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Full-Text Articles in Meteorology
Synergistic Use Of Remote Sensing And Modeling To Assess An Anomalously High Chlorophyll-A Event During Summer 2015 In The South Central Red Sea, Wenzhao Li, Hesham El-Askary, K. P. Manikandan, Mohamed A. Qurban, Michael J. Garay, Olga V. Kalishnikova
Synergistic Use Of Remote Sensing And Modeling To Assess An Anomalously High Chlorophyll-A Event During Summer 2015 In The South Central Red Sea, Wenzhao Li, Hesham El-Askary, K. P. Manikandan, Mohamed A. Qurban, Michael J. Garay, Olga V. Kalishnikova
Mathematics, Physics, and Computer Science Faculty Articles and Research
An anomalously high chlorophyll-a (Chl-a) event (>2 mg/m3) during June 2015 in the South Central Red Sea (17.5° to 22°N, 37° to 42°E) was observed using Moderate Resolution Imaging Spectroradiometer (MODIS) data from the Terra and Aqua satellite platforms. This differs from the low Chl-a values (<0.5 mg/m3) usually encountered over the same region during summertime. To assess this anomaly and possible causes, we used a wide range of oceanographical and meteorological datasets, including Chl-a concentrations, sea surface temperature (SST), sea surface height (SSH), mixed layer depth (MLD), ocean current velocity and aerosol optical depth (AOD) obtained from different sensors and models. Findings confirmed this anomalous behavior in the spatial domain using Hovmöller data analysis techniques, while a time series analysis addressed monthly and daily variability. Our analysis suggests that a combination of factors controlling nutrient supply contributed to the anomalous phytoplankton growth. These factors include horizontal transfer of upwelling water through eddy circulation and possible mineral fertilization from atmospheric dust deposition. Coral reefs might have provided extra nutrient supply, yet this is out of the scope of our analysis. We thought that dust deposition from a coastal dust jet event in late June, coinciding with the phytoplankton blooms in the area under investigation, might have also contributed as shown by our AOD findings. However, a lag cross correlation showed a two- month lag between strong dust outbreak and the high Chl-a anomaly. The high Chl-a concentration at the edge of the eddy emphasizes the importance of horizontal advection in fertilizing oligotrophic (nutrient poor) Red Sea waters.
Inter- And Intra-Annual Variability Of Vegetation In The Northern Hemisphere And Its Association With Precursory Meteorological Factors, Boksoon Myoung, Yong-Sang Choi, Seungbum Hong, Seon Ki Park
Inter- And Intra-Annual Variability Of Vegetation In The Northern Hemisphere And Its Association With Precursory Meteorological Factors, Boksoon Myoung, Yong-Sang Choi, Seungbum Hong, Seon Ki Park
Mathematics, Physics, and Computer Science Faculty Articles and Research
Determination of phenological variation is one of the most critical challenges in dynamic vegetation modeling, given the lack of a strong theoretical framework. Previous studies generally focused on the timing of a phenological event (e.g., bud-burst or onset of growing season) and its atmospheric prompts, but not on the interactive variations across phenological stages. This study, therefore, investigated the inter- and intra-annual variability existing in all the phenological stages and the relations of the variability with four meteorological variables (surface temperature (Ts), shortwave radiation (SW ), vapor pressure deficit (VPD), and precipitation (PRCP)) using a 25-year (1982-2006) dataset of leaf …
Note On The Ndvi-Lst Relationship And The Use Of Temperature-Related Drought Indices Over North America, D. Sun, Menas Kafatos
Note On The Ndvi-Lst Relationship And The Use Of Temperature-Related Drought Indices Over North America, D. Sun, Menas Kafatos
Mathematics, Physics, and Computer Science Faculty Articles and Research
A comprehensive evaluation of the relationship between vegetation and Land Surface Temperature (LST) over the North America is presented. It is found that the correlations between LST and Normalized Difference Vegetation Index (NDVI) depend on the season-of-year and time-of-day. For winter, the correlation between NDVI and LST is positive. The strong negative correlations between LST and NDVI are only found during the warm seasons. Thus temperature-related drought indices may only be used in the warm seasons from May to October, and should be used with caution during cold seasons in North America. The cooling effect of vegetation on LST is …