Solar Maximum Period Research Articles

Large-scale Structure of the Heliospheric Current Sheets within the Heliosheath Inferred from Voyager 2 Observations

In this paper, we conducted an analysis of the heliospheric current sheets (HCSs) in the heliosheath (HS), utilizing observations by Voyager 2 between 2008 and 2018. Employing rigorous criteria, we identified a total of 34 HCSs that indicate significant changes in magnetic polarity. These occurrences were more prevalent during solar maximum periods when the HCS expanded to higher latitudes, coinciding with the spacecraft positioned at an average latitude of −31° from the solar equator. We determined certain features of the large-scale structures of the identified HCSs. Most importantly, employing two distinct methods indicates that the thickness of the HCSs within the HS ranges from ∼0.003 to ∼0.4 au with an average thickness of ∼0.03 to ∼0.1 au, depending on methods of event selection and fitting techniques. This thickness surpasses that known near 1 au or other heliospheric distances. It is also notably thicker than the typical proton inertial length, implying unfavorable conditions for magnetic reconnection. Additionally, our analysis reveals a frequent tilt of HCS planes relative to the solar equatorial plane by a varying angle up to several tens of degrees, likely implying a common occurrence of a warped structure of the HCS within the HS. Longitudinally, the HCS planes closely align with the Parker spiral field direction expected in the HS. Finally, for a large fraction of the identified HCS events, the HCS planes are likely characterized by a rotational discontinuity. These findings are valid within the limits of the 1 hr resolution data used in this study.

Lagged Response of MJO Convection and Precipitation to Solar Ultraviolet Variations on Intraseasonal Time Scales

AbstractComposite analyses of NOAA satellite‐based outgoing longwave radiation data and ERA5 reanalysis data for nearly six solar maximum periods support the existence of a response of tropical convection and precipitation to short‐term (∼27‐day) solar ultraviolet variations. Following solar UV peaks, the response consists of an increase in average convection and precipitation in the equatorial Indian Ocean and a decrease in the western and central tropical Pacific, with maximum amplitude at a lag of 4 to 8 days. The opposite occurs following short‐term solar UV minima. The observed responses are most detectable when the Madden‐Julian oscillation (MJO) is active and appear to be related to a reduced ability of the MJO to propagate across the Maritime Continent barrier following solar UV peaks relative to UV minima. A similar behavior has previously been found when the stratospheric quasi‐biennial oscillation is in its westerly phase relative to its easterly phase.

АНАЛИЗ ВОЗМОЖНЫХ УРОВНЕЙ ОБЛУЧЕНИЯ КОСМОНАВТОВ ПРИ КРАТКОСРОЧНОЙ ЛУННОЙ МИССИИ

Probable dose loads to cosmonauts in a short-term lunar mission including the transit and stay on the surface were estimated using actual measurements and model calculations. It was found that doses of radiation received in a 21-day mission with a 14-day stay on the Moon in the period of minimal solar activity will make about 130 mSv; in the period of solar maximum and in case of a solar event radiation doses may reach 9–12 Svwith the maximum admissible dose of 250 mSv over a month. Increase of mass thickness of radiation shield of the command module from 10 to 20 g/cm2 (aluminum equivalent) and of the EVA spacesuit from 0.2 to 0.5-1.0 g/cm2 (aluminum equivalent) can reduce 1.4 times the total dose to cosmonauts in the period of solar minimum. Minimization of crew radiation levels requires a consideration of the solar activity forecast in order to choose the launch "windows" when high-energy electrons flow in the Earth's external radiation belt is minimal, and space weather along the route to the Moon.

Simulation for the test mass charging rate in the Tianqin orbit

For the purpose of detecting gravitational waves from space, high-energy particles will infiltrate the satellite’s structure and accumulate charges on the test mass, consequently diminishing detection performance. Present investigations into the charging rate of the test mass typically rely on the particle distribution of Earth orbit. However, the influence of the Earth’s magnetosphere needs to be considered for the Tianqin detector because of its geocentric orbit. In this paper, artificial neural network is used to fuse satellite data and the galactic cosmic rays model to give the distribution of high-energy particles in the Tianqin orbit. And then, the charging rate is estimated by Monte Carlo simulation. The simulation results show that the flux of hundreds of MeV particles is a little higher than that in Earth orbit, which lead to 3−4 e s−1 higher than LISA, i.e. the charging rate of approximately 43 e s−1 during periods of solar minimum and 19 e s−1 during periods of solar maximum. These findings hold substantial implications for guiding the design of the charge management system.

