info:eu-repo/semantics/article
Total column water vapor estimation over land using radiometer data from SAC-D/Aquarius
Fecha
2018-02Registro en:
Epeloa, Javier Eduardo; Meza, Amalia Margarita; Total column water vapor estimation over land using radiometer data from SAC-D/Aquarius; Elsevier; Advances in Space Research; 61; 4; 2-2018; 1025-1034
0273-1177
CONICET Digital
CONICET
Autor
Epeloa, Javier Eduardo
Meza, Amalia Margarita
Resumen
The aim of this study is retrieving atmospheric total column water vapor (CWV) over land surfaces using a microwave radiometer (MWR) onboard the Scientific Argentine Satellite (SAC-D/Aquarius). To research this goal, a statistical algorithm is used for the purpose of filtering the study region according to the climate type.A log-linear relationship between the brightness temperatures of the MWR and CWV obtained from Global Navigation Satellite System (GNSS) measurements was used. In this statistical algorithm, the retrieved CWV is derived from the Argentinian radiometer's brightness temperature which works at 23.8 GHz and 36.5 GHz, and taking into account CWVs observed from GNSS stations belonging to a region sharing the same climate type. We support this idea, having found a systematic effect when applying the algorithm; it was generated for one region using the previously mentioned criteria, however, it should be applied to additional regions, especially those with other climate types.The region we analyzed is in the Southeastern United States of America, where the climate type is Cfa (Köppen - Geiger classification); this climate type includes moist subtropical mid-latitude climates, with hot, muggy summers and frequent thunderstorms. However, MWR only contains measurements taken from over ocean surfaces; therefore the determination of water vapor over land is an important contribution to extend the use of the SAC-D/Aquarius radiometer measurements beyond the ocean surface. The CWVs computed by our algorithm are compared against radiosonde CWV observations and show a bias of about -0.6 mm, a root mean square (rms) of about 6 mm and a correlation of 0.89.