闽浙赣地区GPM IMERG降水产品降尺度建模与比较分析

doi:10.12082/dqxxkx.2019.180603

地球信息科学学报 ›› 2019, Vol. 21 ›› Issue (10): 1642-1652.doi: 10.12082/dqxxkx.2019.180603

闽浙赣地区GPM IMERG降水产品降尺度建模与比较分析

史岚^1,^*(),何其全¹,杨娇¹,万逸波^1,²

^1. 南京信息工程大学地理科学学院,南京 210044
^2. 无锡太湖水务有限公司,无锡 214031

收稿日期:2018-11-26 修回日期:2019-05-24 出版日期:2019-10-25 发布日期:2019-10-29
通讯作者: 史岚 E-mail:sl_nim@163.com
作者简介:作者简介：史岚（1978-）,女,江苏扬州人,博士,副教授,主要从事3S技术与气象应用研究。E-mail:sl_nim@163.com
基金资助:
国家自然科学基金青年科学基金项目(41405107);江苏省高等学校自然科学研究面上项目(14KJD170004);江苏省研究生科研与实践创新计划项目(KYCX18_1040)

Downscaling Modeling of the GPM IMERG Precipitation Product and Comparative Analysis in the Fujian-Zhejiang-Jiangxi Region

SHI Lan^1,^*(),HE Qiquan¹,YANG Jiao¹,WAN Yibo^1,²

^1. School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, China;
^2. Wuxi Waterworks Company Limited, Wuxi 214031, China

Received:2018-11-26 Revised:2019-05-24 Online:2019-10-25 Published:2019-10-29
Contact: SHI Lan E-mail:sl_nim@163.com
Supported by:
National Natural Science Foundation of China(41405107);Natural Science Foundation of the Jiangsu Higher Education Institutions of China(14KJD170004);Postgraduate Research & Practice Innovation Program of Jiangsu Province(KYCX18_1040)

摘要/Abstract

摘要：

针对目前的技术手段下难以直接获得大范围高精度精细化降水空间分布的问题,本文以闽浙赣地区为研究范围,选用GPM IMERG降水产品,综合应用地面实测降水数据以及水汽与植被指数数据,基于地理加权回归（GWR）法构建了基于水汽因子的降尺度模型,同时基于最小二乘（OLS）法构建了基于水汽因子与植被指数的对比模型,将降水产品的分辨率从0.1°提升至1 km,最终获得2015年闽浙赣地区各月精细化降水空间分布,使用验证站点实测数据进行验证。结果表明：① 构建的 3个降尺度模型中,GWR模型与2种OLS模型相比,拟合优度分别提升了102.9%和93.9%,模型降尺度结果整体优于2种OLS模型,且月际差异小,稳定性更高;2种OLS模型中,采用了水汽因子的模型拟合效果有8个月份更优;② 融合多源数据的GWR降尺度模型获得的结果在研究区内是可靠的,与GPM降水产品相比,在提升空间分辨率的同时,平均相对误差与均方根误差月均分别下降了42%和32%,精度明显改善。

关键词: GPM IMERG降水产品, 降尺度建模, GWR, 水汽, 闽浙赣地区

Abstract:

In view of present difficulties in providing high-precision precipitation information, this paper constructed three models for downscaling the GPM IMERG precipitation product, based on Geographically Weighted Regression （GWR） and two Ordinary Least Square （OLS） methods. Using these three models, the spatial distribution of precipitation in each month in 2015 was downscaled by integrating the original GPM IMERG product, the ground measured precipitation data, MOD05 water vapor data, and Vegetation index data. The resolution of the precipitation product was downscaled from 0.1° to 1km. Validation results showed that the goodness of the GWR-based model was 102.9% and 93.9%, higher than the goodness of the two OLS models. More specifically, the GWR model has exhibited better stability and less monthly variations. Of the two OLS models, the one that incorporated water vapor exhibited better model fitting goodness in eight months. Compared with the GPM precipitation product, the GWR-based downscaled product, in addition to increase the spatial resolution, decreased the relative error and root-mean-square error by 42% and 32%, respectively. Our findings suggest that the proposed GWR-based model has good potential in downscaling the GPM IMERG precipitation product.

