Sierra Nevada snow melt from SMS-2

A film loop from SMS-2 imagery shows snow melt over the Sierra Nevadas from May 10 to July 8, 1975. The sequence indicates a successful application of geostationary satellite data for monitoring dynamic hydrologic conditions

Sea surface and remotely sensed temperatures off Cape Mendocino, California

During September 3 to 5, 1979, a multisensor oceanographic experiment was conducted off Cape Mendocino, California. The purpose of this experiment was to validate the use of remote sensing techniques over an area along the U.S. west coast where coasted upwelling is known to be intense. Remotely sensed mutlispectral data, including thermal infrared imagery, were collected above an upwelling feature off Cape Mendocino. Data were acquired from the TIRNOS-N and NOAA-6 polar orbiting satellites, the NASA Ames Research Center's high altitude U-2 aircraft, and a U.S. Coast Guard C-130 aircraft. Supporting surface truth data over the same feature were collected aboard the National Oceanic and Atmospheric Administration (NOAA) ship, OCEANOGRAPHER. Atmospheric soundings were also taken aboard the ship. The results indicate that shipboard measurements of sea surface temperatures can be reproduction within 1 C or better through remote observation of absolute infrared radiance values (whether measured aboard the NOAA polar orbiting satellite, the U-2 aircraft, or the Coast Guard aircraft) by using appropriate atmospheric corrections. Also, the patterns of sea surface temperature which were derived independently from the various remote platforms provide a consistent interpretation of the surface temperature field

Biological and physical oceanographic observations pertaining to the trawl fishery in a region of persistent coastal upwelling

An upwelling episode in the Point Sal region of the central California coast is examined by using data obtained by a data buoy. The episodes was interrupted by the abrupt abatement of the strong wind which promotes coastal upwelling. The mean hourly upwelling index is calculated to be higher than the 20 year mean monthly value. During 3 days of light wind commercial bottom trawl operations were possible. Shipboard estimates of chlorophyll content in surface waters during trawling show the high concentrations that are indicative of a rich biomass of phytoplankton, a result of the upwelling episode. Satellite imagery shows the extent of the upwelling water to be of the order of 100 km offshore; the result of many upwelling episodes. Shipboard echo sounder data show the presence of various delmersal species and of zooplakton; the latter graze on the phytoplankton in the upper euphotic layers. The fish catch data are recorded according to species for 2 days of trawling, and the catch per trawl hour is recorded

A Computational Pipeline for High- Throughput Discovery of cis-Regulatory Noncoding RNA in Prokaryotes

Noncoding RNAs (ncRNAs) are important functional RNAs that do not code for proteins. We present a highly efficient computational pipeline for discovering cis-regulatory ncRNA motifs de novo. The pipeline differs from previous methods in that it is structure-oriented, does not require a multiple-sequence alignment as input, and is capable of detecting RNA motifs with low sequence conservation. We also integrate RNA motif prediction with RNA homolog search, which improves the quality of the RNA motifs significantly. Here, we report the results of applying this pipeline to Firmicute bacteria. Our top-ranking motifs include most known Firmicute elements found in the RNA family database (Rfam). Comparing our motif models with Rfam's hand-curated motif models, we achieve high accuracy in both membership prediction and base-pair–level secondary structure prediction (at least 75% average sensitivity and specificity on both tasks). Of the ncRNA candidates not in Rfam, we find compelling evidence that some of them are functional, and analyze several potential ribosomal protein leaders in depth

Design principles for riboswitch function

Scientific and technological advances that enable the tuning of integrated regulatory components to match network and system requirements are critical to reliably control the function of biological systems. RNA provides a promising building block for the construction of tunable regulatory components based on its rich regulatory capacity and our current understanding of the sequence–function relationship. One prominent example of RNA-based regulatory components is riboswitches, genetic elements that mediate ligand control of gene expression through diverse regulatory mechanisms. While characterization of natural and synthetic riboswitches has revealed that riboswitch function can be modulated through sequence alteration, no quantitative frameworks exist to investigate or guide riboswitch tuning. Here, we combined mathematical modeling and experimental approaches to investigate the relationship between riboswitch function and performance. Model results demonstrated that the competition between reversible and irreversible rate constants dictates performance for different regulatory mechanisms. We also found that practical system restrictions, such as an upper limit on ligand concentration, can significantly alter the requirements for riboswitch performance, necessitating alternative tuning strategies. Previous experimental data for natural and synthetic riboswitches as well as experiments conducted in this work support model predictions. From our results, we developed a set of general design principles for synthetic riboswitches. Our results also provide a foundation from which to investigate how natural riboswitches are tuned to meet systems-level regulatory demands

