同一卫星产品(NO2_OMI_TEMIS) -地球科学堆栈交换的较高值范围江南电子竞技平台江南体育网页版 最近30个来自www.hoelymoley.com 2023 - 04 - 16 - t14:36:46z //www.hoelymoley.com/feeds/question/9108 https://creativecommons.org/licenses/by-sa/4.0/rdf //www.hoelymoley.com/q/9108 4 相同卫星产品的较高值范围(NO2_OMI_TEMIS) 汉Zhengzu //www.hoelymoley.com/users/5214 2016 - 11 - 14 - t16:31:02z 2017 - 01 - 16 t05:40:48z

我正在处理对流层的NO2柱密度,我的数据源是TEMIS

NO2 level3数据可以从OMI仪器的原始信息中得到。

我下载了两类数据,。Grd 。Kml 为同月。

我下载的数据上传这里12

KML data

我在谷歌Earth中打开它,图如下:

enter image description here

可以看到NO2 trop的数据范围。列为0~20,与网站上的模板图相同。

GRD data

我没有找到关于这个数据的详细信息。其中-999为no_data place。

我使用python读取并绘制空间分布。

filename = './CH2O-NO2/no2_201306.grd' def read_grd(filename): ncols = np.array(linecache.getline(filename, 1)[6:10]).astype(float) nrows = np.array(linecache.getline(filename, 2)[6:10]).astype(float) xllcorner = np.array(linecache.getline(filename, 3)[10:14]).astype(float) yllcorner = np.array(linecache.getline(filename, 4)[10:14]).astype(float) cellsize = np.array(linecache.getline(filename, 5)[9:14]).astype(float) nan_value = np.array(linecache.getline(filename, 6)[13:17]).astype(float) longitude = xllcorner + cellsize * np.arange(ncols) latitude = yllcorner + cellsize * np.arange(nrows) value = np.loadtxt(filename, skiprows=7) value = value[::-1] return value, longitude, latitude, nan_value no2,lon_no2, lat_no2, nan_value = read_grd(filename) no2[no2 == nan_value] = np.nan def isnt_NaN(num): return num == num no2[isnt_NaN(no2)].max() > 9999.0 

It seems that the high value in grd format data are out of the regular condition which can be learned from previous resarch (Hot spots of NO2 column are about 15~20 10^15 molec/cm2).

Does anyone familiar with the OMI-NO2 data? I don't know how to deal with the irregular value which are way too higher than realistic.

enter image description here

//www.hoelymoley.com/questions/9108/the-higher-value-range-for-the-same-satellite-product-no2-omi-temis/9115#9115 2 相同卫星产品(NO2_OMI_TEMIS)的较高值范围 f.thorpe //www.hoelymoley.com/users/543 2016 - 11 - 16 - t03:07:06z 2017 - 01 - 16 t05:40:48z

似乎您担心数据中的值超过kml文件中显示的颜色条上的最大值。我不担心这个。您使用的是月平均“3级”产品,根据定义,这是高度质量控制的产品。对于全球大多数地区,典型的数值将在1 x 10^14和5 x 10^15摩尔/平方厘米之间变化。超过20 x 10^15 molec/cm2的值只出现在高度污染的地区。OMI NO2产品中非常大的值是现实的,特别是在东南亚,那里获得了最大的NO2柱。我有时甚至看到值超过1 x 10^17。当信号变大时,检索的可信度就会提高。实际上,应该谨慎对待的是较低的值(例如小于8 x 10^14 mol /cm2),因为任何低于这个值的值都可能是“噪音”。为了显示全球范围内值的方差(可以跨越4个数量级),选择的颜色刻度效果很好。 Note that the color bar is a logarithmic scale, which helps give definition to the plots in the regions with typical values. You could rewrite the kml file though, and pick a different max value, if you are interested in better plots of southeast Asia.

If you are interested in learning more about the product, I highly suggest you see Boersma (2011) and also refer to the user manual.

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