ORCID Profile
0000-0001-5397-0201
Current Organisation
UNSW Sydney
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Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-1981
Abstract: & & Subseasonal prediction skill of precipitation is typically low. Sometimes, however, forecasts are accurate and it would be useful to end-users to assess & em& a priori& /em& if this might be the case. We use a 20-year hindcast data set of the ECMWF S2S prediction system and identify periods of high forecast confidence, evaluating model skill of precipitation forecasts for these periods compared to lower confidence predictions.& & & & From reanalysis data, we derive a set of circulation patterns, called archetypes, that represent the broad-scale atmospheric circulation over Australia. These archetypes are combinations of ridges and troughs, and yield different precipitation patterns depending on the location of these features. In the literature, a typical application of circulation patterns is assigning daily reanalysis fields to the closest-matching pattern, thus obtaining conditional distributions of precipitation corresponding to key modes of atmospheric variability. A problem common to such analyses is that the precipitation distributions associated with the circulation patterns can be too similar distinct distributions are required in order for the patterns to be useful in estimating precipitation. We show that by subs ling the archetype occurrences only when they are particularly well-matched to the underlying field, the conditional precipitation distributions become more distinct.& & & & We subs le hindcast fields in the same way, obtaining a s le of periods when the model is confident about its prediction of the upcoming archetype. We then calculate model skill in predicting precipitation for three regions in southern Australia during such periods compared to when the model is not confident about the predicted archetype. Our results suggest that during periods of forecast confidence, precipitation skill is greater than normal for shorter leads (up to ten days) in two of the three regions (the Murray Basin and Western Tasmania). Skill for the third region (Southwest Western Australia) is greater during confident periods for lead times greater than one week, although this is marginal.& &
Publisher: Copernicus GmbH
Date: 16-07-2019
Publisher: Wiley
Date: 07-2020
DOI: 10.1002/MET.1931
Publisher: IOP Publishing
Date: 02-06-2023
Abstract: The record-shattering hot day in the Pacific Northwest in June 2021 is used to motivate a study of record-shattering temperature extremes in a very large hindcast ensemble. The hottest days in the Pacific Northwest in the large ensemble have similar large scale and synoptic patterns to those associated with the observed event. From the perspective of a fixed location, the hottest ensemble days are acutely sensitive to the chance sequencing of a dry period with a precisely positioned weather pattern. These days are thus rare and require very large s les (tens of thousands of years) to capture. The enduring nature of record-shattering heat records can be understood through this lens of weather ‘noise’ and s ling. When a record-shattering event occurs due to chance alignment of weather systems in the optimal configuration, any small s le of years subsequent to the (very unlikely) record event has an extremely low chance of finding yet another chance extreme. While warming of the baseline climate can narrow the gap between more regular extremes and record-shattering extremes, this can take many decades depending on the pace of climate change. Climate models are unlikely to capture record-shattering extremes at fixed locations given by observations unless the model s les are large enough to provide enough weather outcomes to include the optimal weather alignments. This underscores the need to account for s ling in assessing models and changes in weather-sensitive extremes. In particular, climate models are not necessarily deficient in representing extremes if that assessment is based on their absence in undersize s les.
Publisher: California Digital Library (CDL)
Date: 09-06-2023
DOI: 10.31223/X5W09W
Abstract: Solar and wind power are central to Australia’s renewable energy future, which implies an energy sector vulnerable to weather and climate variability. Alignment of weather systems and the influence of large-scale climate modes of variability risks widespread reductions in solar and wind resources, and could induce grid-wide impacts. We therefore systematically analyse the relationship between compound solar and wind droughts with weather systems and large-scale climate modes of variability over multiple time scales. We find that compound solar and wind droughts occur most frequently in winter, affecting at least five significant energy producing regions simultaneously on 10% of days. The associated weather systems vary by season and by drought type, although widespread cloud cover and anticyclonic circulation patterns are common features. Indices of major climate modes are not strong predictors of grid-wide droughts, and are typically within one standard deviation of the mean during seasons with the most widespread events. However, the spatial imprints of the teleconnections display strong regional variations, with drought frequencies varying by more than ten days per season between positive and negative phases of climate modes in some regions. The spatial variability of these teleconnection patterns suggests that droughts in one region may be offset by increased resource in another. Our work highlights the opportunity for minimising the impact of energy production variability by utilising weather and climate intelligence. Exploiting the spatial variability associated with daily weather systems and the seasonal influence of climate modes could help build a more climate-resilient renewables-dominated energy system.
