11:00 〜 13:00
[ACG38-P07] Various Meteorological Conditions Analysis for Overestimation / Underestimation of GSMaP in Mountains Areas
キーワード：GSMaP、過大評価、過小評価、POTEKA、気象条件
POTEKA(POint TEnki KAnsoku in Japanese) equipment can observe the eight meteorological variables such as temperature, relative humidity, sea-level pressure, wind speed, wind direction, sunshine, rain and precipitation. The five variables of temperature, relative humidity, sea-level pressure, wind speed and precipitation are certificated by JMA. As of January 2022, approximately 1000 POTEKA points have installed in the whole of Japan. Although it is not uniform such as AMeDAS observation network, POTEKA composes the localized but high density ground surface meteorological observation networks with the resolution of approximately 1 ~ 10 km. POTEKA observation started from around 2013 at the earliest. Compared with AMeDAS history of more than 40 years, POTEKA observation history is at most 9 years and very short. However, POTEKA has some high density observation networks in the mountains areas where AMeDAS observation point is relatively few. Moreover, some POTEKA points in the mountains areas have the observation history of multiple years.
The precipitation observation of GSMaP in the mountains areas has various characteristics depending on the season / area. The characteristics such as overestimation / underestimation sometimes appear very dominantly compared with the ground precipitation observation. We selected the four mountains areas where POTEKA composed the relatively high density observation network and had the observation history of approximately 3 years. The four areas are ①Nagano, ②Iwate, ③Shimane and ④Ehime/Kochi prefectures. We performed the comparative analysis between GSMaP and POTEKA for the four areas. The overestimation / underestimation of GSMaP appeared variously on the each area for the four months of July to October 2020. Particularly in the case of the overestimation of all four areas, we confirmed that the synoptic low appeared on the south side of Japan islands with high probabilities. Moreover, in the case of the underestimation of all four areas, we confirmed that the synoptic low appeared on the north side of Japan islands with high probabilities. The accuracy probability was approximately 60 ~ 70 %.
In this paper, we will introduce the other different cases from the above high probability cases. For example, we report the following cases.
・The case which the synoptic low didn’t appear on the south side of Japan islands although many areas had the overestimation of GSMaP. (Jul 7th, 2020 and Aug 8th, 2020)
・The case which the synoptic low didn’t appear on the north side of Japan islands although many areas had the underestimation of GSMaP. (Sep 6th, 2020)
・The case which the overestimation / underestimation of GSMaP appeared with mixed. (Aug 22nd, 2020 and Oct 22nd, 2020)
The precipitation observation of GSMaP in the mountains areas has various characteristics depending on the season / area. The characteristics such as overestimation / underestimation sometimes appear very dominantly compared with the ground precipitation observation. We selected the four mountains areas where POTEKA composed the relatively high density observation network and had the observation history of approximately 3 years. The four areas are ①Nagano, ②Iwate, ③Shimane and ④Ehime/Kochi prefectures. We performed the comparative analysis between GSMaP and POTEKA for the four areas. The overestimation / underestimation of GSMaP appeared variously on the each area for the four months of July to October 2020. Particularly in the case of the overestimation of all four areas, we confirmed that the synoptic low appeared on the south side of Japan islands with high probabilities. Moreover, in the case of the underestimation of all four areas, we confirmed that the synoptic low appeared on the north side of Japan islands with high probabilities. The accuracy probability was approximately 60 ~ 70 %.
In this paper, we will introduce the other different cases from the above high probability cases. For example, we report the following cases.
・The case which the synoptic low didn’t appear on the south side of Japan islands although many areas had the overestimation of GSMaP. (Jul 7th, 2020 and Aug 8th, 2020)
・The case which the synoptic low didn’t appear on the north side of Japan islands although many areas had the underestimation of GSMaP. (Sep 6th, 2020)
・The case which the overestimation / underestimation of GSMaP appeared with mixed. (Aug 22nd, 2020 and Oct 22nd, 2020)