NASA provides an extensive library of data points that they’ve captured over the years from their satellites. These datasets include temperature, precipitation and more. NASA hosts this data on a website where you can search and grab information as needed, whether you want the data for the whole world or a specific area. The user can choose a certain range of dates, look for aggregate time frames (hours, days, months etc.). The possibilities are limitless.

NASA提供了一个广泛的数据点库，这些数据点是他们多年来从卫星中捕获的。 这些数据集包括温度，降水量等。 NASA将这些数据托管在一个网站上，您可以根据需要搜索和获取信息，无论您是要使用整个世界还是特定区域的数据。 用户可以选择某个日期范围，查找合计的时间范围(小时，天，月等)。 可能性是无限的。

In this article, let’s explore this huge resource and I’ll describe a step-by-step process to collect data from the website.

在本文中，让我们探索这个巨大的资源，我将描述一个分步过程，以从网站收集数据。

通用光盘 (GES DISC)

GES DISC stands for NASA Goddard Earth Sciences (GES) Data and Information Services Center (DISC). It is a data repository that hosts remote sensing data about precipitation, hydrology, atmosphere and more. It was designed to enable researchers and application developers to get access to NASA data, which they can then use to do analysis and create applications.

GES DISC代表NASA戈达德地球科学(GES)数据和信息服务中心(DISC) 。 它是一个数据库，托管有关降水，水文，大气等的遥感数据。 它旨在使研究人员和应用程序开发人员能够访问NASA数据，然后他们可以将其用于分析和创建应用程序。

数据采集 (DATA COLLECTION)

Let’s walk through the steps for retrieving data from GES DISC. In this particular article, I’ll walk through the steps for downloading precipitation data and for that, I’ll download the GPM monthly data. GPM stands for Global Precipitation Measurement, a joint venture between JAXA and NASA to capture precipitation data across the globe.

让我们逐步介绍从GES DISC检索数据的步骤。 在这篇特别的文章中，我将逐步介绍下载降水量数据的步骤，为此，我将下载GPM月度数据。 GPM代表“全球降水量测量” ，这是JAXA和NASA之间的合资企业，用于捕获全球的降水量数据。

1.登录 (1. Login)

The data repository is located here. Before you download data, you need to create an account on the earthdata website. Simply create an account on this website, verify yourself and you should be good to go.

数据存储库位于此处 。 在下载数据之前，您需要在Earthdata网站上创建一个帐户。 只需在此网站上创建一个帐户，验证自己，就可以了。

Select the Login button on the top right. If you have an account, log in else select the Register button to get registered.

选择右上角的登录按钮。 如果您有帐户，请登录，否则选择“ 注册”按钮进行注册。

2.搜索 (2. Search)

Once we are logged in, we can get started. The website greets you with a search box with Data Collections selected by default. We are looking for data in this collection itself, so we will let it be and start typing in the search box.

登录后，即可开始。 该网站会在搜索框中向您打招呼，默认情况下会选中“ 数据收集” 。 我们正在此集合中寻找数据，因此我们将其保留下来并开始在搜索框中输入内容。

Here, I’ll type precipitation in the search box and press the yellow search button to get the available datasets. You’ll notice a loading icon indicating that the system is processing our search query and will return a list of datasets that match the search query.

在这里，我将在搜索框中键入降水 ，然后按黄色搜索按钮以获取可用的数据集。 您会注意到一个加载图标，指示系统正在处理我们的搜索查询，并将返回与搜索查询匹配的数据集列表。

3.探索数据集列表 (3. Explore the list of datasets)

Once the search completes, you will see a table of various datasets that match the query and a filters section on the left. The table includes information such as image, dataset name, sources, spatial radius, start of data collection date and end of data collection date. Based on your specific requirements, you can use the filters on the left and select conditions that help you get the most precise data.

