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This brief review described spatial-time climate patterns generated by the dynamics and thermodynamics of the Earth’s climate system and methods of identifying these patterns. Specifically, it does discuss the following major climate patterns: El Ni?o-Southern Oscillation (ENSO), Cold Ocean-Warm Land (COWL) pattern, Northern and Southern Annular Patterns (NAM and SAM), Atlantic Multidecadal Oscillation (AMO) and Atlantic Meridional Overturning Circulation (AMOC), Pacific North-American Pattern (PNA) and Pacific Decadal Oscillation Pattern (PDO). In view of an extensive number of publications on some climate patterns, such as the ENSO, which discussed in many hundred of publications, this review is not intended to cover all the details of individual climate patterns but intends only to give a general overview of their structure, mechanisms of their formation and response to external forcing. It is assumed that the climate patterns can be treated as attractors of dynamical systems allowing us to extract and predict some specific features of the patterns such as the origin and evolution of the climate patterns and their role in climate change. Thus the knowledge of patterns allows the climate prediction on long time scales and understanding of how an external forcing affects the frequency of occurrence of climate patterns and their magnitude but not the spatial structure.

Although modern man had developed long before the migration from Africa began ∼ 55,000 years ago, no agricultural societies developed until about ∼ 10,000 years ago. But in the next 5000 years, agricultures developed in several unrelated regions of the world. It was not a chance occurrence that new agricultures independently appeared in the same 5000 years. The question is what inhibited agriculture worldwide for 44,000 years and what changed ∼ 10,000 years ago? We suggest that a major factor influencing the development of agricultural societies was climate stability. From the experience of several independent cultures, we estimate that the development of agriculture needed about 2000 years of climate free from significant climate variations on time scales of a few centuries.

Coronal Mass Ejections (CMEs) and their interplanetary counterparts (ICMEs) are the major sources for strong space weather disturbances. We present a study of statistical properties of fast CMEs (v≥1000 km/s) that occurred during solar cycles 23 and 24. We apply the Max Spectrum and the declustering threshold time methods. The Max Spectrum can detect the predominant clusters, and the declustering threshold time method provides details on the typical clustering properties and timescales. Our analysis shows that during the different phases of solar cycles 23 and 24, fast CMEs preferentially occur as isolated events and in clusters with, on average, two members. However, clusters with more members appear, particularly during the maximum phases of the solar cycles. During different solar cycle phases, the typical declustering timescales of fast CMEs are τc =28-32 hrs, irrespective of the very different occurrence frequencies of CMEs during a solar minimum and maximum. These findings suggest that τc for extreme events may reflect the characteristic energy build-up time for large flare and CME-prolific active regions. Statistically associating the clustering properties of fast CMEs with the disturbance storm time index at Earth suggests that fast CMEs occurring in clusters tend to produce larger geomagnetic storms than isolated fast CMEs. Our results highlight the importance of CME-CME interaction and their impact on Space Weather.

We study the clustering properties of fast Coronal Mass Ejections (CMEs) that occurred during solar cycles 23 and 24. We apply two methods: the Max spectrum method can detect the predominant clusters and the de-clustering threshold time method provides details on the typical clustering properties and time scales. Our analysis shows that during the different phases of solar cycles 23 and 24, CMEs with speed $\geq 1000\ km/s$ preferentially occur as isolated events and in clusters with on average two members. However, clusters with more members appear particularly during the maximum phases of the solar cycles. Over the total period and in the maximum phases of solar cycles 23 and 24, about 50% are isolated events, 18% (12%) occur in clusters with 2 (3) members, and another 20% in larger clusters $\geq 4$, whereas in solar minimum fast CMEs tend to occur more frequently as isolated events (62%). During different solar cycle phases, the typical de-clustering time scales of fast CMEs are $\tau_c=28-32\ hrs$, irrespective of the very different occurrence frequencies of CMEs during solar minimum and maximum. These findings suggest that $\tau_c$ for extreme events may reflect the characteristic energy build-up time for large flare and CME-prolific active ARs. Associating statistically the clustering properties of fast CMEs with the Disturbance storm index Dst at Earth suggests that fast CMEs occuring in clusters tend to produce larger geomagnetic storms than isolated fast CMEs. This may be related to CME-CME interaction producing a more complex and stronger interaction with the Earth magnetosphere., Comment: Accepted for publication in the Astrophysical Journal

