Search Results
. 1993a , b ) locally amount to ±15 W m −2 with the largest contribution from the corrections of air temperature and humidity ( Josey et al. 1999 ). However, the completeness of the corrections applied is still questionable because of the lack of a reference standard. Besides the above-mentioned uncertainties, VOS-based flux products suffer from poor and inhomogeneous sampling. ICOADS sampling varies regionally, ranging from zero to several thousand samples per 2° × 2° box per calendar month
. 1993a , b ) locally amount to ±15 W m −2 with the largest contribution from the corrections of air temperature and humidity ( Josey et al. 1999 ). However, the completeness of the corrections applied is still questionable because of the lack of a reference standard. Besides the above-mentioned uncertainties, VOS-based flux products suffer from poor and inhomogeneous sampling. ICOADS sampling varies regionally, ranging from zero to several thousand samples per 2° × 2° box per calendar month
A System for Retrieval and Incubation of Benthic Sediment Cores at In Situ Ambient Pressure and under Controlled or Manipulated Environmental Conditionsthat are operated by large crews from large vessels. In addition, samples in most cases suffer depressurization upon retrieval. As many piezophiles may only be culturable without depressurization ( Yanagibayashi et al. 1999 ), this may explain why less than 1% of deep-sea prokaryotes can currently be cultured ( Fuhrman et al. 1992 ; Rappe and Giovannoni 2003 ), and most of our knowledge of deep-sea microbial diversity comes from culture-independent studies. Here we describe the design
that are operated by large crews from large vessels. In addition, samples in most cases suffer depressurization upon retrieval. As many piezophiles may only be culturable without depressurization ( Yanagibayashi et al. 1999 ), this may explain why less than 1% of deep-sea prokaryotes can currently be cultured ( Fuhrman et al. 1992 ; Rappe and Giovannoni 2003 ), and most of our knowledge of deep-sea microbial diversity comes from culture-independent studies. Here we describe the design
et al. 2001 ; Ding and Seyfried 2007 ; Vuillemin et al. 2009 ; Tan et al. 2012 ); and 2) collection of fluid samples with suitable samplers and then completion of the analysis using the instruments on board ships or onshore (e.g., Edmond et al. 1992 ; Seewald et al. 2002 ; Wu et al. 2011 ). To date, the in situ chemical sensors and analyzers are mainly focused on the measurement of inorganic matter. The study of the organic chemistry of hydrothermal fluids largely relies on the sampling
et al. 2001 ; Ding and Seyfried 2007 ; Vuillemin et al. 2009 ; Tan et al. 2012 ); and 2) collection of fluid samples with suitable samplers and then completion of the analysis using the instruments on board ships or onshore (e.g., Edmond et al. 1992 ; Seewald et al. 2002 ; Wu et al. 2011 ). To date, the in situ chemical sensors and analyzers are mainly focused on the measurement of inorganic matter. The study of the organic chemistry of hydrothermal fluids largely relies on the sampling
A Periodically Updated Adaptive Sampling Framework for Marine Mobile Observation Platforms1. Introduction Autonomous underwater vehicles (AUVs) with high autonomy and long endurance are capable of performing observation and assurance tasks in different conditions ( Wang et al. 2011 ; Branch et al. 2019 ; Zhang et al. 2019 ). Combined with high-resolution forecasts, the efficiency of AUVs is further improved. The technique of designing an optimal observation scheme using prior information is called adaptive sampling or target observation ( Yilmaz et al. 2006 ; Zhou et
1. Introduction Autonomous underwater vehicles (AUVs) with high autonomy and long endurance are capable of performing observation and assurance tasks in different conditions ( Wang et al. 2011 ; Branch et al. 2019 ; Zhang et al. 2019 ). Combined with high-resolution forecasts, the efficiency of AUVs is further improved. The technique of designing an optimal observation scheme using prior information is called adaptive sampling or target observation ( Yilmaz et al. 2006 ; Zhou et
How Biased Is Aircraft Cloud Sampling?1. Introduction Much of the information that has been gathered about the in situ properties of clouds has been obtained using aircraft sampling. While aircraft provide a very high-resolution record of the internal structure of clouds, that information is limited to a relatively small volume with respect to the size of clouds and ensembles of clouds. Because aircraft sampling is expensive and time limited, sampling is usually directed by a scientist looking either out of the aircraft or at
1. Introduction Much of the information that has been gathered about the in situ properties of clouds has been obtained using aircraft sampling. While aircraft provide a very high-resolution record of the internal structure of clouds, that information is limited to a relatively small volume with respect to the size of clouds and ensembles of clouds. Because aircraft sampling is expensive and time limited, sampling is usually directed by a scientist looking either out of the aircraft or at
