[A-CG41] Satellite Earth Environment Observation

[ACG41-P26] Development of an Algorithm for Estimating Near-Surface Specific Humidity Using Water Vapor Scale Height for GPM/GMI

*Yuta Kyono¹, Hiroyuki Tomita² (1.Hokkaido University Graduate School of Environmental Science, 2.Faculty of Environmental Earth Science and Graduate School of Environmental Science, Hokkaido University)

Keywords:Global Precipitation Measurement mission (GPM), GPM Microwave Imager (GMI), microwave radiometer, near-surface humidity, water vapor scale height, satellite-borne retrievals

Near-surface humidity (Q_a) regulates the evaporation of water from the sea surface is one of the most important parameters affecting the global water cycles. Observation of Q_a has conventionally been made by buoys and ships, but the use of satellite-borne sensors is necessary to estimate Q_a on a global scale. In particular, satellite microwave raidiometers have advanced along with the development of observational retrieval methods for Q_a. Retrieval of Q_a by satellite microwave radiometers has been based in regression between satellite-observed brightness temperature (T_B) and in-situ observations of Q_a. Tomita et al. (2018) developed an algorithm to estimate Q_a using an index called water vapor scale height (H_V), which correlates with the vertical moisture structure, and it was developed for the Special Sensor Microwave Imager (SSM/I) series, Advanced Microwave Scanning Radiometer (AMSR) series, and Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI). However, no algorithm has been developed for the Global Precipitation Measurement (GPM) Microwave Imager (GMI), which is the successor to the TMI and has a wider range of observations than the TMI. In this study, an algorithm for estimation of Q_a for the GMI was developed using 19 v/h, 23 v, 37 v/h, and 89 v/h GHz frequency bands out of the channels that the GMI has: 10 v/h, 19 v/h, 23 v, 37 v/h, 89v/h, 165 v/h, 183±3 v, and 183±8 v (suffixes v and h mean vertical and horizontal polarization respectively) frequency bands. Since the GPM Core Observatory is in a solar asyncronous orbit and the time of observation at a given location is not constant, it is considered to be useful for estimating daily mean values at locations with large daily changes in Q_a, such as mid-latitudes and areas with weak winds affected by fronts and typhoons. First, in-situ observation of Q_a and Satellite-observed T_Bs were matched up with criteria that the temporal and spatial differences had to be less than 30 minutes and 28 km. Second, to establish a relationship between in-situ Q_a and satellite-observed T_Bs, multiple regression was performed on the obtained match-up data for each range of H_V to make regression equation for T_B and Q_a. Finally, Q_a retrievals were peforemed based on the regression equation over the global oceans. The results were validated using instantaneous in-situ data independent of the data used to make the regression equation, and daily gridded global distributions with a horizontal resolution of 0.25° were constructed.
The climatological characteristics of the distribution of the retrieved Q_a were similar to those obtained from previous studies. To evaluate this result, a comparison was made with the daily mean of the global mooring buoy observations. The results showed some scattering in the high humidity range compared to the lower humidity ranges. In this study, the channels used were inthe same frequency bands as AMSR series and SSM/I series to demonstrate the previous study, but the GMI has a feature of high-frequency channels that other satellite microwave radiometers do not have, so there is a potential that these channels can be used for estimation of Q_a. The GPM Core Observatory also has a precipitation radar, Dual Frequency Radar (DPR), which observes 3-dimensional precipitation structure and Spectral Latent Heating (SLH), in addition to the GMI. Further possible improvement of the algorithm for estimation of Q_a wii be explored by using that imformation obtained from the DPR.