As an extension of Lee et al. (2013), solar cycle variation of carbon monoxide (CO) is analyzed with MLS observation, which covers more than thirteen years (2004–2017) including maximum of solar cycle 24. Being produced primarily by the carbon dioxide (CO2) photolysis in the lower thermosphere, the variations of the mesospheric CO concentration are largely driven by the solar cycle modulated ultraviolet (UV) variation. This solar signal extends down to the lower altitudes by the dynamical descent in the winter polar vortex, showing a time lag that is consistent with the average descent velocity. To characterize a global distribution of the solar impact, MLS CO is correlated with the SORCE measured total solar irradiance (TSI) and UV. As high as 0.8 in most of the polar mesosphere, the linear correlation coefficients between CO and UV/TSI are more robust than those found in the previous work. The photochemical contribution explains most (68%) of the total variance of CO while the dynamical contribution accounts for 21% of the total variance at upper mesosphere. The photochemistry driven CO anomaly signal is extended in the tropics by vertical mixing. The solar cycle signal in CO is further examined with the Whole Atmosphere Community Climate Model (WACCM) 3.5 simulation by implementing two different modeled Spectral Solar Irradiances (SSIs): SRPM 2012 and NRLSSI. The model simulations underestimate the mean CO amount and solar cycle variations of CO, by a factor of 3, compared to those obtained from MLS observation. Different inputs of the solar spectrum have small impacts on CO variation.

The variability of interhemispheric symmetry of Earth’s energy serves as an independent indicator of climate change. The analysis of updated data obtained from satellite measurements at the top of the atmosphere (TOA) shows that in accord with Earth’s orbital requirements the annually averaged incident solar radiation is the same in the Northern and Southern Hemispheres, the annual mean of the reflected shortwave radiation is almost north–south symmetric, and the annual mean of the outgoing longwave radiation is larger in the Northern Hemisphere by 1.4 W m−2. These mean radiations systematically differ from the mean radiations found from the numerical atmospheric models that participated in the Coupled Model Intercomparison Project phase 5 (CMIP5). The hemispheric differences of the TOA radiations vary on the annual and interannual time scales. The multidecadal variability in Earth’s north–south temperature difference reveals a similarity of trends in both hemispheres. The Atlantic meridional transport (in contrast to the Pacific meridional transport) is found to be coherent with the interhemispheric ocean heat content (OHC) difference on decadal and multidecadal time scales, indicating a critical role of the Atlantic in the interhemispheric energy balance change.

The recent extended, deep minimum of solar variability and the extended minima in the 19th and 20th centuries (1810–1830 and 1900–1920) are consistent with minima of the Centennial Gleissberg Cycle (CGC), a 90–100 year variation of the amplitude of the 11-year sunspot cycle observed on the Sun and at the Earth. The Earth’s climate response to these prolonged low solar radiation inputs involves heat transfer to the deep ocean causing a time lag longer than a decade. The spatial pattern of the climate response, which allows distinguishing the CGC forcing from other climate forcings, is dominated by the Pacific North American pattern (PNA). The CGC minima, sometimes coincidently in combination with volcanic forcing, are associated with severe weather extremes. Thus the 19th century CGC minimum, coexisted with volcanic eruptions, led to especially cold conditions in United States, Canada and Western Europe.

The study of dynamic relationships between the atmospheric carbon dioxide and the Earth’s global temperature in the current changing climate supported the notion that the trend in the global temperature followed the trend in the atmospheric CO2 before the climate hiatus that started in the beginning of the 21st century. During the hiatus period, the heat trapped by the atmospheric CO2 is going mostly to the ocean. This conclusion is supported by comparison of the CO2 trend with the trend in the ocean heat content. The phase relationships between the CO2 and temperature are more complicated after the removal of the trends. The phase relationships are chaotic on time scales shorter than the annual time scale. During 1986-2008, the atmospheric CO2 changed in an-ti-phase with the global temperature. The phase relationship reversed in 1979 and after 2010. The atmospheric CO2 was in-phase with the global temperature on the El Nino time scale (2.3 - 7 years) except during very strong El Nino years in 1991-1999 when CO2 led the global temperature.

