Topographic and thermal mapping of volcanic terrain using AVTIS ground-based 94-GHz dual-mode radar/radiometric imager

The All-Weather Volcano Topography Imaging Sensor remote sensing instrument is a custom-built millimeter-wave (MMW) sensor that has been developed as a practical field tool for remote sensing of volcanic terrain at active lava domes. The portable instrument combines active and passive MMW measurements to record topographic and thermal data in almost all weather conditions from ground-based survey points. We describe how the instrument is deployed in the field, the quality of the primary ranging and radiometric measurements, and the postprocessing techniques used to derive the geophysical products of the target terrain, surface temperature, and reflectivity. By comparison of changing topography, we estimate the volume change and the lava extrusion rate. Validation of the MMW radiometry is also presented by quantitative comparison with coincident infrared thermal imagery.

Simulation of thermal performance of horizontal slinky-loop heat exchangers for ground source heat pumps

This paper presents results obtained from a numerical simulation for the horizontal slinky-loop heat exchanger of a ground-source heat pump system. A three-dimensional numerical model was developed and the results of the thermal performance of various heat exchanger configurations are presented. The investigation was carried out on five types of loop pitch (loop spacing), three types of loop diameter, three values of soil thermal properties, and allowing continuous and intermittent operation. Comparison was made for the heat transfer rate, the amount of pipe material needed, as well as excavation work required for the horizontal slinky-loop heat exchanger. The results indicate that system parameters have a significant effect on the thermal performance of the system

An effective approach for land-cover classification from airborne lidar fused with co-registered data

Airborne lidar provides accurate height information of objects on the earth and has been recognized as a reliable and accurate surveying tool in many applications. In particular, lidar data offer vital and significant features for urban land-cover classification, which is an important task in urban land-use studies. In this article, we present an effective approach in which lidar data fused with its co-registered images (i.e. aerial colour images containing red, green and blue (RGB) bands and near-infrared (NIR) images) and other derived features are used effectively for accurate urban land-cover classification. The proposed approach begins with an initial classification performed by the Dempster–Shafer theory of evidence with a specifically designed basic probability assignment function. It outputs two results, i.e. the initial classification and pseudo-training samples, which are selected automatically according to the combined probability masses. Second, a support vector machine (SVM)-based probability estimator is adopted to compute the class conditional probability (CCP) for each pixel from the pseudo-training samples. Finally, a Markov random field (MRF) model is established to combine spatial contextual information into the classification. In this stage, the initial classification result and the CCP are exploited. An efficient belief propagation (EBP) algorithm is developed to search for the global minimum-energy solution for the maximum a posteriori (MAP)-MRF framework in which three techniques are developed to speed up the standard belief propagation (BP) algorithm. Lidar and its co-registered data acquired by Toposys Falcon II are used in performance tests. The experimental results prove that fusing the height data and optical images is particularly suited for urban land-cover classification. There is no training sample needed in the proposed approach, and the computational cost is relatively low. An average classification accuracy of 93.63% is achieved.

A high-resolution near-infrared extraterrestrial solar spectrum derived from ground-based Fourier transform spectrometer measurements

A detailed spectrally-resolved extraterrestrial solar spectrum (ESS) is important for line-by-line radiative transfer modeling in the near-infrared (near-IR). Very few observationally-based high-resolution ESS are available in this spectral region. Consequently the theoretically-calculated ESS by Kurucz has been widely adopted. We present the CAVIAR (Continuum Absorption at Visible and Infrared Wavelengths and its Atmospheric Relevance) ESS which is derived using the Langley technique applied to calibrated observations using a ground-based high-resolution Fourier transform spectrometer (FTS) in atmospheric windows from 2000–10000 cm-1 (1–5 μm). There is good agreement between the strengths and positions of solar lines between the CAVIAR and the satellite-based ACE-FTS (Atmospheric Chemistry Experiment-FTS) ESS, in the spectral region where they overlap, and good agreement with other ground-based FTS measurements in two near-IR windows. However there are significant differences in the structure between the CAVIAR ESS and spectra from semi-empirical models. In addition, we found a difference of up to 8 % in the absolute (and hence the wavelength-integrated) irradiance between the CAVIAR ESS and that of Thuillier et al., which was based on measurements from the Atmospheric Laboratory for Applications and Science satellite and other sources. In many spectral regions, this difference is significant, as the coverage factor k = 2 (or 95 % confidence limit) uncertainties in the two sets of observations do not overlap. Since the total solar irradiance is relatively well constrained, if the CAVIAR ESS is correct, then this would indicate an integrated “loss” of solar irradiance of about 30 W m-2 in the near-IR that would have to be compensated by an increase at other wavelengths.

