11email: [email protected] 22institutetext: SRON Netherlands Institute for Space Research, Niels Bohrweg 4, 2333 CA Leiden, The Netherlands 33institutetext: CAS Key Laboratory for Research in Galaxies and Cosmology, Department of Astronomy, University of Science and Technology of China, Hefei 230026, China 44institutetext: School of Astronomy and Space Science, University of Science and Technology of China, Hefei 230026, China 55institutetext: Department of Astronomy, Nanjing University, Nanjing 210093, China 66institutetext: Key Laboratory of Modern Astronomy and Astrophysics (Nanjing University), Ministry of Education, Nanjing 210093, China 77institutetext: Department of Physical, Hiroshima University, 1-3-1 Kagamiyama, HigashiHiroshima, Hiroshima 739-8526, Japan 88institutetext: Department of Physics, University of Strathclyde, Glasgow G4 0NG, UK 99institutetext: Anton Pannekoek Astronomical Institute, University of Amsterdam, P.O. Box 94249, 1090 GE Amsterdam, the Netherlands 1010institutetext: Space Telescope Science Institute, 3700 San Martin Drive, Baltimore, MD 21218, USA 1111institutetext: INAF-IASF Palermo, Via U. La Malfa 153, I-90146 Palermo, Italy 1212institutetext: INAF-Osservatorio Astronomico di Brera, Via E. Bianchi 46, 23807 Merate, LC, Italy 1313institutetext: MAX-Planck-Institut fr Extraterrestrische Physik, Giessenbachstrasse, D-85748, Garching, Germany 1414institutetext: Department of Physics, Technion-Israel Institute of Technology, 32000 Haifa, Israel 1515institutetext: Dipartimento di Matematica e Fisica, Università degli Studi Roma Tre, Via della Vasca Navale 84, 00146 Roma, Italy 1616institutetext: Mullard Space Science Laboratory, University College London, Holmbury St. Mary, Dorking, Surrey RH5 6NT, UK 1717institutetext: Departament de Física, EEBE, Universitat Politècnica de Catalunya, Av. Eduard Maristany 16, E-08019 Barcelona, Spain 1818institutetext: Univ. Grenoble Alpes, CNRS, IPAG, 38000 Grenoble, France 1919institutetext: Telespazio UK for the European Space Agency (ESA), European Space Astronomy Centre (ESAC), Camino Bajo del Castillo, s/n, E-28692 Villanueva de la Cañada, Madrid, Spain 2020institutetext: Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA UK 2121institutetext: School of Physics and Astronomy and Wise Observatory, Tel Aviv University, Tel Aviv 69978, Israel 2222institutetext: Department of Astronomy, University of Geneva, 16 Ch. d0Ecogia, 1290 Versoix, Switzerland 2323institutetext: Italian Space Agency (ASI), Via del Politecnico snc, 00133 Roma, Italy
Transient obscuration event captured in NGC 3227
II. Warm absorbers and obscuration events in archival XMM-Newton and NuSTAR observations
The relation between warm absorber (WA) outflows of AGN and nuclear obscuration activities caused by optically-thick clouds (obscurers) crossing the line of sight is still unclear. NGC 3227 is a suitable target to study the properties of both WAs and obscurers, because it matches the following selection criteria: WAs in both ultraviolet (UV) and X-rays, suitably variable, bright in UV and X-rays, good archival spectra for comparing with the obscured spectra. To investigate WAs and obscurers of NGC 3227 in detail, we used a broadband spectral-energy-distribution model that is built in the first paper of our series and the photoionization code of SPEX software to fit the archival observational data taken by XMM-Newton and NuSTAR in 2006 and 2016. Using unobscured observations, we find four WA components with different ionization states (). The highest-ionization WA component has a much higher hydrogen column density () than the other three components (). The outflow velocities of these WAs range from 100 to 1300 , and show a positive correlation with the ionization parameter. These WA components are estimated to be distributed from the outer region of the broad line region (BLR) to the narrow line region. It is worth noting that we find an X-ray obscuration event in the beginning of the 2006 observation, which was missed by previous studies. It can be explained by a single obscurer component. We also study the previously published obscuration event captured in one observation in 2016, which needs two obscurer components to fit the spectrum. A high-ionization obscurer component (; covering factor ) only appears in the 2016 observation, which has a high column density (). A low-ionization obscurer component (; ) exists in both 2006 and 2016 observations, which has a lower column density (). These obscurer components are estimated to reside within the BLR by their crossing time of transverse motions. The obscurers of NGC 3227 are closer to the center and have larger number densities than the WAs, which indicate that the WAs and obscurers might have different origins.
Key Words.:
X-rays: galaxies – Galaxies: active – Galaxies: Seyfert – Galaxies: individual: NGC 3227 – Techniques: spectroscopic1 Introduction
Active galactic nuclei (AGN) accrete matter onto a central supermassive black hole (SMBH) to produce intense broadband radiation, which can ionize and drive away the surrounding matter in forms of outflows. Many observational proofs have implied that outflows might play an important role in affecting the star formation and evolution of their host galaxies (see the review of King & Pounds, 2015). Ionized outflows can be detected via absorption features along the line of sight in the ultraviolet (UV) and X-rays, which usually have different types (Laha et al., 2021, and references therein) such as broad absorption lines (BALs; Weymann et al., 1981), warm absorbers (WAs; Halpern, 1984; Crenshaw et al., 2003), and ultrafast outflows (UFOs; Tombesi et al., 2010). UFOs might have an origin close to the central engine (; Tombesi et al., 2012) with very high velocities (; Tombesi et al., 2010, 2012). BALs usually reside outside the broad line region (BLR) with high outflow velocities reaching (Trump et al., 2006; Gibson et al., 2009). Compared with UFOs and BALs, WAs have lower outflow velocities from about one hundred to a few thousands of (Kaastra et al., 2000; Ebrero et al., 2013), and they might originate in the accretion disk (e.g., Elvis, 2000; Krongold et al., 2007), BLR (Reynolds & Fabian, 1995), or dusty torus (e.g., Krolik & Kriss, 2001; Blustin et al., 2005). Although different types of outflows have overlaps in distance scales and outflow parameters, the direct connection between these outflows still remains unclear. In this work, we mainly focus on the properties of the WA outflows.
