Sensitivity of rainfall extremes to unprecedented Indian Ocean Dipole events

Strong positive Indian Ocean Dipole (pIOD) events like those in 1997 and 2019 caused significant flooding in East Africa. While future projections indicate an increase in pIOD events, limited historical data hinders a comprehensive understanding of these extremes, particularly for unprecedented events. To overcome this we utilize a large ensemble of seasonal reforecast simulations, which show that regional rainfall continues to increase with pIOD magnitude, with no apparent limit. In particular we find that extreme rain days are highly sensitive to the pIOD index and their seasonal frequency increases super‐linearly with higher pIOD magnitudes. It is vital that socio‐economic systems and infrastructure are able to handle not only the increasing frequency of events like 1997 and 2019 but also unprecedented seasons of extreme rainfall driven by as‐yet‐unseen pIOD events. Future studies should prioritize understanding the hydrological implications and population exposure to these unprecedented extremes in East Africa

The Abisko Polar Prediction School

Polar regions are experiencing rapid climate change, faster than elsewhere on Earth with consequences for the weather and sea ice. This change is opening up new possibilities for businesses such as tourism, shipping, fisheries and oil and gas extraction, but also bringing new risks to delicate polar environments. Effective weather and climate prediction is essential to managing these risks, however our ability to forecast polar environmental conditions over periods from days to decades ahead falls far behind our abilities in the mid-latitudes. In order to meet the growing societal need for young scientists trained in this area, a Polar Prediction School for early career scientists from around the world was held in April 2016

Uncertainties Associated with Quantifying Climate Change Impacts on Human Health: A Case Study for Diarrhea

Background: Climate change is expected to have large impacts on health at low latitudes where droughts and malnutrition, diarrhea, and malaria are projected to increase. Objectives: The main objective of this study was to indicate a method to assess a range of plausible health impacts of climate change while handling uncertainties in a unambiguous manner. We illustrate this method by quantifying the impacts of projected regional warming on diarrhea in this century. Methods: We combined a range of linear regression coefficients to compute projections of future climate change-induced increases in diarrhea using the results from five empirical studies and a 19-member climate model ensemble for which future greenhouse gas emissions were prescribed. Six geographical regions were analyzed. Results: The model ensemble projected temperature increases of up to 4°C over land in the tropics and subtropics by the end of this century. The associated mean projected increases of relative risk of diarrhea in the six study regions were 8–11% (with SDs of 3–5%) by 2010–2039 and 22–29% (SDs of 9–12%) by 2070–2099. Conclusions: Even our most conservative estimates indicate substantial impacts from climate change on the incidence of diarrhea. Nevertheless, our main conclusion is that large uncertainties are associated with future projections of diarrhea and climate change. We believe that these uncertainties can be attributed primarily to the sparsity of empirical climate–health data. Our results therefore highlight the need for empirical data in the cross section between climate and human health

Lagged oceanic effects on the East African short rains

The East African ‘short rains’ in October–December (OND) exhibit large interannual variability. Drought and flooding are not unusual, and long-range rainfall forecasts can guide planning and preparedness for such events. Although seasonal forecasts based on dynamical models are making inroads, statistical models based on sea surface temperature (SST) precursors are still widely used, making it important to better understand the strengths and weaknesses of such models. Here we define a simple statistical forecast model, which is used as a tool to shed light on the dynamics that link SSTs and rainfall across time and space, as well as on why such models sometimes fail. Our model is a linear regression, where the August states of El Niño-Southern Oscillation (ENSO) and the Indian Ocean Dipole (IOD) predict about 40% of the short rains variability in 1950–2020. The forecast errors are traced back to the initial SSTs: too-wet (too-dry) forecasts are linked linearly to positive (negative) initial ENSO and IOD states in August. The link to the initial IOD state is mediated by changes in the IOD between August and OND, highlighting a physical mechanism for prediction busts. We also identify asymmetry and nonlinearity: when ENSO and/or the IOD are positive in August, the range and variance of OND forecast errors are larger than when the SST indices are negative. Upfront adjustments of predictions conditional on initial SSTs would have helped in some years with large forecast busts, such as the dry 1987 season during a major El Niño, for which the model erroneously predicts copious rainfall, but it would have exacerbated the forecast in the wet 2019 season, when the IOD was strongly positive and the model predicts too-dry conditions