Contrasting the responses of three different ground-based instruments to energetic electron precipitation

In order to make best use of the opportunities provided by space missions such as the Radiation Belt Storm Probes, we determine the response of complementary subionospheric radiowave propagation measurements (VLF), riometer absorption measurements (CNA), and GPS-produced total electron content (vTEC) to different energetic electron precipitation (EEP). We model the relative sensitivity and responses of these instruments to idealised monoenergetic beams of precipitating electrons, and more realistic EEP spectra chosen to represent radiation belts and substorm precipitation. In the monoenergetic beam case, we find riometers are more sensitive to the same EEP event occurring during the day than during the night, while subionospheric VLF shows the opposite relationship, and the change in vTEC is independent. In general, the subionospheric VLF measurements are much more sensitive than the other two techniques for EEP over 200 keV, responding to flux magnitudes two-three orders of magnitude smaller than detectable by a riometer. Detectable TEC changes only occur for extreme monoenergetic fluxes. For the radiation belt EEP case, clearly detectable subionospheric VLF responses are produced by daytime fluxes that are ~10 times lower than required for riometers, while nighttime fluxes can be 10,000 times lower. Riometers are likely to respond only to radiation belt fluxes during the largest EEP events and vTEC is unlikely to be significantly disturbed by radiation belt EEP. For the substorm EEP case both the riometer absorption and the subionospheric VLF technique respond significantly, as does the change in vTEC, which is likely to be detectable at ~3-4 TECu.

Comprehensive ground-based and in situ observations of substorm expansion phase onset

In this paper, we present comprehensive ground-based and space-based in situ geosynchronous observations of a substorm expansion phase onset on 1 October 2005. The Double Star TC-2 and GOES-12 spacecraft were both located within the substorm current wedge during the substorm expansion phase onset, which occurred over the Canadian sector. We find that an onset of ULF waves in space was observed after onset on the ground by extending the AWESOME timing algorithm into space. Furthermore, a population of low-energy field-aligned electrons was detected by the TC-2 PEACE instrument contemporaneous with the ULF waves in space. These electrons appear to be associated with an enhancement of field-aligned Poynting flux into the ionosphere which is large enough to power visible auroral displays. The observations are most consistent with a near-Earth initiation of substorm expansion phase onset, such as the Near-Geosynchronous Onset (NGO) substorm scenario. A lack of data from further downtail, however, means other mechanisms cannot be ruled out.

Spatial and radiometric fidelity of airborne multispectral imagery in the context of land-cover change analyses

The goal was to quantitatively estimate and compare the fidelity of images acquired with a digital imaging system (ADAR 5500) and generated through scanning of color infrared aerial photographs (SCIRAP) using image-based metrics. Images were collected nearly simultaneously in two repetitive flights to generate multi-temporal datasets. Spatial fidelity of ADAR was lower than that of SCIRAP images. Radiometric noise was higher for SCIRAP than for ADAR images, even though noise from misregistration effects was lower. These results suggest that with careful control of film scanning, the overall fidelity of SCIRAP imagery can be comparable to that of digital multispectral camera data. Therefore, SCIRAP images can likely be used in conjunction with digital metric camera imagery in long-term landcover change analyses.

Cloud optical and microphysical properties derived from ground-based and satellite sensors over a site in the Yangtze Delta region

