https://github.com/bluegreen-labs/daymetpy

A python script to download Daymet data
https://github.com/bluegreen-labs/daymetpy

climate-data data-retrieval daymet ornl-daac python

Last synced: about 1 month ago
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A python script to download Daymet data

• Host: GitHub
• URL: https://github.com/bluegreen-labs/daymetpy
• Owner: bluegreen-labs
• License: other
• Created: 2016-03-08T17:07:29.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2019-10-07T03:41:40.000Z (about 5 years ago)
• Last Synced: 2024-08-09T23:23:42.922Z (5 months ago)
• Topics: climate-data, data-retrieval, daymet, ornl-daac, python
• Language: Python
• Homepage: http://bluegreen-labs.github.io/daymetpy
• Size: 325 KB
• Stars: 20
• Watchers: 2
• Forks: 10
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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## daymetpy: A python library for accessing Daymet surface weather data

 

daymetpy attempts to fill the need for easy, integrated access to gridded daily Daymet weather data. The data are hosted by the Oak Ridge National Laboratories DAAC and accessed from [their web service](https://daymet.ornl.gov/web_services.html).

## Installation

Install the package using [pip](https://en.wikipedia.org/wiki/Pip_(package_manager)) and the following command:

```python

pip install daymetpy

```

## Use

Example code to calculate the temperature difference between Denver and Miami is given below. This gives an idea of code functionality and use. A worked example in an ipython notebook format can be found in the 'example' subdirectory.

```python

import sys

import daymetpy

import pandas as pd

import seaborn as sns

import matplotlib.pyplot as plt

denver_loc = (-104.9903, 39.7392)

miami_loc = (-80.2089, 25.7753)

denver = daymetpy.daymet_timeseries(lon=denver_loc[0], lat=denver_loc[1], start_year=2012, end_year=2014)

miami = daymetpy.daymet_timeseries(lon=miami_loc[0], lat=miami_loc[1], start_year=2012, end_year=2014)

fig, ax1 = plt.subplots(1, figsize=(18, 10))

rolling3day = denver.rolling(15).mean()

ax1.fill_between(rolling3day.index, rolling3day.tmin, rolling3day.tmax, 

                 alpha=0.4, lw=0, label='Denver', color=sns.xkcd_palette(['faded green'])[0])

ax1.set_title('Denver vs Miami temps (15 day mean)', fontsize=20)

rolling3day = miami.rolling(15).mean()

ax1.fill_between(rolling3day.index, rolling3day.tmin, rolling3day.tmax, 

                 alpha=0.4, lw=0, label='Miami', color=sns.xkcd_palette(['dusty purple'])[0])

ax1.set_ylabel(u'Temp. (°C)', fontsize=20)

fig.tight_layout()

plt.legend(fontsize=20)

```

## Requirements

Pandas / seaborn are required.

## Contributors

* Koen Hufkens: [email protected]

* Colin Talbert