While there have been some recent set-backs within science and climate research and disturbing news about NOAA, there is also continuing efforts on responding to climate change. During my travels to Mozambique and Ghana, I could sense a real appreciation for knowledge, and an eagerness to learn how to calculate risks connected to climate change.
Recent events have shown incredibly high rainfall amounts that have devastated cities and countries, as well as droughts that have exacerbated the risk of wildfires. It is well known that global warming gives more extreme rainfall, and this is primarily explained as a result of warmer air being able to hold more humidity. It is, in other words, the Clapeyron-Clausius equation that describes how the water vapour pressure relates to temperature.
An additional explanation for extreme rainfall amounts is how daily rainfall is unevenly distributed over Earth’s surface area. There are now several papers documenting that the daily precipitation falls on a diminishing fraction of Earth’s surface over time, based on satellite data, reanalysis data, and global climate model simulations (Dobler et al., 2024 and references therein).
Changes in how rainfall is distributed over Africa can explain both flooding as well as droughts, and it is important to derive reliable information about the probability of heavy rainfall in order to be prepared for what the future climate will bring.
It is urgent to start climate change adaptation because of the rapid global warming (e.g. pulse.climate.copernicus.eu) and global statistics show that temperature and rainfall have already become more extreme. Also, climate change adaptation may send a message of the urgency and importance for mitigation.
In Mozambique I helped organise a CORDEX Flagship Pilot Study (FPS) workshop in Maputo where we worked on capacity building based on an open source tool for empirical-statistical downscaling. This tool is useful for studying consequences of climate change and providing valuable information for climate adaptation (Benestad et al., 2025).
The CORDEX FPS southeast Africa workshop hed in Maputo was attended by scholars from 8 of the countries in the region and the attendants completed training in downscaling an ensemble of CMIP6 simulations of total annual rainfall based on local in-situ rain gauge data.
One particular type of adaptation measures is connected to climate and health which is going on in Ghana. The annual meeting of the SPRINGS project was held near Akosombo in the Volta catchment, and one of its aims is to provide estimates of future rainfall to feed hydrological models in order to calculate the water quality and model the spread of pathogens that lead to diarrhoea outbreak.
This knowledge will be used for policy-making and intervention strategies for both water management and health planning. To get a better understanding of the local situation, we inspected a pumping station, as shown below, with water treatment and water supply to the communities.
Pump station that supplies communities with water.
The water provided by the pumping stations and the water treatment plants, however, doesn’t always cover all needs, and the alternative is to fetch water from the Vota river.
A local girl fetches water from the Volta river.
Manure and feces on the ground and in the fields spread into brooks and rivers when there is heavy rainfall, and we need robust estimates of how often we can expect days of heavy rain to assess future risks of such health problems.
We use a very simple formula to estimate how often we can expect days with heavy rainfall, and the graphics below gives an example of observed (red) and calculated (black) annual frequency of days with more than 20 mm in Maputo, Mozambique. A similar calculation for Tanzania gives a similar good match, and we expect to find a similar match for rain gauge data from Ghana once we get access to it. This calculation is only based on the annual wet-day frequency and the wet-day mean precipitation (Benestad et al., 2025).
A comparison between the observed (red) number of days per year with heavy rainfall (more than 20 mm) and simple calculations (black) based on the wet-day frequence () and wet-day mean precipitation (). It shows that the simple formula can give an approximate number of days with heavy rainfall per year (here shown as number of days divided by 365.25 days).
Both the workshop in Maputo and the SPRINGS project exploit this simplified and approximate estimation of heavy rainfall, which is a step towards extreme rainfall amounts, but nevertheless not quite sufficient for rainfall amounts in the excess of 100 mm/day.
Another important part of the SPRINGS project is the co-production of knowledge, involving a diversity of disciplines and cross-disciplinary collaborations. The connection between academia and the scientific community on the one hand, and the society on the other, is becoming increasingly important. Climate change is making the news in various ways, and challenges for Ghana involves both migration pressure and flooding.
A facimile of a random news paper showing media coverage of climate change in Ghana.
We also know that similar problems can be expected in both Europe and North America, and that climate change affect animal and human health.
Another thing that I like to emphasise is that we have the necessary knowledge about climate change based on science and data. The Earth is continuously monitored through satellites, instruments on the ground and in the air, and Earth’s climate is reproduced through extensive model simulations (If you cannot get the information from American sites, there is the Copernicus Climate Change Services; “C3S”).
We also know what is needed to stop global warming: the atmospheric concentrations of greenhouse gases such as CO2 and methane must stabilise, and the forests must be protected.
References
A. Dobler, R.E. Benestad, C. Lussana, and O. Landgren, "CMIP6 models project a shrinking precipitation area", npj Climate and Atmospheric Science, vol. 7, 2024. http://dx.doi.org/10.1038/s41612-024-00794-z
R.E. Benestad, K.M. Parding, and A. Dobler, "Downscaling the probability of heavy rainfall over the Nordic countries", Hydrology and Earth System Sciences, vol. 29, pp. 45-65, 2025. http://dx.doi.org/10.5194/hess-29-45-2025