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多时间尺度、多分辨率、多PET计算方式的 日/周/月干旱指标SPEI计算代码及测试文件
共22个文件
txt:10个
csv:4个
py:3个
需积分: 0 8 下载量 74 浏览量
2024-09-15
12:01:23
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SPEI是最常用的干旱指标,考虑了降雨和潜在蒸散发的水平衡状况,并通过不同时间尺度上累积水平衡状况反映不同时间长度的干旱情况,具体来说3个月尺度的SPEI反映农业、土壤干旱,6个月尺度的SPEI反映水文干旱。 在现有能搜到的SPEI计算代码中,R库SPEI包可以计算月分辨率的SPEI,python库的Climate_indices包也是计算月分辨率的SPEI,没有公开的代码计算日分辨率的SPEI。考虑计算日分辨率的SPEI是因为,月分辨率的SPEI不能捕捉持续仅几周的短期干旱事件,不能精确捕捉草地生产力变化情况。一些文章提到了构建日分辨率的SPEI指标的方法,如Wang et al.,2015 (https://doi.org/10.1002/joc.4244), 李军(https://doi.org/10.5194/hess-25-1587-2021),但没有公开具体的计算代码,本文主要目的是介绍如何计算日分辨率的SPEI,帮助广大计算日分辨率SPEI指标。 得到SPEI后,通常可以分析一个地区的干湿趋势,同时也可以基于游程理论提取干旱事件。
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SPEI_code_share.zip (22个子文件)
SPEI_code_share
test_data
input
prec.txt 122KB
Tmin.txt 138KB
Tmax.txt 137KB
Pres.txt 149KB
Tmean.txt 137KB
Wind.txt 122KB
RH.txt 136KB
SSD.txt 126KB
output
PET.txt 122KB
SPEI_daily.csv 426KB
SPEI_compare2.jpg 52KB
SPEI_compare.jpg 122KB
SPEI_compare_PET_method.jpg 47KB
SPEI_monthly.csv 14KB
Rn.txt 127KB
SPEI_8day.csv 54KB
SPEI_daily_HG.csv 427KB
utilsPY.py 48KB
test_run_cal_spei _share.py 6KB
draw_spei.py 3KB
__pycache__
test_run_cal_spei _share.cpython-39.pyc 3KB
utilsPY.cpython-39.pyc 28KB
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