown by the green bars.  Figure 7, but for the results of the northern hemisphere. 520 Figure 9. The influences of IMF By reversals on the ice particle radius changes δrm at different NLCs brightness.