According to Tarter et al. (1969), the ionization parameter can be defined by
(1) |
where is the ionizing luminosity over 1–1000 Ryd, is the hydrogen number density of the absorbing gas, and is the radial distance of the absorbing gas to the central engine. WAs might be driven by radiation pressure (e.g., Proga & Kallman, 2004), magnetic forces (e.g., Blandford & Payne, 1982; Konigl & Kartje, 1994; Fukumura et al., 2010), or thermal pressure (e.g., Begelman et al., 1983; Krolik & Kriss, 1995; Mizumoto et al., 2019), and show a wide range of ionization parameter () and hydrogen column density () (Laha et al., 2014). Investigating properties of WAs can help us to understand the formation of AGN outflows and their feedback efficiency to the host galaxy. These WAs have been found in about 50% of nearby AGN (e.g., Reynolds, 1997; Kaastra et al., 2000; Porquet et al., 2004; Tombesi et al., 2013; Laha et al., 2014), and the properties of WAs show differences among different AGN, such as the different ionization states, column densities, and outflow velocities (Tombesi et al., 2013; Laha et al., 2014).
Moreover, the X-ray spectra of some AGN present dramatic hardening accompanied by flux-drops on short timescales, which might be due to the X-ray transient obscuration events (Markowitz et al., 2014). Transient obscuration events can also cause absorption features in the soft X-ray and UV bands, which usually appear and disappear on shorter timescales compared with outflows. These obscuration events might be explained by discrete optically thick clouds or gas clumps crossing the line of sight, which are referred to as obscurers. These shielding gas clumps or obscurers might ensure that the radiatively driven disk winds in broad absorption line quasars are not over-ionized by UV/X-ray ionizing radiation and are accelerated further (Murray et al., 1995; Proga et al., 2000; Kaastra et al., 2014). The obscuration events may be triggered by the collapse of the BLR (Kriss et al., 2019a, b; Devereux, 2021). When the continuum radiation decreases, the BLR clouds will collapse towards the accretion disk; when the continuum brightens again, these collapsed clouds might be blown away as obscurers (Kriss et al., 2019b). X-ray obscuration events also have been found in many AGN, such as NGC 5548 (Kaastra et al., 2014), NGC 3783 (Mehdipour et al., 2017; Kaastra et al., 2018; De Marco et al., 2020), NGC 985 (Ebrero et al., 2016a), and NGC 1365 (Risaliti et al., 2007; Walton et al., 2014; Rivers et al., 2015). These obscurers may be located within the BLR (Lamer et al., 2003; Risaliti et al., 2007; Lohfink et al., 2012; Longinotti et al., 2013; De Marco et al., 2020; Kara et al., 2021), or close to the outer BLR (e.g., Kaastra et al., 2014; Beuchert et al., 2015; Mehdipour et al., 2017), or near the inner torus (e.g., Beuchert et al., 2017).
Until now the relation between the WA outflows and the nuclear obscuration activity is not yet well understood. Whether the WAs and obscurers have the same origin or how shielding by the obscuration affects the WAs and their appearance is not well known. Studying WAs in targets that have transient obscuration enables us to probe these questions. Transient obscuration events have been studied simultaneously in UV and X-rays in only a few AGN that have WAs outflows, such as NGC 5548 (Kaastra et al., 2014), and NGC 3783 (Mehdipour et al., 2017), and also Mrk 335 (Longinotti et al., 2013; Parker et al., 2019). Studying NGC 3227 (a Seyfert 1.5 galaxy at the redshift of 0.003859111The redshift of NGC 3227 is obtained from the NASA/IPAC Extragalactic Database (NED). The NED is funded by the National Aeronautics and Space Administration and operated by the California Institute of Technology.) is a rare opportunity towards a more general characterization. NGC 3227 was one of eight suitable targets selected for the Neil Gehrels Swift Observatory monitoring/triggering programme (Mehdipour et al., 2017), which matches the following selection criteria: WAs in both UV and X-rays, suitably variable, bright in UV and X-rays, good archival spectra for comparing with the obscured spectra. Using our target of opportunity (ToO) monitoring programme of the Neil Gehrels Swift Observatory, we captured another X-ray obscuration event in NGC 3227 in 2019 (Mehdipour et al., 2021, hereafter Paper I), which was observed simultaneously with XMM-Newton, NuSTAR, and Hubble Space Telescope/Cosmic Origins Spectrograph (HST/COS) to get a deeper multi-wavelength understanding of the transient obscuration phenomenon in AGN. The studies of WA and the obscurer are interlinked, so without having a proper model for the WA, the new obscurer cannot be accurately studied. In this work (the second paper of our series), we aim to study a comprehensive model for the WA, and then use this WA model to investigate the obscuration events appearing in NGC 3227.
It should be noted that photoionization modelling strongly depends on the ionizing spectral-energy-distribution (SED). Therefore, to properly derive the ionization structure of the WA, having an accurate broadband SED model is important. A few papers have reported studies of the WAs in NGC 3227 (Komossa & Fink, 1997; Beuchert et al., 2015; Turner et al., 2018; Newman et al., 2021) and its nuclear obscurations activities (Lamer et al., 2003; Markowitz et al., 2014; Beuchert et al., 2015; Turner et al., 2018). However, the contribution of the SED components that dominate in the UV/optical band lacks consideration, which might affect the fitting results of the WAs and obscurers (see Paper I). The main effect of using different SEDs is that the derived ionization parameter would be different. The total hydrogen column density of the WA (i.e. sum of the individual components) would be similar, but how is distributed over different ionization components depends on the SED. We refer the readers to Mehdipour et al. (2016) where the effect of using different SEDs, and codes, is shown. With these considerations, we firstly built a broadband SED model from the near infrared (NIR) to hard X-rays for NGC 3227 in our Paper I. In this paper, we use this broadband SED model and a robust photoionization code (pion model; Mehdipour et al., 2016) in the SPEX package (Kaastra et al., 1996) v3.05.00 (Kaastra et al., 2020) to analyze the archival XMM-Newton and NuSTAR data taken in 2006 (Markowitz et al., 2009) and 2016 (Turner et al., 2018). SPEX is currently the only code that enables the SED and the ionization balance to be fitted simultaneously, while all other codes have to pre-calculate the ionization balance on a given SED. The pion model is a self-consistent model that can simultaneously calculate the thermal/ionization balance and the plasma spectrum in photoionization equilibrium. In this work, we focus on properties of the WAs and obscuration events of NGC 3227 with the archival 2006 and 2016 data. The detailed analysis of the 2019 obscuration events will be presented in Paper III by Mao et al. (in prep). The discussion about how the obscurer changes over the course of the 2019 observations with the XMM-Newton/EPIC-pn data will be presented in Paper IV by Grafton-Waters et al. (in prep).
