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[netcdf] ERA-Interim土壤数据读取问题。

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新浪微博达人勋

发表于 2020-2-5 09:11:07 | 显示全部楼层 |阅读模式

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我目前在处理使用ERA5的土壤水分数据。该数据共有四层土壤,但是我在读取NC数据的时候发现有swvl1_0001 swvl2_0001 swvl3_0001 swvl4_0001
swvl1_0005 swvl2_0005 swvl3_0005 swvl4_0005
前面的参数代表土壤层数,但是我始终没找到0001和0005代表什么,如果说是分辨率的话,他们都是0.25度的。



所以我的问题是该数据集的0001和0005分别代表什么?我查资料暂时没找到说明,谢谢各位老师回复。
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 楼主| 发表于 2020-2-5 10:48:31 | 显示全部楼层
自问自答。已经搞清楚了这个问题。
因为我下载数据的时候包含了2019年12月份的数据,而这个月份的再分析数据还没出来,只有近实时数据,因此在下载NC数据的时候,就包含了0001 和 0005这两个类型的数据。具体0001 和 0005代表什么。大家可以看下面的网站内容。我贴一下,大家可以参考
ERA5 CDS requests which return a mixture of ERA5 and ERA5T data (such as for November 2019)
转至元数据结尾
由 Michela Giusti创建于一月 31, 2020 转至元数据起始
The ERA5 hourly and monthly data are made available with a 3 month delay. This means that after a month has passed, another month's worth of ERA5 data is written to the dataset.

ERA5T (near real time) data are used to fill the gap between the end of the ERA5 data and 5 days before the present date. The oldest month of these is overwritten each month as new ERA5 data become available.

So currently (January 2020):

ERA5 data are currently from 1979 - 31/10/19.
ERA5T data are from 1/11/19- 26/1/20 (5 day delay)

However for data from 00 UTC to 06 on 1/11/19, accumulated variables (fluxes, precipitation) come from ERA5 (which has 'experiment version' 0001), while instantaneous variables (e.g temperature) come from ERA5T (which has 'experiment version' 0005).
This is because the accumulated variables are derived from the forecast fields of ERA5.

For November 2019, data is separated in the following way:

00-06 UTC on 1/11/19 from ERA5 (expver 0001)
07-23 UTC on 1/11/19 and 2-30/11/19 from ERA5T (expver 0005)
When these data are converted to netCDF a single time coordinate is used which covers the period 1-30/11/19 (720 hourly timesteps).
Both expver versions use the full time extent of time coordinate but the expver 0001 data only covers the first 7 timesteps, the remaining 713 timesteps are 'padded' with empty fields.
For the expver 0005 data, the first 7 timesteps are padded with empty fields, with the remaining timesteps coming from the ERA5T data.

By combing the valid data from each variable, the full ERA5/5T data coverage will be obtained for the entire time range (all of November 2019 in this case).

When the November 2019 ERA5 data are released in February 2020, they will overwrite the ERA5T data for November and for accumulated variables for 00-06 in 1/12/19.

This process will be repeated each month as new ERA5 data are released, overwriting the existing ERA5T data.

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