3D-Matched-Filter Galaxy Cluster Finder I: Selection Functions and CFHTLS Deep Clusters

We present an optimised galaxy cluster finder, 3D-Matched-Filter (3D-MF), which utilises galaxy cluster radial profiles, luminosity functions and redshift information to detect galaxy clusters in optical surveys. This method is an improvement over other matched-filter methods, most notably through implementing redshift slicing of the data to significantly reduce line-of-sight projections and related false positives. We apply our method to the Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) Deep fields, finding ~170 galaxy clusters per square degree in the 0.2 <= z <= 1.0 redshift range. Future surveys such as LSST and JDEM can exploit 3D-MF's automated methodology to produce complete and reliable galaxy cluster catalogues. We determine the reliability and accuracy of the statistical approach of our method through a thorough analysis of mock data from the Millennium Simulation. We detect clusters with 100% completeness for M_200 >= 3.0x10^(14)M_sun, 88% completeness for M_200 >= 1.0x10^(14)M_sun, and 72% completeness well into the 10^(13)M_sun cluster mass range. We show a 36% multiple detection rate for cluster masses >= 1.5x10^(13)M_sun and a 16% false detection rate for galaxy clusters >~ 5x10^(13)M_sun, reporting that for clusters with masses <~ 5x10^(13)M_sun false detections may increase up to ~24%. Utilising these selection functions we conclude that our galaxy cluster catalogue is the most complete CFHTLS Deep cluster catalogue to date.Comment: 18 pages, 17 figures, 5 tables; v2: added Fig 5, minor edits to match version published in MNRA

Jerks abound: An analysis of geomagnetic observatory data from 1957 to 2008

We present a two-step method for the removal of external field signals and the identification of geomagnetic jerks in magnetic observatory monthly mean data, providing quantitative uncertainty estimates on jerk occurrence times and amplitudes with minimal a priori information. We apply the method to the complete time series of X-, Y- and Z-components at up to 103 observatory locations in the period of 1957–2008. We find features fitting the definition of jerks in individual components to be frequent and not globally contemporaneous. Identified regional jerks have no consistent occurrence pattern and the most widespread in any given year is identified at <30% of observatories worldwide. Whilst we identify jerks throughout the period of study, relative peaks in the global number of jerk occurrences are found in 1968–71, 1973–74, 1977–79, 1983–85, 1989–93, 1995–98 and 2002–03 with the suggestion of further poorly sampled events in the early 1960s and late 2000s. The mean uncertainties on individual jerk occurrence times and amplitudes are found to be ±0.3 yrs and ±2.1 nT/yr2, respectively, for all field components. Jerk amplitudes suggest possible periodic trends across Europe and North America, which may be related to the 6-yr periods detected independently in the secular variation and length-of-day

The Central Regions of M31 in the 3 - 5 micron Wavelength Region

Images obtained with NIRI on the Gemini North telescope are used to investigate the photometric properties of the central regions of M31 in the 3 - 5 micron wavelength range. The light distribution in the central arcsecond differs from what is seen in the near-infrared in the sense that the difference in peak brigh tness between P1 and P2 is larger in M' than in K'; no obvious signature of P3 is dete cted in M'. These results can be explained if there is a source of emission that contributes ~ 20% of the peak M' light of P1 and has an effective temperature of no more than a few hundred K that is located between P1 and P2. Based on the red K-M' color of this source, it is suggested that the emission originates in a circumstellar dust shell surrounding a single bright AGB star. A similar bright source that is ~ 8 arcsec from the center of the galaxy is also detected in M'. Finally, the (L', K-L') color-magnitude diagram of unblended stars shows a domin ant AGB population with photometric characteristics that are similar to those of the most luminous M giants in the Galactic bulge.Comment: To appear in the Astronomical Journa

Fingerprint of Climate Change on Southern Ocean Carbon Storage

The Southern Ocean plays a critical role in the uptake, transport, and storage of carbon by the global oceans. It is the ocean's largest sink of CO2, yet it is also among the regions with the lowest storage of anthropogenic carbon. This behavior results from a unique combination of high winds driving the upwelling of deep waters and the subduction and northward transport of surface carbon. Here we isolate the direct effect of increasing anthropogenic CO2 in the atmosphere from the indirect effect of climate variability and climate change on the reorganization of carbon in the Southern Ocean interior using a combination of modeling and observations. We show that the effect of climate variability and climate change on the storage of carbon in the Southern Ocean is nearly as large as the effect of anthropogenic CO2 during the period 1998–2018 compared with the climatology around the year 1995. We identify a distinct climate fingerprint in dissolved inorganic carbon (DIC), with elevated DIC concentration in the ocean at 300–600 m that reinforces the anthropogenic CO2 signal, and reduced DIC concentration in the ocean around 2,000 m that offsets the anthropogenic CO2 signal. The fingerprint is strongest at lower latitudes (30°–55°S). This fingerprint could serve to monitor the highly uncertain evolution of carbon within this critical ocean basin, and better identify its drivers.publishedVersio

A statistical gap-filling method to interpolate global monthly surface ocean carbon dioxide data

We have developed a statistical gap-filling method adapted to the specific coverage and prop-erties of observed fugacity of surface ocean CO2(fCO2). We have used this method to interpolate the Sur-face Ocean CO2Atlas (SOCAT) v2 database on a 2.5832.58 global grid (south of 708N) for 1985–2011 atmonthly resolution. The method combines a spatial interpolation based on a ‘‘radius of influence’’ to deter-mine nearby similar fCO2values with temporal harmonic and cubic spline curve-fitting, and also fits long-term trends and seasonal cycles. Interannual variability is established using deviations of observations fromthe fitted trends and seasonal cycles. An uncertainty is computed for all interpolated values based on thespatial and temporal range of the interpolation. Tests of the method using model data show that it performsas well as or better than previous regional interpolation methods, but in addition it provides a near-globaland interannual coverage

Can core-surface flow models be used to improve the forecast of the Earth's main magnetic field?

[1] Geomagnetic main field models used for navigation are updated every 5 years and contain a forecast of the geomagnetic secular variation for the upcoming epoch. Forecasting secular variation is a difficult task. The change of the main magnetic field is thought to be principally due to advection of the field by flow at the surface of the outer core on short timescales and when large length scales are considered. With accurate secular variation (SV) and secular acceleration (SA) models now available from new satellite missions, inverting for the flow and advecting it forward could lead to a more accurate prediction of the main field. However, this scheme faces two significant challenges. The first arises from the truncation of the observable main field at spherical harmonic degree 13. This can however be handled if the true core flow is large scale and has a rapidly decaying energy spectrum. The second is that even at a given single epoch the instantaneous SV and SA cannot simultaneously be explained by a steady flow. Nevertheless, we find that it may be feasible to use flow models for an improved temporal extrapolation of the main field. A medium-term (≈10 years) hindcast of the field using a steady flow model outperforms the usual extrapolation using the presently observed SV and SA. On the other hand, our accelerated, toroidal flow model, which explains a larger portion of the observed average SA over the 2000–2005 period, fails to improve both the short-term and medium-term hindcasts of the field. This somewhat paradoxical result is related to the occurrence of so-called geomagnetic jerks, the still poorly known dynamical nature of which remains the main obstacle to improved geomagnetic field forecasts