recent/climate and future/climate make the world's recent climate data and IPCC future climate projections accessible for analysis at weather station, basin and country scale, using a simple dashboard interface that highlights key uncertainties and provides outputs that help understand recent and future climate trends
recent/climate uses data from the global historical climatology network (GHCN) daily and monthly datasets. The Global Historical Climatology Network Daily (GHCN-Daily) dataset includes over 130,000 stations in >180 countries. ~66,000 current stations report precipitation data. More than 25,000 current stations provide temperature data. Temperature records date back to the 1800s, with many stations having over 100 years of data. Precipitation data span a similar period, supporting detailed climate analysis and modelling. Other climate variables are included where available. The data are raw, with quality control flags applied for each record.
The Global Historical Climatology Network Monthly (GHCN-Monthly) dataset contains monthly mean temperature for ~26,000 stations and precipitation summaries for more than 120,000 stations report monthly precipitation totals, including over 33,000 current observing sites. Temperature records extend from the early 1700s to the present, and precipitation from the 1800s. The data are available in raw, quality controlled only or fully homogenized versions, making them a key resource for climate monitoring and historical analysis.
recent/climate helps visualize and explore these global weather station data. It supports climate research, education, and policy by making these data available for station and country level trend analysis. Users can analyse historical trends, understand data quality and gaps, examine weather extremes, and apply insights relevant to many fields, including agriculture and water management. A range of outputs from the tool are shown below.
School lesson inserts for using recent/climate are available at edustation
Distribution of daily temperature stations in UK (bubble size and colour proportional to length of record()
Temperature anomalies for UK Rothamsted station, with trend line (from daily data)
Precipitation anomalies for Rothamsted, UK (from daily data)
Seasonality of precipitation for Rothamsted, UK with years on x-axis and months of the year on y-axis (from daily data)
Missing data and data gaps for Tajikistan daily rainfall data. Yellow=>350 days of data , dark blue=<100 days of data. White=no data. Years on x-axis, stations on y-axis
Daily temperature anomalies for Kurgan Tyube station, Tajikistan, 2024
Climate stripes visualisation for daily maximum temperature, aggregate for all stations in Tajikistan
UK maximum temperature, number of stations poer year with >350 days of data
recent/mclimate helps visualize and explore the GHCN monthly data in three forms:
QCU – Unadjusted Observations: Raw station-reported monthly temperature data with minimal quality control. Suitable for those needing original data values.
QCF – Quality-Controlled Observations: Includes the same data as QCU, but with failed or suspect values removed via QC checks. Recommended for general observational analysis.
QFE – Homogenised Data: Bias-adjusted using the Pairwise Homogenisation Algorithm.
Typically covers the 1961–1990 reference period. Best for climate trend analysis.
Unadjusted raw observations: temperature change Rothamsted 1870-2024. +0.63 °C per century
Quality-controlled Observations: Rothamsted 1870-2024. +0.84 °C per century
Homogenised data: Rothamsted 1960-2010. +3.1 °C per century
future/climate explores global climate futures at country and basin level in a dashboard-based interface. It supports understanding and analysis of national and watershed-level IPCC CMIP6 climate projections from multiple GCMs. Differences between scenarios and geographies can be explored alongside model uncertainties. The data can be explored alongside national level poverty data.
School lesson inserts for using future/climate are available at edustation
Rainfall change to 2030s SSP370, by country
Rainfall change to 2030s SSP370, by basin
Rainfall change to 2030s SSP370, by watershed of dam
Rainfall change to 2030s SSP370 (x-axis) ranked countries (y-axis) with poverty headcount (bubble colour) and population (bubble size)
Rainfall change to 2030s for Tajikistan by scenario: SSP126, SSP245, SSP370, SSP585
Rainfall change to 2030s SSP370 for Tajikistan (black line) relation to neighbouring countries,
Rainfall change to 2030s SSP370 for Tajikistan: mean of all GCMs (black line), individual GCMs (other lines)