Ground-based Monitoring Stations Research Articles

Total column ozone and solar UV-B erythemal irradiance over Kishinev, Moldova

Results of the total column ozone and ultraviolet (UV-B) erythemally weighted irradiance measurements at the ground-based solar monitoring station at the Kishinev (Moldova) are presented. Diffuse and global components of solar UV-B erythemal irradiance on horizontal plane were continuously measured with sensors UV-S-B-C (of broadband 280-315 nm), Kipp&Zonen. Monthly totals of global and diffuse components of solar UV-B erythemal radiation reveal distinct seasonal variation with respective minimum in winter and maximum in summer. Typical values for these components in limiting cases are presented. A simple polynomial relationship between the global and diffuse components of solar UV-B erythemal radiation measured for cloudless days was derived. It was shown that coefficients of the polynomial depend on daily mean value of aerosol optical thickness (AOT). Collocated measurements of AOT have been carried out with the sunphotometer Cimel CE-318 within the framework of the Aerosol Robotic Network (AERONET) program, managed by NASA/GSFC. Total column ozone content was retrieved from direct solar ultraviolet radiation measurements at 3 discrete wavelengths centered at 305.5, 312.5, and 320 nm within the UV-B range. Ozone measurements were regularly carried out with the hand-held MICROTOPS II Ozonemeter, Solar Light Co. Monthly average values of total column ozone content measured with the MICROTOPS II at the Kishinev are in close agreement with those ones retrieved from the multiyear (1978-2004) database statistics acquired from satellite platforms measurements with the Total Ozone Mapping Spectrometer (TOMS). It was shown the existence of seasonal variability of the total column ozone content with respective minimum values observed at the end of autumn and winter, and maximum values observed at the end of winter and in spring. The maximum and minimum of daily mean values of total column ozone ever measured with TOMS at the satellite platforms overpassed Kishinev site, amounted of ~540 DU (on February 19, 1985) and ~204 DU (on December 1, 1999). Yearly mean value of total column ozone measured at the Kishinev was ~ 338 DU. Total column ozone measurements carried out with MICROTOPS at the Kishinev site from September 2003 to August 2004, gave maximum and minimum values of ozone daily means at ~ 489 DU (on February 12, 2004) and ~259 DU (on December 3, 2003). The estimation of total column ozone trend derived from the TOMS multi-year statistics was ~ -10 DU/decade.

Low-Amplitude Anisotropic Wave Train Events during Passage of Interplanetary Magnetic Clouds / Mazas Amplitūdas Anizotropiju Viļņu Parādību Secība Starpplanētu Magnētisko Mākoņu Rašanās Laikā

The work presents a continuation in the series related to the long-term space observations made by ground-based neutron monitoring stations. The cosmic ray intensity variation is considered as affected by interplanetary magnetic clouds during low-amplitude anisotropic wave train (LAAWT) events. It was observed that the solar wind velocity is higher than normal (> 300 km/s) while the interplanetary magnetic field (IMF) strength is lower than normal on the arrival of magnetic cloud during LAAWT events. The proton density is found to remain significantly low at high solar-wind velocity, which was expected. The north/south component of interplanetary magnetic field turns southward one day before the arrival of cloud and remains in this direction after that. The cosmic ray intensity is found to increase with the solar wind velocity. It is noteworthy that the cosmic ray intensity significantly increases before and 90 h after the arrival of such a cloud, and decreases gradually after its passage. The north/south component of IMF (Bz) is found to significantly correlate with latitude angle (Ө) and disturbance storm time index Dst, whereas the geomagnetic activity index (Ap) significantly anti-correlates with these parameters, decreasing with (Ө) and Dst increasing on the arrival of interplanetary magnetic cloud during LAAWT events.

A semi-empirical model for predicting hourly ground-level fine particulate matter (PM2.5) concentration in southern Ontario from satellite remote sensing and ground-based meteorological measurements

Abstract A semi-empirical model is developed to predict the hourly concentration of ground-level fine particulate matter (PM 2.5 ) coincident to satellite overpass, at a regional scale. The model corrects the aerosol optical depth (AOD) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) by the assimilated parameters characterizing the boundary layer and further adjusts the corrected value according to meteorological conditions near the ground. The model was built and validated using the data collected for southern Ontario, Canada for 2004. Overall, the model is able to explain 65% of the variability in ground-level PM 2.5 concentration. The model-predicted values of PM 2.5 mass concentration are highly correlated with the actual observations. The root-mean-square error of the model is 6.1 µg/m³. The incorporation of ground-level temperature and relative humidity is found to be significant in improving the model predictability. The coarse resolution of the assimilated meteorological fields limits their value in the AOD correction. Although MODIS AOD data is acquired on a daily basis and the valid data coverage can sometimes be very limited due to unfavourable weather conditions, the model provides a cost-effective approach for obtaining supplemental PM 2.5 concentration information in addition to the ground-based monitoring station measurement.