Performance evaluation for vertical TEC predictions over the East Africa and South America: IRI-2016 and IRI-2020 versions

In this paper, we evaluate and report the International Reference Ionosphere (IRI) model's vertical Total Electron Content (TEC) regional profile. Diurnal, monthly, seasonal, and storm-time characteristics of IRI estimates over the equatorial region's ionosphere are validated. We compared the vertical TEC derived from IRI-2020 and its predecessor, IRI-2016, with the GPS-TEC measurements. Results show that IRI (both versions) agrees with observed TEC during solar cycle maximum periods. Exceptionally, over Turkwel station, IRI-2020 produced double peak profiles on the March equinox, June solstice, and September equinox and overestimated with larger discrepancies. Over the other three stations, both IRI versions reproduced the seasonal averaged observed TEC with only slight time lags and discrepancies. During geomagnetically perturbed times, IRI-2020 better indicated positively enhanced GPS-TEC than IRI-2016. However, during the March 17, 2015 storm, IRI-2020 underestimated the storm-enhanced TEC over Bahir Dar station at all phases of the storm. IRI-2016 shows good performances for negative storms where lower TEC measurements are recorded.

The role of global thermospheric zonal winds on the variability of equatorial ionospheric irregularities

We analyze the role of thermospheric winds on the variability of ionospheric plasma density irregularities for solar maximum periods using ionospheric plasma density profiles from the three Swarm satellites and zonal wind data from the Horizontal Wind Model 14 (HWM14). The results show that the plasma density irregularities are strongest during post-midnight hours compared to pre-midnight hours in the African – American longitude sector and this is associated with an enhancement in eastward zonal wind after midnight. In addition, the occurrence of plasma irregularities are observed to show a westward shift. The zonal wind reversal from westward to eastward during post-sunset hours is found to be very important for the generation and variability of plasma irregularities. In the African – American longitudinal sector, where plasma irregularities are the most intense, the eastward wind is strongest in December solstice than for the other seasons. Moreover, plasma irregularity during the December solstice is comparable to the Rayleigh-Taylor Instability mechanism (RTI) favored equinox seasons. But, plasma irregularities are weakest in the June solstice where the zonal eastward wind over geomagnetic equatorial region is weakest as compared to the other seasons. Zonal wind reversal from westward to eastward around post-sunset hours occurred early for seasons with stronger ionospheric irregularity activity whereas the reversal is delayed for the season with weakest ionospheric irregularity activity in the African – American sector. Our results are confirmations of the theoretical prediction on the role of eastward zonal wind in plasma instability growth rate by Kudeki et al. (2007).

Occurrence features of Intermediate Descending Layers [IL] over the equatorial location of Thiruvananthapuram

A study has been carried out on the various aspects of occurrence of Intermediate Descending Layers [IL] on the bottom side of the F region over the magnetic equatorial location of Thiruvananthapuram [8.5 0 N; 77 0 E; dip lat of 0.5 0 N] in India for the period from 2000−2008 using ionosonde observations. Diurnally, the IL occurrence exhibits a double peak pattern with maximum occurrence in the post noon [15–17 IST], followed by early morning [7–9 IST]. The IL has a solsticial maximum [both summer and winter] probability of occurrence [∼70% during 2006 and 20% during 2002] with minima during equinoxes [∼10% during 2002 and 40% during 2006]. The solar cycle variability of IL is brought out in the present study using data from solar cycle 23. The occurrence is found to be high during solar minimum period [70%] and low during solar maximum period [10%]. The diurnal and seasonal behaviour of IL parameters like the peak frequency and the base height are also reported in this study. The role of gravity waves in determining the above stated features of occurrence is being proposed.

