In Northeast Brazil (NEB), severe droughts have high socioeconomic impacts. In this study, the spatial–temporal characteristics of drought were evaluated based on a new drought index at 4‐km spatial resolution, derived from regional empirical relationships between a remote sensing‐based index and rain‐gauge‐based standardized precipitation index (SPI), a well‐known drought meteorological index. This index was used to compare the spatial pattern of severe drought events (1982–1983, 1992–1993, 1997–1998, and 2012–2013) of the last 30 years. Strong El Niño related droughts were found to be generally spatially limited, affecting around 30% of NEB and concentrated in the northern part of the region, while 2012 drought, which was not El Niño related, was widespread, reaching 46% of NEB. These results stressed the importance of analyzing droughts at the subregion scale using data with higher spatial resolution. Statistically significant trends (p < 0.05) toward drier conditions detected in the SPI time‐series were linked to the tropical Atlantic Ocean warming trend, which result in an increased drought risk and social vulnerability in the region.

Across the UK, water abstracted from ground, surface, and tidal stores is regulated through a system of licenses to protect both the sources and the environment. Similar permits are required for discharging wastewater to rivers or onto the ground. These abstractions and discharges can have a significant impact on UK Rivers, but measurements are not readily available, which discourages their use in hydrological models of river flows. However, these very unique data sets provide a means to improve the performance of spatially distributed hydrological models, particularly during periods when abstraction regulations change and at ungauged river locations. To demonstrate this, point source abstraction and discharge measurements across England have been transformed into 1 × 1 km resolution gridded data and used with an enhanced formulation of the Grid‐to‐Grid (G2G) hydrological model where these processes are mathematically represented. A comparison of G2G‐simulated and gauged river flows for 605 catchments across England between 1999 and 2014 indicates that model simulation of river flows is generally improved at gauged locations downstream of abstraction/discharge sites. The main improvement is in the simulation of low flows, for which the median performance is improved by 10.7%, however, the impact on simulation of high river flows is more modest (1.5% improvement). These results demonstrate the potential gains available to the international hydrological and land‐surface modeling community from using records of actual water use (where available) in models, in place of more widely used national statistics.

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

Extreme polar vortex events known as sudden stratospheric warmings can influence surface winter weather conditions, but their timing is difficult to predict. Here, we examine factors that influence their occurrence, with a focus on their timing and vertical extent. We consider the roles of the troposphere and equatorial stratosphere separately, using a split vortex event in January 2009 as the primary case study. This event cannot be reproduced by constraining wind and temperatures in the troposphere alone, even when the equatorial lower stratosphere is in the correct phase of the quasi biennial oscillation. When the flow in the equatorial upper stratosphere is also constrained, the timing and spatial evolution of the vortex event is captured remarkably well. This highlights an influence from this region previously unrecognised by the seasonal forecast community. We suggest that better representation of the flow in this region is likely to improve predictability of extreme polar vortex events and hence their associated impacts at the surface.

Early warning of weather-related hazards enables farmers, policy makers and aid agencies to mitigate their exposure to risk. We present a new operational framework, Tropical Applications of Meteorology using SATellite data and ground based measurements-AgricuLtural EaRly warning sysTem (TAMSAT-ALERT), which aims to provide early warning for meteorological risk to agriculture. TAMSAT-ALERT combines information on land-surface properties, seasonal forecasts and historical weather to quantitatively assess the likelihood of adverse weather-related outcomes, such as low yield. This article describes the modular TAMSAT-ALERT framework and demonstrates its application to risk assessment for low maize yield in northern Ghana (Tamale). The modular design of TAMSAT-ALERT enables it to accommodate any impact or land-surface model driven with meteorological data. The implementation described here uses the well-established General Large Area Model (GLAM) for annual crops to provide probabilistic assessments of the meteorological hazard for maize yield in northern Ghana (Tamale) throughout the growing season. The results show that climatic risk to yield is poorly constrained in the beginning of the season, but as the season progresses, the uncertainty is rapidly reduced. Based on the assessment for the period 2002–2011, we show that TAMSAT-ALERT can estimate the meteorological risk on maize yield 6 to 8 weeks in advance of harvest. The TAMSAT-ALERT methodology implicitly weights forecast and observational inputs according to their relevance to the metric being assessed. A secondary application of TAMSAT-ALERT is thus an evaluation of the usefulness of meteorological forecast products for impact assessment. Here, we show that in northern Ghana (Tamale), the tercile seasonal forecasts of seasonal cumulative rainfall and mean temperature, which are routinely issued to farmers, are of limited value because regional and seasonal temperature and rainfall are poorly correlated with yield. This finding speaks to the pressing need for meteorological forecast products that are tailored for individual user applications.

The influence of the Semi‐Annual Oscillation (SAO) on the timing and evolution of major sudden stratospheric warmings (SSWs) is examined using the 2008/2009 SSW as the primary case‐study. When the zonal winds in both the troposphere and the SAO region of the equatorial upper stratosphere/lower mesosphere are relaxed towards reanalysis fields in the UK Met Office Unified Model, a remarkably accurate representation of the January 2009 SSW is achieved. The accurate timing of the SSW is determined by the SAO zonal wind relaxation. The westerly‐to‐easterly phase transition of the SAO in the lower mesosphere (0.1–0.5 hPa) is found to be a key factor for this influence. It defines an initial conical‐shaped vortex that determines the upward propagation of wave activity and subsequent evolution of wave mean‐flow interaction. Internal transient wave reflection in the subtropics and associated wave‐induced acceleration of the mean‐flow is found to be an important component, strengthening the vortex and thus delaying the onset of the SSW. The sensitivity of SSW timing to the equatorial westerly winds in the lower mesosphere is further explored in the context of all major SSWs during the 1979–2018 period. The timing of SSWs is found to be significantly correlated with the timing of the equinoctial westerly‐to‐easterly phase transition at 0.3 hPa in early winter (r = 0.79). This relationship is discussed in the context of the more widely recognised influence of the quasi‐biennial oscillation (QBO). These results suggest that accurate simulation of the timing of SAO phase transitions, as well as knowledge of the QBO phase, is likely to provide additional and extended Northern Hemisphere wintertime seasonal forecast skill.