Deep Convective Clouds (DCC) are extreme rain events associated with large thunderstorms. They form in 0.6 % of the area of the tropical oceans. As the tropical oceans warm in a future climate, the frequency of occurrence of DCC may change. Between 2003 and 2016 the yearly mean temperature of the tropical ocean varied by almost 1 K. We use Atmospheric Infrared Sounder (AIRS) data for this time period to derive the probability of the DCC process as function of the Sea Surface Temperature (SST). The onset of the DCC process shifts about 0.5 K per 1 K of warming of the mean tropical SST. When these results are applied to the temperature distribution predicted by CMIP5 climate models for the end of this century, we find that the frequency of DCC, i.e. the percent of the area of the tropical oceans associated with DCC, which is 0.6 percent in the current climate, increases to 0.9 %, close to a 50 % increase.

We apply a nonlinear mean-field dynamo model which includes a budget equation for the dynamics of Wolf numbers to predict solar activity. This dynamo model takes into account the algebraic and dynamic nonlinearities of the alpha effect, where the equation for the dynamic nonlinearity is derived from the conservation law for the magnetic helicity. The budget equation for the evolution of the Wolf number is based on a formation mechanism of sunspots related to the negative effective magnetic pressure instability. This instability redistributes the magnetic flux produced by the mean-field dynamo. To predict solar activity on the time scale of one month we use a method based on a combination of the numerical solution of the nonlinear mean-field dynamo equations and the artificial neural network. A comparison of the results of the prediction of the solar activity with the observed Wolf numbers demonstrates a good agreement between the forecast and observations., Comment: 15 pages, 6 figures, jpp.cls, final version

The recent extended minimum of solar and geomagnetic variability (XSM) mirrors the XSMs in the nineteenth and twentieth centuries: 1810–1830 and 1900–1910. Such extended minima also were evident in aurorae reported from 450 A.D. to 1450 A.D. This paper argues that these minima are consistent with minima of the Centennial Gleissberg Cycles (CGCs), a 90–100 year variation observed on the Sun, in the solar wind, at the Earth, and throughout the heliosphere. The occurrence of the recent XSM is consistent with the existence of the CGC as a quasiperiodic variation of the solar dynamo. Evidence of CGCs is provided by the multicentury sunspot record, by the almost 150 year record of indexes of geomagnetic activity (1868 to present), by 1000 years of observations of aurorae (from 450 to 1450 A.D.) and millennial records of radionuclides in ice cores. The aa index of geomagnetic activity carries information about the two components of the solar magnetic field (toroidal and poloidal), one driven by flares and coronal mass ejections (related to the toroidal field) and the other driven by corotating interaction regions in the solar wind (related to the poloidal field). These two components systematically vary in their intensity and relative phase giving us information about centennial changes of the sources of solar dynamo during the recent CGC over the last century. The dipole and quadrupole modes of the solar magnetic field changed in relative amplitude and phase; the quadrupole mode became more important as the XSM was approached. Some implications for the solar dynamo theory are discussed.

New global satellite data from the Atmospheric Infrared Sounder (AIRS) are applied to study the tropospheric relative humidity (RH) distribution and its influence on outgoing longwave radiation (OLR) for January and July in 2003, 2007, and 2011. RH has the largest maxima over 90% in the equatorial tropopause layer in January. Maxima in July do not arise above 60%. Seasonal variations of about 20% in zonally averaged RH are observed in the equatorial region of the low troposphere, in the equatorial tropopause layer, and in the polar regions. The seasonal variability in the recent decade has increased by about 5% relative to that in 1973–88, indicating a positive trend. The observed RH profiles indicate a moist bias in the tropical and subtropical regions typically produced by the general circulation models. The new data and method of evaluating the statistical significance of bimodality confirm bimodal probability distributions of RH at large tropospheric scales, notably in the ascending branch of the Hadley circulation. Bimodality is also seen at 500–300 hPa in mid- and high latitudes. Since the drying time of the air is short compared with the mixing time of moist and dry air, the bimodality reflects the large-scale distribution of sources of moisture and the atmospheric circulation. Analysis of OLR dependence on surface temperature shows a 0.2 W m−2 K−1 difference in sensitivities between clear-sky and all-sky OLR, indicating a positive longwave cloud radiative forcing. Diagrams of the clear-sky OLR as functions of percentiles of surface temperature and relative humidity in the tropics are designed to provide a new measure of the supergreenhouse effect.