Northern Monterey Bay upwelling shadow front : observations of a coastally and surface-trapped buoyant plume

Author Posting. © American Geophysical Union, 2009. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research 114 (2009): C12013, doi:10.1029/2009JC005623.During the upwelling season in central California, northwesterly winds along the coast produce a strong upwelling jet that originates at Point Año Nuevo and flows southward across the mouth of Monterey Bay. A convergent front with a mean temperature change of 3.77 ± 0.29°C develops between the warm interior waters and the cold offshore upwelling jet. To examine the forcing mechanisms driving the location and movement of the upwelling shadow front and its effects on biological communities in northern Monterey Bay, oceanographic conditions were monitored using cross-shelf mooring arrays, drifters, and hydrographic surveys along a 20 km stretch of coast extending northwestward from Santa Cruz, California, during the upwelling season of 2007 (May–September). The alongshore location of the upwelling shadow front at the northern edge of the bay was driven by: regional wind forcing, through an alongshore pressure gradient; buoyancy forces due to the temperature change across the front; and local wind forcing (the diurnal sea breeze). The upwelling shadow front behaved as a surface-trapped buoyant current, which is superimposed on a poleward barotropic current, moving up and down the coast up to several kilometers each day. We surmise that the front is advected poleward by a preexisting northward barotropic current of 0.10 m s−1 that arises due to an alongshore pressure gradient caused by focused upwelling at Point Año Nuevo. The frontal circulation (onshore surface currents) breaks the typical two-dimensional wind-driven, cross-shelf circulation (offshore surface currents) and introduces another way for water, and the material it contains (e.g., pollutants, larvae), to go across the shelf toward shore.Funded primarily by the Gordon and Betty Moore Foundation and the David and Lucile Packard Foundation

DNA-decorated carbon nanotubes for chemical sensing

We demonstrate a new, versatile class of nanoscale chemical sensors based on single-stranded DNA (ss-DNA) as the chemical sensors recognition site and single-walled carbon nanotube field effect transistors (swCN-FET) as the electronic read-out component. swCN-FETs with a nanoscale coating of ss-DNA respond to gas odors that do not cause a detectable conductivity change in bare devices. Responses of ss-DNA/swCN-FETs differ in sign and magnitude for different gases, and can be tuned by choosing the base sequence of the ss-DNA. ss-DNA/swCN-FET sensors detect a variety of odors, with rapid response and recovery times on the scale of seconds. The sensor surface is self-regenerating: samples maintain a constant response with no need for sensor refreshing through at least 50 gas exposure cycles. This very remarkable set of attributes makes sensors based on ss-DNA decorated nanotubes very promising for "electronic nose" and "electronic tongue" applications ranging from homeland security to disease diagnosis.Comment: 9 pages, 5 figures, Nano Letters web release: 23-Aug-200

A novel method to improve temperature simulations of general circulation models based on ensemble empirical mode decomposition and its application to multi-model ensembles

A novel method based on the ensemble empirical mode decomposition (EEMD) method was developed to improve model performance. This method was evaluated by applying it to global surface air temperatures, which were simulated by eight general circulation models from the Coupled Model Intercomparison Project Phase 5 (CMIP5). The temperature simulations of the eight models were separated into their different components by EEMD. The model's performance improved after the first high-frequency component was removed from the original simulations by EEMD for each model, on both the global and continental scale. Moreover, EEMD was more effective in improving the model's performance compared to the wavelet transform method. The multi-model ensembles (MMEs) were calculated based on the EEMD-improved model simulations using the Average Ensemble Mean, Multiple Linear Regression, Singular Value Decomposition and Bayesian Model Averaging methods. The results showed that the MME forecasts performed better when the calculations were based on the EEMD-improved simulations as opposed to the original simulations on both the global and continental scale. Therefore, the results of the MME were further improved by using the EEMD-improved model simulations. This new method provides a simple way to improve model performance and can be easily applied to further improve MME simulations