Abstract. A regional atmospheric inversion method has been developed to determine the spatial and temporal distribution of CO 2 sinks and sources across New Zealand for 2011-2013. This approach infers net air-sea and air-land CO 2 fluxes from measurement records, using back-trajectory simulations from the Numerical Atmospheric dispersion Modelling Environment (NAME) Lagrangian dispersion model, driven by meteorology from the New Zealand Limited Area Model (NZLAM) weather prediction model. The inversion uses in situ measurements from two fixed sites, Baring Head on the southern tip of New Zealand's North Island (41.408 • S, 174.871 • E) and Lauder from the central South Island (45.038 • S, 169.684 • E), and ship board data from monthly cruises between Japan, New Zealand, and Australia. A range of scenarios is used to assess the sensitivity of the inversion method to underlying assumptions and to ensure robustness of the results. The results indicate a strong seasonal cycle in terrestrial land fluxes from the South Island of New Zealand, especially in western regions covered by indigenous forest, suggesting higher photosynthetic and respiratory activity than is evident in the current a priori land process model. On the annual scale, the terrestrial biosphere in New Zealand is estimated to be a net CO 2 sink, removing 98 (±37) Tg CO 2 yr −1 from the atmosphere on average during 2011-2013. This sink is much larger than the reported 27 Tg CO 2 yr −1 from the national inventory for the same time period. The difference can be partially reconciled when factors related to forest and agricultural management and exports, fossil fuel emission estimates, hydrologic fluxes, and soil carbon change are considered, but some differences are likely to remain. Baseline uncertainty, model transport uncertainty, and limited sensitivity to the northern half of the North Island are the main contributors to flux uncertainty.
Wind data at time scales from 10 min to 1 h are an important input for modeling the performance of wind farms and their impact on many countries’ national electricity systems. Planners need long-term realistic (i.e., meteorologically spatially and temporally consistent) wind-farm data for projects studying how best to integrate wind power into the national electricity grid. In New Zealand, wind data recorded at wind farms are confidential for commercial reasons, however, and publicly available wind data records are for sites that are often not representative of or are distant from wind farms. In general, too, the public sites are at much lower terrain elevations than hilltop wind farms and have anemometers located at 10 m above the ground, which is much lower than turbine hub height. In addition, when available, the mast records from wind-farm sites are only for a short period. In this paper, the authors describe a novel and practical method to create a multiyear 10-min synthetic wind speed time series for 15 wind-farm sites throughout the country for the New Zealand Electricity Commission. The Electricity Commission (known as the Electricity Authority since 1 October 2010) is the agency that has regulatory oversight of the electricity industry and that provides advice to central government. The dataset was constructed in such a way as to preserve meteorological realism both spatially and temporally and also to respect the commercial secrecy of the wind data provided by power-generation companies.
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.
Strong southerly winds regularly occur in the Cook Strait region of New Zealand. Occasionally, these winds are strong enough to cause severe damage to property and threaten human life. One example of a storm containing such winds is the “Wellington Storm,” which occurred on 20 June 2013. For this case, wind speeds in Cook Strait were stronger than those observed or forecast elsewhere in the storm. Even though wind speeds of this intensity are rare, storms affecting New Zealand with central pressures equal to the Wellington Storm (~976 hPa) are not uncommon. Numerical experiments have been carried out to investigate the possible reasons for the exceptional damaging southerly winds (DSWs) occurring in this storm. Analyses of the simulations showed that DSWs in Cook Strait for this event were actually barrier jets, not gap winds as they appeared. The strength of barrier jets in Cook Strait is sensitive to the precise location of the storm center. This explains the uncommon occurrence of DSWs in Cook Strait. Numerical experiments that used scaled (either increased or decreased) New Zealand orography showed that the barrier jets became shallower and weaker when the mountain top heights were lower. This decrease in barrier jet strength with mountain height is largely consistent with the results from linear-scale analyses in previous publications. This result implies that numerical simulations using a lower topography than actual (usually the case in current operational NWP) may lead to errors in timing and in forecasting the strength of the damaging winds associated with barrier jets.
<p>Atmospheric observations of CO<sub>2</sub> and other greenhouse gases have been widely used to constrain estimates of terrestrial and oceanic CO<sub>2 </sub>fluxes through atmospheric inverse modelling. Yet, applying these methods at national scale to verify and improve the National Inventory Report (NIR) and support the Paris agreement remains at the frontier of CO<sub>2</sub> science.</p><p>We use inverse modelling to estimate New Zealand&#8217;s carbon uptake and emissions using atmospheric measurements and model. This effort is part of a five year CarbonWatch-NZ research programme, which aims to develop a complete top-down picture of New Zealand's carbon balance using national inverse modelling and targeted studies of New Zealand&#8217;s forest, grassland and urban environments. In addition to quantifying New Zealand&#8217;s carbon emissions on a national scale, we also focus on identifying the prevailing processes driving CO<sub>2</sub> changes in New Zealand to support climate mitigation.</p><p>In an initial study based on the inversion system used in CarbonWatch-NZ, a significantly stronger (30-60 %) sink was found relative to the NIR (Steinkamp et al., 2017), suggesting a strong CO<sub>2</sub> uptake in Fiordland, a region covered by indigenous temperate rainforest in New Zealand's South Island. Here, we present new results of CarbonWatch-NZ by expanding the studied time period from 2011-2013 to 2020, expanding our atmospheric observing network from two (Baring Head, 41.41&#176;S, 174.87&#176;E and Lauder, 38.33&#176;S, 176.38&#176;E) to a total of eleven in situ greenhouse gas measurement sites and improving our atmospheric model resolution by roughly a factor of ten (NAME model, 1.5 km).</p><p>Our new results suggest that the strong sink observed in 2011-2013 did not diminish, but for recent years we have found an even stronger sink than for before. Additional measurements collected in the Fiordland region (i.e., mixing ratios, CO<sub>2</sub> isotopes, carbonyl sulphide) also suggest a stronger CO<sub>2</sub> uptake, supporting our inversion results. Both the measurements and inversion results show that the CO<sub>2 </sub>uptake does not seem to shut down completely during winter time, suggesting that there might be something about this ecosystem that we do not yet understand. This winter uptake signal is also present in independent data collected in and around New Zealand as part of the ATom campaigns (Atmospheric Tomography Mission). Implementing observations from an additional site in the North Island (Maunga Kakaramea, 45.034&#176;S, 169.68&#176;E) has increased the strength of the sink, pointing to additional strong sink region at the top of the North Island.</p><p>&#160;</p><p>References</p><p>Kay Steinkamp, Sara E. Mikaloff Fletcher, Gordon Brailsford, Dan Smale, Stuart Moore, Elizabeth D. Keller, W. Troy Baisden, Hitoshi Mukai and Britton B. Stephens, Atmospheric CO2 observations and models suggest strong carbon uptake by forests in New Zealand, Atmospheric Chemistry and Physics, 2017.</p>
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