Introducing NK-ClimVault
The R&D Center of Nippon Koei Co., Ltd. has embarked on the challenge of collecting and processing vast datasets, encompassing over 60 Earth System Models (climate models). This includes conducting quality checks on model outputs and correcting biases. Our objective is to provide interactive maps, graphs, and downloadable climate projection data, focusing on long-term averages and indicators of extreme weather. To achieve this goal, we have developed NK-ClimVault, an online platform designed to serve as an initial reference for climate risk assessment and climate change adaptation projects.
Climate Information Available Online
Our website provides access to files, graphs, and maps of past and projected climate conditions under various future scenarios of greenhouse gas emissions into the atmosphere.
Maps and Graphs
Interactive maps can be found on the Atlas section of NK-ClimVault. Users are prompted to select a group of indicators, depending on their specific requirements. These indicator groups include Average Temperature, Warm Weather, Cold Weather, and Precipitation.
The maps for each indicator are globally available over land. Within the “Map Settings” panel, users can toggle between Historical and Projected Change views. Historical maps showcase the average annual values of the selected indicator spanning from 1981 to 2010, derived from the W5E5 observational dataset. Users can assess the disparity between the output of climate models and this observational dataset by clicking on the maps. This action prompts a graph displaying the observed value for that location, along with climate model variability before and after bias correction.
When selecting Projected Change, users can choose the future scenario and one of three future periods: Immediate Future, Near Future, and Far Future.
The interactive maps are generated using outputs from models participating in the 6th cycle of the Coupled Model Intercomparison Project (CMIP6). Since April 2023, users have had the option to switch between CMIP5 and CMIP6 maps by adjusting the “Dataset” option in the “Map Settings” panel. For CMIP5, future climate simulations were conducted based on four main scenarios known as Representative Concentration Pathways (RCPs; van Vuuren et al., 2011). These scenarios were labeled according to the approximate radiative forcing expected to be reached by the year 2100 (i.e., 2.6, 4.5, 6.0, and 8.5 W m-2).
source: Chen et al., 2021. Framing, Context and Methods. In Delmonte et al., (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.
The CMIP6 simulations use a new range of scenarios based on Shared Socio-Economic Pathways (SSPs; O’Neill et al., 2016). The set of SSPs recognizes that global radiative forcing levels can be achieved by different pathways of greenhouse gases, aerosols, and land use. The set of SSPs therefore establishes a matrix of global forcing levels and socio-economic storylines. There are four priority scenarios that CMIP6 participating modelling groups were asked to perform, SSP1-2.6 for sustainable pathways, SSP2-4.5 for middle-of-the-road, SSP3-70 for regional rivalry, and SSP5-8.5 for fossil fuel-rich development.
RCP scenarios or SSP scenarios are often associated with changes in Global Mean Surface Air Temperature at the end of the 21st century. The following figure illustrates as warming stripes from blue (cold) to red (warm) the multi-model average of GSAT for the past and five future SSP scenarios.
source: Chen et al., 2021. Framing, Context and Methods. In Delmonte et al., (2021). Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.
The available maps correspond to indicators commonly referenced in climate change adaptation studies. Presently, the “Average Temperature” indicator group includes Mean Annual Temperature (TG), Mean Daily Maximum Temperature (TX), Mean Daily Minimum Temperature (TN), and Diurnal Temperature Range (DTR). In future updates of NK-ClimVault, we plan to generate additional similar indicators useful for describing the long-term average state of the atmosphere. These may include Boreal Summer Mean Daily Maximum Temperature (TXJJA), Boreal Winter Mean Daily Minimum Temperature (TNDJF), and Boreal Summer Mean Specific Humidity (HUJJA).
Maps for the other three indicator groups are detailed in the table below. These indicators aid in describing and assessing extreme weather conditions. Users can access information on how each indicator is calculated, along with a visual description, by selecting the “I” button next to the indicator in the “Map Settings” panel. The available extreme weather indicators are based on daily temperature values or daily precipitation amount. Some are based on fixed thresholds that are of relevance to particular applications. In these cases, thresholds are the same for all locations. Other indices are based on thresholds that vary from location to location. In these cases, thresholds are typically defined as a percentile of the relevant data series.
Indicator codes and definitions correspond to those proposed by the discontinued Expert Team on Climate Change Detection and Indices (ETCCDI).
Downloadable Files
Currently, only CMIP5 bias-corrected data is available for free download in the Downloads section. In accordance with regulations set by climate model output distributors, all data users are required to provide their name and email address. Therefore, to access the data downloads, we request minimal personal information to create an account.
The data that can be downloaded corresponds to time series of mean, maximum, and minimum daily surface air temperature, along with daily precipitation amounts for almost 1,000 cities. These cities were selected based on a minimum population threshold of 500,000.
Users are given the flexibility to choose the Representative Concentration Pathway (RCP) scenario and the temporal scale for the requested file. Temporal scales other than daily are computed as averages or aggregations for temperature and precipitation, respectively.
The downloaded data are CSV files containing time series spanning from 2011 to 2100 for the selected meteorological variable, scenario, and temporal scale across all available climate models. Additionally, each file includes the time series from the historical reference period of 1981 to 2010 for all available climate models.
The number of available climate models varies depending on the selected scenario, with the RCP4.5 and RCP8.5 scenarios having the largest number of climate models (30 and 31, respectively).
Original CMIP5 data, original CMIP6 data, bias-corrected CMIP6 data, data for large unpopulated regions, and additional variables are available upon request only.
Requests of climate data provision
The purchase of climate information is currently only available upon request by email to admin@nk-climvault.com. The data that can be purchased falls under one of the following three categories:
- Bias-corrected meteorological variables of the CMIP5 or CMIP6 datasets.
- Climate and extreme weather indicators (listed above).
- Custom climate and extreme weather indicators.
Grid-based provision of climate data
The CSV files available for download on NK-ClimVault, as well as those obtainable upon request, contain spatially averaged data from grid cells measuring 0.5° in global latitude and longitude coordinates. The central coordinates of each grid align with those used in the observational dataset W5E5 and cannot be altered. Consequently, grids over land are accessible within latitudes of -64.75° to 84.75° and longitudes of -179.75° to 179.75°, with increments of 0.5°.
Each grid covers an area of approximately 50km × 50km for locations near the Equator. The latitudinal extension in kilometers increases for higher latitudes. Below is an example illustrating nine grids covering the coastline near Kampong Saom (Sihanoukville) city in Preah Sihanouk Province, Cambodia.
The coastlines were borrowed from OpenStreetMap and are used only for illustrative purposes.
Bias-corrected meteorological variables
The bias-corrected CMIP6 meteorological variables that are currently available are:
- Mean Daily Surface Air Temperature
- Maximum Daily Surface Air Temperature
- Minimum Daily Surface Air Temperature
- Daily Precipitation Amount
- Surface Specific Humidity
- Downward Solar Radiation
- 2m-altitude Wind Speed (simple bias-correction of long-term average only)