Key words: GPM IMERG precipitation product, downscaling modeling, GWR, water vapor, Fujian-Zhejiang-Jiangxi region

史岚,何其全,杨娇,万逸波. 闽浙赣地区GPM IMERG降水产品降尺度建模与比较分析[J]. 地球信息科学学报, 2019, 21(10): 1642-1652.

SHI Lan,HE Qiquan,YANG Jiao,WAN Yibo. Downscaling Modeling of the GPM IMERG Precipitation Product and Comparative Analysis in the Fujian-Zhejiang-Jiangxi Region[J]. Journal of Geo-information Science, 2019, 21(10): 1642-1652.

图/表 10

图1

表1

图2

表2

图3

图4

图5

图6

表3

GPM原始数据与降尺度结果精度指标"

月份	R		MRE/%		RMSE/mm		$S s$
月份	原始GPM	降尺度结果	原始GPM	降尺度结果	原始GPM	降尺度结果	原始GPM	降尺度结果
1	0.451	0.812	34.43	13.01	19.19	8.90	-0.609	0.654
2	0.940	0.958	31.84	22.78	19.88	15.80	0.866	0.916
3	0.917	0.966	14.67	10.03	24.71	15.48	0.829	0.933
4	0.703	0.849	27.83	16.86	33.57	24.04	0.448	0.717
5	0.781	0.908	20.25	11.89	87.18	59.54	0.601	0.814
6	0.854	0.962	28.27	14.97	79.02	40.01	0.699	0.923
7	0.594	0.769	17.05	13.30	50.81	41.08	0.335	0.565
8	0.768	0.801	30.98	24.15	81.24	75.94	0.557	0.613
9	0.706	0.879	25.88	16.48	55.58	37.40	0.492	0.770
10	0.676	0.856	32.14	16.52	33.15	24.44	0.431	0.691
11	0.919	0.931	41.10	21.11	34.15	29.70	0.823	0.866
12	0.892	0.974	19.52	4.56	31.30	9.25	0.406	0.948

表3

图7

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月份	R		MRE/%		RMSE/mm
月份	原始GPM	融合GPM	原始GPM	融合GPM	原始GPM	融合GPM
1	0.451	0.804	34.43	12.68	5.54	2.60
2	0.940	0.962	31.84	22.22	5.74	4.42
3	0.917	0.956	14.67	11.06	7.13	5.10
4	0.703	0.803	27.83	18.15	9.69	7.97
5	0.781	0.917	20.25	11.52	25.17	16.42
6	0.854	0.957	28.27	15.45	22.81	12.24
7	0.594	0.744	17.05	15.06	14.67	12.65
8	0.768	0.774	30.98	27.37	23.45	22.60
9	0.706	0.888	25.88	16.76	16.04	10.46
10	0.676	0.855	32.14	17.79	9.57	6.98
11	0.919	0.943	41.10	22.59	9.86	7.87
12	0.892	0.976	19.52	4.28	9.04	2.56

月份	R²			AIC
月份	OLS_NDVI模型	OLS_PWV模型	GWR_PWV模型	OLS_NDVI模型	OLS_PWV模型	GWR_PWV模型
1	0.245	0.235	0.781	25 911.77	26 248.06	22 080.06
2	0.766	0.762	0.946	30 974.77	31 291.86	26 339.71
3	0.377	0.443	0.902	34 699.48	34 626.82	28 805.83
4	0.385	0.391	0.816	32 379.88	31 632.09	28 647.43
5	0.455	0.458	0.879	39 411.65	39 299.39	34 772.91
6	0.373	0.370	0.912	40 366.09	40 744.17	34 126.50
7	0.265	0.274	0.773	36 740.84	36 136.28	33 275.12
8	0.536	0.548	0.794	37 655.52	36 931.75	35 307.04
9	0.550	0.545	0.820	35 016.98	35 013.09	32 309.58
10	0.229	0.231	0.817	31 590.47	31 875.78	27 092.22
11	0.492	0.553	0.943	36 241.38	36 146.63	29 248.77
12	0.349	0.446	0.806	33 279.96	33 033.82	29 497.57

闽浙赣地区GPM IMERG降水产品降尺度建模与比较分析

Downscaling Modeling of the GPM IMERG Precipitation Product and Comparative Analysis in the Fujian-Zhejiang-Jiangxi Region

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