This paper is organized as follows. In Sect. 2, we present the archival data that are used in this work and the data reduction process. In Sect. 3, we introduce the spectral analysis based on the broadband SED model. In Sect. 4, we present and discuss the results about WAs and obscurer components. In Sect. 5, we give a summary of our conclusions. In this work, Cash statistic (Kaastra, 2017, hereafter C-stat) will be used to estimate the goodness of fit and statistical errors will be given at 1 (68%) confidence level. We adopt the following flat CDM cosmological parameters: =70 km s Mpc, =0.30, and =0.70.
\addstackgap[.5] # | Observatory | ObsID | Date | Exposure |
(yyyy-mm-dd) | (ks) | |||
\addstackgap[.5] Obs1 | XMM | 0400270101 | 2006-12-03 | 108 |
\addstackgap[.5] Obs2 | XMM | 0782520201 | 2016-11-09 | 92 |
NuSTAR | 60202002002 | 2016-11-09 | 50 | |
\addstackgap[.5] Obs3 | XMM | 0782520301 | 2016-11-25 | 74 |
NuSTAR | 60202002004 | 2016-11-25 | 43 | |
\addstackgap[.5] Obs4 | XMM | 0782520501 | 2016-12-01 | 87 |
NuSTAR | 60202002008 | 2016-12-01 | 42 | |
\addstackgap[.5] Obs5 | XMM | 0782520601 | 2016-12-05 | 87 |
NuSTAR | 60202002010 | 2016-12-05 | 41 | |
\addstackgap[.5] Obs6 | XMM | 0782520701 | 2016-12-09 | 88 |
NuSTAR | 60202002012 | 2016-12-09 | 39 |
2 Observations and Data Reduction
In Table 1, we list the archival data that are used in this work. These data include six XMM-Newton observations (Markowitz et al., 2009; Turner et al., 2018) and five NuSTAR observations (Turner et al., 2018). We do not use the archival XMM-Newton observations taken in 2000 and on 2016 November 29, because the spectrum of the 2000 observation has a lower signal to noise ratio (S/N) owing to its short exposure time, and the observation on 2016 November 29 shows a relatively unstable softness ratio curve (see Fig. 1 of Turner et al., 2018), which may bias the estimation of WAs parameters.
2.1 XMM-Newton data
The data reduction was done using XMM-Newton Science Analysis Software (SAS) version 18.0.0, following the standard data analysis procedure222See https://www.cosmos.esa.int/web/xmm-newton/sas-threads for details.. The cleaned event files of EPIC-pn data were produced using the epproc pipeline and flaring particle background larger than 0.4 count/s was excluded. The EPIC-pn spectra and lightcurves were extracted from a circular region with a radius of 30 arcsec for the source and from a nearby source-free circular region with a radius of 35 arcsec for the background. Response matrices and ancillary response files of each observation were produced using the SAS tasks arfgen and rmfgen. Following the standard procedure, the first-order data of RGS1 and RGS2 were extracted using the SAS task rgsproc and flaring particle background larger than 0.2 count/s was excluded. We then combined the spectra of RGS1 and RGS2 using the SAS task rgscombine. We refer readers to our Paper I for the detailed data reduction of the Optical Monitor (OM) data. Only the OM UVW1 filter is available for both 2006 and 2016 observations.
2.2 NuSTAR data
For the two telescope modules (FPMA and FPMB) data of NuSTAR, level 1 calibrated and level 2 cleaned event files were produced using the standard procedure of the nupipeline task of HEASoft v6.27. The level 3 products including lightcurves, spectra and response files were extracted using the task nuproducts from a circular region with a radius of 90 arcsec for the source and from a nearby source-free circular region with the same radius for the background. Finally, we produced combined spectra of FPMA and FPMB data using tasks mathpha and produced combined response files using tasks addrmf and addarf.


\addstackgap[.5] Comp. | Parameter | Obs1 | Obs2 | Obs3 | Obs4 | Obs5 | Obs6 |
\addstackgap[.5] dbb | Normalization () | 5.87 (s) | 7.51 (s) | 7.15 (s) | 6.87 (s) | 7.27 (s) | 7.39 (s) \addstackgap[.5] |
\addstackgap[.5] comt | Normalization () | \addstackgap[.5] | |||||
\addstackgap[.5] pow | Normalization () | \addstackgap[.5] | |||||
Photon index | \addstackgap[.5] | ||||||
\addstackgap[.5] refl | Incident power-law Normalization | 4.02 (c) | 2.93 (c) | 2.25 (c) | 3.60 (c) | 4.64 (c) | 4.59 (c) \addstackgap[.5] |
Incident power-law photon index | 1.81 (c) | 1.73 (c) | 1.66 (c) | 1.78 (c) | 1.88 (c) | 1.86 (c) \addstackgap[.5] | |
Reflection scale s | \addstackgap[.5] | ||||||
\addstackgap[.5] Luminosity | 0.3–2 keV luminosity | 1.28 | 0.90 | 0.66 | 1.14 | 1.42 | 1.48 \addstackgap[.5] |
() | 2–10 keV luminosity | 1.45 | 1.20 | 1.00 | 1.32 | 1.50 | 1.54 \addstackgap[.5] |
1–1000 Ryd ionizing luminosity | 19.1 | 17.8 | 14.6 | 19.8 | 19.2 | 23.5 \addstackgap[.5] | |
Bolometric luminosity | 43.3 | 47.1 | 42.4 | 46.6 | 47.1 | 52.2 \addstackgap[.5] | |
\addstackgap[.5] -stat / -expt. | (SED+WAs) | 34392794 (S1b)∗ | 44563621∗ | 38343584 | 41053588 | 41213570 | 37623638 (S6c) \addstackgap[.5] |
(Best-fit) | (SED+OCL+WAs) | 32612926 (S1a) | 38193670 (S6b) \addstackgap[.5] | ||||
(SED+OCH+OCL+WAs) | 37863654 (S6a) \addstackgap[.5] |
3 Spectral Analysis
For the 2016 archival data, we will consider each set of XMM-Newton and NuSTAR observations taken on the same date as a single dataset (see Obs2 to Obs6 in Table 1), where XMM-Newton (OM UVW1 filter at 2910 , RGS data in the 6–37 wavelength range, and EPIC-pn data in the 2–10 keV energy band) and NuSTAR (combined FPMA and FPMB data in the 5–78 keV energy range) data are used simultaneously for the spectral analysis. For Obs1 that was taken on 2006 December 03, only XMM-Newton observation is available (see Table 1), and we used Obs5 to verify that the best-fit parameters of the WAs do not significantly change without NuSTAR observation. In Figs. 1 and 2, we show the XMM-Newton/EPIC-pn light curves, softness ratio curves (the ratio of count rates between 0.3–2 and 2–10 keV bands), and the correlation between the softness ratio and 0.3–10 keV count rate for Obs1 to Obs6. According to these results, we make a preliminary analysis for the state of each observation.
