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We present an estimate of the bulk flow in a volume of radii 150−200 h−1 Mpc using the minimum variance method with data from the CosmicFlows-4 (CF4) catalogue. The addition of new data in the CF4 has resulted in an increase in the estimate of the bulk flow in a sphere of radius 150 h−1 Mpc relative to the CosmicFlows-3 (CF3). This bulk flow has an $\sim 0.015~{{\ \rm per\ cent}}$ chance of occurring in the standard cosmological model with cosmic microwave background derived parameters. Given that the CF4 is deeper than the CF3, we were able to use the CF4 to accurately estimate the bulk flow on scales of 200 h−1 Mpc (equivalent to 266 Mpc for Hubble constant H0 = 75 km s−1 Mpc−1) for the first time. This bulk flow is in even greater tension with the standard model, having $\sim 1.5\times 10^{-4}\ \%$ probability of occurring. To estimate the bulk flow accurately, we introduce a novel method to calculate distances and velocities from distance moduli that is unbiased and accurate at all distances. Our results are completely independent of the value of H0.

 

Gridded air temperature data are required in various fields such as ecological modeling, weather forecasting, and surface energy balance assessment. In this work, a piecewise multiple linear regression model is used to produce high‐resolution (250 m) daily maximum (T_max), minimum (T_min), and mean (T_mean) near‐surface air temperature maps for the State of Hawaiʻi for a 32‐year period (1990–2021). Multiple meteorological and geographical variables such as the elevation, daily rainfall, coastal distance index, leaf area index, albedo, topographic position index, and wind speed are independently tested to determine the most well‐suited predictor variables for optimal model performance. During the mapping process, input data scarcity is addressed first by gap‐filling critical stations at high elevation using a predetermined linear relationship with other strongly‐correlated stations, and second, by supplementing the training dataset with station data from neighboring islands. Despite the numerous covariates physically linked to temperature, the most parsimonious model selection uses elevation as its sole predictor, and the inclusion of the additional variables results in increased cross‐validation errors. The mean absolute error of resultant estimatedT_maxandT_minmaps over the Hawaiian Islands from 1990 to 2021 is 1.7°C and 1.3°C, respectively. Corresponding bias values are 0.01°C and −0.13°C, respectively for the same variables. Overall, the results show the proposed methodology can robustly generate daily air temperature maps from point‐scale measurements over complex topography.

 

Abstract PHANGS-HST is an ultraviolet-optical imaging survey of 38 spiral galaxies within ∼20 Mpc. Combined with the PHANGS-ALMA, PHANGS-MUSE surveys and other multiwavelength data, the dataset will provide an unprecedented look into the connections between young stars, H ii regions, and cold molecular gas in these nearby star-forming galaxies. Accurate distances are needed to transform measured observables into physical parameters (e.g., brightness to luminosity, angular to physical sizes of molecular clouds, star clusters and associations). PHANGS-HST has obtained parallel ACS imaging of the galaxy halos in the F606W and F814W bands. Where possible, we use these parallel fields to derive tip of the red giant branch (TRGB) distances to these galaxies. In this paper, we present TRGB distances for 11 galaxies from ∼4 to ∼15 Mpc, based on the first year of PHANGS-HST observations. Five of these represent the first published TRGB distance measurements (IC 5332, NGC 2835, NGC 4298, NGC 4321, and NGC 4328), and eight of which are the best available distances to these targets. We also provide a compilation of distances for the 118 galaxies in the full PHANGS sample, which have been adopted for the first PHANGS-ALMA public data release.