The utilization of the altimetric satellite’s on-board radiometer for atmospheric observation is demonstrated. This study uses the Wet Tropospheric Correction (WTC) data from the Topex/Jason altimetry mission series (Topex/Poseidon, Jason-1, Jason-2/OSTM, and Jason-3). The data spans nearly 30 years, making them sufficient for climate study. Precipitable Water Vapor (PWV) is derived from the WTC and used to study the water vapor variability over the Tropical Indian Ocean (TIO). Standard EOF (Empirical Orthogonal Function) analysis on the derived PWV anomaly (PWVA) in the TIO generates two leading modes. The first mode has a dipole spatial structure that explains 18.3% of the total variance, and the second one has a basin-wide homogeneous structure that explains 12.3% of the total variance. Correlation analysis with IOD and ENSO monitoring indices has shown that these two modes are associated with the two interannual variabilities. Further analyses using composite techniques are done to distinguish the different of mechanism and impact between the two. A new monitoring index is proposed here which uses the altimetry-derived PWV anomaly data. The index is computed from the difference of PWV anomaly between the dipole regions in TIO, which effectively describes the activity of the Indian Ocean Walker Circulation (IOWC). This research showcased the feasibility of using the data measured by the radiometer of altimetric satellites for atmospheric studies, a potential continuation of this research would be the use of the synchronous altimeter-radiometer measurement for more advanced analysis such as the ocean-atmosphere coupling.

Altimetry satellites have an on-board microwave radiometer whose original function is to measure the Tropospheric Wet Delay (TWD) for their main sea level measurement using radar altimeter. The TWD, as it reflects the amount of water vapor in the atmosphere, could be used to derive the Precipitable Water Vapor (PWV) which would be a good parameter to study the atmosphere variability, especially in Indonesia where rainfall is the main variable of its climate. Studies on altimetry-derived PWV are conducted, which include: analyzing their correlation with rainfall observation dataset, and assessing how well they could capture some key atmospheric phenomena in Indonesia. The results show that there are fairly high correlation between the altimetry-derived PWV and the rainfall data in monthly-scale with 0.63 Pearson correlation coefficient. Moreover, they could very well capture some key phenomena in Indonesia such as the monsoon and El Niño Southern Oscillation (ENSO) variation. Thus, a new way of utilizing altimetry satellite data is introduced in this paper: to observe the atmosphere using its water vapor data derived from the microwave radiometer. This open the possibility of utilizing altimetry satellites for both oceanographic and meteorological studies as it could measures both oceanic and atmospheric parameter, with its radar altimeter and microwave radiometer, respectively.

In the early April 2021, the tropical cyclone Seroja was formed over the Savu Sea in the southeastern Indonesia. In this study, we utilized the Global Navigation Satellite Systems (GNSS) observations to derive precipitable water vapor (PWV) from several permanent stations in the region to study Seroja. From in situ meteorological observations, we found that surface pressure values dropped by more than 20 hPa during Seroja, relative humidity increased, and temperature was reduced. PWV at two nearest stations showed an upward trend (around 70 mm at its peak) during the formation of the cyclone, then dropped immediately (less than 20 mm). After Seroja, the mean PWV was lower (56 mm before and 39 mm after), whereas the standard deviation was higher (5-6 mm before and 9 mm after). We also compared hourly PWV with precipitation from GSMaP. Before Seroja, some precipitation events occurred, followed by heavy rains that lasted for several days when the cyclone was passing. After Seroja had passed, both PWV and precipitation dropped significantly. However, while PWV values after Seroja was fluctuating, no rain occurred. We then investigated the water vapor budget to understand the change of PWV over time. We found that precipitation and the divergence of moisture flux played an important role in the change of PWV over time. Heavy precipitation during Seroja resulted in a drop in PWV, although the negative divergence provided a bit of offset. After Seroja had passed, no precipitation occurred and the change of PWV could be attributed mainly to the moisture divergence. The lagged correlation between PWV and precipitation was determined using moving average over the timeseries. The highest correlation was found 1-2 days before the event with moving average periods of 7 and 10 days.

Kandungan total uap air troposfer (precipitable water vapor) di suatu tempat dapat diestimasi berdasarkan karakteristik bias gelombang elektromagnetik dari satelit navigasi GPS, berupa zenith wet delay (ZWD). Pola musiman deret waktu ZWD sangat penting dalam studi siklus hidrologi khususnya yang terkait dengan kejadian-kejadian banjir. Artikel ini menganalisis korelasi musiman antara ZWD dan debit sungai Cikapundung di wilayah Bandung Utara berdasarkan estimasi rataan pola musimannya. Berdasarkan rekonstruksi sejumlah komponen harmonik ditemukan bahwa pola musiman ZWD memiliki kemiripan dan korelasi yang kuat dengan pola musiman debit sungai. Pola musiman ZWD dan debit sungai dipengaruhi secara kuat oleh fenomena pertukaran Monsun Asia dan Monsun Australia. Korelasi linier di antara keduanya menunjukkan hasil yang sangat kuat, dimana hampir 90% fluktuasi debit sungai dipengaruhi oleh kandungan uap air di troposfer dengan level signifikansi 95%. Berdasarkan spektrum amplitudo silang dan koherensi, kedua kuantitas ini nampak didominasi oleh siklus monsun satu tahunan disertai indikasi adanya pengaruh siklus tengah tahunan dan 4 bulanan.

<p>The mean temperature weighted with water vapor pressure (Tm) is an important parameter to obtain precipitable water vapor (PWV) from the Global Navigation Satellite Systems (GNSS) observations. This study investigates the possible impacts of equatorial troposphere on Tm estimates and its relation with surface temperature Ts. We calculated Tm in Indonesia from a Numerical Weather Model at nine InaCORS sites. We used 3-hourly ERA5 pressure, temperature, and humidity profiles for the year 2019. We found that Tm and surface temperature Ts in Indonesia have low correlation, less than 0.4. Seasonal and site-specific Tm-Ts relationships have slightly higher correlation, although the values can vary significantly. The highest correlation of around 0.7 is found at site CPUT in Kalimantan. We calculated Tm at nine additional stations in Kalimantan and found that stations located farther from the coast tend to have higher correlation, independent of the seasons. This suggests that Tm is also influenced by the vicinity to the coast. Based on our findings, the use of a general Tm-Ts relationship in Indonesia may not be appropriate. Further studies are necessary to develop an improved Tm over Indonesian region.</p>