Publisher: Wiley
Date: 13-07-2018
DOI: 10.1002/JOC.5199
Publisher: Copernicus GmbH
Date: 16-07-2019
Abstract: Abstract. Dynamical model skill in forecasting extratropical precipitation is limited beyond the medium-range (around 15 days), but such models are often more skilful at predicting atmospheric variables. We explore the potential benefits of using weather pattern (WP) predictions as an intermediary step in forecasting UK precipitation and meteorological drought on sub-seasonal time scales. MSLP forecasts from the ECMWF ensemble prediction system (ECMWF-EPS) are post-processed into probabilistic WP predictions. Then we derive precipitation estimates and dichotomous drought event probabilities by s ling from the conditional distributions of precipitation given the WPs. We compare this model to the direct precipitation and drought forecasts from ECMWF-EPS and to a baseline Markov chain WP method. A perfect-prognosis model is also tested to illustrate the potential of WPs in forecasting. Using a range of skill diagnostics, we find that for 31- and 46-day lead-times, dynamical, and to a lesser extent Markov, model forecasts using WPs can achieve higher skill scores that the non-WP method, particularly for precipitation. Forecast skill scores are generally modest (rarely above 0.4), although those for the perfect-prognosis model highlight the potential predictability of precipitation and drought using WPs, with certain situations yielding skill scores of almost 0.8, and drought event hit and false alarm rates of 70 % and 30 %, respectively.
Publisher: American Meteorological Society
Date: 22-03-2021
Abstract: The CSIRO Climate retrospective Analysis and Forecast Ensemble system: version 1 (CAFE60v1) provides a large (96 member) ensemble retrospective analysis of the global climate system from 1960 to present with sufficiently many realizations and at spatio-temporal resolutions suitable to enable probabilistic climate studies. Using a variant of the ensemble Kalman filter, 96 climate state estimates are generated over the most recent six decades. These state estimates are constrained by monthly mean ocean, atmosphere and sea ice observations such that their trajectories track the observed state while enabling estimation of the uncertainties in the approximations to the retrospective mean climate over recent decades. For the atmosphere, we evaluate CAFE60v1 in comparison to empirical indices of the major climate teleconnections and blocking with various reanalysis products. Estimates of the large scale ocean structure, transports and biogeochemistry are compared to those derived from gridded observational products and climate model projections (CMIP). Sea ice (extent, concentration and variability) and land surface (precipitation and surface air temperatures) are also compared to a variety of model and observational products. Our results show that CAFE60v1 is a useful, comprehensive and unique data resource for studying internal climate variability and predictability, including the recent climate response to anthropogenic forcing on multi-year to decadal time scales.
Publisher: MDPI AG
Date: 15-06-2022
DOI: 10.3390/CLI10060083
Abstract: With increased interest in climate forecasts and projections, it is important to understand more about their sources and levels of skill. A starting point here is to describe the nature of the skill associated with forecasts and projections. Climate forecasts and projections typically both include time varying forcing of the climate, but only forecasts have initial conditions set close to the observed climate state. Climate forecasts therefore derive skill from both initial conditions and from forcing. The character of the initial condition skill and forcing skill is different. Skill from initial conditions results in a narrowing of expectations relative to a climatological distribution and points toward a more favoured part of the distribution. Forcing skill could result from a shift in the preferred parts of the climatological distribution in response to forcing, or it could result from a shift in the entire distribution, or both. Assessments of forcing skill require time averages of the target variable that are long enough so that the contributions from internal variations are small compared to the forced response. The assessment of skill of climate forecasts and projections is inherently partial because of the small number of repeated trials possible on typical climate time scales but is nonetheless the only direct measure of their performance.
