scholarly journals New Zealand weather extremes and climate-related events; a model-based assessment

2021 ◽  
Author(s):  
◽  
Ben Nistor
Keyword(s):  
New Zealand ◽  
Climate Models ◽  
Extreme Event ◽  
Austral Summer ◽  
Rainfall Threshold ◽  
Natural Variability ◽  
Weather Extremes ◽  
Detection And Attribution ◽  
Weather And Climate ◽  
Anthropogenic Forcings

<p>Extreme weather and climate-related events can have pronounced environmental, economic and societal impacts, yet large natural variability within Earth’s constantly evolving climate system challenges the understanding of how these phenomena are changing. Increasingly powerful climate models have made it possible to study how certain factors, including anthropogenic forcings, have modified the likelihood and magnitude of extreme events.  This study examines climate observations, reanalysis fields and model output to assess how weather extremes and climate-related events have changed. Part 1 investigates the detection and attribution of surface climate changes in relation to ozone depletion. Part 2 uses probabilistic event attribution and storyline frameworks to evaluate the role of anthropogenic forcings in altering the risk of extreme 1-day rainfall (RX1D) events for Christchurch, New Zealand in light of an unprecedented rainfall event that occurred in March 2014.  Extremely large simulations of possible weather generated by the weather@home Australia-New Zealand (w@h ANZ) model found ozone forcings induced significant changes globally (< 3 hPa) in simulations of mean sea level pressure for 2013. A clear seasonal response was detected in the Southern Hemisphere (SH) circulation that was consistent with prior studies. Ozone-induced changes to average monthly rainfall were not significant in New Zealand with large natural variability and the limitation of one-year simulations challenging attribution to this climate forcing.  In Christchurch, model and observational data give evidence of human activity increasing the likelihood and magnitude (+17%) of RX1D events despite significant drying trends for mean total rainfall (-66%) in austral summer. For events similar to that observed during March 2014, the fraction of attributable risk (FAR) is estimated to be 27.4%. This result was robust across different spatial averaging areas though is sensitive to the rainfall threshold examined. Unique meteorological conditions in combination with anomalously high sea surface temperatures (SSTs) in the tropical South Pacific were likely important to the occurrence of this extreme event. These results demonstrate how human influence can be detected in present-day weather and climate events.</p>

scholarly journals New Zealand weather extremes and climate-related events; a model-based assessment

2021 ◽  
Author(s):  
◽  
Ben Nistor
Keyword(s):  
New Zealand ◽  
Climate Models ◽  
Extreme Event ◽  
Austral Summer ◽  
Rainfall Threshold ◽  
Natural Variability ◽  
Weather Extremes ◽  
Detection And Attribution ◽  
Weather And Climate ◽  
Anthropogenic Forcings

<p>Extreme weather and climate-related events can have pronounced environmental, economic and societal impacts, yet large natural variability within Earth’s constantly evolving climate system challenges the understanding of how these phenomena are changing. Increasingly powerful climate models have made it possible to study how certain factors, including anthropogenic forcings, have modified the likelihood and magnitude of extreme events.  This study examines climate observations, reanalysis fields and model output to assess how weather extremes and climate-related events have changed. Part 1 investigates the detection and attribution of surface climate changes in relation to ozone depletion. Part 2 uses probabilistic event attribution and storyline frameworks to evaluate the role of anthropogenic forcings in altering the risk of extreme 1-day rainfall (RX1D) events for Christchurch, New Zealand in light of an unprecedented rainfall event that occurred in March 2014.  Extremely large simulations of possible weather generated by the weather@home Australia-New Zealand (w@h ANZ) model found ozone forcings induced significant changes globally (< 3 hPa) in simulations of mean sea level pressure for 2013. A clear seasonal response was detected in the Southern Hemisphere (SH) circulation that was consistent with prior studies. Ozone-induced changes to average monthly rainfall were not significant in New Zealand with large natural variability and the limitation of one-year simulations challenging attribution to this climate forcing.  In Christchurch, model and observational data give evidence of human activity increasing the likelihood and magnitude (+17%) of RX1D events despite significant drying trends for mean total rainfall (-66%) in austral summer. For events similar to that observed during March 2014, the fraction of attributable risk (FAR) is estimated to be 27.4%. This result was robust across different spatial averaging areas though is sensitive to the rainfall threshold examined. Unique meteorological conditions in combination with anomalously high sea surface temperatures (SSTs) in the tropical South Pacific were likely important to the occurrence of this extreme event. These results demonstrate how human influence can be detected in present-day weather and climate events.</p>

An Initialized Attribution Method for Extreme Events on Subseasonal to Seasonal Time-Scales

