Adjoint-Based Observation Impact of Advanced Microwave Sounding Unit-A (AMSU-A) on the Short-Range Forecast in East Asia

Abstract

The effect of Advanced Microwave Sounding Unit-A (AMSU-A) observations on the short-range forecast in East Asia (EA) was investigated for the Northern Hemispheric (NH) summer and winter months, using the Forecast Sensitivity to Observations (FSO) method. For both periods, the contribution of radiosonde (TEMP) to the EA forecast was largest, followed by AIRCRAFT, AMSU-A, Infrared Atmospheric Sounding Interferometer (IASI), and the atmospheric motion vector of Communication, Ocean and Meteorological Satellite (COMS) or Multi-functional Transport Satellite (MTSAT). The contribution of AMSU-A sensor was largely originated from the NOAA 19, NOAA 18, and MetOp-A (NOAA 19 and 18) satellites in the NH summer (winter). The contribution of AMSU-A sensor on the MetOp-A (NOAA 18 and 19) satellites was large at 00 and 12 UTC (06 and 18 UTC) analysis times, which was associated with the scanning track of four satellites. The MetOp-A provided the radiance data over the Korea Peninsula in the morning (08:00~11:30 LST), which was important to the morning forecast. In the NH summer, the channel 5 observations on MetOp-A, NOAA 18, 19 along the seaside (along the ridge of the subtropical high) increased (decreased) the forecast error slightly (largely). In the NH winter, the channel 8 observations on NOAA 18 (NOAA 15 and MetOp-A) over the Eastern China (Tibetan Plateau) decreased (increased) the forecast error. The FSO provides useful information on the effect of each AMSU-A sensor on the EA forecasts, which leads guidance to better use of AMSU-A observations for EA regional numerical weather prediction.

Assimilation of GPM-retrieved ocean surface meteorology data for two snowstorm events during ICE-POP 2018

“…Numerous studies showed that in situ and remote-sensed observations for surface conditions and the upper atmosphere can provide a better description for both storm-scale processes and large-scale environments, leading to improved precipitation forecasts (Zupanski et al, 2002;Cucurull et al, 2004;Zhang et al, 2006;Fillion et al, 2010;Hartung et al, 2011;Hamill et al, 2013;Salslo and Greybush, 2017;English et al, 2018;Zhang et al, 2019). In South Korea, data assimilation also indicated significant benefits for winter forecasts (Kim et al, 2013;Kim and Kim, 2017;Yang and Kim, 2021). For example, Kim et al (2013) demonstrated the assimilation of the conventional surface and upper air observations, aircraft, and multiple satellite observations located upwind or in the vicinity of the Korean Peninsula into the Korea Meteorological Administration (KMA) Unified Model.…”

Assimilation of GPM-retrieved Ocean Surface Meteorology Data for Two Snowstorm Events during ICE-POP 2018

“…Studies showed that in situ and remote sensed observations for surface conditions and the upper-atmosphere can provide a better description for both storm-scale processes and large-scale environments leading to improved precipitation forecasts (Zupanski et al, 2002;Cucurull et al, 2004;Zhang et al, 2006;Fillion et al, 2010;Hartung et al, 2011;Hamill et al, 2013;Salslo and Greybush, 2017;English et al, 2018;Zhang et al, 2019). In South Korea, data assimilation also indicated significant benefit for winter 95 forecast (Kim et al, 2013;Kim and Kim, 2017;Yang and Kim, 2021). For example, Kim et al (2013) demonstrated the assimilation of the conventional surface and upper air observations, aircraft, and multiple https://doi.org/10.5194/gmd-2021-161 Preprint.…”

Comment on gmd-2021-161

“…forecast(Kim et al, 2013;Kim and Kim, 2017; Yang and Kim, 2021). For example,Kim et al (2013) demonstrated the assimilation of the conventional surface and upper air observations, aircraft, and multiplehttps://doi.org/10.5194/gmd-2021-161 Preprint.…”