-
•
Obs1: This observation was considered to be in an unobscured state by Markowitz et al. (2009). However, compared with the average softness ratio of the six observations (see the dashed red line in the bottom panel of Fig. 1), a significant spectral hardening (softness ratio below the average value) occurred in the beginning of this observation (see the bottom panel of the first column in Fig. 1), which might indicate the existence of an obscuration event. After this spectral hardening period, the softness ratio of Obs1 returns to the average value, which might indicate that this obscuration event has disappeared. These phenomena mean that these two periods of Obs1 should be analyzed separately. According to the difference between the softness ratio of Obs1 and the average softness ratio of the six observations, Obs1 is subdivided into the following two slices: S1a and S1b (see the first column in Fig. 1). S1b is consistent with being in an unobscured state as it follows the correlation of Obs2 to Obs5 (see the right panel of Fig. 2). However, S1a has a harder spectrum that is similar to S6a and S6b (see the right panel of Fig. 2), which might be in an obscured state, but it was not reported in the previous works.
-
•
Obs2 to Obs5: According to Turner et al. (2018), Obs2 to Obs5 are in unobscured states, which show a linear correlation between the softness ratio (0.3–11–10 keV) and 0.3–10 keV count rate. We confirm this linear correlation for these observations (softness ratio is calculated between the 0.3–2 and 2–10 keV bands in this work) in the left panel of Fig. 2. It is worth noting that although Obs2 and Obs3 show a spectral hardening during some periods, these periods still follow the correlation of unobscured states (see the left panel of Fig. 2). Therefore, these periods might not be in obscured states.
-
•
Obs6: Turner et al. (2018) had observed a rapid obscuration event in Obs6. To restudy this obscuration event using a broadband SED model and the pion model in SPEX, we followed Turner et al. (2018) to subdivide Obs6 into three slices: S6a, S6b, and S6c (see Fig. 1). S6c shows an unobscured state as it follows the correlation of Obs2 to Obs5 (see the right panel of Fig. 2). However, S6a and S6b deviate from the correlation of Obs2 to Obs5 (see the right panel of Fig. 2), therefore, might be in obscured states.
Next we make the detailed spectral analysis for these observational data. We begin our spectral modelling by using a broadband SED model from the NIR to the hard X-ray bands for NGC 3227. We refer readers to our Paper I for full details about this SED model and we only give a brief introduction here. The main spectral components that are used in this work are shown below:
-
1.
The intrinsic broadband SED (see details in Paper I), which is composed of a disk blackbody component (dbb), a warm Comptonized disk component (comt) from the optical to the soft X-ray band, an X-ray power-law component (pow), and a neutral reflection component (refl) in the hard X-ray energy band. For pow of NGC 3227, we used 309 keV (Turner et al., 2018) as the high-energy exponential cut-off and used 13.6 eV as the low-energy exponential cut-off.
-
2.
The obscurer components, which heavily absorb the X-ray spectrum. We used the pion model in SPEX to fit their absorption features in the spectrum.
-
3.
The warm absorber (WA) components, which produce absorption features in soft X-rays. We also used the pion model to fit these absorption features.
-
4.
The Galactic X-ray absorption, which was taken into account by the hot model in SPEX with the hydrogen column density (Murphy et al., 1996).
Obs2 to Obs5, S1b, and S6c are in unobscured states, so we will fit their spectra using the spectral components 1, 3, and 4. S1a, S6a, and S6b are in obscured states, so their spectra will be fitted with the spectral components 1–4. Next we will present the details of the spectral analysis for spectral components 1, 2, and 3.
3.1 The intrinsic broadband SED
For the archival data, only the OM UVW1 filter data is available for all the six observations, so the parameters of the dbb component might not be well constrained in the fit. Moreover we do not expect a strong variability in the shape of the emission from the outer disc on short timescales and commonly the variability of the flux in long wavelengths is significantly smaller than that in the X-ray band. Therefore, we assume that the shape of the dbb component of each archival observation is similar to that of the 2019 observation which has optical and UV observational data to constrain the dbb component (see Paper I). That is to say, we fixed the maximum temperature of the dbb component of the archival data to the 10 eV of the 2019 observation (see Paper I), and scaled the dbb normalization of the archival observations according to the normalization of the 2019 observation (the scale factor of each archival observation is the OM UVW1 flux ratio between the 2019 observation and each archival observation). For the comt component, its normalization was free in the fit and the following parameters were fixed to those of the 2019 observation (see details in Paper I): seed photon temperature eV, electron temperature eV, and optical depth . The dbb and comt components mainly dominate in the energy band below 0.5 keV (see Paper I), so fixing the shapes of these two components might bring uncertainties to the parameter estimates for the WAs. Even so, the normalizations of these two components, which are free in the fits, are still the main factors to affect the fitting result. For each slice in an obscured state (S1a, S6a, and S6b), we assumed that it has the same intrinsic broadband SED as the unobscured slice in the same observation (S1b, S6c, and S6c, respectively). Therefore, we fixed the parameters of dbb, comt, pow, and refl components of S1a to those of S1b in the fit. Similarly, these parameters of S6a and S6b were fixed to those of S6c. For the refl component, the scaling factor of the reflected spectrum (s) was free in the fit, the incident power-law normalization and photon index were coupled to those of the pow component. We summarize the best-fit parameters of the intrinsic broadband SED in Table 2, which will be discussed in Section 4.1.