Publisher: American Meteorological Society
Date: 12-04-2021
Abstract: From time to time atmospheric flows become organized and form coherent long-lived structures. Such structures could be propagating, quasi-stationary, or recur in place. We investigate the ability of Principal Components Analysis (PCA) and Archetypal Analysis (AA) to identify long-lived events, excluding propagating forms. Our analysis is carried out on the Southern Hemisphere mid-tropospheric flow represented by geopotential height at 500hPa ( Z 500 ). The leading basis patterns of Z 500 for PCA and AA are similar and describe structures representing (or similar to) the Southern Annular Mode (SAM) and Pacific South American (PSA) pattern. Long-lived events are identified here from sequences of 8 days or longer where the same basis pattern dominates for PCA or AA. AA identifies more long-lived events than PCA using this approach. The most commonly occurring long-lived event for both AA and PCA is the annular SAM-like pattern. The second most commonly occurring event is the PSA-like Pacific wavetrain for both AA and PCA. For AA the flow at any given time is approximated as weighted contributions from each basis pattern, which lends itself to metrics for discriminating among basis patterns. These show that the longest long-lived events are in general better expressed than shorter events. Case studies of long-lived events featuring a blocking structure and an annular structure show that both PCA and AA can identify and discriminate the dominant basis pattern that most closely resembles the flow event.
Publisher: American Meteorological Society
Date: 04-2021
Abstract: Large-scale cloud features referred to as cloudbands are known to be related to widespread and heavy rain via the transport of tropical heat and moisture to higher latitudes. The Australian northwest cloudband is such a feature that has been identified in simple searches of satellite imagery but with limited investigation of its atmospheric dynamical support. An accurate, long-term climatology of northwest cloudbands is key to robustly assessing these events. A dynamically based search algorithm has been developed that is guided by the presence and orientation of the subtropical jet stream. This jet stream is the large-scale atmospheric feature that determines the development and alignment of a cloudband. Using a new 40-yr dataset of cloudband events compiled by this search algorithm, composite atmospheric and ocean surface conditions over the period 1979–2018 have been assessed. Composite cloudband upper-level flow revealed a tilted low pressure trough embedded in a Rossby wave train. Composites of vertically integrated water vapor transport centered around the jet maximum during northwest cloudband events reveal a distinct atmospheric river supplying tropical moisture for cloudband rainfall. Parcel backtracking indicated multiple regions of moisture support for cloudbands. A thermal wind anomaly orientated with respect to an enhanced sea surface temperature gradient over the Indian Ocean was also a key composite cloudband feature. A total of 300 years of a freely coupled control simulation of the ACCESS-D system was assessed for its ability to simulate northwest cloudbands. Composite analysis of model cloudbands compared reasonably well to reanalysis despite some differences in seasonality and frequency of occurrence.
Publisher: Springer Science and Business Media LLC
Date: 25-03-2022
DOI: 10.1038/S41612-022-00248-4
Abstract: Wildfire can cause significant adverse impacts to society and the environment. Weather and climate play an important role in modulating wildfire activity. We explore the joint occurrence of global fire weather and meteorological drought using a compound events framework. We show that, for much of the globe, burned area increases when periods of heightened fire weather compound with dry antecedent conditions. Regions associated with wildfire disasters, such as southern Australia and the western USA, are prone to experiencing years of compound drought and fire weather. Such compound events have increased in frequency for much of the globe, driven primarily by increases in fire weather rather than changes in precipitation. El Ni $$\\tilde{{{{\\rm{n}}}}}$$ n ̃ o Southern Oscillation is associated with widespread, spatially compounding drought and fire weather. In the Northern Hemisphere, a La Ni $$\\tilde{{{{\\rm{n}}}}}$$ n ̃ a signature is evident, whereas El Ni $$\\tilde{{{{\\rm{n}}}}}$$ n ̃ o is associated with such events in the tropics and, to a lesser degree, the Southern Hemisphere. Other climate modes and regional patterns of atmospheric circulation are also important, depending on the region. We show that the lengths of the fire weather seasons in eastern Australia and western North America have increased substantially since 2000, raising the likelihood of overlapping fire weather events in these regions. These cross-hemispheric events may be linked to the occurrence of El Ni $$\\tilde{{{{\\rm{n}}}}}$$ n ̃ o, although the sea-surface temperature magnitudes are small. Instead, it is likely that anthropogenic climate change is the primary driver of these changes.
Publisher: Springer Science and Business Media LLC
Date: 16-07-2021
DOI: 10.1038/S41467-021-23771-Z
Abstract: Assessments of climate forecast skill depend on choices made by the assessor. In this perspective, we use forecasts of the El Niño-Southern-Oscillation to outline the impact of bias-correction on skill. Many assessments of skill from hindcasts (past forecasts) are probably overestimates of attainable forecast skill because the hindcasts are informed by observations over the period assessed that would not be available to real forecasts. Differences between hindcast and forecast skill result from changes in model biases from the period used to form forecast anomalies to the period over which the forecast is made. The relative skill rankings of models can change between hindcast and forecast systems because different models have different changes in bias across periods.
