25 research outputs found
Characterization of precipitation product errors across the United States using multiplicative triple collocation
Validation of precipitation estimates from various products is a challenging problem, since the true precipitation is unknown. However, with the increased availability of precipitation estimates from a wide range of instruments (satellite, ground-based radar, and gauge), it is now possible to apply the triple collocation (TC) technique to characterize the uncertainties in each of the products. Classical TC takes advantage of three collocated data products of the same variable and estimates the mean squared error of each, without requiring knowledge of the truth. In this study, triplets among NEXRAD-IV, TRMM 3B42RT, GPCP 1DD, and GPI products are used to quantify the associated spatial error characteristics across a central part of the continental US. Data are aggregated to biweekly accumulations from January 2002 through April 2014 across a 2° à 2° spatial grid. This is the first study of its kind to explore precipitation estimation errors using TC across the US. A multiplicative (logarithmic) error model is incorporated in the original TC formulation to relate the precipitation estimates to the unknown truth. For precipitation application, this is more realistic than the additive error model used in the original TC derivations, which is generally appropriate for existing applications such as in the case of wind vector components and soil moisture comparisons. This study provides error estimates of the precipitation products that can be incorporated into hydrological and meteorological models, especially those used in data assimilation. Physical interpretations of the error fields (related to topography, climate, etc.) are explored. The methodology presented in this study could be used to quantify the uncertainties associated with precipitation estimates from each of the constellations of GPM satellites. Such quantification is prerequisite to optimally merging these estimates
Analysis of the platypus genome suggests a transposon origin for mammalian imprinting
Comparisons between the platypus and eutherian mammalian genomes provides new insights into how epigenetic imprinting may have evolved in mammalian genomes
Relationship between vegetation microwave optical depth and cross-polarized backscatter from multiyear Aquarius observations
Soil moisture retrieval algorithms based on passive microwave remote sensing observations need to account for vegetation attenuation and emission, which is generally parameterized as vegetation optical depth (VOD). This multisensor study tests a new method to retrieve VOD from cross-polarized radar backscattering coefficients. Three years of Aquarius/SAC-D data were used to establish a relationship between the cross-polarized backscattering coefficient ĎHV and VOD derived from a multitemporal passive dual-channel algorithm (VODMT). The dependence of the correspondence is analyzed for different land use classes. There are no systematic differences in the slope for woody versus nonwoody vegetation, resulting in a strong correlation (80% explained-variance) and a global linear relationship when all classes are combined. The relationship is stable over the years of observations. The comparison of the Aquarius-derived VODMT to Soil Moisture and Ocean Salinity's multi-angular VOD estimates shows similar spatial patterns and temporal behavior, evident in high correlations. However, VODMT has considerably higher mean values, but lower dynamic range globally. Most of the differences can be attributed to differences in instrument sampling. The main result of this study, a relationship between backscatter and VOD, will permit high-resolution mapping of VOD with synthetic aperture radar measurements. These maps allow future studies of scaling and heterogeneity effects of vegetation on soil moisture retrieval at the coarser scales of land microwave radiometry. The study shows that VOD based on passive measurements and predicted by active measurements are comparable globally and that the breakdown by land cover classification does not affect the relationship appreciably
Genome sequence of an Australian kangaroo, Macropus eugenii, provides insight into the evolution of mammalian reproduction and development.
BACKGROUND: We present the genome sequence of the tammar wallaby, Macropus eugenii, which is a member of the kangaroo family and the first representative of the iconic hopping mammals that symbolize Australia to be sequenced. The tammar has many unusual biological characteristics, including the longest period of embryonic diapause of any mammal, extremely synchronized seasonal breeding and prolonged and sophisticated lactation within a well-defined pouch. Like other marsupials, it gives birth to highly altricial young, and has a small number of very large chromosomes, making it a valuable model for genomics, reproduction and development. RESULTS: The genome has been sequenced to 2 Ă coverage using Sanger sequencing, enhanced with additional next generation sequencing and the integration of extensive physical and linkage maps to build the genome assembly. We also sequenced the tammar transcriptome across many tissues and developmental time points. Our analyses of these data shed light on mammalian reproduction, development and genome evolution: there is innovation in reproductive and lactational genes, rapid evolution of germ cell genes, and incomplete, locus-specific X inactivation. We also observe novel retrotransposons and a highly rearranged major histocompatibility complex, with many class I genes located outside the complex. Novel microRNAs in the tammar HOX clusters uncover new potential mammalian HOX regulatory elements. CONCLUSIONS: Analyses of these resources enhance our understanding of marsupial gene evolution, identify marsupial-specific conserved non-coding elements and critical genes across a range of biological systems, including reproduction, development and immunity, and provide new insight into marsupial and mammalian biology and genome evolution
Short-Term and Long-Term Surface Soil Moisture Memory Time Scales Are Spatially Anticorrelated at Global Scales