3.2 Warm absorber components
The hydrogen column density (), outflow velocity () and turbulent velocity () of the WAs are not well constrained simultaneously for the spectrum with low S/N and these parameters might not vary significantly between different observations. Therefore, we fixed these parameters of Obs1–Obs4 and Obs6 to the best-fit results of Obs5 (see Table 3), because Obs5 has the highest S/N. Therefore, for Obs1–Obs4 and Obs6, only was free in the fit (see Table 3). Actually, , , and are not expected to be constant, so our assumption will bring extra uncertainties to the parameter estimates. However, , , and might not vary significantly on short timescales compared with , so a significant impact on the fitting results with these parameters fixed might not be expected. For simplicity, we assumed that the WAs fully cover the X-ray source (covering factor ) and have solar abundances (Lodders et al., 2009). The best-fit results of the WAs are discussed in Sect. 4.2.
3.3 Obscurer components
Parameters and of the obscurer components were difficult to constrain owing to the lack of well defined and strong absorption lines, and we verified that changing their values had little impact on other parameters. Therefore, we fixed and of the obscurer components to their default values ( and ). With that, the obscurer components, , , and are free in the fit. We will discuss the best-fit results of obscurer components in Sect. 4.3.
4 Results and Discussion
4.1 Intrinsic broadband SED
The broadband SED model provides a good description for the observational data (see Table 2 and Fig. 3: Obs5 is taken as an example). Compared with other observations or slices, Obs1 S1b and Obs2 have relatively worse fitting results (see Table 3), which are mainly due to the uncertainties in the intercalibration between XMM-Newton and NuSTAR. The intrinsic unabsorbed broadband SEDs of Obs1 to Obs6 are shown in Fig. 4 and their best-fit parameters are listed in Table 2. The intrinsic broadband SED of NGC 3227 shows a significant variability at energies 0.03 keV especially in the X-ray band (see Fig. 4). According to the Spearman’s rank method, there is a positive correlation between the photon index of the pow component (; see Table 2) and the intrinsic 2–10 keV luminosity (; see Table 2) (the correlation coefficients and the associated -values ), which shows a “softer-when-brighter” behavior. This behavior has been observed in many Seyfert galaxies (e.g., Markowitz & Edelson, 2004; Ponti et al., 2006; Sobolewska & Papadakis, 2009; Soldi et al., 2014). Peretz & Behar (2018) also found a softer-when-brighter variability behavior in NGC 3227, which might be driven by varying absorption rather than by the intrinsic variability of the central source. The averaged ionizing luminosity over 1–1000 Ryd is around (see Table 2), which is two times larger than the results of Beuchert et al. (2015) and Turner et al. (2018). This might be due to the different SED model in the UV and soft X-ray bands. The averaged full-band bolometric luminosity () is about (see Table 2), which is 1.5 times smaller than the result of Woo & Urry (2002) based on the flux integration method. According to the reverberation mapping method, the black hole mass () of NGC 3227 is for NGC 3227 (Bentz & Katz, 2015). The Eddington luminosity () of NGC 3227 is , which is calculated by (Rybicki & Lightman, 1979). Therefore, the averaged Eddington ratio of NGC 3227 is about 6%.

\addstackgap[.5] | 03 Dec. 2006 | 09 Nov. 2016 | 25 Nov. 2016 | 01 Dec. 2016 | 05 Dec. 2016 | 09 Dec. 2016 | ||||
Component | Parameter | Obs1 | Obs2 | Obs3 | Obs4 | Obs5 | Obs6 | |||
S1b | S1a∗ | S6c | S6b∗ | S6a∗ \addstackgap[.5] | ||||||
\addstackgap[.5] | 2.27 (f) | 2.27 (f) | 2.27 (f) | 2.27 (f) | 2.27 (f) | 2.27 (f) | 2.27 (f) | 2.27 (f) \addstackgap[.5] | ||
WA1 | 2.93 | 3.02 | 2.94 \addstackgap[.5] | |||||||
1270 (f) | 1270 (f) | 1270 (f) | 1270 (f) | 1270 (f) | 1270 (f) | 1270 (f) | 1270 (f) \addstackgap[.5] | |||
20 (f) | 20 (f) | 20 (f) | 20 (f) | 20 (f) | 20 (f) | 20 (f) | 20 (f) \addstackgap[.5] | |||
0.25 (f) | 0.25 (f) | 0.25 (f) | 0.25 (f) | 0.25 (f) | 0.25 (f) | 0.25 (f) | 0.25 (f) \addstackgap[.5] | |||
WA2 | 2.51 | 2.56 | 2.47 \addstackgap[.5] | |||||||
500 (f) | 500 (f) | 500 (f) | 500 (f) | 500 (f) | 500 (f) | 500 (f) | 500 (f) \addstackgap[.5] | |||
140 (f) | 140 (f) | 140 (f) | 140 (f) | 140 (f) | 140 (f) | 140 (f) | 140 (f) \addstackgap[.5] | |||
0.12 (f) | 0.12 (f) | 0.12 (f) | 0.12 (f) | 0.12 (f) | 0.12 (f) | 0.12 (f) | 0.12 (f) \addstackgap[.5] | |||
WA3 | 1.88 | 1.94 | 1.86 \addstackgap[.5] | |||||||
440 (f) | 440 (f) | 440 (f) | 440 (f) | 440 (f) | 440 (f) | 440 (f) | 440 (f) \addstackgap[.5] | |||
50 (f) | 50 (f) | 50 (f) | 50 (f) | 50 (f) | 50 (f) | 50 (f) | 50 (f) \addstackgap[.5] | |||
0.16 (f) | 0.16 (f) | 0.16 (f) | 0.16 (f) | 0.16 (f) | 0.16 (f) | 0.16 (f) | 0.16 (f) \addstackgap[.5] | |||
WA4 | \addstackgap[.5] | |||||||||
110 (f) | 110 (f) | 110 (f) | 110 (f) | 110 (f) | 110 (f) | 110 (f) | 110 (f) \addstackgap[.5] | |||
260 (f) | 260 (f) | 260 (f) | 260 (f) | 260 (f) | 260 (f) | 260 (f) | 260 (f) \addstackgap[.5] |
4.2 Warm absorber components
At least four WA components (see Table 3) were required to improve the fitting result ( for adding WA1, for adding WA2, for adding WA3, for adding WA4). We added another component (a fifth component), but it did not improve the fitting result (). Our result is not consistent with that in Turner et al. (2018), which detected three WA components. It might be due to the different SED model and photoionization models between our and their works. The best-fit model shows some weak residual emission features in the 0.5–0.6 keV band (see Fig. 3) caused by the oxygen line emission from distant regions, similar to NGC 5548 (Mao et al., 2018). The quality of our spectrum is insufficient to do detailed modelling of these emission lines, and they are too weak to affect our modelling of the absorbing wind components. Therefore they will not be discussed further.