Publisher: Springer Science and Business Media LLC
Date: 08-12-2021
DOI: 10.1038/S41612-021-00220-8
Abstract: Between June 2019 and March 2020, thousands of wildfires spread devastation across Australia at the tragic cost of many lives, vast areas of burnt forest, and estimated economic losses upward of AU$100 billion. Exceptionally hot and dry weather conditions, and preceding years of severe drought across Australia, contributed to the severity of the wildfires. Here we present analysis of a very large ensemble of initialized climate simulations to assess the likelihood of the concurrent drought and fire-weather conditions experienced at that time. We focus on a large region in southeast Australia where these fires were most widespread and define two indices to quantify the susceptibility to fire from drought and fire weather. Both indices were unprecedented in the observed record in 2019. We find that the likelihood of experiencing such extreme susceptibility to fire in the current climate was 0.5%, equivalent to a 200 year return period. The conditional probability is many times higher than this when we account for the states of key climate modes that impact Australian weather and climate. Drought and fire-weather conditions more extreme than those experienced in 2019 are also possible in the current climate.
Publisher: American Meteorological Society
Date: 02-2021
Abstract: Subseasonal forecast skill is not homogeneous in time, and prior assessment of the likely forecast skill would be valuable for end-users. We propose a method for identifying periods of high forecast confidence using atmospheric circulation patterns, with an application to southern Australia precipitation. In particular, we use archetypal analysis to derive six patterns, called archetypes, of daily 500-hPa geopotential height ( Z 500 ) fields over Australia. We assign Z 500 reanalysis fields to the closest-matching archetype and subsequently link the archetypes to precipitation for three key regions in the Australian agriculture and energy sectors: the Murray Basin, southwest Western Australia, and western Tasmania. Using a 20-yr hindcast dataset from the European Centre for Medium-Range Weather Forecasts subseasonal-to-seasonal prediction system, we identify periods of high confidence as when hindcast Z 500 fields closely match an archetype according to a distance criterion. We compare the precipitation hindcast accuracy during these confident periods compared to normal. Considering all archetypes, we show that there is greater skill during confident periods for lead times of less than 10 days in the Murray Basin and western Tasmania, and for greater than 6 days in southwest Western Australia, although these conclusions are subject to substantial uncertainty. By breaking down the skill results for each archetype in idually, we highlight how skill tends to be greater than normal for those archetypes associated with drier-than-average conditions.
Publisher: CSIRO Publishing
Date: 13-05-2022
DOI: 10.1071/WF21072
Abstract: Climate projections indicate that dangerous fire weather will become more common over the coming century. We examine the potential of a network of temperature- and moisture-sensitive tree-ring sites in southeastern Australia to reconstruct the number of high fire-danger days for the January–March season. Using the Forest Fire Danger Index (FFDI), we show that modestly statistically skilful reconstructions for the far southeast of Australia (western Tasmania), where the majority of tree-ring predictors are located, can be developed. According to the averaged reconstructions for the 1590–2008 period, there have been 16 years prior to the start of the FFDI records (1950), and 7 years since 1950, with (mean + 1σ) high fire-danger days in the 3-month season. The western Tasmanian reconstructions indicate extended relatively high fire-danger periods in the 1650s–1660s and 1880s–1890s. Fire danger has also been relatively high since 2000 CE. A persistent increase in the number of high fire-danger days over the past four decades has not been matched over the previous 390 years. This work indicates it is possible to produce statistically useful reconstructions of high seasonal fire danger – as opposed to fire occurrence – but that availability of local proxy records is key.