Deep convective clouds (DCCs) have been widely studied because of their association with heavy precipitation and severe weather events. Changes in the properties of DCCs are likely in a changing climate. Ten years of data collected by Atmospheric Infrared Sounder (AIRS) allow us to identify decadal trends in frequency of occurrence of DCCs over land and ocean. In the past, DCCs have been identified in the thermal infrared by three methods: (1) thresholds based on the absolute value of an atmospheric window channel brightness temperature; (2) thresholds based on the difference between the brightness temperature in an atmospheric window channel and the brightness temperature centered on a strong water vapor absorption line; and (3) a threshold using the difference between the window channel brightness temperature and the tropopause temperature based on climatology. Simultaneous observations of these infrared identified DCCs with the Advanced Microwave Sounding Unit–Humidity Sounder for Brazil (AMSU-HSB) using 183 GHz water channels provide a statistical correlation with microwave deep convection and overshooting convection. In the past 10 years, the frequency of occurrence of DCCs has decreased for the tropical ocean, while it has increased for tropical land. The area of the tropical zone associated with DCCs is typically much less than 1%. We find that the least frequent, more extreme DCCs show the largest trend in frequency of occurrence, increasing over land and decreasing over ocean. The trends for land and ocean closely balance, such that the DCC frequency changed at an insignificant rate for the entire tropical zone. This pattern of essentially zero trend for the tropical zone, but opposite land/ocean trends, is consistent with measurements of global precipitation. The changes in frequency of occurrence of the DCCs are correlated with the Niño34 index, which defines the sea surface temperature (SST) anomaly in the east-central Pacific. This is also consistent with patterns seen in global precipitation. This suggests that the observed changes in the frequency are part of a decadal variability characterized by shifts in the main tropical circulation patterns, which does not fully balance in the 10-year AIRS data record. The regional correlations and anti-correlations of the DCC frequency anomaly with the Multivariate ENSO Index (MEI) provide a new perspective for the regional analysis of past events, since the SST anomaly in the Nino34 region is available in the form of the extended MEI from 1871.

More than eight years (2004-2012) of carbon monoxide (CO) measurements from the Aura Microwave Limb Sounder (MLS) are analyzed. The mesospheric CO, largely produced by the carbon dioxide (CO2) photolysis in the lower thermosphere, is sensitive to the solar irradiance variability. The long-term variation of observed mesospheric MLS CO concentrations at high latitudes is likely driven by the solar-cycle modulated UV forcing. Despite of different CO abundances in the southern and northern hemispheric winter, the solar-cycle dependence appears to be similar. This solar signal is further carried down to the lower altitudes by the dynamical descent in the winter polar vortex. Aura MLS CO is compared with the Solar Radiation and Climate Experiment (SORCE) total solar irradiance (TSI) and also with the spectral irradiance in the far ultraviolet (FUV) region from the SORCE Solar-Stellar Irradiance Comparison Experiment (SOLSTICE). Significant positive correlation (up to 0.6) is found between CO and FUVTSI in a large part of the upper atmosphere. The distribution of this positive correlation in the mesosphere is consistent with the expectation of CO changes induced by the solar irradiance variations.

