Engineering topics

Wenig, Mark

Publications and source records attributed to Wenig, Mark.

3 records

NASA NTRS2017

The Version 3 OMI NO2 Standard Product

We describe the new version 3.0 NASA Ozone Monitoring Instrument (OMI) standard nitrogen dioxide (NO2) products (SPv3). The products and documentation are publicly available from the NASA Goddard Earth Sciences Data and Information Services Center (https://disc.gsfc.nasa.gov/datasets/OMNO2_V003/summary/). The major improvements include (1) a new spectral fitting algorithm for NO2 slant column density (SCD) retrieval and (2) higher-resolution (1° latitude and 1.25° longitude) a priori NO2 and temperature profiles from the Global Modeling Initiative (GMI) chemistry–transport model with yearly varying emissions to calculate air mass factors (AMFs) required to convert SCDs into vertical column densities (VCDs). The new SCDs are systematically lower (by ∼10-40%) than previous, version 2, estimates. Most of this reduction in SCDs is propagated into stratospheric VCDs. Tropospheric NO2 VCDs are also reduced over polluted areas, especially over western Europe, the eastern US, and eastern China. Initial evaluation over unpolluted areas shows that the new SPv3 products agree better with independent satellite- and ground-based Fourier transform infrared (FTIR) measurements. However, further evaluation of tropospheric VCDs is needed over polluted areas, where the increased spatial resolution and more refined AMF estimates may lead to better characterization of pollution hot spots.

Ozone Monitoring Instrument (OMI)↗

NASA NTRS2012

Dust Episodes in Hong Kong (South China) and their Relationship with the Sharav and Mongolian Cyclones and Jet Streams

The study presented in this paper analyses two dust episodes in Hong Kong, one occurring in March 2006 and the other on 22 March 2010. The latter is the worst dust episode on Hong Kong record. The focus is on the relationship between the dust episodes and the Sharav/Mongolian cyclones and jet streams. The 16 March 2006 episode is traceable to a continental-scale Saharan dust outbreak of 5-9 March 2006 caused by the cold front of an East Mediterranean Sharav cyclone arriving at north-west Africa on 5 March 2006. The eastward movement of the cyclone along the North African coast is clearly illustrated in the geopotential height contours. Simulations by the chemistry transport model GOCART provide a visible evidence of the transport as well as an estimate of contributions from the Sahara to the aerosol concentration levels in Hong Kong. The transport simulations suggest that the dust is injected to the polar jet north of the Caspian Sea, while it is transported eastward simultaneously by the more southerly subtropical jet. The major source of dust for Hong Kong is usually the Gobi desert. Despite the effect of remote sources, the 16 March 2006 dust episode was still mainly under the influence of the Mongolian cyclone cold fronts. In the recent episode of 22 March 2010, the influence of the Mongolian cyclone predominated as well. It appears that the concurrent influence of the Sharav and Mongolian cyclones on Hong Kong and East Asia is not a common occurrence. Besides transporting dusts from non-East Asian sources to Hong Kong and East Asia, the strong subtropical jet on 21 March 2010 (i.e. 1 day prior to the major dust episode) is believed to have strengthened an easterly monsoon surge to South China causing the transport of voluminous dusts to Taiwan and Hong Kong the following day.

Lee, Y. C.↗

NASA NTRS2004

Parameter Estimation in Atmospheric Data Sets

In this study the structure tensor technique is used to estimate dynamical parameters in atmospheric data sets. The structure tensor is a common tool for estimating motion in image sequences. This technique can be extended to estimate other dynamical parameters such as diffusion constants or exponential decay rates. A general mathematical framework was developed for the direct estimation of the physical parameters that govern the underlying processes from image sequences. This estimation technique can be adapted to the specific physical problem under investigation, so it can be used in a variety of applications in trace gas, aerosol, and cloud remote sensing. As a test scenario this technique will be applied to modeled dust data. In this case vertically integrated dust concentrations were used to derive wind information. Those results can be compared to the wind vector fields which served as input to the model. Based on this analysis, a method to compute atmospheric data parameter fields will be presented. .

Wenig, Mark↗