Using LiDAR and quickbird data to model plant production and quantify uncertainties associated with wetland detection and land cover generalizations

Spatiotemporal data from satellite remote sensing and surface meteorology networks have made it possible to continuously monitor global plant production, and to identify global trends associated with land cover/use and climate change. Gross primary production (GPP) and net primary production (NPP) are routinely derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard satellites Terra and Aqua, and estimates generally agree with independent measurements at validation sites across the globe. However, the accuracy of GPP and NPP estimates in some regions may be limited by the quality of model input variables and heterogeneity at fine spatial scales. We developed new methods for deriving model inputs (i.e., land cover, leaf area, and photosynthetically active radiation absorbed by plant canopies) from airborne laser altimetry (LiDAR) and Quickbird multispectral data at resolutions ranging from about 30 m to 1 km. In addition, LiDAR-derived biomass was used as a means for computing carbon-use efficiency. Spatial variables were used with temporal data from ground-based monitoring stations to compute a six-year GPP and NPP time series for a 3600 ha study site in the Great Lakes region of North America. Model results compared favorably with independent observations from a 400 m flux tower and a process-based ecosystem model (BIOME-BGC), but only after removing vapor pressure deficit as a constraint on photosynthesis from the MODIS global algorithm. Fine-resolution inputs captured more of the spatial variability, but estimates were similar to coarse-resolution data when integrated across the entire landscape. Failure to account for wetlands had little impact on landscape-scale estimates, because vegetation structure, composition, and conversion efficiencies were similar to upland plant communities. Plant productivity estimates were noticeably improved using LiDAR-derived variables, while uncertainties associated with land cover generalizations and wetlands in this largely forested landscape were considered less important.

A Framework for Novelty Detection in Jet Engine Vibration Data

A novelty detection approach to condition monitoring of aerospace gas-turbine engines is presented, providing a consistent framework for on- and off-line analysis, each with differing typical implementation constraints. On-line techniques are introduced for observing abnormality in engine behaviour during aircraft flights, and are shown to provide early warning of engine events in real-time. Off-line techniques within the same analysis framework are shown to allow the tracking of single engines and fleets of engines from ground-based monitoring stations on a flight-by-flight basis. Results are validated by comparison to conventional techniques, in application to aerospace engines and other industrial high-integrity systems.

Applications of MODIS satellite data and products for monitoring air quality in the state of Texas

The Center for Space Research (CSR), in conjunction with the Monitoring Operations Division (MOD) of the Texas Commission on Environmental Quality (TCEQ), is evaluating the use of remotely sensed satellite data to assist in monitoring and predicting air quality in Texas. The challenges of meeting air quality standards established by the US Environmental Protection Agency (US EPA) are impacted by the transport of pollution into Texas that originates from outside our borders and are cumulative with those generated by local sources. In an attempt to quantify the concentrations of all pollution sources, MOD has installed ground-based monitoring stations in rural regions along the Texas geographic boundaries including the Gulf coast, as well as urban regions that are the predominant sources of domestic pollution. However, analysis of time-lapse GOES satellite imagery at MOD, clearly demonstrates the shortcomings of using only ground-based observations for monitoring air quality across Texas. These shortcomings include the vastness of State borders, that can only be monitored with a large number of ground-based sensors, and gradients in pollution concentration that depend upon the location of the point source, the meteorology governing its transport to Texas, and its diffusion across the region. With the launch of NASA's MODerate resolution Imaging Spectroradiometer (MODIS), the transport of aerosol-borne pollutants can now be monitored over land and ocean surfaces. Thus, CSR and MOD personnel have applied MODIS data to several classes of pollution that routinely impact Texas air quality. Results demonstrate MODIS data and products can detect and track the migration of pollutants. This paper presents one case study in which continental haze from the northeast moved into the region and subsequently required health advisories to be issued for 150 counties in Texas. It is concluded that MODIS provides the basis for developing advanced data products that will, when used in conjunction with ground-based observations, create a cost-effective and accurate pollution monitoring system for the entire state of Texas.

Assessing the meteorological conditions of a deep Italian Alpine valley system by means of a measuring campaign and simulations with two models during a summer smog episode

The typical features of a summer smog episode in the highly complex terrain of the Province of Bolzano (Northern Italy) were investigated by numerical modelling with two non-hydrostatic models, ground-based monitoring stations, and vertical profiling with two sodars and an ultra-light aircraft. High ozone concentrations are most likely to appear in situations where the local circulation in the valleys is decoupled from the synoptic flow above during anticyclonic weather regimes. Both models (MM5 and TVM) produced similar results and were able to simulate the local winds in the valleys. A comparison of the measured data to the model simulation results made an evaluation of the performance of the two models in such complex terrain possible. Both models proved to be suitable for the simulation of the meteorological conditions during such summer smog episodes in complex terrain.

The Characterization of an Air Pollution Episode Using Satellite Total Ozone Measurements

A case study is presented which demonstrates that measurements of total ozone from a space-based platform can be used to study a widespread air pollution episode over the southeastern U.S. In particular, the synoptic-scale distribution of surface-level ozone obtained from an independent analysis of ground-based monitoring stations appears to be captured by the synoptic-scale distribution of total ozone, even though about 90 percent of the total ozone is in the stratosphere. Additional analyses of upper air meteorological data, other satellite imagery, and in situ aircraft measurements of ozone likewise support the fact that synoptic-scale variability of tropospheric ozone is primarily responsible for the observed variability in total ozone under certain conditions. The use of the type of analysis discussed in this study may provide an important technique for understanding the global budget of tropospheric ozone.