The WFDEI meteorological forcing data set has been generated using the same methodology as the widely used WATCH Forcing Data (WFD) by making use of the ERA‐Interim reanalysis data. We discuss the ...specifics of how changes in the reanalysis and processing have led to improvement over the WFD. We attribute improvements in precipitation and wind speed to the latest reanalysis basis data and improved downward shortwave fluxes to the changes in the aerosol corrections. Covering 1979–2012, the WFDEI will allow more thorough comparisons of hydrological and Earth System model outputs with hydrologically and phenologically relevant satellite products than using the WFD.
Key Points
Global three hourly meteorological forcing data at half‐degree spatial resolution
Covers 1979–2012
Improvements compared to the WATCH forcing data
Urbanisation is estimated to result in 6 billion urban dwellers by 2050. Cities will be exposed to climate change from greenhouse gas induced radiative forcing, and localised effects from ...urbanisation such as the urban heat island. An urban land‐surface model has been included in the HadAM3 Global Climate Model. It shows that regions of high population growth coincide with regions of high urban heat island potential, most notably in the Middle East, the Indian sub‐continent, and East Africa. Climate change has the capacity to modify the climatic potential for urban heat islands, with increases of 30% in some locations, but a global average reduction of 6%. Warming and extreme heat events due to urbanisation and increased energy consumption are simulated to be as large as the impact of doubled CO2 in some regions, and climate change increases the disparity in extreme hot nights between rural and urban areas.
Context.
The Low Frequency Array (LOFAR) Two-metre Sky Survey (LoTSS) is a low-frequency radio continuum survey of the Northern sky at an unparalleled resolution and sensitivity.
Aims.
In order to ...fully exploit this huge dataset and those produced by the Square Kilometre Array in the next decade, automated methods in machine learning and data-mining will be increasingly essential both for morphological classifications and for identifying optical counterparts to the radio sources.
Methods.
Using self-organising maps (SOMs), a form of unsupervised machine learning, we created a dimensionality reduction of the radio morphologies for the ∼25k extended radio continuum sources in the LoTSS first data release, which is only ∼2 percent of the final LoTSS survey. We made use of
PINK
, a code which extends the SOM algorithm with rotation and flipping invariance, increasing its suitability and effectiveness for training on astronomical sources.
Results.
After training, the SOMs can be used for a wide range of science exploitation and we present an illustration of their potential by finding an arbitrary number of morphologically rare sources in our training data (424 square degrees) and subsequently in an area of the sky (∼5300 square degrees) outside the training data. Objects found in this way span a wide range of morphological and physical categories: extended jets of radio active galactic nuclei, diffuse cluster haloes and relics, and nearby spiral galaxies. Finally, to enable accessible, interactive, and intuitive data exploration, we showcase the LOFAR-PyBDSF Visualisation Tool, which allows users to explore the LoTSS dataset through the trained SOMs.
Given difficulties with modelling radiation fog and the similarity of meteorological conditions linked to dewfall and frost we investigated the formation of dew, frost and fog. For a site in the UK ...seven years of data were analysed representing high‐resolution atmospheric profiles and dew meter measurements for radiation nights with stable conditions. Classical dewfall occurs by condensation when the surface is below the dew point and cooler than the air above. However, the profiles show that, in the absence of fog, typically dew and frost form with the surface warmer than the immediately overlying air due to lifted temperature minima (LTMs) at about 0.15 m. Observations of aerosol number density and average hydrated radii show that aerosol optical extinction (and hence their radiative effect) is weakly but significantly correlated with the intensity of LTMs. Low wind speed on stable nights allows settling of aerosols which radiatively cool the air near the ground more quickly than the surface cools – thus creating LTMs. In the presence of LTMs typically dew and frost form not by condensation, but by occult deposition of water droplets onto the canopy and ground. Among radiation fog observations, 91% are associated with light near‐surface winds and LTMs. When the rate of removal of suspended water droplets by occult deposition generating dew or frost is too slow, then build‐up of droplets in the air just above the surface leads to the formation of radiation fog. Future modelling should allow for the accumulation of near‐surface aerosols and their radiative effects during stable nights to represent the formation of LTMs. Modelling of typical dew and frost will require representation of occult deposition. Assessing rates of occult deposition compared to rates of generation of suspended water droplets is needed to forecast the onset of radiation fog formed near the ground.
