Search Results

You are looking at 71 - 80 of 807 items for :

  • Journal of Atmospheric and Oceanic Technology x
  • Refine by Access: All Content x
Clear All
C. W. Fairall, A. B. White, J. B. Edson, and J. E. Hare

given by where c dn , c Tn , and c qn are the transfer coefficients for velocity, temperature, and moisture; the subscript n refers to the neutral value ( ξ = 0), and the transfer coefficients for stress and sensible and latent heat are denoted by C x . Here X s is the mean variable value at the surface, and X r the value at some reference height z r . Note that in this convention X = U 1 , U 2 are the horizontal wind components relative to the fixed earth, and S is the

Full access
Raquel Niclòs, Vicente Caselles, César Coll, Enric Valor, and Eva Rubio

autonomous system. The measurements took place during the 2000 and 2001 Wind and Salinity Experiment (WISE) campaigns conducted in the framework of the Soil Moisture and Ocean Salinity (SMOS) mission, sponsored by the European Space Agency (ESA). The SMOS request in salinity accuracy is ±0.1 psu (1 psu = 1 g of salt in 1 kg of seawater), which is derived from the Global Ocean Data Assimilation Experiment (GODAE) requirements for global ocean-circulation studies ( Kerr et al. 2001 ; Berger et al. 2002

Full access
Nadya T. Vinogradova and Rui M. Ponte

1. Introduction An important component of the calibration and validation effort of any satellite mission is the comparison between remotely sensed and in situ measurements. For the recently launched Aquarius/Satelite de Aplicaciones Cientificas-D ( SAC-D ; Lagerloef et al. 2008 ; Lagerloef 2012 ) and Soil Moisture and Ocean Salinity ( SMOS ; Font et al. 2010 ) satellite missions dedicated to measuring sea surface salinity (SSS), comparison between retrieved and in situ observations is

Full access
Qinghua Yang, Martin Losch, Svetlana N. Losa, Thomas Jung, and Lars Nerger

sparsely gridded sea ice thickness observations, there are very few studies with ice thickness assimilation. Lisæter et al. (2007) examined the potential for ice thickness assimilation in coupled sea ice–ocean models with an ensemble Kalman filter (EnKF). Yang et al. (2014) assimilated the first near-real-time European Space Agency’s (ESA) Soil Moisture Ocean Salinity (SMOS) satellite–based sea ice thickness data into a coupled sea ice–ocean model using a local ensemble-based singular evolutive

Full access
Hengqian Yan, Ren Zhang, Gongjie Wang, Huizan Wang, Jian Chen, and Senliang Bao

1. Introduction Satellite observations have become essential tools to depict phenomena and features in the ocean. Almost all kinds of sea surface fields, including sea surface temperature (SST), sea surface height (SSH), sea surface ice, and chlorophyll concentration, have been mapped by the satellite platforms for a long time. Nevertheless, remote sensing of sea surface salinity (SSS) was not realized until the launch of Soil Moisture Ocean Salinity (SMOS) mission in 2009 ( Font et al. 2010

Full access
Claire Henocq, Jacqueline Boutin, Gilles Reverdin, François Petitcolin, Sabine Arnault, and Philippe Lattes

detection of SSS, will be launched in the next two years. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) satellite mission will derive SSS on individual pixels with a spatial resolution at ground level of about 40 km and global surface ocean coverage of between 3 and 7 days ( Barre et al. 2008 ). The accuracy expected on a single observation goes from 0.5 at the center of the swath to 1.7 practical salinity scale (pss) of 1978 at the edge on SSS, at 35 pss and 15°C ( Zine et al

Full access
Dean Vickers and L. Mahrt

1. Introduction Our purpose is twofold: to (i) study the cospectral gap that separates turbulent and mesoscale contributions to the calculated fluxes of heat, moisture, and momentum; and (ii) present a description of multiresolution decomposition including a simple example. Multiresolution analysis applied to time series decomposes the record into averages on different time scales and represents the simplest possible orthogonal decomposition. Multiresolution (MR) spectra yield information on

Full access
M. Adam, B. B. Demoz, D. D. Venable, E. Joseph, R. Connell, D. N. Whiteman, A. Gambacorta, J. Wei, M. W. Shephard, L. M. Miloshevich, C. D. Barnet, R. L. Herman, and J. Fitzgibbon

1. Introduction Water vapor is an important constituent of the atmosphere. The vertical distribution of moisture is important in determining atmospheric stability. Water vapor is also the most radiatively active atmospheric trace gas in the infrared ( Ramanathan 1988 ) and thus could produce strong forcing from feedback associated with anthropogenically driven climate change ( Cess et al. 1990 ). In addition, there is significant variability in the distribution of water vapor on temporal and

Full access
M. Talone, C. Gabarró, A. Camps, R. Sabia, J. Gourrion, M. Vall-llossera, and J. Font

1. Introduction a. The SMOS mission In May 1999 the European Space Agency (ESA) approved the Soil Moisture and Ocean Salinity (SMOS) Mission as the second of its Living Planet Programme Earth Explorer Opportunity Missions to provide global and frequent soil moisture and sea surface salinity (SSS) maps. SMOS was launched on 2 November 2009, and after the first calibration and checkout period (the so-called “commissioning phase”), SSS level 3 products will be distributed; the expected accuracy is

Full access
Xuelei Feng, Feiqin Xie, Chi O. Ao, and Richard A. Anthes

atmospheric research. Numerous studies have demonstrated the high quality of RO data in the upper troposphere and lower stratosphere from GPS/Meteorology (MET) ( Rocken et al. 1997 ; Kursinski et al. 1997 ; Feng and Herman 1999 ; Tsuda et al. 2000 ) and CHAMP ( Wickert et al. 2001 ). However, these earlier RO missions, which were equipped with phase-locked loop tracking receivers, encountered significant signal tracking challenges in the presence of large moisture variations in the lower troposphere

Free access