In a series of 10-day campaigns in Ontario and Quebec, Canada, between 2005 and 2007, ozonesondes were launched twice daily in conjunction with continuous high-resolution wind-profiling radar measurements. Windprofilers can measure rapid changes in the height of the tropopause, and in some cases follow stratospheric intrusions. Observed stratospheric intrusions were studied with the aid of a Lagrangian particle dispersion model and the Canadian operational weather forecast system. Definite stratosphere-troposphere transport (STT) events occurred approximately every 2–3 days during the spring and summer campaigns, whereas during autumn and winter, the frequency was reduced to every 4–5 days. Although most events reached the lower troposphere, only three events appear to have significantly contributed to ozone amounts in the surface boundary layer. Detailed calculations find that STT, while highly variable, is responsible for an average, over the seven campaigns, of 3.1% of boundary layer ozone (1.2 ppb), but 13% (5.4 ppb) in the lower troposphere and 34% (22 ppb) in the middle and upper troposphere, where these layers are defined as 0–1 km, 1–3 km, and 3–8 km respectively. Estimates based on counting laminae in ozonesonde profiles, with judicious choices of ozone and relative humidity thresholds, compare moderately well, on average, with these values. The lamina detection algorithm is then applied to a large dataset from four summer ozonesonde campaigns at 18 North American sites between 2006 and 2011. The results show some site-to-site and year-to-year variability, but stratospheric ozone contributions average 4.6% (boundary layer), 15% (lower troposphere) and 26% (middle/upper troposphere). Calculations were also performed based on the TOST global 3D trajectory-mapped ozone data product. Maps of STT in the same three layers of the troposphere suggest that the STT ozone flux is greater over the North American continent than Europe, and much greater in winter and spring than in summer or fall. When averaged over all seasons, magnitudes over North America show similar ratios between levels to the previous calculations, but are overall 3–4 times smaller. This may be because of limitations (trajectory length and vertical resolution) to the current TOST-based calculation.

Effectively forecasting and communicating flood hazards at national or continental scales is critical to reducing impacts of flooding. Yet, it remains a challenge due to the predominance of ungauged catchments in often complex and steep terrain. We present the development, communication, and evaluation of a national flood awareness system, the Aotearoa (New Zealand) Flood Awareness System, AFAS. Forecasts are produced with an uncalibrated, semi‐distributed hydrological model, driven by a high‐resolution convective‐scale atmospheric model with statistical perturbations in rainfall, soil moisture and baseflow to generate a 50‐member ensemble. We implement a relative flow and flood exceedance threshold framework to evaluate hourly forecasts across six categories from below normal to extremely high. Forecast performance is categorically assessed against observations, for a 2.5‐year reforecast, at 272 sites nationwide, up to 48 h ahead. Overall, AFAS produces skilful streamflow forecasts in catchments with complex topography, even with operational delays ingesting observations. We explore a novel approach to river forecast communication using daily videos. We suggest rethinking large‐scale streamflow forecast communication by balancing a depth with breadth approach (pointwise absolute flows versus distributed relative flows), to raise collective awareness before and during natural disasters. AFAS appears to be the first system producing public‐friendly videos to communicate streamflow forecasts in their topographical context. Future development of AFAS will benefit from a federated approach across national and regional agencies, including sharing of real‐time weather observations, forecasting tools and expertise.

[1] A hidden seasonal switching model for daily rainfall over a region is proposed where season onset times are stochastic and can vary from year to year. The model allows seasons to occur earlier or later than expected and have varying lengths. This stochastic seasonal variation accommodates considerably more of the observed intraannual rainfall variability than can be represented using seasonal models with standard fixed seasons. In essence, the model dynamically classifies daily rainfall time series into seasons whose onsets vary from year to year and within which the model parameters are assumed to be time homogeneous. A variety of nonseasonal models could have been used to describe daily rainfall within seasons. Here a generalization of the Richardson model is adopted which has rainfall states (dry, light rain, and heavy rain) some of which are hidden or unobserved. It is further assumed that the rainfall states generate rainfall that is independent of season (seasonally invariant), so it is only the dynamics of the rainfall states that vary from season to season. A suitable estimation strategy based on maximum likelihood and the EM algorithm is developed for fitting the model across a region. This strategy is validated on simulated data. Various forms of the model are fitted to daily rainfall measurements from 12 sites in southern New Zealand. These results are discussed and compared to those from fitting standard fixed season models.

New Zealand's National Institute of Water and Atmospheric Research publishes climate normals for New Zealand that are used for reporting the regional state of the climate, climate extremes and variability. Temperature and precipitation patterns are affected by both anthropogenic climate change and natural climate variability which in turn affect the climatological normal values calculated every decade. This study investigates how New Zealand's normals for temperature and precipitation have shifted over time at the national, regional and seasonal scales from the 1941–1970 period to the 1991–2020 period. Contrary to WMO recommendations, but aligned with many other countries, New Zealand's climate normals have traditionally not undergone homogenisation. The impact of introducing some homogenisation in the latest 1991–2020 normals, in contrast to historical non‐homogenized station normals, has been assessed using a new homogenized “Seventeen‐Station” temperature series from 1941 to 2020. We demonstrate that interpolating sparse non‐homogenized normals spatially to a grid can produce significant erroneous patterns and therefore undermine the accuracy of the conclusions drawn when using such normals. We find that the historical non‐homogenized temperature normals have a consistent negative bias in the long‐term trend at national, regional and seasonal scales. Our analysis of homogeneity tested precipitation showed consistent decreases at a national scale across all normal periods relative to the 1951–1980 precipitation normal. We also highlight how fixed period temperature and precipitation normals do not fully reflect the current state of a climate that is influenced by decadal variability and global warming. To derive normals fit for use in a changing climate it is suggested that automated methods for broad data homogenisation be developed along with alternative methods to derive normals that account for a non‐stationary climate.

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.