Water vapor retrievals from the ground-based direct-Sun measurements based on the spectral Langley method

1. Introduction

Water vapor is the crucial gas of the atmosphere's hydrological cycle (IPCC, 2013), mainly emitted from ocean evaporation. It affects the water cycle in drylands through absorption by soil (Lopez-Canfin et al., 2022) and impacts the global radiation budget by absorbing infrared light, thereby acting as a natural greenhouse gas (Trenberth et al., 2007). Through water evaporation and condensation, water vapor provides the energy to drive moist convection and subsequent precipitation and determines the potential stability of the atmospheric columns (Fragkos et al., 2019). In particular, condensation of water vapor in the lower troposphere induces latent heat and affects the vertical structure of the tropospheric diabatic heating (Trenberth and Stepaniak, 2003). To accurately predict and analyze the climate, it is essential to have a precise understanding and estimation of water vapor. Water vapor measurements are also useful for analyzing the hygroscopic growth of atmospheric particles, thus affecting aerosol optical properties (e.g., Jeong et al., 2018, 2022).

Total precipitable water vapor (TPW) represents the amount of atmospheric water vapor contained in a vertical column of a unit cross-section and can be accurately measured by ground-based sun-tracking instruments based on Beer’s Law. Radiosonde measurements have been used to measure TPW for a long time. However, this measurement has limitations (e.g., freezing of moisture sensors, the release of latent heat, and phase lag can lead the errors in the estimation of moisture) (Campmany et al., 2010). To consider these limitations and the spatial-temporal coverage, several measurements have been developed, including satellite and ground-based measurements, and complement the TPW from radiosonde (e.g., Halthore et al., 1997; Holben et al., 1998; Dostalek and Schmit, 2001; Mears et al., 2015). In particular, the Aerosol Robotic Network (AERONET), a global network of Cimel sun photometer, retrieves the TPW by measuring the water vapor absorption band around 940 nm (Holben et al., 1998), and Several studies extensively have evaluated the AERONET TPW products using microwave radiometry, GPS, and radiosondes data (Sapucci et al., 2007; Campmany et al., 2010; Pérez-Ramírez et al., 2014). POM instruments deployed for the SKY radiometer NETwork (SKYNET) also measure direct solar irradiance from the ground and provide TPW retrievals with aerosol products (Campanelli et al., 2014).

Recently expanding ground-based hyperspectral remote sensing instruments such as the Pandora and Spectral Measurements for Atmospheric Radiative Transfer-spectroradiometer (SMART-s) also retrieve trace gases, including ozone (O₃), nitrogen dioxide (NO₂), and formaldehyde (HCHO) in addition to the aerosol and TPW. This study aims to develop a retrieval algorithm of the TPW using the SMART-s measurements based on the spectral Langley calibration method (Jeong et al., 2018) to analyze trace gas-aerosol-cloud interactions. To check consistency, we also compared the retrieved water vapor amount with the collocated AERONET measurements in this study.

2. Method

2.1. Measurements

Pandora network group at NASA (National Aeronautics and Space Administration) / GSFC (Goddard Space Flight Center) initially developed the SMART-s instrument (Jeong et al., 2018), and the SMART-s shares most parts of the standard Pandora instrument except for the spectrometer. The same manufacturer (i.e., Avantes; https://www.avantes. com/) built the SMART-s, and the Pandora spectrometer, but the SMART-s covers a wider spectral range (i.e., 280-820 nm) with a lower spectral resolution (~1.0 nm Fullwidth-half-maximum with about ×3.7 oversampling). Detailed information on the SMART-s instrument is summarized in Jeong et al. (2022). We deployed the SMART-s at Suwon, South Korea (37.26°N latitude, 126.99°E longitude), which is a downwind area of the Seoul-Metropolitan area during the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) campaign from 1 December 2023 to 15 February 2024 (see Figure 1). One AERONET instrument was also deployed during this period, and we used the AERONET TPW data (Version 3.0, Level 2.0) to check retrieval consistency in this study.

Fig. 1.

(a) Measurement location of the SMART-s instrument marked with yellow circle. (b) Picture of SMART-s and AERONET instruments deployed in Suwon.