Publisher: Copernicus GmbH
Date: 06-07-2023
DOI: 10.5194/EMS2023-187
Abstract: Australia has significant potential for solar and wind energy generation. The size of the country, including its latitudinal extent, means its resource potential varies dramatically both in space and throughout the year. In the northern tropics, sunshine is relatively abundant year-round. In the mid-latitudes, solar power is weakened in winter, leaving a greater reliance on other forms of generation. The eastern states have plans to install significant capacity in onshore wind, offshore wind and solar energy generation and battery storage across nearly 40 Renewable Energy Zones. These will complement existing capacity and hydroelectric schemes. This talk examines the occurrence and co-occurrence of wind and solar lulls across Australia, with an emphasis on the eastern state Renewable Energy Zones. We focus on spatially-compounding events that have the potential to impact large-scale energy generation through affecting a substantial number of energy farms simultaneously. We will assess the likelihood and extent to which these events can occur both for in idual Zones and across the entire network. We also analyse the synoptic processes associated with these large-scale events, and whether they may also affect energy demand through heating or cooling requirements in major cities. The talk will also investigate the role of large-scale climate modes of variability, such as the El Ni& #241 o Southern Oscillation, the Indian Ocean Dipole and the Southern Annular Mode, in modulating wind and solar lull occurrences. These modes are a key feature of Australia& #8217 s climate variability, and hence may be a useful resource when assessing the likelihood of reduced or enhanced renewable energy generation in upcoming months and seasons.
Publisher: American Meteorological Society
Date: 2020
Publisher: Wiley
Date: 12-12-2019
DOI: 10.1002/JOC.5932
Publisher: Copernicus GmbH
Date: 14-01-2020
DOI: 10.5194/NHESS-20-107-2020
Abstract: Abstract. Dynamical model skill in forecasting extratropical precipitation is limited beyond the medium-range (around 15 d), but such models are often more skilful at predicting atmospheric variables. We explore the potential benefits of using weather pattern (WP) predictions as an intermediary step in forecasting UK precipitation and meteorological drought on sub-seasonal timescales. Mean sea-level pressure forecasts from the European Centre for Medium-Range Weather Forecasts ensemble prediction system (ECMWF-EPS) are post-processed into probabilistic WP predictions. Then we derive precipitation estimates and dichotomous drought event probabilities by s ling from the conditional distributions of precipitation given the WPs. We compare this model to the direct precipitation and drought forecasts from the ECMWF-EPS and to a baseline Markov chain WP method. A perfect-prognosis model is also tested to illustrate the potential of WPs in forecasting. Using a range of skill diagnostics, we find that the Markov model is the least skilful, while the dynamical WP model and direct precipitation forecasts have similar accuracy independent of lead time and season. However, drought forecasts are more reliable for the dynamical WP model. Forecast skill scores are generally modest (rarely above 0.4), although those for the perfect-prognosis model highlight the potential predictability of precipitation and drought using WPs, with certain situations yielding skill scores of almost 0.8 and drought event hit and false alarm rates of 70 % and 30 %, respectively.
Publisher: Elsevier BV
Date: 12-2021
Publisher: Public Library of Science (PLoS)
Date: 08-03-2023
DOI: 10.1371/JOURNAL.PCLM.0000134
Abstract: Global coffee production is at risk from synchronous crop failures, characterised by widespread concurrent reductions in yield occurring in multiple countries at the same time. For other crops, previous studies have shown that synchronous failures can be forced by spatially compounding climate anomalies, which in turn may be driven by large-scale climate modes such as the El Niño Southern Oscillation (ENSO). We provide a systematic analysis of spatially compounding climate hazards relevant to global coffee production. We identify 12 climate hazards from the literature, and assess the extent to which these hazards occur and co-occur for the top 12 coffee producing regions globally. We find that the number of climate hazards and compound events has increased in every region between 1980 and 2020. Furthermore, a clear climate change signature is evident, as the type of hazard has shifted from overly cool conditions to overly warm. Spatially compounding hazards have become particularly common in the past decade, with only one of the six most hazardous years occurring before 2010. Our results suggest that ENSO is the primary mode in explaining annual compound event variability, both globally and regionally. El Niño-like sea-surface temperatures in the Pacific Ocean are associated with decreased precipitation and increased temperatures in most coffee regions, and with spatially compounding warm and dry events. This relationship is reversed for La Niña-like signatures. The Madden Julian Oscillation also shows a strong association with climate hazards to coffee, with increased activity in the Maritime Continent related to a global increase in the number of cold or wet hazards and a decrease in the number of warm or dry hazards. With climate change projections showing a continued rise in temperatures in the tropics is likely, we suggest that coffee production can expect ongoing systemic shocks in response to spatially compounding climate hazards.
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Doug Richardson.