The global spread of invasive plant pathogens is increasing, putting natural forests and ecosystem services under threat. Spatial data can quantify range non‐overlap between invasive pathogens and their hosts to identify existing and potentially restorable refugia to enable ‘escape’ from the pathogen. In 2017, myrtle rustAustropuccinia psidiiwas detected in New Zealand. New Zealand has 27 native woody and liana species in the plant family susceptible to the disease (Myrtaceae), many of which are ecosystem dominants and economically important. Spatial methods were used to compare the current New Zealand distribution of myrtle rust with the modelled distributions of its potential native hosts. To guide management and set priorities for conservation of at‐risk species, areas of potential refugia where a Myrtaceae species is predicted to occur outside the pathogen range were identified under two myrtle rust distribution scenarios. Myrtle rust will thrive in New Zealand's warmer regions. Many native Myrtaceae are distributed within this area, but several species occur extensively outside the core range of the disease. Species distributed in cooler southern regions will be best placed to persist in refugia. Myrtaceae species with specific habitat requirements and narrow geographical ranges in warmer (northern) areas are likely to require ex situ or active in situ management. Even widely distributed species will benefit from the restoration of suitable habitat that supports multiple species outside the myrtle rust range. Synthesis and applications. Spatial data can be used to identify refugia and restoration opportunities, and thus inform landscape‐level management responses to invasive pathogens. This approach can guide decisions over where to implement in situ (e.g. fungicide spraying) versus ex situ (e.g. seed banking, botanic gardens) management efforts.

In this study, the resilience of large cities and their built infrastructure in New Zealand to extreme winds, is investigated by coupling the outputs of a very high-resolution, 333-m resolution, numerical weather prediction (NWP) model with computational fluid dynamics (CFD) simulations. Following an extreme wind event on 18 September 2020 in Auckland, in which two trucks travelling over the Auckland Harbour bridge tipped over and damaged the bridge structure, a CFD simulation of airflow over the bridge using the Reynolds-averaged Navier–Stokes (RANS) method and NWP wind speed forecasts as the inlet profile is conducted. The 333 m NWP forecasts were validated against four nearby observation sites, showing generally high correlations of greater than 0.8 and low mean bias ($\pm 3$ m s⁻¹) and RMSE ($<3$ m s⁻¹) values. The CFD-based estimates of the mean wind speed-up over the bridge showed that the mean wind speed could increase by a factor of 1.15–1.20 in the vicinity of the road where the toppled vehicles were travelling. Additionally, NWP forecasts and CFD estimates of wind gusts at the maximum bridge height, within the area not affected by the bridge structure, agreed well with a value of about 25 m s⁻¹. An anemometer mounted at the top of the bridge arch measured a higher gust wind speed of about 35 m s⁻¹ that could have been influenced by the gust speed-up resulting from the flow separation from the bridge arch, which is demonstrated in the CFD results. The results demonstrate the importance of understanding localised wind speed-up effects and distinguishing them from the approaching undisturbed airflow.

This paper describes how a combination of high-resolution numerical modeling, a robust homogenization algorithm, and local pressure observations have been used to understand and reconcile time series of daily, seasonal, and annual peak wind gusts recorded at observing sites in the Cook Strait region of New Zealand. The homogenization algorithm consists of corrections for the relocation of masts, changes in instrumentations, data acquisition and signal processing, surrounding surface roughness, and measurement heights. In addition, a statistical method, penalized maximal F test (PMFT), was used to assess the homogeneity of the wind speed time series and detect and eliminate all remaining, undocumented, artificial (i.e., nonclimatic) breakpoints. A three-dimensional time-dependent computational fluid dynamics (CFD) simulation was carried out using the Gerris model to characterize the turbulence environment at the mast sites and to estimate topographic speedup effects. Trends in magnitudes and frequencies of the homogenized seasonal and annual peak wind gusts are evaluated and presented for the Cook Strait region. The pressure gradients between pairs of stations were used to study the correlation between the gust wind speeds and the pressure field. A high-resolution convection-resolving numerical weather prediction model [the New Zealand Convective-Scale Model (NZCSM)] was employed to aid the interpretation of results and analyze wind trends. The trend in gust speeds is also shown to be consistent with larger-scale NCEP–NCAR reanalysis pressure trends. The homogenization algorithm showed promising results in eliminating the artificial breakpoints and trends. Overall, strong correlations were found between the homogenized gust speeds, the pressure field across the region, and NZCSM predictions.

Despite significant advances in distributed renewable energy systems (DRES), the technology still faces several substantial challenges that prevent the large-scale adoption of these systems into a country’s energy sector. The intermittency of renewables, uncertainties associated with real-time multi-horizon weather and load forecasts, and lack of comprehensive control systems are among the main technical and regulatory challenges for the real-world adoption of DRES. This paper outlines the current state of knowledge in the real-world operation of DRES and also describes pathways and methodologies that enable and facilitate the uptake of DRES in a country’s energy sector.

In the southwest Pacific, a meandering jet‐stream in the upper troposphere is sometimes found at ~30° S during austral winters and is usually treated as a sub‐tropical jet (STJ) due to its low latitude. For two contrasting cases, we have conducted analyses from two perspectives to identify the STJ and PFJ: first, using previously published qualitative criteria to identify jet‐cores and second, investigating the jet‐stream axes of STJ and PFJ identified using 2‐PVU curves. The results showed that the chosen meandering jet‐stream case at ~30° S was a merged, and for a time, a superposed STJ and PFJ. Downstream of the jet‐streak, the PFJ split to the south and the STJ to the east. This is in significant contrast to the horizontally well‐separated jet‐stream case chosen in this study. Some processes likely contributing to the superposition of the STJ and PFJ were analyzed and discussed. The movement of PFJ that was closely associated with the movement of the low over the Tasman Sea and the convection in and near the tropical region may have played dominant roles.