Evaluation and spatial downscaling of CRU TS precipitation data in the Philippines

被引:12
|
作者
Salvacion A.R. [1 ,6 ]
Magcale-Macandog D.B. [2 ]
Cruz P.C.S. [3 ]
Saludes R.B. [4 ]
Pangga I.B. [5 ]
Cumagun C.J.R. [5 ]
机构
[1] Department of Community and Environmental Resource Planning, College of Human Ecology, University of the Philippines Los Baños, College, 4031, Laguna
[2] Institute of Biological Sciences, College of Arts and Sciences, University of the Philippines Los Baños, College, 4031, Laguna
[3] Institute of Crop Science, College of Agriculture and Food Science, University of the Philippines Los Baños, College, 4031, Laguna
[4] Agrometeorology and Farm Structures Division, College of Engineering and Agro-Industrial Technology, Institute of Agricultural Engineering, University of the Philippines Los Baños, College, 4031, Laguna
[5] Institute of Weed Science, Entomology and Plant Pathology, College of Agriculture and Food Science, University of the Philippines Los Baños, College, 4031, Laguna
[6] School of Environmental Science and Management, University of the Philippines Los Baños, College, 4031, Laguna
关键词
CRU TS; Delta downscaling; Philippines; Precipitation;
D O I
10.1007/s40808-018-0477-2
中图分类号
学科分类号
摘要
This study evaluated and downscaled (using Delta Method) Climate Research Unit time series (CRU TS) monthly precipitation gridded data in the Philippines. Based on the results, raw CRU TS data tends to underestimate (average percent bias = 0.89%) precipitation for most months of the year while downscaled CRU TS showed the opposite (average percent bias = − 2.99%). Overall both raw and downscaled CRU showed acceptable performance when compared with the observed monthly precipitation record. However, downscaled CRU TS data showed better accuracy (lower Mean Absolute Error and Root Mean Squared Error) and better performance (higher Nash–Sutcliffe Efficiency) compared with the raw CRU TS data. On the average, the computed evaluation statistics for downscaled CRU TS data were 79.87 (MAE), 144.56 (RMSE), and 0.43 (NSE) while 87.82 (MAE), 163.69 (RMSE), and 0.30 (NSE) for raw CRU TS. © 2018, Springer International Publishing AG, part of Springer Nature.
引用
收藏
页码:891 / 898
页数:7
相关论文
共 50 条
  • [21] Review on spatial downscaling of satellite derived precipitation estimates
    Kofidou, Maria
    Stathopoulos, Stavros
    Gemitzi, Alexandra
    ENVIRONMENTAL EARTH SCIENCES, 2023, 82 (18)
  • [22] Spatial and Temporal Downscaling of TRMM Precipitation with Novel Algorithms
    Zhang, Huihui
    Loaiciga, Hugo A.
    Ha, Da
    Du, Qingyun
    JOURNAL OF HYDROMETEOROLOGY, 2020, 21 (06) : 1259 - 1278
  • [23] Spatial downscaling of precipitation using adaptable random forests
    He, Xiaogang
    Chaney, Nathaniel W.
    Schleiss, Marc
    Sheffield, Justin
    Water Resources Research, 2016, 52 (10): : 8217 - 8237
  • [24] Spatial downscaling of TRMM-based precipitation data using vegetative response in Xinjiang, China
    Zhang, Qiang
    Shi, Peijun
    Singh, Vijay P.
    Fan, Keke
    Huang, Jiajun
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2017, 37 (10) : 3895 - 3909
  • [25] Spatial downscaling of TRMM precipitation data based on the orographical effect and meteorological conditions in a mountainous area
    Fang, Jian
    Du, Juan
    Xu, Wei
    Shi, Peijun
    Li, Man
    Ming, Xiaodong
    ADVANCES IN WATER RESOURCES, 2013, 61 : 42 - 50
  • [26] Spatial downscaling of European climate data
    Moreno, Adam
    Hasenauer, Hubert
    INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2016, 36 (03) : 1444 - 1458
  • [27] Precipitation downscaling in climate modelling using a spatial dependence function
    Sen, Zekai
    INTERNATIONAL JOURNAL OF GLOBAL WARMING, 2009, 1 (1-3) : 29 - 42
  • [28] Spatial Downscaling of Satellite Precipitation Data in Humid Tropics Using a Site-Specific Seasonal Coefficient
    Mahmud, Mohd Rizaludin
    Hashim, Mazlan
    Matsuyama, Hiroshi
    Numata, Shinya
    Hosaka, Tetsuro
    WATER, 2018, 10 (04)
  • [29] Statistical Downscaling in the Tropics Can Be Sensitive to Reanalysis Choice: A Case Study for Precipitation in the Philippines
    Manzanas, R.
    Brands, S.
    San-Martin, D.
    Lucero, A.
    Limbo, C.
    Gutierrez, J. M.
    JOURNAL OF CLIMATE, 2015, 28 (10) : 4171 - 4184
  • [30] Evaluation of statistical downscaling in short range precipitation forecasting
    Fernandez-Ferrero, A.
    Saenz, J.
    Ibarra-Berastegi, G.
    Fernandez, J.
    ATMOSPHERIC RESEARCH, 2009, 94 (03) : 448 - 461