A ‘hurricane-like’ polar low fuelled by sensible heat flux: high-resolution numerical simulations

An unusually deep (961 hPa) hurricane-like polar low over the Barents Sea during 18–21 December 2002 is studied by a series of fine-mesh (3 km) experiments using the Weather Research and Forecasting (WRF) model. The simulated polar low was similar to hurricanes and similar previous case-studies in that it had a clear, calm and warm eye structure surrounded by moist convection organized in spiral cloud bands, and the highest surface wind speedswere found in the eye wall. The proximity to the sea ice and the high surface wind speeds (about 25ms−1) during the deepening stage triggered extremely high surface sensible and latent heat fluxes at the eye wall of about 1200 and 400 W m−2, respectively. As the polar low moved eastward and weakened, maximum surface sensible and latent heat fluxes dropped to about 600 and 300Wm−2, respectively. Two types of sensitivity experiments were designed to analyse the physical properties of the polar low. Firstly, physical processes such as condensational heating and sensible and/or latent heat fluxes were switched off–on throughout the simulation. In the second type, these processes were turned off–on after the polar low had reached its peak intensity, which minimized the deformation of the polar-low environment,making it suitable to study the direct effect of physical processes on themature vortex. The experiments suggest that the deepening stage of the polar low was dominated by baroclinic growth and that upper-level potential vorticity forcing contributed throughout its life cycle. After the deepening stage, the baroclinicity vanished and the polar low was fuelled by surface sensible heat fluxes while latent heat fluxes played a minor role. Condensational heating was not essential for the energetics of the polar low. Surprisingly, in experiments where condensational heating was turned off throughout the simulation, the polar low intensified

Downscaling an intense precipitation event in complex terrain: the importance of high grid resolution

Floods due to intense rainfall are a major hazard to both people and infrastructure in western Norway. Here steep orography enhances precipitation and the complex terrain channels the runoff into narrow valleys and small rivers. In this study we investigate a major rainfall and flooding event in October 2014. We compare high-resolution numerical simulations with measurements from rain gauges deployed in the impacted region. Our study has two objectives: (i) to understand the dynamical processes that drove the high rainfall and (ii) the importance of high grid resolution to resolve intense rainfall in complex terrain. This is of great interest for numerical weather prediction and hydrological modelling. Our approach is to dynamically downscale the ERA-Interim reanalysis with the Weather Research and Forecasting model (WRF). We find that WRF gives a substantially better representation of precipitation both in terms of absolute values as well as spatial and temporal distributions than a coarse resolution reanalysis. The largest improvement between the WRF simulations is found when we decrease the horizontal model grid spacing from 9 km to 3 km. Only minor additional improvements are obtained when downscaling further to 1 km. We believe that this is mainly related to the orography in the study area and its representation in the model. Realistic representations of gravity waves and the seeder–feeder effect seem to play crucial roles in reproducing the precipitation distribution correctly. An analysis of associated wavelengths shows the importance of the shortest resolvable length scales. On these scales our simulations also show differences in accumulated precipitation of up to 300 mm over four days, further emphasising the need for resolving short wavelengths. Therefore, our results clearly demonstrate the need for high-resolution dynamical downscaling for extreme weather impact studies in regions with complex terrain

Marine cold-air outbreaks in the North Atlantic: temporal distribution and associations with large-scale atmospheric circulation

The spatial and temporal distributions of marine cold air outbreaks (MCAOs) over the northern North Atlantic have been investigated using re-analysis data for the period from 1958 to 2007. MCAOs are large-scale outbreaks of cold air over a relatively warm ocean surface. Such conditions are known to increase the severity of particular types of hazardous mesoscale weather phenomena. We used a simple index for identifying MCAOs: the vertical potential temperature gradient between the sea surface and 700 hPa. It was found that atmospheric temperature variability is considerably more important than the sea surface temperature variability in governing both the seasonal and the inter-annual variability of MCAOs. Furthermore, a composite analysis revealed that a few well-defined and robust synoptic patterns are evident during MCAOs in winter. Over the Labrador and Irminger Seas the MCAO index was found to have a correlation of 0.70 with the North Atlantic Oscillation index, while over the Barents Sea a negative correlation of 0.42 was found