top of page
Copy of Logistics and transportation of
white_logo_transparent_background.png

Climate Data API Documentation

Climate change data available through the Correntics Climate Data API can be directly used for physical risk assessments and climate change impact studies. We provide climate extreme indices using scientific high-resolution, multi-model, and multi-scenario datasets based on the latest CMIP6 models. The API enables data integration into existing systems and helps to create new tools to analyze or visualize climate data. This allows you to build a customized climate scenario analysis and simplifies automated reporting. 

Getting Started

Step 1: Request token

To use the Climate Data API service, please request a token through the API Request form

Step 2: Start a query

Climate data can be accessed directly via programmatic queries. Below, we provide a short example of how climate data can be accessed easily through the Correntics API.

***

Example of a query to the Correntics API

***

Import matplotlib as plt

Import pandas as pd

Import correntics

correntics.login(

             # USERNAME, PASSWORD

)

correntics.list_indices( )

# -- tx10p:Cool days

# -- tn90p:Warm nights

# -- tx90p:Warm days

# -- fd:Frost days

# -- rx5day:Max 5-day precipitation amount

# -- csdi:Cold spell duration indicator

# -- txx:Max Tmax

# ...

# ZURICH  =  47.3769° N,  8.5417° E

res  =  correntics.query_hazard(

index="tx90p",

lon=8.5417,

lat=47.3769,

scenario=["ssp126", "ssp585"],

year=range(1950, 2080, 10)

)

print(res)

#  [

#          {

#              "scenario":  "ssp126",

#                "value":  29.599689483642578,

#                "year":  "1950"

#          }

#           ...     

#  ]

plt.figure(figsize=(8,  4), dpi=80)

df = pd.DataFrame(res)

df_ssp126 = df[df.scenario == "ssp126"]

df_ssp585 = df[df.scenario == "ssp585"]

plt.plot(df_ssp126.year, df_ssp126.value, label="SSP1 - 2.6", color="173c66")

plt.plot(df_ssp585.year, df_ssp585.value, label="SSP5 - 8.5", color="951b1e")

plt.legend()

plt.xlabel("Year")

plt.ylabel("Percentage of days (%)")

plt.title("Percentage of days when TX > 90th percentile of the reference period")

plt.grid(True)

plt.show()

Climate Data API Example: Percentage of Warm Days under different climate scenarios.

Available Data

The Correntics Climate Data API consists of a broad set of climate data 

Climate
Indices

Comprehensive collection of widely used climate extreme indices

The Correntics climate indices are calculated from the latest CMIP6 climate models and are based on the definition by the Expert Team on Climate Change detection and Indices (ETCCDI). 

Temperature Indices

  • Warm Spell Duration Index (wsdi)

  • Cold Spell Duration Index (csdi)

  • Mean Diurnal Temperature Range (dtr)

  • Growing Season Length (gsl)

  • Number of Frost Days (fd)

  • Number of Icing Days (id)

  • Number of Tropical Nights (tr)

  • Number of Summer Days (su)

  • Percentage of Days when Daily Minimum Temperature is Below the 10th Percentile (tn10p - Cool nights)

  • Percentage of Days when Daily Minimum Temperature is Above the 90th Percentile (tn90p - Warm nights)

  • Percentage of Days when Daily Maximum Temperature is Below the 10th Percentile (tx10p - Cool days)

  • Percentage of Days when Daily Maximum Temperature is Above the 90th Percentile (tx90p - Warm days)

  • Annual Maximum of Daily Minimum Temperature (tnx)

  • Annual Minimum of Daily Minimum Temperature (tnn)

  • Annual Maximum of Daily Maximum Temperature (txx)

  • Annual Minimum of Daily Maximum Temperature (txn)

  • Annual Daily Maximum (tasmax)

  • Annual Daily Minimum (tasmin)

Precipitation indices
  • Annual Total Precipitation (pr)

  • Annual Maximum 1-day Precipitation (rx1day)

  • Annual Maximum Consecutive 5-day Precipitation (rx5day)

  • Maximum Number of Consecutive Days Per Year with Less Than 1 mm of Precipitation (cdd)

  • Maximum Number of Consecutive Days Per Year with At Least 1mm of Precipitation (cwd)

  • Annual Count of Days with At Least 10mm of Precipitation (r10mm)

  • Annual Count of Days with At Least 1mm of Precipitation (r1mm)

  • Annual Count of Days with At Least 20mm of Precipitation (r20mm)

  • Annual Total Precipitation when Daily Precipitation Exceeds the 99th Percentile of Wet Day Precipitation (r99p)

Climate Scenarios

Shared Socioeconomic Pathways (SSPs) scenarios used in the Sixth Assessment Report (AR6) from the Intergovernmental Panel on Climate Change (IPCC)

Scenario analysis for a given climate extreme indices
SSP1-2.6

Sustainable development within environmental boundaries. Resource efficient consumption and emphasis on human well-being  to achieve sustainable development goals. Radiative forcing of 2.6 W/m² by the end of the century.

SSP2-4.5

Social, economic, and technological trends remain almost unchanged with some countries making relatively good progress while others fall short of expectations. Environmental systems still degrade, while overall resource and energy consumption  slightly declines. Radiative forcing of 4.5 W/m² by the end of the century. 

SSP3-7.0

Slow economic growth, material-intensive consumption, investment in education, and technological development decline, and inequalities between countries persist and worsen over time. Radiative forcing of 7.0 W/m² by the end of the century.

SSP5-8.5

Rapid economic growth and social development that is coupled with the exploitation of abundant fossil fuel resources. Radiative forcing of 8.5 W/m² by the end of the century.

API Request

Please fill out the following request form to get access to the Correntics Climate Data API. 

Thanks for requesting! We will contact you.

white_logo_transparent_background.png

Correntics AG

Josefstrasse 219

8005 Zürich
info@correntics.com
+41 78 736 67 55

© 2022 by correntics.com

bottom of page