Remotely sensed land surface temperature (LST) data, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) LST thermal infrared products, are useful for monitoring surface processes on ...the Greenland Ice Sheet in remote areas but must be validated to ensure accuracy. Using data from the Programme for Monitoring the Greenland Ice Sheet (PROMICE), we conducted a MODIS LST validation (MOD/MYD11 C6 swath level product) using radiometric in-situ skin temperature records from 2014 to 2017 over 17 PROMICE sites mostly in the ice sheet's ablation zone. There is a significant cold bias in MODIS LST when compared to PROMICE skin temperature, particularly when PROMICE records temperatures below 0°C (mean bias: 2.4 ± 0.01°C mean ± standard error, RMSE = 3.2°C). Multiple linear regression analysis reveals the difference between MODIS LST and PROMICE skin temperature is larger at lower temperatures, lower latent heat fluxes and higher specific humidity. Our results confirm the presence of a progressive cold bias in the MODIS LST that should be considered in use of this product, and we identify and corroborate areas for ongoing algorithm development.
As rapid warming of the Arctic occurs, it is imperative that climate
indicators such as temperature be monitored over large areas to understand
and predict the effects of climate changes. ...Temperatures are traditionally
tracked using in situ 2 m air temperatures and can also be assessed using
remote sensing techniques. Remote sensing is especially valuable over the
Greenland Ice Sheet, where few ground-based air temperature measurements
exist. Because of the presence of surface-based temperature inversions in
ice-covered areas, differences between 2 m air temperature and the
temperature of the actual snow surface (referred to as “skin” temperature)
can be significant and are particularly relevant when considering validation
and application of remote sensing temperature data. We present results from
a field campaign extending from 8 June to 18 July 2015, near Summit
Station in Greenland, to study surface temperature using the following
measurements: skin temperature measured by an infrared (IR) sensor, 2 m air
temperature measured by a National Oceanic and Atmospheric Administration
(NOAA) meteorological station, and a Moderate Resolution Imaging Spectroradiometer (MODIS) surface temperature product. Our data indicate
that 2 m air temperature is often significantly higher than snow skin
temperature measured in situ, and this finding may account for apparent
biases in previous studies of MODIS products that used 2 m air temperature
for validation. This inversion is present during our study period when
incoming solar radiation and wind speed are both low. As compared to our in
situ IR skin temperature measurements, after additional cloud masking, the
MOD/MYD11 Collection 6 surface temperature standard product has an RMSE of
1.0 ∘C and a mean bias of −0.4 ∘C, spanning a range of
temperatures from −35 to −5 ∘C (RMSE =
1.6 ∘C and mean bias = −0.7 ∘C prior to cloud
masking). For our study area and time series, MODIS surface temperature
products agree with skin surface temperatures better than previous studies
indicated, especially at temperatures below −20 ∘C, where other
studies found a significant cold bias. We show that the apparent cold
bias present in other comparisons of 2 m air temperature and MODIS surface
temperature may be a result of the near-surface temperature inversion.
Further investigation of how in situ IR skin temperatures compare to MODIS
surface temperature at lower temperatures (below −35 ∘C) is
warranted to determine whether a cold bias exists for those temperatures.
The physical structure of polar firn plays a key role in the mechanisms by which glaciers and ice sheets preserve a natural archive of past atmospheric composition. This study presents the first ...measurements of gas diffusivity and permeability along with microstructural information measured from the near-surface firn through the firn column to pore close-off. Both fine- and coarse-grained firn from Summit, Greenland are included in this study to investigate the variability in firn caused by seasonal and storm-event layering. Our measurements reveal that the porosity of firn (derived from density) is insufficient to describe the full profiles of diffusivity and permeability, particularly at porosity values above 0.5. Thus, even a model that could perfectly predict the density profile would be insufficient for application to issues involving gas transport. The measured diffusivity profile presented here is compared to two diffusivity profiles modeled from firn air measurements from Summit. Because of differences in scale and in firn processes between the true field situation, firn modeling, and laboratory measurements, the results follow a similar overall pattern but do not align; our results constitute a lower bound on diffusive transport. In comparing our measurements of both diffusivity and permeability to previous parameterizations from numerical 3-D lattice-Boltzmann modeling, it is evident that the previous relationships to porosity are likely site-specific. We present parameterizations relating diffusivity and permeability to porosity as a possible tool, though use of direct measurements would be far more accurate when feasible. The relationships between gas transport properties and microstructural properties are characterized and compared to existing relationships for general porous media, specifically the Katz-Thompson (KT), Kozeny-Carman (KC), and Archie's law approximations. While those approximations can capture the general trend of gas transport relationships, they result in high errors for individual samples and fail to fully describe firn variability, particularly the differences between coarse- and fine-grained firn. We present a direct power law relationship between permeability and gas diffusivity based on our co-located measurements; further research will indicate if this type of relationship is site-specific. This set of measurements and relationships contributes a unique starting point for future investigations in developing more physically based models of firn gas transport.
