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Wind profiles from radiosondes launched over New Zealand on June 29, 2014 during the Deep Propagating Gravity Wave Experiment (DEEPWAVE; June–July 2014) showed an interesting feature of two sharp peaks in wind speed: one in the upper troposphere and the other in the lower stratosphere. Analysis showed that the lower peak at around 11.5 km was associated with the upper‐tropospheric jet. Inertia‐gravity waves (IGWs) were found over the South Island from the upper troposphere to the lower stratosphere. The IGWs perturbed the environmental winds, leading to strong and weak wind layers that were tilted in a westerly direction and extended from 10 to 16 km in the IGW zone over the South Island. As a result, the upper wind peak was observed at ~14.5 km and the weak winds immediately below at ~13 km in the IGW zone. These IGWs had vertical wavelengths of ~3 km, horizontal wavelengths of 300–400 km, periods of 9–10 h, and a phase speed of ~11 m∙s−1. Numerical experiments showed that airflow over New Zealand's Southern Alps was not the main source for these IGWs. Further analysis suggested that the source of these IGWs in the lower stratosphere was likely due to the spontaneous adjustment of airflow associated with the upper‐tropospheric jet streak. [ABSTRACT FROM AUTHOR]

Snow frequently occurs over New Zealand. The seasonal snow accumulation can be about 3 m deep in early spring at some locations. Thus, for numerical weather prediction and climate modelling over New Zealand, a reliable, sophisticated snow model that can properly describe the physical processes associated with snow cover is required. In the past, owing to a lack of snow observations, modelling and verification of snow processes was limited over New Zealand. In the present study, the multilayer snow scheme of the Joint UK Land Environment Simulator (JULES)—the land surface model used in New Zealand regional weather and climate models—was used to simulate the snow water equivalent (SWE) and snow density at two sites in the South Island of New Zealand. The model captured seasonal and interannual variability in snow accumulation and melt. However, large errors in the simulated SWE (up to 300 mm) were found during snowmelt periods and in relatively warm winters when a significant amount of liquid water was present in snow. Sensitivity tests showed that errors in the simulated long wave radiation (a negative bias of about 6 W/m2), snow albedo (0.05–0.10) and air temperature for snow occurrence (Tc, about 0.5 K) were the major factors causing large errors in the simulated SWE. In addition, the simulated snow density was lower than observed. The relatively warm and humid maritime climate of New Zealand appears to make snow simulation in New Zealand more sensitive to long wave radiation, snow albedo and Tc than for continents. [ABSTRACT FROM AUTHOR]

ABSTRACT Hourly observations of soil moisture volumetric content (at depths of 0-0.4 m) have been conducted for a few years at 55 climate stations with diverse soil types and annual rainfall in New Zealand. Thirty two of these stations also have surface meteorological observations. In this study, these observations were used for the first time to validate a land surface model ( LSM) for soil moisture simulation, the Joint UK Land Environment Simulator ( JULES). At the 32 stations, the yearly mean absolute differences ( MADs) of the simulated soil moisture volumetric ratio were about 5% or smaller, except at four South Island stations, where larger MADs of 8-12% were found. Further analysis of rainfall and soil moisture observations at these four stations showed that the observed soil moisture includes a contribution from lateral soil water flow, which is not considered in the one-dimensional version of JULES used in this study. For the remaining 28 stations, the relatively small yearly MADs (∼5%) were mainly due to biases. To understand the major factors contributing to the errors/biases, three sensitivity tests were conducted. These tests showed that errors in the soil texture data were the most likely contributor to the errors in simulated soil moisture. This study demonstrates that for a better simulation of soil moisture in New Zealand, especially in the lower South Island, a LSM needs to include lateral soil moisture/water flow, and to use more accurate prescriptions of the hydraulic and thermal properties of the soil. [ABSTRACT FROM AUTHOR]