sustained synoptic observations, that is, to map ocean structures at adequate spatial resolution faster than significant changes occur. This requirement is not realized by many traditional platforms of oceanographic sampling because of their physical, economic, and/or operational limits. For this reason, ocean observations are transforming from platform-based capabilities to networks of sensor nodes ( Curtin et al. 1993 ; Curtin and Bellingham 2009 ). It is envisioned that future ocean observations
sustained synoptic observations, that is, to map ocean structures at adequate spatial resolution faster than significant changes occur. This requirement is not realized by many traditional platforms of oceanographic sampling because of their physical, economic, and/or operational limits. For this reason, ocean observations are transforming from platform-based capabilities to networks of sensor nodes ( Curtin et al. 1993 ; Curtin and Bellingham 2009 ). It is envisioned that future ocean observations
1. Introduction The National Weather Radar Testbed Phased Array Radar (NWRT PAR; hereafter PAR) is a research radar that collects data from a 9.4-cm-wavelength, single-faced, phased-array antenna that supports adaptable scanning strategies and volumetrically scans storms at time scales of seconds instead of several minutes ( Zrnić et al. 2007 ). Such high temporal resolution sampling provides an unprecedented opportunity to study rapidly evolving weather phenomena that are undersampled
1. Introduction The National Weather Radar Testbed Phased Array Radar (NWRT PAR; hereafter PAR) is a research radar that collects data from a 9.4-cm-wavelength, single-faced, phased-array antenna that supports adaptable scanning strategies and volumetrically scans storms at time scales of seconds instead of several minutes ( Zrnić et al. 2007 ). Such high temporal resolution sampling provides an unprecedented opportunity to study rapidly evolving weather phenomena that are undersampled
A Pressure-Tight Sampler with Flexible Titanium Bag for Deep-Sea Hydrothermal Fluid Sampleslaboratory has always been an effective means of studying the organic chemistry of hydrothermal fluids. In the past few decades, a variety of samplers have been designed and constructed to collect fluid samples from hydrothermal vents. These devices can be generally divided into two kinds: 1) syringe-type samplers, such as the “major” sampler ( Von Damm et al. 1985 ; Butterfield et al. 1990 ), the isobaric gas-tight sampler ( Seewald et al. 2002 ; Proskurowski et al. 2008 ; McDermott et al. 2015
laboratory has always been an effective means of studying the organic chemistry of hydrothermal fluids. In the past few decades, a variety of samplers have been designed and constructed to collect fluid samples from hydrothermal vents. These devices can be generally divided into two kinds: 1) syringe-type samplers, such as the “major” sampler ( Von Damm et al. 1985 ; Butterfield et al. 1990 ), the isobaric gas-tight sampler ( Seewald et al. 2002 ; Proskurowski et al. 2008 ; McDermott et al. 2015
1. Introduction Oceanographic sampling campaigns are limited in duration, resolution, and extent by the capabilities of measurement platforms. The continual development of new platforms and compatible instrumentation not only extends these limits but also enables the exploration of less accessible environments. Over the last 10 years, the development of remotely operated vehicles (ROVs) such as JASON ( Ballard 1993 ) has aided oceanographic sampling in a variety of inaccessible areas. More
1. Introduction Oceanographic sampling campaigns are limited in duration, resolution, and extent by the capabilities of measurement platforms. The continual development of new platforms and compatible instrumentation not only extends these limits but also enables the exploration of less accessible environments. Over the last 10 years, the development of remotely operated vehicles (ROVs) such as JASON ( Ballard 1993 ) has aided oceanographic sampling in a variety of inaccessible areas. More
observations are sampling scales smaller than can be represented by the state variables . The latter is often referred to as representation error. However, for simplicity we shall assume that the error in is negligible. In this study the observations are top-of-the-atmosphere (TOA) brightness temperatures , which can be directly related to TOA radiances using Planck’s law (e.g., Salby 1996 , p. 209). The state is a vector of temperature and specific humidity on 51 model levels. The TOA
observations are sampling scales smaller than can be represented by the state variables . The latter is often referred to as representation error. However, for simplicity we shall assume that the error in is negligible. In this study the observations are top-of-the-atmosphere (TOA) brightness temperatures , which can be directly related to TOA radiances using Planck’s law (e.g., Salby 1996 , p. 209). The state is a vector of temperature and specific humidity on 51 model levels. The TOA