4.2.1 Parameters of the warm absorbers
The logarithm of the ionization parameter (in units of ) of the four WA components is around 3.0 for WA1, 2.5 for WA2, 2.0 for WA3, and 1.0 for WA4 (see Table 3). WA2, WA3, and WA4 have a similar column density around , while WA1 has a much higher value near (see Table 3). In paper I, we adopt a de-ionization scenario for the WAs and simultaneous fitted the spectra of the archival unobscured observation taken on 2016 December 05 and the new obscured observations taken in 2019. In this work, we fit the spectra taken on 2016 December 05 alone. Therefore, some different results between Paper I and Paper II can be expected because of the different spectral modelling. The X-ray transmission of each WA component in our line of sight to the central region is shown in the top panel of Fig. 5. WA1 mainly absorbs the continuum radiation between 0.8 and 10 keV. WA2 and WA3 produce absorption features between 0.7 and 5 keV. WA4 heavily absorbs the continuum below 5 keV. From WA1 to WA4, the outflow velocity gradually decreases from to (see Table 3), which shows a positive correlation with the ionization parameter. This correlation is consistent with the results for AGN samples (Tombesi et al., 2013; Laha et al., 2014). These previous studies indicated that this correlation cannot be explained by the radiatively driven or magneto hydrodynamically driven outflowing mechanism (Tombesi et al., 2013; Laha et al., 2014), and it might be explained by the equilibrium between the radiation pressure on WAs and the drag pressure from the ambient circumnuclear medium (see details in Wang et al., submitted).

4.2.2 Radial location of the warm absorbers
We use three methods to estimate the upper or lower limit of the locations of the various WA components. First, we assume that the thickness () of the WA cloud does not exceed its distance () to the SMBH (Krolik & Kriss, 2001; Blustin et al., 2005). As , so the upper limit of the distance , where is the volume filling factor. Combining with Eq. 1, can be estimated by
(2) |
Assuming that the total outflow momentum of the WA cloud is equal to the momentum of the absorbed radiation () plus the momentum of the ionizing luminosity being scattered (), can be calculated by
(3) |
(Blustin et al., 2005; Grafton-Waters et al., 2020). Here, is given by
(4) |
where is the absorbed luminosity, and is calculated by
(5) |
where is the optical depth for Thomson scattering, and is the Thomson scattering cross-section. We use the ionizing luminosity of Obs5 to estimate the distance as the WAs parameters are mainly from the spectral fitting of Obs5. The estimated upper limit ( in Eq. 2) of the radial location of each WA component is summarized in Table 4, which is 0.007 pc for WA1, 0.24 pc for WA2, 0.71 pc for WA3, and 265 pc for WA4.
The second method is based on the assumption that the outflow velocities of winds are larger than or equal to their escape velocities (Blustin et al., 2005), then we can obtain the lower limit of by
(6) |
where is the gravitational constant. The lower limit of the radial location of each WA component is estimated to be 0.03 pc for WA1, 0.2 pc for WA2, 0.3 pc for WA3, and 4 pc for WA4 (see Table 4).

The third method to estimate the radial location of WAs is based on the recombination timescale. Following Bottorff et al. (2000), the recombination timescale of the ion is defined as
(7) |
where is the recombination coefficient (recombination rate from the ion to ), is the electron number density of the absorbing gas, and is the fraction of ion . We select the ions that contribute significantly to the spectral fit for each WA component as the indicators of this component. Some of these parameters can be obtained from SPEX code (Mao & Kaastra, 2016): and come from atomic physics, and and are estimated from the ionization balance. Then we can obtain (see Table 4). The of each WA component can be estimated by the variation timescale of the ionization parameters between different observations (e.g., Ebrero et al., 2016b). For WA1, the ionization parameter shows a significant variation between Obs2 and Obs3, so its might be lower than the time interval between Obs2 and Obs3 (16 days). For WA2, there is a significant change for the ionization parameter between Obs3 and Obs5, so its might be smaller than the time interval between Obs3 and Obs5 (10 days). For both WA3 and WA4, Obs3 and Obs4 have a significantly different ionization parameter, which indicates that their might be smaller than the time interval between Obs3 and Obs4 (6 days). However, we cannot make a clear conclusion about the lower limits of the for these WA components because of the low number of observations. We list the of each WA component in Table 4. According to , , and Eq. 1 (we also use the ionizing luminosity of Obs5 here), the radial distance is estimated to be 0.16 pc for WA1, 0.3 pc for WA2, 0.6 pc for WA3, 13 pc for WA4 (see Table 4). These estimates are consistent with the results obtained by Eqs. 2 and 6 (see Table 4 and Fig. 6).