The authors present an analysis of the global midtropospheric CO2 retrieved for all-sky (clear and cloudy) conditions from measurements by the Atmospheric Infrared Radiation Sounder on board the Aqua satellite in 2003–09. The global data coverage allows the identification of the set of CO2 spatial patterns and their time variability by applying principal component analysis and empirical mode decomposition. The first, dominant pattern represents 93% of the variability and exhibits the linear trend of 2 ± 0.2 ppm yr−1, as well as annual and interannual dependencies. The single-site record of CO2 at Mauna Loa compares well with variability of this pattern. The first principal component is phase shifted relative to the Southern Oscillation, indicating a causative relationship between the atmospheric CO2 and ENSO. The higher-order patterns show regional details of CO2 distribution and display the semiannual oscillation. The CO2 distributions are compared with the distribution of two major characteristics of air transport: the vertical velocity and potential temperature surfaces at the same height. In agreement with modeling, CO2 concentration closely traces the potential temperature surfaces (isentropes) in middle and high latitudes. However, its vertical transport in the tropics, where these surfaces are mostly horizontal, is suppressed. The results are in agreement with the previous results on annual and interannual CO2 time variability obtained by using the network flask data. This knowledge of the global CO2 spatial patterns can be useful in climate analyses and potentially in the challenging task of connecting CO2 sources and sinks with its distribution in the atmosphere.

The global-mean top-of-atmosphere incident solar radiation (ISR) minus the outgoing longwave radiation (OLR) and the reflected shortwave radiation (RSW) is the net incident radiation (NET). This study analyzes the global-mean NET sensitivity to a change in the global-mean surface temperature by applying the interannual anomaly correlation technique to 9 yr of Atmospheric Infrared Sounder (AIRS) global measurements of RSW and OLR under cloudy and clear conditions. The study finds the observed sensitivity of NET that includes the effects of clouds to be −1.5 ± 0.25 (1σ) W m−2 K−1 and the clear NET sensitivity to be −2.0 ± 0.2 (1σ) W m−2 K−1, consistent with previous work using Earth Radiation Budget Experiment and Clouds and the Earth’s Radiant Energy System data. The cloud effect, +0.5 ± 0.2 (1σ) W m−2 K−1, is a positive component of the NET sensitivity. The similarity of the NET sensitivities derived from forced and unforced models invites a comparison between the observed sensitivities and the effective sensitivities calculated for the Fourth Assessment Report models, although this requires some caution: The effective model sensitivities with clouds range from −0.88 to −1.64 W m−2 K−1, the clear NET sensitivity in the models ranges from −2.32 to −1.73 W m−2 K−1, and the cloud forcing sensitivities range from +0.14 to +1.18 W m−2 K−1. The effective NET and clear NET sensitivities derived from the models are statistically consistent with those derived from the AIRS data, considering the observational and model derivation uncertainties.

We use the 8-year long satellite temperature data (2002–2010) from Atmospheric InfraRed Sounder (AIRS) and Atmospheric Microwave Sounding Unit (AMSU) on the Aqua satellite to identify temperature trends in the troposphere and low stratosphere over the Nino 3.4 region of the Tropical Pacific Ocean in the most recent 11-year solar cycle. Employing more extended sea surface temperature (SST) data for five solar cycles (1950–2009) in this region we show that the satellite trends reflect a typical decrease of the sea surface temperature (SST) in the Nino 3.4 region in the declining phase of the solar cycle. The magnitude of the SST decrease depends on the solar cycle and ranges between 0.07 K/yr and 0.27 K/yr for the last five solar cycles.

Unambiguous determination of trends is the central theme of climate change studies. A promising way to validate and quantify a warming trend of few degrees on a time scale of a century, predicted by climate models, is the use of measurements provided by satellites. However, climate variables, such as temperature and concentration of water vapor in the Earth's atmosphere, are noisy and subject to seasonal and interannual variabilities. The lifetime of any single satellite is relatively short (< 5–10 years) and producing long-term data records by using successive satellite introduces inter-calibration problems. Standard methods of trend determination, such as the least square fit of a linear trend, require sufficiently long time series and thus are not effective for the analysis of satellite data. Here, we applied the Empirical Mode Decomposition (EMD) and find it to be more efficient in the search for climate trends in the relatively short time series provided by satellites. We give examples of climate time series analyses using the EMD and discuss the problems we encounter in calculation and interpretation of trends extracted from the data limited in time extent.