Land-atmosphere feedbacks occurring on daily to weekly time scales can magnify the intensity and duration of extreme weather events, such as droughts, heat waves, and convective storms. For such feedbacks to occur, the coupled land-atmosphere system must exhibit sufficient memory of soil moisture anomalies associated with the extreme event. The soil moisture autocorrelation e-folding time scale has been used previously to estimate soil moisture memory. However, the theoretical basis for this metric (i.e., that the land water budget is reasonably approximated by a red noise process) does not apply at finer spatial and temporal resolutions relevant tomodern satellite observations and models. In this study, two memory time scale metrics are introduced that are relevant to modern satellite observations andmodels: the ''long-termmemory'' ĎL and the ''short-term memory'' ĎS. Short- and long-term surface soil moisture (SSM) memory time scales are spatially anticorrelated at global scales in both a model and satellite observations, suggesting hot spots of land-atmosphere couplingwill be located in different regions, depending on the time scale of the feedback. Furthermore, the spatial anticorrelation between ĎS and ĎL demonstrates the importance of characterizing these memory time scales separately, rather than mixing them as in previous studies. Keywords: Atmosphere-land interaction; Biosphere-atmosphere interaction; Hydrologic cycle; Hydrology; Hydrometeorology; Soil moistureNational Basic Research Program of China (2015CB953703)National Key Research and Development Program of China (2017YFA0603703)National Natural Science Foundation of China (91537210 and 91747101
Evaluation of microbial extracts for contamination control in plant tissue culture systems
SIGLEAvailable from British Library Document Supply Centre- DSC:DX97483 / BLDSC - British Library Document Supply CentreGBUnited Kingdo
Role of large eddies in the breakdown of the Reynolds analogy in an idealized mildly unstable atmospheric surface layer
While the breakdown in similarity between turbulent transport of heat and momentum (or Reynolds analogy) is not disputed in the atmospheric surface layer (ASL) under unstably stratified conditions, the causes of this breakdown are still debated. One reason for the breakdown is differences between how coherent structures transport heat and momentum, and their differing responses to increasing instability. Monin-Obukhov Similarity Theory (MOST), which hypothesizes that only local length-scales play a role in ASL turbulent transport, implicitly assumes that large-scale structures are inactive, despite their large energy content. Widely adopted mixing-length models also rest on this assumption in the ASL. The difficulty of characterizing low-wavenumber turbulent motions with field measurements motivates the use of high-resolution Direct Numerical Simulation (DNS), which is free from subgrid-scale parametrizations and adhoc assumptions near the boundary. Despite the low Reynolds number and idealized geometry of the DNS, DNS-estimated MOST functions are consistent with ASL field experiments, as are low-frequency features of the spectra. Parsimonious spectral models for MO stability correction functions for momentum (Ďm) and heat (Ďh) are derived, based on idealized vertical velocity variance and buoyancy variance spectra fit to the corresponding DNS spectra. For Ďm, a spectral model, based only on local length-scales, matches DNS and field measurements well. In contrast, for Ďh, the model is substantially biased unless contributions from larger length-scales are also included. These results are supported by sensitivity analyses based on field measurements that are independent of the DNS. They show that ASL heat transport is not MO-similar, even under mild stratification, and in the absence of entrainment, non-stationarity and canopy effects. It further suggests that the breakdown of the Reynolds analogy is at least partially caused by the influence of large eddies on turbulent heat transport
Role of large eddies in the breakdown of the Reynolds analogy in an idealized mildly unstable atmospheric surface layer
While the breakdown in similarity between turbulent transport of heat and momentum (or Reynolds analogy) is not disputed in the atmospheric surface layer (ASL) under unstably stratified conditions, the causes of this breakdown are still debated. One reason for the breakdown is differences between how coherent structures transport heat and momentum, and their differing responses to increasing instability. Monin-Obukhov Similarity Theory (MOST), which hypothesizes that only local length-scales play a role in ASL turbulent transport, implicitly assumes that large-scale structures are inactive, despite their large energy content. Widely adopted mixing-length models also rest on this assumption in the ASL. The difficulty of characterizing low-wavenumber turbulent motions with field measurements motivates the use of high-resolution Direct Numerical Simulation (DNS), which is free from subgrid-scale parametrizations and adhoc assumptions near the boundary. Despite the low Reynolds number and idealized geometry of the DNS, DNS-estimated MOST functions are consistent with ASL field experiments, as are low-frequency features of the spectra. Parsimonious spectral models for MO stability correction functions for momentum (Ďm) and heat (Ďh) are derived, based on idealized vertical velocity variance and buoyancy variance spectra fit to the corresponding DNS spectra. For Ďm, a spectral model, based only on local length-scales, matches DNS and field measurements well. In contrast, for Ďh, the model is substantially biased unless contributions from larger length-scales are also included. These results are supported by sensitivity analyses based on field measurements that are independent of the DNS. They show that ASL heat transport is not MO-similar, even under mild stratification, and in the absence of entrainment, non-stationarity and canopy effects. It further suggests that the breakdown of the Reynolds analogy is at least partially caused by the influence of large eddies on turbulent heat transport