The radial location of the optical BLR of NGC 3227 is estimated to be around 0.0032 pc from the time lag between the H line and continuum at 5100 (Denney et al., 2009). The optical [O III] 5007 image indicates that the narrow line region (NLR) of NGC 3227 can extend to 100 pc (Schmitt & Kinney, 1996), even to 500 pc (Mundell et al., 1995). According to Nenkova et al. (2008b), the inner radius of the torus can be estimated by
(8) |
with a dust temperature of K. If (see Sect. 4.1), is about 0.09 pc. The outer radius can be estimated by . Using the clumpy model (Nenkova et al., 2002, 2008a, 2008b), Alonso-Herrero et al. (2011) estimated that the of NGC 3227 is about 17, so is around 1.46 pc. The distance estimates for the BLR, torus, NLR, and each WA component of NGC 3227 are shown in Fig. 6.
As Fig. 6 shows, WA1 lies between the outer region of the BLR and the inner region of torus; WA2 and WA3 might be in the torus. WA4 likely resides between the outer torus and the NLR, and it is the one that is farthest away from the AGN compared with other WAs, which might explain the lowest ionization parameter of this component (see details in Section 4.2.1 and Table 3). For the distance estimation of WA1, the first and second methods give inconsistent results, which might be due to the following reasons: (1) these two methods use different assumptions, which can be expected to have different results; (2) we did not consider the possible contribution from the momentum associated with other processes (e.g., magnetic field), which might be not negligible for WA1 and might make (see Eq. 3) and (see Eq. 2) being underestimated.
\addstackgap[.5] Parameter | WA1 | WA2 | WA3 | WA4 |
Method 1∗: Distance thickness | ||||
1.68 | 1.44 | 1.54 | 51.3 \addstackgap[.5] | |
9.6 | 1.1 | 0.5 | 0.7 \addstackgap[.5] | |
0.049 | 0.039 | 0.011 | 0.006 \addstackgap[.5] | |
(pc) d | 0.007 | 0.24 | 0.71 | 265 \addstackgap[.5] |
Method 2†: Outflow velocity escape velocity | ||||
(pc)e | 0.03 | 0.2 | 0.3 | 4 \addstackgap[.5] |
Method 3‡: Recombination timescale method | ||||
5.6 | 5.4 | 3.9 | 7.2 \addstackgap[.5] | |
(days) | 16 | 10 | 6 | 6 \addstackgap[.5] |
4.0 | 6.3 | 7.5 | 14.0 \addstackgap[.5] | |
(pc) h | 0.16 | 0.3 | 0.6 | 13 \addstackgap[.5] |
$$a$$$$a$$footnotetext: Momentum outflow rate from the radiation being absorbed.
$$b$$$$b$$footnotetext: Momentum outflow rate from the radiation being scattered.
$$c$$$$c$$footnotetext: Volume filling factor.
$$d$$$$d$$footnotetext: The distances of the WAs that are estimated by the first method.
$${\dagger}$$$${\dagger}$$footnotetext: The second method to estimate the distances of the WAs, which is based on the assumption that the outflow velocities of winds () are larger than or equal to their escape velocities () (see Eq. 6).
$$e$$$$e$$footnotetext: The distances of the WAs that are estimated by the second method.
$${\ddagger}$$$${\ddagger}$$footnotetext: The third method to estimate the distances of the WAs, which is based on the recombination timescale (see Eq. 7).
$$f$$$$f$$footnotetext: Recombination time scale.
$$g$$$$g$$footnotetext: Electron number density.
$$h$$$$h$$footnotetext: The distances of the WAs that are estimated by the third method.
4.3 Obscurer components
According to the softness ratio (see Sect. 3), S6a, S6b, and S1a seem to be in obscured states, which may be caused by the clouds (obscurer components) crossing the line of sight. Then we make detailed spectral modellings to check whether the obscurer components are required to explain the significant spectral variation in these slices. Firstly, we fixed the parameters of the intrinsic SED and WAs of S1a to those of S1b that is in the unobscured state because we do not expect strong variabilities in the SED shape and WAs parameters on small time scales between S1a and S1b. However, the absorption features in the soft X-rays cannot be explained by WAs alone. Therefore, we add an obscurer component, which greatly improves the fitting result (). Similarly, we firstly fixed the intrinsic SED and WAs parameters of S6b to those of S6c that is in the unobscured state. One obscurer component is also required to improve the fitting result with . Adding a second obscurer component cannot improve the fitting result of both S1a and S6b. For S6a, we firstly fixed its intrinsic SED and WAs parameters to those of S6c, which cannot explain the observational data well. We verified that two obscurer components are required to improve the fitting result: for adding one obscurer component and for adding a second obscurer component.
4.3.1 Parameters of the obscurer components
The spectral analysis indicates that S6a has two obscurer components: a high-ionization component (; S6a OCH) with of and a low-ionization component (; S6a OCL) with of . S6b and S1a only have one low-ionization obscurer component respectively: for S6b OCL with of and for S1a OCL with of (see Table 5). The low-ionization obscurer component (OCL) has a lower column density () than the high-ionization obscurer component (OCH; ) (see Table 5). S6a OCL has a larger covering factor than S6a OCH, considering 1 level uncertainties. Our result for S6a is not consistent with that in Turner et al. (2018) which only found one obscurer component with , , and . It might be due to the different SED model and different spectral modelling process. The X-ray transmission of each obscurer component in our line of sight to NGC 3227 is shown in Fig. 5. OCL components can produce absorption features at energies lower than 6 keV, and the OCH component mainly absorbs the continuum at energies higher than 0.5 keV.
\addstackgap[.5] Comp. | Parameter | S6a | S6b | S1a |
---|---|---|---|---|
\addstackgap[.5] | \addstackgap[.5] | |||
OCH | \addstackgap[.5] | |||
\addstackgap[.5] | ||||
\addstackgap[.5] | ||||
OCL | \addstackgap[.5] | |||
\addstackgap[.5] |
4.3.2 Radial location of the obscurer components
As we mention in Sect. 3.3, we cannot constrain the outflow velocities of the obscurer components, so we cannot estimate the distance of the obscurer components using the methods for the WAs. Here we estimate the distance of the obscurer components based on the crossing time of the obscuring cloud. For simplicity, we assume that an obscuring cloud moves around the central black hole () in a circular orbit of radius , so that the keplerian velocity of the obscuring cloud crossing the line of sight is . Assuming a spherical geometry for the obscuring cloud, its diameter is and the size of this cloud crossing the line of sight is approximately equal to , so that can also be given by , where is the crossing time of the obscuring cloud. Therefore, we can obtain a relation for :
(9) |
Following Lamer et al. (2003), we combine Eqs. 1 and 9 to obtain :
(10) |
where , , is in days, and .