2020 ◽  
pp. 1-53
Author(s):  
Guomin Wang ◽  
Pandora Hope ◽  
Eun-Pa Lim ◽  
Harry H Hendon ◽  
Julie M Arblaster
Keyword(s):  
Extreme Events ◽  
Extreme Event ◽  
Global Climate ◽  
Climate Extreme ◽  
Weather Extremes ◽  
Climate Services ◽  
Weather And Climate ◽  
Heat Event ◽  
Climate Events ◽  
Historical Levels

AbstractWhen record-breaking climate and weather extremes occur, decision-makers and planners want to know whether they are random natural events with historical levels of re-occurrence or are reflective of an altered frequency or intensity as a result of climate change. This paper describes a method to attribute extreme weather and climate events to observed increases in atmospheric CO2 using an initialized sub-seasonal to seasonal coupled global climate prediction system. Application of this method provides quantitative estimates of the contribution arising from increases in the level of atmospheric CO2 to individual weather and climate extreme events. Using a coupled sub-seasonal to seasonal forecast system differs from other methods because it has the merit of being initialized with the observed conditions and subsequently reproducing the observed events and their mechanisms. This can aid understanding when the reforecasts with and without enhanced CO2 are compared and communicated to a general audience. Atmosphere-ocean interactions are accounted for. To illustrate the method, we attribute the record Australian heat event of October 2015. We find that about half of the October 2015 Australia-wide temperature anomaly is due to the increase in atmospheric CO2 since 1960. This method has the potential to provide attribution statements for forecast events within an outlook period, i.e. before they occur. This will allow for informed messaging to be available as required when an extreme event occurs, which is of particular use to weather and climate services.

scholarly journals The Effect of Local Circulation Variability on the Detection and Attribution of New Zealand Temperature Trends

2009 ◽  
Vol 22 (23) ◽  
pp. 6217-6229 ◽  
Author(s):  
S. M. Dean ◽  
P. A. Stott
Keyword(s):  
New Zealand ◽  
Climate Models ◽  
Strong Relationship ◽  
Internal Variability ◽  
Meridional Flow ◽  
Temperature Record ◽  
Local Circulation ◽  
Detection And Attribution ◽  
Temperature Trends ◽  
Model Control

Abstract A representative temperature record for New Zealand based on station data from 1853 onward is used in conjunction with four coupled climate models to investigate the causes of recent warming over this small midlatitude country. The observed variability over interannual and decadal time scales is simulated well by the models. The variability of simulated 50-yr trends is consistent with the very short observational record. For a simple detection analysis it is not possible to separate the observed 30- and 50-yr temperature trends from the distribution created by internal variability in the model control simulations. A pressure index that is representative of meridional flow (M1) is used to show that the models fail to simulate an observed trend to more southerly flows in the region. The strong relationship between interannual temperature variability and the M1 index in both the observations and the models is used to remove the influence of this circulation variability from the temperature records. Recent 50-yr trends in the residual temperature record cannot be explained by natural climate variations, but they are consistent with the combined climate response to anthropogenic greenhouse gas emissions, ozone depletion, and sulfate aerosols, demonstrating a significant human influence on New Zealand warming. This result highlights the effect of circulation variability on regional detection and attribution analyses. Such variability can either mask or accelerate human-induced warming in observed trends, underscoring the importance of determining the underlying forced trend, and the need to adequately capture regional circulation effects in climate models.

Using large ensembles to investigate the impacts of climate extremes

2020 ◽  
Author(s):  
Nathalie Schaller
Keyword(s):  
Extreme Events ◽  
Climate Models ◽  
Extreme Event ◽  
Climate Extremes ◽  
Heavy Precipitation ◽  
Ensemble Member ◽  
Human Influence ◽  
Weather Extremes ◽  
Large Ensembles ◽  
Thames River

&lt;p&gt;Large ensembles are key to investigate climate and weather extremes and their impacts, as they, by definition, rarely occur. One field that relies heavily on them is probabilistic event attribution, i.e. where one tries to quantify how human influence affects the probability of occurrence of the extreme event in question. An ensemble of over 130&amp;#8217;000 members allowed us to quantify that human influence increased the probability of heavy precipitation by around 40% in the January 2014 floods in southern England. By using a hydrological model, we could then quantify that the probability of 30-day peak river flows of the Thames river was increased by around 20%. However, it was unclear whether the number of properties at risk in the catchment was affected. This study also showed how uncertainty increases at each step of the modelling chain and how some factors, like the characteristics of the Thames catchment in this case, might play a bigger role in assessing impacts than potentially the size of the ensemble.&lt;/p&gt;&lt;p&gt;Large ensembles are also useful to understand the physical mechanisms behind extreme events. In another study about the relationship between atmospheric blocking and heatwaves, we used three large ensembles from different climate models. While we found that the 2003 European heatwave and blocking conditions were well contained within the 3 ensembles&amp;#8217; envelope, and that the models simulated even more extreme events, the 2010 Russian event was outside the ensembles&amp;#8217; envelope, except for one single ensemble member.&lt;/p&gt;&lt;p&gt;Finally, I will present two projects, one on floods in Norway and one about the health impacts of having a heatwave combined with high air pollution, where large ensembles would be useful, but are competing with the need for high spatial resolution for computational resources.&lt;/p&gt;