In stable nocturnal conditions most radiation fog forms when the air near the surface is cooler than the grass canopy and soil, that is, during a lifted temperature minimum (LTM). Observations show LTMs result from low turbulence plus radiative cooling of the air by near‐surface aerosols. Under LTMs most dewfall occurs by water droplet collision with the surface (occult deposition) rather than condensation. Radiation fog forms when occult deposition is too slow to prevent increasing water droplet concentration above the surface.
ABSTRACT
Feedback from low-excitation radio galaxies (LERGs) plays a key role in the lifecycle of massive galaxies in the local Universe; their evolution, and the impact of these active galactic ...nuclei on early galaxy evolution, however, remain poorly understood. We use a sample of 10 481 LERGs from the first data release of the LOFAR two-metre Sky Survey Deep Fields, covering ∼25 deg2, to present the first measurement of the evolution of the radio luminosity function (LF) of LERGs out to z ∼ 2.5; this shows relatively mild evolution. We split the LERGs into those hosted by quiescent and star-forming galaxies, finding a new dominant population of LERGs hosted by star-forming galaxies at high redshifts. The incidence of LERGs in quiescent galaxies shows a steep dependence on stellar mass out to z ∼ 1.5, consistent with local Universe measurements of accretion occurring from cooling of hot gas haloes. The quiescent-LERGs dominate the LFs at z < 1, showing a strong decline in space density with redshift, tracing that of the available host galaxies, while there is an increase in the characteristic luminosity. The star-forming LERG LF increases with redshift, such that this population dominates the space densities at most radio-luminosities by z ∼ 1. The incidence of LERGs in star-forming galaxies shows a much weaker stellar-mass dependence, and increases with redshift, suggesting a different fuelling mechanism compared to their quiescent counterparts, potentially associated with the cold gas supply present in the star-forming galaxies.
Due to their steep spectra, low-frequency observations of Fanaroff–Riley type II (FR II) radio galaxies potentially provide key insights in to the morphology, energetics and spectrum of these ...powerful radio sources. However, limitations imposed by the previous generation of radio interferometers at metre wavelengths have meant that this region of parameter space remains largely unexplored. In this paper, the first in a series examining FR IIs at low frequencies, we use LOFAR (LOw Frequency ARray) observations between 50 and 160 MHz, along with complementary archival radio and X-ray data, to explore the properties of two FR II sources, 3C 452 and 3C 223. We find that the morphology of 3C 452 is that of a standard FR II rather than of a double-double radio galaxy as had previously been suggested, with no remnant emission being observed beyond the active lobes. We find that the low-frequency integrated spectra of both sources are much steeper than expected based on traditional assumptions and, using synchrotron/inverse-Compton model fitting, show that the total energy content of the lobes is greater than previous estimates by a factor of around 5 for 3C 452 and 2 for 3C 223. We go on to discuss possible causes of these steeper-than-expected spectra and provide revised estimates of the internal pressures and magnetic field strengths for the intrinsically steep case. We find that the ratio between the equipartition magnetic field strengths and those derived through synchrotron/inverse-Compton model fitting remains consistent with previous findings and show that the observed departure from equipartition may in some cases provide a solution to the spectral versus dynamical age disparity.
ABSTRACT
New-generation radio telescopes like LOFAR are conducting extensive sky surveys, detecting millions of sources. To maximize the scientific value of these surveys, radio source components ...must be properly associated into physical sources before being cross-matched with their optical/infrared counterparts. In this paper, we use machine learning to identify those radio sources for which either source association is required or statistical cross-matching to optical/infrared catalogues is unreliable. We train a binary classifier using manual annotations from the LOFAR Two-metre Sky Survey (LoTSS). We find that, compared to a classification model based on just the radio source parameters, the addition of features of the nearest-neighbour radio sources, the potential optical host galaxy, and the radio source composition in terms of Gaussian components, all improve model performance. Our best model, a gradient boosting classifier, achieves an accuracy of 95 per cent on a balanced data set and 96 per cent on the whole (unbalanced) sample after optimizing the classification threshold. Unsurprisingly, the classifier performs best on small, unresolved radio sources, reaching almost 99 per cent accuracy for sources smaller than 15 arcsec, but still achieves 70 per cent accuracy on resolved sources. It flags 68 per cent more sources than required as needing visual inspection, but this is still fewer than the manually developed decision tree used in LoTSS, while also having a lower rate of wrongly accepted sources for statistical analysis. The results have an immediate practical application for cross-matching the next LoTSS data releases and can be generalized to other radio surveys.