On the one hand, Obs5 is in an unobscured state, which indicates that OCH and OCL of S6a do not start to cross the line of sight during the observational time of Obs5. One the other hand, OCH of S6a disappears in the observational time of S6b. Therefore, of OCH should be larger than the exposure time of S6a (39 ks) and smaller than the time interval between Obs5 and Obs6 (309 ks). If we assume that S6a and S6b have different OCL components, of S6a OCL should be also between 39 and 309 ks (similar to the case of S6a OCH), and of S6b OCL should be comparable to the exposure time of S6b (20 ks). Similarly, of S1a OCL should be larger than the exposure time of S1a (20 ks), and smaller than the time interval (372 days) between Obs1 and an unobscured observation taken in November 2005 (see Fig. A12 of Markowitz et al., 2014). The estimated crossing time of each obscurer component is summarized in Table 6. Then we can use Eq. 10 to constrain the location of each obscurer component, which is shown in Table 6 and Fig. 6. These obscurer components are estimated to be located within the BLR, which is consistent with the results in previous works (Lamer et al., 2003; Beuchert et al., 2015; Turner et al., 2018).
The obscurers of NGC 3227 are closer to the SMBH than the WAs and also have a significantly larger hydrogen or electron number density than the WAs (see Figure 6). Besides that, the obscurers usually appear on a short timescale while WAs can exist for a long time, and the appearance of the obscurers mainly affects the ionization state of the WAs on the short timescale. These results indicate that the obscurers and WA outflows might have different origin. For example, obscurers might be triggered by the collapse of inner BLR clouds (Kriss et al., 2019a, b; Devereux, 2021), while WA outflows might be formed by the outflowing of the clouds between outer BLR and NLR under the drive of the radiation pressure (e.g., Proga & Kallman, 2004), magnetic forces (e.g., Blandford & Payne, 1982; Konigl & Kartje, 1994; Fukumura et al., 2010), or thermal pressure (e.g., Begelman et al., 1983; Krolik & Kriss, 1995; Mizumoto et al., 2019). However, we cannot get a solid conclusion in this work, which might require more high-quality data to investigate.
\addstackgap[.5] Comp. | (pc) | |
---|---|---|
\addstackgap[.5] S6a OCH | 39–305 ks | 0.001–0.002 \addstackgap[.5] |
S6a OCL | 39–305 ks | 0.011–0.02 \addstackgap[.5] |
S6b OCL | 20 ks | 0.004 \addstackgap[.5] |
S1a OCL | 20 ks–372 days | 0.004–0.07 \addstackgap[.5] |
5 SUMMARY AND CONCLUSIONS
The relation between WA outflows of AGN and nuclear obscuration activities is still unclear. NGC 3227 is a suitable target to study the properties of both WAs and obscurers, which might help us understand their correlation. To investigate the WA components of NGC 3227 in detail, we use a broadband SED model (Paper I) and the photoionization model in SPEX software to fit the unobscured spectra of the archival and previously published XMM-Newton and NuSTAR observations taken in 2006 and 2016. Based on the broadband SED and WAs parameters, we also study the X-ray obscuration events in the archival observations.
We detect four ionization phases for the WAs in NGC 3227 using the unobscured observations: . The highest-ionization WA component has a much higher hydrogen column density () than the other three WA components (). The outflow velocities of these WA components range from to , and show a positive correlation with the ionization parameter. Our estimates of the radial location of these WA components indicate that the WAs of NGC 3227 might reside over radii ranging from the BLR to the torus, even to the NLR.
We find an obscuration event in 2006, which was missed by previous studies. One obscurer component is required for this 2006 obscuration event. For the previously published obscuration event in 2016, we detect two obscurer components. A high-ionization obscurer component (; covering factor ) only appears in the 2016 observation, which has a column density around , while both the 2006 and 2016 observations have a low-ionization obscurer component ( 1.0–1.9; ), which has a lower column density () than the high-ionization obscurer component. Assuming that the variations of flux is caused by the transverse motion of obscurers across the line of sight, we estimate the locations of obscurers to be within the BLR.
The obscurers of NGC 3227 are closer to the SMBH than the WAs and have a significantly larger hydrogen or electron number density than the WAs. In addition, the obscurers usually appear on a short timescale while the WAs can exist for a long time. These proofs indicate that the obscurers and WAs of NGC 3227 might have different origins.
Acknowledgements.
We thank the referee for helpful comments that improved this paper. This research has made use of the NASA/IPAC Extragalactic Database (NED), which is funded by the National Aeronautics and Space Administration and operated by the California Institute of Technology. YJW gratefully acknowledges the financial support from the China Scholarship Council. YJW and YQX acknowledge support from NSFC-12025303, 11890693, 11421303, the CAS Frontier Science Key Research Program (QYZDJ-SSW-SLH006), the K.C. Wong Education Foundation, and the science research grants from the China Manned Space Project with NO. CMS-CSST-2021-A06. SRON is supported financially by NWO, the Netherlands Organization for Scientific Research. JM acknowledges the support from STFC (UK) through the University of Strathclyde UK APAP network grant ST/R000743/1. GP acknowledges funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 865637). E.B. is funded by a Center of Excellence of THE ISRAEL SCIENCE FOUNDATION (grant No. 2752/19). SB acknowledges financial support from ASI under grants ASI-INAF I/037/12/0 and n. 2017-14-H.O., and from PRIN MIUR project ”Black Hole winds and the Baryon Life Cycle of Galaxies: the stone-guest at the galaxy evolution supper”, contract no. 2017PH3WAT. BDM acknowledges support via Ramón y Cajal Fellowship RYC2018-025950-I. SGW acknowledges the support of a PhD studentship awarded by the UK Science & Technology Facilities Council (STFC). DJW acknowledges support from STFC in the form of an Ernest Rutherford fellowship. P.O.P acknowledges financial support from the CNES french agency and the PNHE high energy national program of CNRS.References
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