Measuring the F-corona intensity through time correlation of total and polarized visible light images

We present a new correlation method for deriving the F-corona intensity distribution, which is based on the analysis of the evolution of the total and polarized visible light (VL) images. We studied the one-month variation profiles of the total and polarized brightness acquired with Large Angle Spectrometric COronagraph and found that in some regions they are highly correlated. Assuming that the F-corona does not vary significantly on a timescale of one month, we estimated its intensity in the high-correlation regions and reconstructed the corresponding intensity maps both during the solar-minimum and solar-maximum periods. Systematic uncertainties were estimated by performing dedicated simulations. We compared the resulting F-corona images with those determined using the inversion technique and found that the correlation method provides a smoother intensity distribution. We also obtained that the F-corona images calculated for consecutive months show no significant variation. Finally, we note that this method can be applied to the future high-cadence VL observations carried out with the Metis/Solar Orbiter coronagraph.

Proton Temperature Anisotropies in the Venus Plasma Environment During Solar Minimum and Maximum

AbstractThe proton population in Venus' plasma environment is characterized during periods of solar minimum and maximum using data from a particle mass‐energy spectrometer. Such characterizations at different levels of solar activity provides physical insight into solar‐cycle‐dependent plasma phenomena around the planet, for example mirror modes in the magnetosheath. Statistical distributions of proton bulk speeds and temperatures are generated using a previously developed method which applies Maxwellian fits to measurements of the protons' velocity distribution function. Spatial maps and probability‐density histograms comparing the proton parameters between the two time periods are presented. The temperatures perpendicular (T⊥) and parallel (T∥) to the background magnetic field are found to be 20%–35% lower during solar maximum. Though the overall distributions of the temperature ratio T⊥/T∥ do not change, the regions with higher anisotropy (T⊥/T∥ > 1) are found farther downstream from the bow shock during solar maximum than minimum. This is consistent with the previously observed growth of mirror modes during solar maximum and their decay during minimum.

Effects of the geomagnetic field time–varying components compensation as evidenced by heart rate variability of healthy males.

Evolutionarily, a human organism is adapted to the natural geomagnetic environment and its slight alterations. However, during geomagnetic storms (GMSs), the strength of the geomagnetic field (GMF) sharply increased hundreds of times and can pose a serious threat to people. We examine the effects of controlled compensation in the time-varying components of the GMF, using a specially created experimental setup with electrically shielding solutions, providing an electromagnetically quiet environment. The measurement of heart rate variability (HRV) on 25 healthy young male volunteers was carried out in the laboratory using the experimental setup at different levels of outdoor geomagnetic activity (GMA). The geomagnetic K-index was used to characterize the magnitude of GMSs; volunteers were tested during quiet magnetic days (K = 1–3), days with K = 4, and days with GMSs (K ≥ 5) in the period of solar cycle maximum. During quiet magnetic days, the comparison between HRV baseline values with values measured under GMF time-varying components compensation mode (CM) did not reveal any changes. On days with K = 4 some HRV indices shifted from their initial values, but it was statistically not significant. However, on days with GMSs statistically significant changes in SDNN* (p = 0.033) and LF* (p = 0.011) indices of HRV were observed in the GMS CM compared to their baseline values. The experiments showed that GMSs cause a sensitive reaction of the heart rate regulatory mechanism, the effect of which can be canceled in the GMS CM. The efficiency of the used technology is supported by the results of this study. * SDNN (Standard Deviation Normal to Normal R-R of cardiointervals), LF (Low frequency spectral band of cardiointervals).

F Region Electric Field Effects on the Intermediate Layer Dynamics During the Evening Prereversal Enhancement at Equatorial Region Over Brazil

AbstractUsing ionograms from the Brazilian equatorial site of São Luís (SL, 2° S; 44° W, I = −3.8°), the relationship between the uplift of the intermediate layers (ILs) at sunset and the prereversal enhancement of the zonal electric field (PRE) is investigated. The ILs were studied during the solar maximum (2003) and minimum activity (2009) periods. The presence of the ILs during the PRE occurrence time was very low during both years. In 2003, six ILs’ events were observed, being four of them in the summer solstice and one in the March equinox. In 2009, only a single event was registered and occurred during the December month. The results show that depending on the height at which the ILs are located, their upward movement at sunset can be in some way related to the normal F layer rise at sunset due to the PRE. The initial altitude at which such ascending ILs were observed was higher than their normal height near sunset. Additionally, the eastward prompt penetration electric fields (PPEFs) during weak magnetic storms can also contribute to the IL’s rise. An interesting case of uplift of a sporadic‐E layer from ∼120 to 290 km probably due to the PPEF is also investigated.