The Plumbing of Land Surface Models Haughton, Ned; Abramowitz, Gab; Pitman, Andy J. ...
Journal of hydrometeorology,
06/2016, Letnik:
17, Številka:
6
Journal Article
Recenzirano
Odprti dostop
The Protocol for the Analysis of Land Surface Models (PALS) Land Surface Model Benchmarking Evaluation Project (PLUMBER) illustrated the value of prescribing a priori performance targets in model ...intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation. For latent heat flux, all land surface models were outperformed by a regression against downward shortwave radiation, surface air temperature, and relative humidity. These results are explored here in greater detail and possible causes are investigated. It is examined whether particular metrics or sites unduly influence the collated results, whether results change according to time-scale aggregation, and whether a lack of energy conservation in flux tower data gives the empirical models an unfair advantage in the intercomparison. It is demonstrated that energy conservation in the observational data is not responsible for these results. It is also shown that the partitioning between sensible and latent heat fluxes in LSMs, rather than the calculation of available energy, is the cause of the original findings. Finally, evidence is presented that suggests that the nature of this partitioning problem is likely shared among all contributing LSMs. While a single candidate explanation for why land surface models perform poorly relative to empirical benchmarks in PLUMBER could not be found, multiple possible explanations are excluded and guidance is provided on where future research should focus.
The interactions between the land surface and the atmosphere can impact weather and climate through the exchanges of water, energy, carbon and momentum. The properties of the land surface are ...important when modelling these exchanges correctly especially with models being used at increasingly higher resolution. The Joint UK Land Environment Simulator (JULES) currently uses a tiled representation of land cover but can only model a single dominant soil type within a grid box. Hence, there is no representation of sub-grid-scale soil heterogeneity. This paper introduces and evaluates a new flexible surface–soil tiling scheme in JULES. Several different soil tiling approaches are presented for a synthetic case study. The changes to model performance have been compared to the current single-soil scheme and a high-resolution “Truth” scenario. Results have shown that the different soil tiling strategies do have an impact on the water and energy exchanges due to the way vegetation accesses the soil moisture. Tiling the soil according to the surface type, with the soil properties set to the dominant soil type under each surface is the best performing configuration. The results from this setup simulate water and energy fluxes that are the closest to the high-resolution Truth scenario but require much less information on the soil type than the high-resolution soil configuration.
ABSTRACT Spectral energy distribution (SED) fitting has been extensively used to determine the nature of the faint radio source population. Recent efforts have combined fits from multiple SED-fitting ...codes to account for the host galaxy and any active nucleus that may be present. We show that it is possible to produce similar-quality classifications using a single energy-balance SED fitting code, prospector, to model up to 26 bands of UV–far-infrared aperture-matched photometry for ∼31 000 sources in the ELAIS-N1 field from the LOFAR Two-Metre Sky Survey (LoTSS) deep fields first data release. One of a new generation of SED-fitting codes, prospector accounts for potential contributions from radiative active galactic nuclei (AGN) when estimating galaxy properties, including star formation rates (SFRs) derived using non-parametric star formation histories. Combining this information with radio luminosities, we classify 92 per cent of the radio sources as a star-forming galaxy, high-/low-excitation radio galaxy, or radio-quiet AGN and study the population demographics as a function of 150 MHz flux density, luminosity, SFR, stellar mass, redshift, and apparent r-band magnitude. Finally, we use prospector SED fits to investigate the SFR–150 MHz luminosity relation for a sample of ∼133 000 3.6 μm-selected z < 1 sources, finding that the stellar mass dependence is significantly weaker than previously reported, and may disappear altogether at $\log _{10} (\mathrm{SFR}/M_\odot \, \mathrm{yr}^{-1}) \gt 0.5$. This approach makes it significantly easier to classify radio sources from LoTSS and elsewhere, and may have important implications for future studies of star-forming galaxies at radio wavelengths.
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