A new ensemble-based statistical methodology to verify changes in weather and climate models

2021 ◽  
Author(s):  
Christian Zeman ◽  
Christoph Schär
Keyword(s):  
Climate Models ◽  
Climate Model ◽  
Numerical Models ◽  
Hypothesis Test ◽  
Model Development ◽  
Atmospheric Model ◽  
Statistical Hypothesis ◽  
Model Parameters ◽  
Rounding Errors ◽  
Weather And Climate

&lt;p&gt;Since their first operational application in the 1950s, atmospheric numerical models have become essential tools in weather and climate prediction. As such, they are a constant subject to changes, thanks to advances in computer systems, numerical methods, and the ever increasing knowledge about the atmosphere of Earth. Many of the changes in today's models relate to seemingly unsuspicious modifications, associated with minor code rearrangements, changes in hardware infrastructure, or software upgrades. Such changes are meant to preserve the model formulation, yet the verification of such changes is challenged by the chaotic nature of our atmosphere - any small change, even rounding errors, can have a big impact on individual simulations. Overall this represents a serious challenge to a consistent model development and maintenance framework.&lt;/p&gt;&lt;p&gt;Here we propose a new methodology for quantifying and verifying the impacts of minor atmospheric model changes, or its underlying hardware/software system, by using ensemble simulations in combination with a statistical hypothesis test. The methodology can assess effects of model changes on almost any output variable over time, and can also be used with different hypothesis tests.&lt;/p&gt;&lt;p&gt;We present first applications of the methodology with the regional weather and climate model COSMO. The changes considered include a major system upgrade of the supercomputer used, the change from double to single precision floating-point representation, changes in the update frequency of the lateral boundary conditions, and tiny changes to selected model parameters. While providing very robust results, the methodology also shows a large sensitivity to more significant model changes, making it a good candidate for an automated tool to guarantee model consistency in the development cycle.&lt;/p&gt;

scholarly journals Changes in the width of the tropical belt due to simple radiative forcing changes in the GeoMIP simulations

2016 ◽  
Vol 16 (15) ◽  
pp. 10083-10095 ◽  
Author(s):  
Nicholas A. Davis ◽  
Dian J. Seidel ◽  
Thomas Birner ◽  
Sean M. Davis ◽  
Simone Tilmes
Keyword(s):  
Carbon Dioxide ◽  
Radiative Forcing ◽  
General Circulation ◽  
Climate Models ◽  
Temperature Response ◽  
Austral Summer ◽  
Hadley Cell ◽  
Solar Constant ◽  
Cell Width ◽  
Climate Forcings

Abstract. Model simulations of future climates predict a poleward expansion of subtropical arid climates at the edges of Earth's tropical belt, which would have significant environmental and societal impacts. This expansion may be related to the poleward shift of the Hadley cell edges, where subsidence stabilizes the atmosphere and suppresses precipitation. Understanding the primary drivers of tropical expansion is hampered by the myriad forcing agents in most model projections of future climate. While many previous studies have examined the response of idealized models to simplified climate forcings and the response of comprehensive climate models to more complex climate forcings, few have examined how comprehensive climate models respond to simplified climate forcings. To shed light on robust processes associated with tropical expansion, here we examine how the tropical belt width, as measured by the Hadley cell edges, responds to simplified forcings in the Geoengineering Model Intercomparison Project (GeoMIP). The tropical belt expands in response to a quadrupling of atmospheric carbon dioxide concentrations and contracts in response to a reduction in the solar constant, with a range of a factor of 3 in the response among nine models. Models with more surface warming and an overall stronger temperature response to quadrupled carbon dioxide exhibit greater tropical expansion, a robust result in spite of inter-model differences in the mean Hadley cell width, parameterizations, and numerical schemes. Under a scenario where the solar constant is reduced to offset an instantaneous quadrupling of carbon dioxide, the Hadley cells remain at their preindustrial width, despite the residual stratospheric cooling associated with elevated carbon dioxide levels. Quadrupled carbon dioxide produces greater tropical belt expansion in the Southern Hemisphere than in the Northern Hemisphere. This expansion is strongest in austral summer and autumn. Ozone depletion has been argued to cause this pattern of changes in observations and model experiments, but the results here indicate that seasonally and hemispherically asymmetric tropical expansion can be a basic response of the general circulation to climate forcings.