搜索完成后，您将在左侧看到包含与查询匹配的各种数据集的表格。 该表包含诸如图像，数据集名称，来源，空间半径，数据收集日期的开始和数据收集日期的结束之类的信息。 根据您的特定要求，您可以使用左侧的过滤器并选择条件以帮助您获得最精确的数据。

In this example, I’m looking for GPM monthly data. So, in the filters, under Project, I selected GPM. This filtered the datasets that belong to GPM. From the Time Res. column, I looked for the dataset which had 1 month resolution. This means that data is aggregated on a monthly basis.

在此示例中，我正在寻找GPM每月数据。 因此，在过滤器的Project下，我选择了GPM。 这过滤了属于GPM的数据集。 从时间资源。 列，我查找了具有1个月分辨率的数据集。 这意味着数据是每月汇总的。

From the list, it’s the third dataset called GPM IMERG Final Precipitation L3 1 month 0.1 degree x 0.1 degree V06 (GPM_3IMERGM 06). To explore more about this dataset, I simply click on its name (which is a hyperlink) and it takes me to the dataset page.

从列表中，它是第三个数据集，称为GPM IMERG最终降水L3 1个月0.1度x 0.1度V06(GPM_3IMERGM 06) 。 要探索有关此数据集的更多信息，我只需单击其名称(这是一个超链接)，便会带我到数据集页面。

4.浏览数据集页面 (4. Explore the dataset page)

The page has detailed information about the dataset along with an image. This is followed by the summary of the dataset (referred to as Product). The most essential parts are the buttons we see on the right side of the screen. You can explore the various services and more but we are interested in the link Subset / Get Data. This is the step where we get started with downloading the data. Click on this link.

该页面具有有关数据集的详细信息以及图像。 接下来是数据集的摘要(称为Product )。 最重要的部分是我们在屏幕右侧看到的按钮。 您可以探索各种服务以及更多服务，但是我们对链接Subset / Get Data感兴趣。 这是我们开始下载数据的步骤。 点击此链接。

5.选择数据 (5. Select data)

On clicking the link, a popup shows up as seen in the image below.

单击链接后，将弹出一个弹出窗口，如下图所示。

The dataset we get is pretty huge because it captures information for the whole globe across several years. A good idea is to select a certain range of dates that you’re looking for and certain area of the globe.

我们获得的数据集非常庞大，因为它可以捕获几年来全球的信息。 一个好主意是选择您要查找的特定日期范围和全球特定区域。

In the example here, I’ll capture all the original files, which means all the variables they have. I’ll refine the range from January 1, 2001 to December 31, 2020. Lastly, based on your selection above, you might see certain options for the Output format. As I am selecting original files, I only see HDF5.

在这里的示例中，我将捕获所有原始文件，这意味着它们具有所有变量。 我将细化2001年1月1日至2020年12月31日的范围。最后，根据上面的选择，您可能会看到Output格式的某些选项。 在选择原始文件时，我只会看到HDF5。

I’ve worked with HDF5 file format and there is a very simple package h5py which enables you to read these files directly into python. But to just view these files, a popular software, HDFView is often used.

我使用的是HDF5文件格式，有一个非常简单的软件包h5py ，使您可以将这些文件直接读入python。 但是，为了仅查看这些文件，通常使用HDFView 。

Next, press the button Get Data and it’ll start running to generate a number of links that will allow you to download the data.

接下来，按下获取数据按钮，它将开始运行以生成许多链接，这些链接使您可以下载数据。

6.下载资料 (6. Download data)

The popup shows a list of links, each corresponding to one data file based on the selection. There are two ways to download data from here.

弹出窗口显示一个链接列表，每个链接都基于选择对应一个数据文件。 有两种从此处下载数据的方法。

6.1一次单个文件 (6.1 Single file at a time)

Click on the link of the data file you want to download. If you’re logged in, the dataset will start downloading. It is fast, simple and requires no extra steps for downloading data.

单击要下载的数据文件的链接。 如果您已登录，则数据集将开始下载。 它快速，简单，不需要额外的步骤来下载数据。

6.2一次多个文件 (6.2 Multiple files at once)

However, if you are downloading multiple files (say 30–40 files), this is not the most efficient way. Using curl, you can download all the files using just one single command.