One‐Day Forecasting of Global TEC Using a Novel Deep Learning Model

AbstractIn this study, we make a global total electron content (TEC) forecasting using a novel deep learning method, which is based on conditional generative adversarial networks. For training, we use the International GNSS Service (IGS) TEC maps from 2003 to 2012 with 2‐h time cadence. Our model has two input images (IGS TEC map and 1‐day difference map between the present day and the previous day) and one output image (1‐day future map). The model is tested with two data sets: solar maximum period (2013–2014) and solar minimum period (2017–2018). Then, we compare the results of our model with those of 1‐day Center for Orbit Determination in Europe (CODE) prediction model. Our major results can be summarized as follows. First, we successfully apply our model to the forecast of global TEC maps. Second, our model well predicts daily TEC maps with 1 day in advance using only previous TEC maps. The averaged root mean square error, bias, and standard deviation between AI‐generated and IGS TEC maps are 2.74 TECU, −0.32 TECU, and 2.59 TECU, respectively. Third, our model generates some peak structures around equatorial regions. Fourth, our model shows better performance than 1‐day CODE prediction model during both solar maximum and minimum periods. Fifth, another model with additional input data Kp index gives a slight improvement of the results. Our study shows that our deep learning model based on an image translation method will be effective for forecasting of future images using previous data.

Evaluation of the dusk and early nighttime Total Electron Content modeling over the eastern Brazilian region during a solar maximum period

The ionosphere is one of the main sources of errors for the GNSS (Global Navigation Satellite System) users in low-latitude regions. The ionosphere delays the signal propagation, directly influencing the pseudorange estimation, which is fundamental for positioning estimation. This study aims at evaluating empirical and theoretical models that generate profiles of Total Electron Content (TEC), with respect to their ability to represent the spatiotemporal distribution of the ionospheric plasma. For this purpose, the TEC data calculated from measurements obtained by receivers from the Brazilian Network for Continuous Monitoring of GNSS Systems (RBMC) were compared with ionospheric models that provide the TEC values. The TEC calculation procedure is presented in the manuscript. The Klobuchar model, the empirical model IRI-2016, which has the NeQuick model integrated in its calculations, and the SAMI2 model were evaluated. Data from 2 years around solar maximum period was used considering averaged values over Brazilian region. The evaluations carried out between the TEC values obtained from the models and the real TEC data showed that the models have some deviations, therefore requiring future improvements. According to the results, the deviations may reach approximately 7 m and are originated from physical peculiarities on the spatial environment over the Brazilian region.

Generation of Non‐Substorm Pi2s at Low and Middle Latitudes

AbstractThis study analyzes the characteristics of non‐substorm Pi2 (impulsive pulsations [3–25 mHz]) from low and middle latitudes and investigates the trends of these oscillations. Pi2 events are identified from geomagnetic H‐component data from low and middle latitude observatories Hyderabad (HYB, L = 1.03) and Paratunka (PET, L = 2.1) respectively, during solar maximum period (2015–2016) for quietest geomagnetic conditions, with stringent criteria of interplanetary parameters and activity indices. Data from five high‐latitude stations from THEMIS ground magnetometer chain, covering all local time sectors are additionally analyzed to verify the absence of substorms, pseudo substorms, etc. which may also generate Pi2 signatures. Variation of non‐substorm Pi2 periods with geomagnetic activity index Kp and solar wind speed (Vsw) show inverse relations with Pi2 period at HYB. In addition, non‐substorm Pi2s are distributed equally in all local time sectors with ratio of second harmonic to fundamental Pi2 ranging within 1.3–2.2. These trends of non‐substorm Pi2s indicate plasmaspheric cavity resonance (PCR) as the dominant source at low latitude, confirmed using a theoretical model. In contrast, non‐substorm Pi2 periods do not show a steady trend with Kp and Vsw at midlatitude station PET. Local time variations show an increased period in the premidnight sector at PET. A close agreement between theoretical estimates and observed periods of non‐substorm Pi2‐s at PET, leads to the inference of Alfvenic nature of these modes, attributable to a resonant oscillation.