Principal Components Analysis (PCA) and Independent Component Analysis (ICA) are used to identify global patterns in solar and space data. PCA seeks orthogonal modes of the two-point correlation matrix constructed from a data set. It permits the identification of structures that remain coherent and correlated or which recur throughout a time series. ICA seeks for maximally independent modes and takes into account all order correlations of the data. We apply PCA to the interplanetary-magnetic-field polarity near one AU and to the 3.25R source-surface fields in the solar corona. The rotations of the two-sector structures of these systems vary together to high accuracy during the active interval of solar cycle 23. We then use PCA and ICA to hunt for preferred longitudes in northern hemisphere, Carrington maps of magnetic fields., Comment: 20 pages, 13 figures

The high-energy solar proton data obtained from instruments onboard the IMP-8 spacecraft are used to investigate statistical distributions of event fluences, event durations, and time intervals between adjacent events. The results show that: (1) the event fluences can be approximately fit to a log-normal distribution and (2) the distributions of event durations and time intervals between the events can be represented by Poisson distributions. A virtual data set was generated using these distributions to extend the Solar Probe method [Feynman, J., Tylka, A.J., Reames, D.B., Gabriel, S.B. Near-sun energetic particle environment of Solar Probe-Phase1 final report, JPL Report, 2000] of obtaining the mission-integrated fluences to longer missions. By using the virtual data set generated in this study, we are able to obtain the smooth distribution of mission fluences for missions of any duration, which is not possible when only the available data sets was used.

We discuss effects of solar variability on the Earth’s large-scale climate patterns. These patterns are naturally excited as deviations (anomalies) from the mean state of the Earth’s atmosphere-ocean system. We consider in detail an example of such a pattern, the North Annular Mode (NAM), a climate anomaly with two states corresponding to higher pressure at high latitudes with a band of lower pressure at lower latitudes and the other way round. We discuss a mechanism by which solar variability can influence this pattern and formulate an updated general conjecture of how external influences on Earth’s dynamics can affect climate patterns.

We present a simple dynamic model of solar variability influence on climate, which is truncated from the stratospheric wave-zonal flow interaction dynamics over a β-plane. The model consists of three ordinary differential equations controlled by two parameters: the initial amplitude of planetary waves and the vertical gradient of the zonal wind. The changes associated with the solar UV variability, as well as with seasonal variations, are introduced as periodic modulations of the zonal wind gradient. Influence of the Quasi-Biennial Oscillation is included as a periodic change of the width of the latitudinal extent of the β-plane. The major climate response to these changes is seen through modulation of the number of cold and warm winters.

We analyze a 9 hr sequence of simultaneous, high-resolution, high-cadence G-band and K-line solar filtergrams plus magnetograms of lower cadence and resolution. Images include both network and internetwork. The magnetic and filtergram intensities, their fluctuations, and relative phases change with progressive strengthening of local magnetic field. At increased flux levels, sudden photospheric downflows create long-lived magnetic elements. For weak magnetic fields the K-line and G-band intensities include an oscillatory component with period 4 minutes. For stronger fields, the K-line period shifts to 5 minutes, while the G-band fluctuations fade due to dissociation of their source, the CH radical. These K-line and G-band fluctuations, whose periods are longer than the acoustic cutoff, are coherent and in phase. They also are coherent with fluctuations of the magnetic field. Weak-field magnetic fluctuations lead the intensity fluctuations by a phase shift of 90°. Strong-field magnetic fluctuations trail the intensities by 100°. These are interpreted as standing waves in the photosphere and low chromosphere. Another class of G-band fluctuations, with periods shorter than the acoustic cutoff, is associated both with stronger magnetic fields and with enhanced K-line emission with fluctuations longer than the cutoff period. This suggests waves excited by rapid photospheric perturbations and propagating up along magnetic flux tubes.

A simple dynamic model, truncated from the stratospheric wave–zonal flow interaction Holton and Mass model, is introduced and studied. This model consists of three ordinary differential equations controlled by two parameters: the initial amplitude of planetary waves and the vertical gradient of the zonal wind. The changes associated with seasonal variations and with the solar variability are introduced as periodic modulations of the zonal wind gradient. The major climatic response to these changes is seen through modulation of the number of cold and warm winters.