1. Correlations between phenotypic traits are important in a number of contexts in physiological ecology, evolutionary physiology, and behaviour. Correlations can reflect functional connections or ...trade-offs among performance traits (e.g. bite force, jumping distance) and can reveal causal relationships between whole-organism traits and lower-level biochemical or morphological traits. 2. However, when one or both traits exhibit intraindividual variability (i.e. repeatability < 1), conventional estimates of Pearson product-moment correlation coefficients are biased towards zero (= attenuated). The magnitude of this bias decreases with increases in the number of measurements used to calculate the mean value of the trait for each individual. The bias varies inversely with the repeatability of each trait. 3. We present an estimator for the correlation coefficient that eliminates this bias. This estimator is based on an equation originally presented in 1904 by Spearman, and applied by researchers in psychological testing and nutritional epidemiology. The estimator is a simple function of the within- and among-individual components of variance for each of the two traits. 4. Simulations show that optimal sampling effort usually involves a small number of trials per individual and a large sample of individuals (for a fixed total sample size), although correlations between traits with low repeatabilities may be more precisely estimated with a larger number of trials per individual and a smaller number of individuals. 5. In addition to reducing the accuracy of the estimate, attenuation also reduces statistical power for detecting significant correlations. However, we do not recommend using the unbiased estimator for testing whether correlations differ from zero, because this inflates Type I error rates. Instead, the uncorrected (conventional) estimator should be used for hypothesis testing. 6. The unbiased estimator is not appropriate for correlations involving maximum or minimum values for each individual (e.g. maximum sprint speed) because sampling distributions of these extreme values typically have different properties than the sampling distributions of individual mean values.
The COMPASS collaboration has collected the currently largest data set on diffractively produced π−π−π+ final states using a negative pion beam of 190 GeV/c momentum impinging on a stationary proton ...target. This data set allows for a systematic partial-wave analysis in 100 bins of three-pion mass, 0.5<m3π<2.5 GeV/c2, and in 11 bins of the reduced four-momentum transfer squared, 0.1<t′<1.0 (GeV/c)2. This two-dimensional analysis offers sensitivity to genuine one-step resonance production, i.e. the production of a state followed by its decay, as well as to more complex dynamical effects in nonresonant 3π production. In this paper, we present detailed studies on selected 3π partial waves with JPC=0−+, 1++, 2−+, 2++, and 4++. In these waves, we observe the well-known ground-state mesons as well as a new narrow axial-vector meson a1(1420) decaying into f0(980)π. In addition, we present the results of a novel method to extract the amplitude of the π−π+ subsystem with IGJPC=0+0++ in various partial waves from the π−π−π+ data. Evidence is found for correlation of the f0(980) and f0(1500) appearing as intermediate π−π+ isobars in the decay of the known π(1800) and π2(1880).
Lizard life-history characteristics vary widely among species and populations. Most authors seek adaptive or phylogenetic explanations for life-history patterns, which are usually presumed to reflect ...genetic differences. However, lizard life histories are often phenotypically plastic, varying in response to temperature, food availability, and other environmental factors. Despite the importance of temperature to lizard ecology and physiology, its effects on life histories have received relatively little attention. We present a theoretical model predicting the proximate consequences of the thermal environment for lizard life histories. Temperature, by affecting activity times, can cause variation in annual survival rate and fecundity, leading to a negative correlation between survival rate and fecundity among populations in different thermal environments. Thus, physiological and evolutionary models predict the same qualitative pattern of life-history variation in lizards. We tested our model with published life-history data from field studies of the lizard Sceloporus undulatus, using climate and geographical data to reconstruct estimated annual activity seasons. Among populations, annual activity times were negatively correlated with annual survival rate and positively correlated with annual fecundity. Proximate effects of temperature may confound comparative analyses of lizard life-history variation and should be included in future evolutionary models.
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