Effect of UVB Irradiation on Cu2+-Binding Organic Ligands and Cu2+ Speciation in Alpine Lake Waters of New Zealand

2005 ◽  
Vol 2 (1) ◽  
pp. 56 ◽  
Author(s):  
Sylvia Sander ◽  
Jonathan P. Kim ◽  
Barry Anderson ◽  
Keith A. Hunter
Keyword(s):  
New Zealand ◽  
Surface Waters ◽  
Natural Waters ◽  
Austral Summer ◽  
Organic Ligands ◽  
Conditional Stability ◽  
Uvb Radiation ◽  
Dissolved Metals ◽  
Conditional Stability Constant ◽  
Uvb Irradiation

Environmental Context. The bioavailability of dissolved metals in natural waters is directly affected by metal-sequestering agents. These agents include soil-derived matter and compounds released by microorganisms, since copper can support or inhibit aquatic microorganisms depending on concentration. During summer the levels of copper increase in surface waters, an effect intuitively attributable to increased ultraviolet light degrading the sequestering agents more effectively, leading to a concurrent release of the metal. This paper shows that the amount of degradation attributable to light is too low to explain the metal release and that a biological influence may instead be responsible. Abstract. The influence of UVB irradiation on the Cu2+ binding by natural organic ligands in six alpine lakes on the South Island, New Zealand, has been investigated using competitive ligand equilibration with salicylaldoxime and detection by cathodic stripping voltammetry (CLE-CSV). During austral summer 2002–2003 the total dissolved Cu ([Cu]T), the concentration of strong Cu2+-binding ligands ([L]T), and their conditional stability constant K´´ were determined in surface samples of all six lakes. All lakes exhibited appreciable concentrations of a strong Cu2+ binding ligand with similar K´´ values and concentrations always exceeding [CuT], thus dominating Cu2+ speciation. Four lakes (Hayes, Manapouri, Wanaka, Te Anau) showed no appreciable trend in [LT] throughout the summer, whereas in Lakes Wakatipu and Hawea [LT] increased steadily throughout this period. Laboratory UVB irradiation of lake water samples using a 400 W mercury lamp with a Pyrex glass filter (λ > 280 nm) showed that Cu2+-binding ligands are destroyed by UVB radiation, causing [L]T to decrease with a rate of –0.588 nmol L–1 h–1 (r2 0.88). From this we calculate that the in situ ligand destruction rate by UVB in summer for surface waters of these lakes is too small to significantly affect [LT], and conclude that variations in ligand concentrations must result from seasonally variable biological factors.

Multiscale Convective Organization and the YOTC Virtual Global Field Campaign

2012 ◽  
Vol 93 (8) ◽  
pp. 1171-1187 ◽  
Author(s):  
Mitchell W. Moncrieff ◽  
Duane E. Waliser ◽  
Martin J. Miller ◽  
Melvyn A. Shapiro ◽  
Ghassem R. Asrar ◽  
...  
Keyword(s):  
Time Scales ◽  
Climate Models ◽  
Water Cycle ◽  
Building Blocks ◽  
Tropical Convection ◽  
Global Water Cycle ◽  
Weather And Climate ◽  
Impact Phenomena ◽  
Meteorological Systems ◽  
The Tropics

The Year of Tropical Convection (YOTC) project recognizes that major improvements are needed in how the tropics are represented in climate models. Tropical convection is organized into multiscale precipitation systems with an underlying chaotic order. These organized systems act as building blocks for meteorological events at the intersection of weather and climate (time scales up to seasonal). These events affect a large percentage of the world's population. Much of the uncertainty associated with weather and climate derives from incomplete understanding of how meteorological systems on the mesoscale (~1–100 km), synoptic scale (~1,000 km), and planetary scale (~10,000 km) interact with each other. This uncertainty complicates attempts to predict high-impact phenomena associated with the tropical atmosphere, such as tropical cyclones, the Madden–Julian oscillation, convectively coupled tropical waves, and the monsoons. These and other phenomena influence the extratropics by migrating out of the tropics and by the remote effects of planetary waves, including those generated by the MJO. The diurnal and seasonal cycles modulate all of the above. It will be impossible to accurately predict climate on regional scales or to comprehend the variability of the global water cycle in a warmer world without comprehensively addressing tropical convection and its interactions across space and time scales.

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