3. Results

Figure 2a shows an example of the spectral optical thickness fitting result based on the SMART-s algorithm from 550 to 680 nm, where weak water vapor absorption bands are distributed. This sample was measured on 6 January 2024 at 03:37 UTC when the aerosol optical thickness was low. Figure 2b shows the spectral bias of the fitted spectrum from the measured optical thickness, which ranged about ±0.1 at around 380 and 630 nm. These biases are attributable to uncertainties in the calibrated slit function of the instrument and HITRAN database and various broadening processes the SMART-s algorithm does not account for yet. Jeong et al. (2018) adopted 4~5 polynomials for the spectral fitting of the aerosol optical thickness from 330 to 800 nm. In contrast, we adopted two low-order polynomials (i.e., zero and first order) as the fitting window of the TPW spectral fitting is narrower than that of the aerosol algorithm (i.e., 550-680 nm). Note that the low-order polynomials in Figure 2a (blue line) represent aerosol and cloud optical thickness (ACT), which is also useful information for analyzing the water vapor interactions with aerosols and clouds (e.g., Jeong et al., 2018, 2022).

Fig. 2.

(a) An example of spectral fitting of optical depth in the water vapor absorption band from 550 to 680 nm on 6 January 2024 at 03:37 UTC at Suwon, South Korea. Panel (b) indicates the residual between measured optical thickness and fitting parameters.

Figure 3 shows temporal variations of the TPW in Suwon retrieved from the AERONET (green) and SMART-s (red) during the measurement period. The AERONET instrument stopped measurements from 16 December 2023 to 22 January 2024 due to connection issues, and the SMART-s stopped operation on 15 February 2024. Wintertime in South Korea is typically dry, and the retrieved TPW data ranges up to 2 cm, as shown in Figure 3. During the measurement period, TPW retrievals from the SMART-s showed excellent consistency with the AERONET products. During the analysis period, 32,186 and 1,270 samples are collected by the SMART-s and AERONET, respectively.

Fig. 3.

Temporal variation of total precipitable water vapor in Suwon, South Korea, from 1 December 2023 to 28 February 2024.

Figure 4 compares retrieved TPW from the SMART-s with the collocated AERONET products during the measurement period. It shows excellent consistency with a correlation coefficient of 0.99 and a mean bias error (MBE) of -0.023. The dotted line depicts a one-to-one line, and the solid line indicates the regression line, which is close together (slope of 1.03 and offset of -0.04). The color of the circles represents the ACT. Relatively higher discrepancies appeared when the ACT is high, as shown in Figure 4. The direct-Sun algorithm assumes all the photons recorded are direct solar irradiance, which is valid when the optical thickness of the atmosphere is low. However, for the thick cloud cases (e.g., ACT > 4.0), measured direct-Sun data could be contaminated by the diffuse sky radiances within the field-of-view (FOV) of the collimator (i.e., ~2.2°). During the quality assurance processes of the SMART-s algorithm, retrievals with optical depths greater than 3.0 and air mass factors higher than 4.0 are screened. In general, the SMART-s direct-Sun TPW retrievals showed good agreement with the benchmark AERONET data.

Fig. 4.

Comparison of the total precipitable water (TPW) retrievals from the SMART-s with those from the AERONET (Version 3, Level 2.0) data in Suwon, South Korea from 1 December 2023 to 15 January 2024. The color of the circles depicts cloud and aerosol optical thickness (ACT) at 550 nm.

4. Summary and Discussions

The SMART-s and AERONET were deployed at Suwon, South Korea, during the ASIA-AQ campaign from December 2023 to February 2024. We retrieved the total precipitable water from the SMART-s direct-Sun measurement based on the spectral Langley calibration method in this study. Retrieved TPW from the SMART-s showed excellent agreement with the benchmark AERONET products (correlation coefficient of 0.99, slope of 1.03, and offset of -0.04). In the future, the TPW retrievals, in addition to the previously developed products (e.g., aerosol, cloud, NO₂, O₃, HCHO) from globally networked instruments, can provide valuable information for analyzing their interactions and impacts on meteorology and climate systems. It also can be used to validate various satellite-based TPW inversion products.

Acknowledgments

이 논문은 2023년도 정부(교육부)의 재원으로 한국연구재단의 G-램프(LAMP) 사업(No. RS-2023-00301702) 및 2024년도 교육부의 재원으로 한국연구재단의 지원을 받아 수행된 지자체-대학 협력기반 지역혁신 사업의 결과입니다(2023RIS-007).

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