Comparison of quiet-time ionospheric total electron content from the IRI-2016 model and from gridded and station-level GPS observations

Abstract. Earth's ionosphere is an important medium of radio wave propagation in modern times. However, the effective use of the ionosphere depends on the understanding of its spatiotemporal variability. Towards this end, a number of ground- and space-based monitoring facilities have been set up over the years. The information from these stations has also been complemented by model-based studies. However, assessment of the performance of ionospheric models in capturing observations needs to be conducted. In this work, the performance of the IRI-2016 model in simulating the total electron content (TEC) observed by a network of Global Positioning System (GPS) receivers is evaluated based on the RMSE, the bias, the mean absolute error (MAE) and skill score, the normalized mean bias factor (NMBF), the normalized mean absolute error factor (NMAEF), the correlation, and categorical metrics such as the quantile probability of detection (QPOD), the quantile categorical miss (QCM), and the quantile critical success index (QCSI). The IRI-2016 model simulations are evaluated against gridded International Global Navigation Satellite System (GNSS) Service (IGS) GPS-TEC and TEC observations at a network of GPS receiver stations during the solar minima in 2008 and solar maxima in 2013. The phases of modeled and simulated TEC time series agree strongly over most of the globe, as indicated by a high correlations during all solar activities with the exception of the polar regions. In addition, lower RMSE, MAE, and bias values are observed between the modeled and measured TEC values during the solar minima than during the solar maxima from both sets of observations. The model performance is also found to vary with season, longitude, solar zenith angle, and magnetic local time. These variations in the model skill arise from differences between seasons with respect to solar irradiance, the direction of neutral meridional winds, neutral composition, and the longitudinal dependence of tidally induced wave number four structures. Moreover, the variation in model performance as a function of solar zenith angle and magnetic local time might be linked to the accuracy of the ionospheric parameters used to characterize both the bottom- and topside ionospheres. However, when the NMBF and NMAEF are applied to the data sets from the two distinct solar activity periods, the difference in the skill of the model during the two periods decreases, suggesting that the traditional model evaluation metrics exaggerate the difference in model skill. Moreover, the performance of the model in capturing the highest ends of extreme values over the geomagnetic equator, midlatitudes, and high latitudes is poor, as noted from the decrease in the QPOD and QCSI as well as an increase in the QCM over most of the globe with an increase in the threshold percentile TEC values from 10 % to 90 % during both the solar minimum and the solar maximum periods. The performance of IRI-2016 in simulating observed low (as low as the 10th percentile) and high (higher than the 90th percentile) TEC correctly over equatorial ionization anomaly (EIA) crest regions is reasonably good given that IRI-2016 is a climatological model. However, it is worth noting that the performance of the IRI-2016 model is relatively poor in 2013 compared with 2008 at the highest ends of the TEC distribution. Therefore, this study reveals the strengths and weaknesses of the IRI-2016 model in simulating the observed TEC distribution correctly during all seasons and solar activities for the first time.

Machine learning algorithm to forecast ionospheric time delays using Global Navigation satellite system observations

Global Navigation satellite systems (GNSS) are predominantly affected by Ionospheric space weather. The GNSS signal delays due to ionospheric Total Electron Content (TEC) can be forecasted using advances in the emerging mathematics tools and algorithms. Machine learning algorithms such as Gaussian Process Regression (GPR) is considered in the present paper to implement in the forecasting of low-latitude ionospheric conditions. The GPS receiver data is obtained for 8 years (2009–2016) during 24th solar cycle from International GNSS Services (IGS) station located in Bengaluru (Geographical latitude: 12.97° N, Geographical longitude: 77.59° E), India. The performance of GPR model is validated using statistical parameters such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and correlation coefficient. The results of the proposed GPR model were compared with the Auto Regressive Moving Average (ARMA) model and Artificial Neural Networks (ANN) model during solar maximum period and descending phase of 24th solar cycle. The experiment results are evident that GPR model is significantly providing the promising results in forecasting the ionospheric time delays for GNSS signals. The outcome of the work can be useful to develop web based Ionospheric TEC forecasting system to alert the GNSS users.