We analyze a unique 9 hr sequence of near-simultaneous, high-resolution and high-cadence G-band and K-line solar filtergrams, together with magnetograms of lower cadence and resolution. Our focus is on the phenomena surrounding discrete photospheric darkening events in internetwork G-band intensities. 72% of the darkenings are followed after 2 minutes by K-line brightenings. In the remaining cases, the darkenings are instead preceded by K-line brightenings 2 minutes earlier. Equivalent results are found when reference is shifted to K-line brightening events, although these two sets overlap by no more than 15%. The timing and coupling of the photospheric darkenings and chromospheric brightenings appear to be regulated by a preexisting 4 minute oscillation of the solar atmosphere. Other oscillations with periods in the range 1-8 minutes also are present, and in general the wave power is doubled at the time of an event. Our results favor an acoustic source for enhanced amplitudes of K-line intensity oscillations. The magnetic field acts as a passive tracer of horizontal photospheric flows that converge on the photospheric darkening events and then rebound.

We use the aa index of geomagnetic activity recorded for 130 years to study the strength and phase properties of the solar dynamo. We split the monthly averaged aa into two parts: one part proportional to the sunspot number and the other part proportional to the residual. We argue that the first part is a proxy for the solar dynamo's large-scale mean toroidal magnetic field. The residual has the same periodicity as the sunspot cycle and has closely related amplitude, but is shifted in phase. We relate this residual to the poloidal field generated from the toroidal field in the dynamo process. The changes in both components demonstrate that there was a long-term trend in the strength and relative phases of the toroidal and poloidal components of the mean-field dynamo. The changes in the relative phase of the toroidal and poloidal fields suggest that the distributions of the differential rotation and helicity within the Sun's convection zone have changed over timescales of 50 years.

Using spacecraft data collected over three solar cycles, Neugebauer et al. [2000] found a persistent dependence of the solar wind speed and the radial component of the interplanetary magnetic field on solar longitude, defined in a coordinate system with a rotation period of 27.03 days. Here we investigate the solar source of this period using observations of the photospheric magnetic field. We study the lowest-order nonaxisymmetric modes of the solar field extracted from synoptic charts of the Wilcox Solar Observatory. We find there is a robust magnetic structure on the Sun, which rotates with the period found by Neugebauer et al. [2000] in the solar wind. This rotation is more rapid than the solar equatorial and core rotations. We discuss the association of this nonaxisymmetric mode with the magnetic field generated by the solar mean field dynamo.

Below the scale of supergranules we find that cellular flows are present in the solar photosphere at two distinct size scales, approximately 2 Mm and 4 Mm, with distinct characteristic times. Simultaneously present in the flow is a non-cellular component, with turbulent scaling properties and containing 30% of the flow energy. These results are obtained by means of wavelet spectral analysis and modeling of vertical photospheric motions in a 2-hour sequence of 120 SOHO/MDI, high resolution, Doppler images near disk center. The wavelets permit detection of specific local flow patterns corresponding to convection cells.

The diffusion properties of photospheric bright points associated with magnetic elements (magnetic bright points) in the granulation network are analyzed. We find that the transport is subdiffusive for times less than 20 minutes but normal for times larger than 25 minutes. The subdiffusive transport is caused by the walkers being trapped at stagnation points in the intercellular pattern. We find that the distribution of waiting times at the trap sites obeys a truncated Levy type (power-law) distribution. The fractal dimension of the pattern of sites available to the random walk is less than 2 for the subdiffusive range and tends to 2 in the normal diffusion range. We show how the continuous time random walk formalism can give an analytical explanation of the observations. We simulate this random walk by using a version of a phenomenological model of renewing cells introduced originally for supergranules by Simon, Title, & Weiss. We find that the traps that cause the subdiffusive transport arise when the renewed convection cell pattern is neither fixed nor totally uncorrelated from the old pattern, as required in Leighton's model, but in some intermediate state between these extremes.