Comprehensive surface-based retrievals of cloud optical and microphysical properties were made at Taihu, a highly polluted site in the central Yangtze Delta region, during a research campaign from May 2008 to December 2009. Cloud optical depth (COD), effective radius (Re), and liquid water path (LWP) were retrieved from measurements made with a suite of ground-based and spaceborne instruments, including an Analytical Spectral Devices spectroradiometer, a multi␣lter rotating shadowband radiometer, a multichannel microwave radiometer profiler, and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua satellites. Retrievals from zenith radiance measurements capture better the temporal variation of cloud properties than do retrievals from hemispherical fluxes. Annual mean LWP, COD, and Re are 115.8 ± 90.8 g/m2, 28.5 ± 19.2, and 6.9 ± 4.2 microns. Over 90% of LWP values are less than 250 g/m2. Most of the COD values (>90%) fall between 5 and 60, and ~80% of Re values are less than 10 microns. Maximum (minimum) values of LWP and Re occur in summer (winter); COD is highest in winter and spring. Raining and nonraining clouds have signi␣cant differences in LWP, COD, and Re. Rainfall frequency is best correlated with LWP, followed by COD and Re. Cloud properties retrieved from multiple ground-based instruments are also compared with those from satellite retrievals. On average, relative to surface retrievals, mean differences of satellite retrievals in cloud LWP, COD, and Re were -33.6 g/m2 (-26.4%), -5.8 (-31.4%), and 2.9 ␣m (29.3%) for 11 MODIS-Terra overpasses and -43.3 g/m2 (-22.3%), -3.0 (-10.0%), and -1.3 ␣m (-12.0%) for 8 MODIS-Aqua overpasses, respectively. These discrepancies indicate that MODIS cloud products still suffer from large uncertainties in this region.

Quantifying uncertainty in remotely sensed land cover maps

Remotely sensed land cover maps are increasingly used as inputs into environmental simulation models whose outputs inform decisions and policy-making. Risks associated with these decisions are dependent on model output uncertainty, which is in turn affected by the uncertainty of land cover inputs. This article presents a method of quantifying the uncertainty that results from potential mis-classification in remotely sensed land cover maps. In addition to quantifying uncertainty in the classification of individual pixels in the map, we also address the important case where land cover maps have been upscaled to a coarser grid to suit the users’ needs and are reported as proportions of land cover type. The approach is Bayesian and incorporates several layers of modelling but is straightforward to implement. First, we incorporate data in the confusion matrix derived from an independent field survey, and discuss the appropriate way to model such data. Second, we account for spatial correlation in the true land cover map, using the remotely sensed map as a prior. Third, spatial correlation in the mis-classification characteristics is induced by modelling their variance. The result is that we are able to simulate posterior means and variances for individual sites and the entire map using a simple Monte Carlo algorithm. The method is applied to the Land Cover Map 2000 for the region of England and Wales, a map used as an input into a current dynamic carbon flux model.

Twenty-first-century climate impacts from a declining Arctic sea ice cover

A steady decline in Arctic sea ice has been observed over recent decades. General circulation models predict further decreases under increasing greenhouse gas scenarios. Sea ice plays an important role in the climate system in that it influences ocean-to-atmosphere fluxes, surface albedo, and ocean buoyancy. The aim of this study is to isolate the climate impacts of a declining Arctic sea ice cover during the current century. The Hadley Centre Atmospheric Model (HadAM3) is forced with observed sea ice from 1980 to 2000 (obtained from satellite passive microwave radiometer data derived with the Bootstrap algorithm) and predicted sea ice reductions until 2100 under one moderate scenario and one severe scenario of ice decline, with a climatological SST field and increasing SSTs. Significant warming of the Arctic occurs during the twenty-first century (mean increase of between 1.6° and 3.9°C), with positive anomalies of up to 22°C locally. The majority of this is over ocean and limited to high latitudes, in contrast to recent observations of Northern Hemisphere warming. When a climatological SST field is used, statistically significant impacts on climate are only seen in winter, despite prescribing sea ice reductions in all months. When correspondingly increasing SSTs are incorporated, changes in climate are seen in both winter and summer, although the impacts in summer are much smaller. Alterations in atmospheric circulation and precipitation patterns are more widespread than temperature, extending down to midlatitude storm tracks. Results suggest that areas of Arctic land ice may even undergo net accumulation due to increased precipitation that results from loss of sea ice. Intensification of storm tracks implies that parts of Europe may experience higher precipitation rates.