Geocoronal Hydrogen Emission Variation Over Two Solar Cycles

AbstractGround‐based hydrogen Balmer‐α observations from Northern midlatitudes span multiple solar cycles, facilitating investigation of decadal scale variations, including natural variability in the hydrogen response to solar geophysical changes. Here we present a reanalysis of ground‐based hydrogen emission observations from the early 1990s and their comparison with observations obtained in 2000–2001 in the context of the extended Northern Hemisphere midlatitude geocoronal hydrogen emission data set. This work suggests an increase in hydrogen emission intensity between the solar‐maximum period of 1990–1991 (Solar Cycle 22) and the near‐solar‐maximum period of 2000–2001 (Solar Cycle 23), with the caveat that this is a limited data set and that there are calibration uncertainties discussed in this paper. Solar activity was higher during the earlier solar maximum period. Thus, the apparent increase in intensity is counter to previous observations from midlatitudes in which the observed intensity increases with higher solar activity. This increase was also not seen in comparison of intensities from three solar minima periods. Further, the apparent increase in intensity is also likely of larger magnitude than model simulations would predict due to increases in methane and carbon dioxide. We will discuss the reanalysis and recalibration of the 1990–1991 observations using current analysis approaches and the interpretation of these observations in the context of observations and modeling of hydrogen variation over different time scales. The detailed review of the calibration procedures has also provided insights to guide design of future observations.

Maximum Proton Trapping Energy in the Earth Radiation Belt

During the PAMELA satellite experiment started in 2006 onboard the Resurs-DK1 spacecraft (350–600 km, an inclination of 70°), cosmic ray charged particle fluxes in low near-Earth orbits were measured to the beginning of 2016. The data obtained during the experiment on high-energy proton (0.1–10 GeV) fluxes in the radiation belt made it possible to measure maximum proton trapping energies in various solar activity phases. The measurement results showed that the maximum proton trapping energy at L shells of 1.16–1.22 in the periods of both solar activity minimum (2009) and maximum (2014) was ∼2 GeV.

Characteristics of equatorial nighttime spread F – An analysis on season-longitude, solar activity and triggering causes

To understand global variability and triggering mechanisms of ionospheric nighttime equatorial spread F (ESF), we analyzed measurements from satellite and a ground-based GPS station for the years between 2010 and 2017. In this study we present seasonal-longitudinal as well as monthly variability of ESF occurrence for solar minimum and yearly variations of ESF occurrence for solar maximum and minimum periods. One of the long standing open questions in the study of ESF is what exactly initiates the Rayleigh-Taylor (RT) plasma instability growth. This question is the focus of the present work. Zonal background eastward electric field and E × B upward plasma drift speed patterns are found to be critically important in understanding plasma irregularity formation. In addition to particular patterns observed on these parameters, the background plasma density in the local evening hours just before the onset of ESF occurrence is very important. Stronger plasma densities just before the onset of irregularities resulted in stronger plasma irregularities, while relatively less dense plasma just before the onset of irregularities resulted in relatively lower plasma irregularities. Seasonal variations in ESF activity between March and September equinox seasons with comparable plasma densities can be defined in terms of the rate of change of solar flux F10.7 (dF10.7/day) index. Strongest ESF occurrence and strongest dF10.7/day are measured in the same month out of all other months in 2016 and 2017. Longitudinal variations of ESF activity in our measurements are related to longitudinal variations of plasma densities. We also found that ESF occurrence is better correlated with rate of change of F10.7 index for months in equinox seasons than for months in solstice seasons for the years between 2013 and 2016.

Association between Solar Variability and Teleconnection Index

In this study, we investigate the associations between the solar variability and teleconnection indices, which influence atmospheric circulation and subsequently, the spatial distribution of the global pressure system. A study of the link between the Sun and a large-scale mode of climate variability, which may indirectly affect the Earth’s climate and weather, is crucial because the feedbacks of solar variability to an autogenic or internal process should be considered with due care. We have calculated the normalized cross-correlations of the total sunspot area, the total sunspot number, and the solar North–South asymmetry with teleconnection indices. We have found that the Southern Oscillation Index (SOI) index is anti-correlated with both solar activity and the solar North–South asymmetry, with a ∼3-year lag. This finding not only agrees with the fact that El Niño episodes are likely to occur around the solar maximum, but also explains why tropical cyclones occurring in the solar maximum periods and in El Niño periods appear similar. Conversely, other teleconnection indices, such as the Arctic Oscillation (AO) index, the Antarctic Oscillation (AAO) index, and the Pacific-North American (PNA) index, are weakly or only slightly correlated with solar activity, which emphasizes that response of terrestrial climate and weather to solar variability are local in space. It is also found that correlations between teleconnection indices and solar activity are as good as correlations resulting from the teleconnection indices themselves.