但是，如果要下载多个文件(例如30–40个文件)，则这不是最有效的方法。 使用curl ，您只需一个命令即可下载所有文件。

curl is a command line tool for transferring data using various network protocols.

curl是用于使用各种网络协议传输数据的命令行工具。

However, to use curl to download these data files, we need to perform some steps for the first time. The complete instructions vary by operating system and are available here.

但是，要使用curl下载这些数据文件，我们需要第一次执行一些步骤。 完整的说明因操作系统而异，可在此处获得 。

Here’s a general overview of the steps in the most easy way to understand terms (as followed on MacOS):

以下是最容易理解术语的步骤的一般概述(在MacOS上如下)：

Get all links

获取所有链接

Above the list of links, you’ll see a link called Download links list. When you click on it, a new tab opens up with all the links in one place. Select and copy all the text and save it to a file called url.txt on your machine.

在链接列表上方，您会看到一个名为下载链接列表的链接 。 当您单击它时，将打开一个新选项卡，其中所有链接都放在一个位置。 选择并复制所有文本，然后将其保存到计算机上的url.txt文件中。

Create required files

创建所需的文件

In the terminal, perform the following:

在终端中，执行以下操作：

• Go to your home using cd ~

  使用cd ~回家

• Create a new file .netrc using touch .netrc and another file for keeping track of session during multiple curl calls using touch .urs_cookies

  使用touch .netrc创建一个新文件.netrc，并使用touch .urs_cookies创建另一个文件以在多次卷曲调用期间跟踪会话

• We will now save the login credentials inside this file. Type the command echo “machine urs.earthdata.nasa.gov login <uid> password <password>” >> .netrc while replacing <uid> with your username and <password> with your password

  现在，我们将登录凭据保存在该文件中。 键入命令echo “machine urs.earthdata.nasa.gov login <uid> password <password>” >> .netrc同时用用户名替换<uid>和用密码替换<password>

• Change its access permissions using chmod 0600 .netrc

  使用chmod 0600 .netrc更改其访问权限

• Type the command cat url.txt | tr -d ‘\r’ | xargs -n 1 curl -LJO -n -c ~/.urs_cookies -b ~/.urs_cookies in the terminal where your file url.txt is located and all files will be downloaded one after the other.

  键入命令cat url.txt | tr -d '\r' | xargs -n 1 curl -LJO -n -c ~/.urs_cookies -b ~/.urs_cookies cat url.txt | tr -d '\r' | xargs -n 1 curl -LJO -n -c ~/.urs_cookies -b ~/.urs_cookies cat url.txt | tr -d '\r' | xargs -n 1 curl -LJO -n -c ~/.urs_cookies -b ~/.urs_cookies ，位于文件url.txt所在的终端中，所有文件将一个接一个地下载。

wget is also another option but I haven’t used it as curl performs well and I didn’t feel the need to try wget.

wget也是另一种选择，但是我没有使用它，因为curl表现良好，而且我不认为需要尝试wget。

7.查看数据 (7. View data)

Once the HDF5 files are downloaded, you can use HDFView to open these files and look at the dataset. You will need an account to download this software.

下载HDF5文件后，您可以使用HDFView打开这些文件并查看数据集。 您将需要一个帐户来下载该软件。

The data can be downloaded in other formats as well such as netCDF, ASCII etc. and there are ways to work with these files too but I haven’t worked with them personally.

数据可以以其他格式下载，例如netCDF，ASCII等。并且也可以使用这些文件，但是我个人还没有使用它们。

And we’re all set!!

而且我们都准备好了！！

结论 (Conclusion)

You now have a set of data files containing resourceful data collected by NASA over the years, which you can use for your own work. In an upcoming article, I will describe the steps to read a HDF5 file in Python and understand its components to use the data.

现在，您将拥有一组数据文件，其中包含NASA多年来收集的资源丰富的数据，您可以将其用于自己的工作。 在下一篇文章中，我将描述在Python中读取HDF5文件并了解其使用数据的组件的步骤。

Hope this was insightful. If you have any questions, ideas or suggestions, please mention them in the comments.

希望这是有见地的。 如果您有任何问题，想法或建议，请在评论中提及。