Measurements of stratospheric ozone at a mid-latitude observing station Valentia, Ireland (51.94° N, 10.25° W), using ground-based and ozonesonde observations from 1994 to 2009

Sixteen years (1994 – 2009) of ozone profiling by ozonesondes at Valentia Meteorological and Geophysical Observatory, Ireland (51.94° N, 10.23° W) along with a co-located MkIV Brewer spectrophotometer for the period 1993–2009 are analyzed. Simple and multiple linear regression methods are used to infer the recent trend, if any, in stratospheric column ozone over the station. The decadal trend from 1994 to 2010 is also calculated from the monthly mean data of Brewer and column ozone data derived from satellite observations. Both of these show a 1.5 % increase per decade during this period with an uncertainty of about ±0.25 %. Monthly mean data for March show a much stronger trend of ~ 4.8 % increase per decade for both ozonesonde and Brewer data. The ozone profile is divided between three vertical slots of 0–15 km, 15–26 km, and 26 km to the top of the atmosphere and a 11-year running average is calculated. Ozone values for the month of March only are observed to increase at each level with a maximum change of +9.2 ± 3.2 % per decade (between years 1994 and 2009) being observed in the vertical region from 15 to 26 km. In the tropospheric region from 0 to 15 km, the trend is positive but with a poor statistical significance. However, for the top level of above 26 km the trend is significantly positive at about 4 % per decade. The March integrated ozonesonde column ozone during this period is found to increase at a rate of ~6.6 % per decade compared with the Brewer and satellite positive trends of ~5 % per decade.

RuII(α-diimine) or RuIII(α-diimine·–)? Structural, spectroscopic, and theoretical evidence for the stabilization of a prominent metal-to-Ligand charge- transfer excited-state configuration in the ground state

The new compounds [Ru(R-DAB)(acac)2] (R-DAB = 1,4-diorganyl- 1,4-diazabuta-1,3-diene; R = tert-butyl, 4-methoxyphenyl, 2,6-dimethylphenyl; acac– = 2,4-pentanedionate) exhibit intrachelate ring bond lengths 1.297

The role of soil microbes in the global carbon cycle: tracking the below-ground microbial processing of plant-derived carbon for manipulating carbon dynamics in agricultural systems.

It is well known that atmospheric concentrations of carbon dioxide (CO2) (and other greenhouse gases) have increased markedly as a result of human activity since the industrial revolution. It is perhaps less appreciated that natural and managed soils are an important source and sink for atmospheric CO2 and that, primarily as a result of the activities of soil microorganisms, there is a soil-derived respiratory flux of CO2 to the atmosphere that overshadows by tenfold the annual CO2 flux from fossil fuel emissions. Therefore small changes in the soil carbon cycle could have large impacts on atmospheric CO2 concentrations. Here we discuss the role of soil microbes in the global carbon cycle and review the main methods that have been used to identify the microorganisms responsible for the processing of plant photosynthetic carbon inputs to soil. We discuss whether application of these techniques can provide the information required to underpin the management of agro-ecosystems for carbon sequestration and increased agricultural sustainability. We conclude that, although crucial in enabling the identification of plant-derived carbon-utilising microbes, current technologies lack the high-throughput ability to quantitatively apportion carbon use by phylogentic groups and its use efficiency and destination within the microbial metabolome. It is this information that is required to inform rational manipulation of the plant–soil system to favour organisms or physiologies most important for promoting soil carbon storage in agricultural soil.

Supplementary feeding of wild birds indirectly affects ground beetle populations in suburban gardens

Supplementary feeding of wild birds by domestic garden-holders is a globally widespread and popular form of human–wildlife interaction, particularly in urban areas. Vast amounts of energy are thus being added to garden ecosystems. However, the potential indirect effects of this activity on non-avian species have been little studied to date, with the only two previous studies taking place under experimentally manipulated conditions. Here we present the first evidence of a localised depletive effect of wild bird feeding on ground beetles (Coleoptera: Carabidae) in suburban gardens under the usual feeding patterns of the garden-holders. We trapped significantly fewer ground beetles directly under bird-feeding stations than in matched areas of habitat away from feeders. Video analysis also revealed significantly higher activity by ground-foraging birds under the feeding stations than in the control areas. Small mammal trapping revealed no evidence that these species differ in abundance between gardens with and without bird feeders. We therefore suggest that local increases in ground-foraging activity by bird species whose diets encompass arthropods as well as seed material are responsible for the reduction in ground beetle numbers. Our work therefore illustrates that providing food for wild birds can have indirect negative effects on palatable prey species under typical conditions.