Search

When record-breaking climate and weather extremes occur, decision-makers and planners want to know whether they are random natural events with historical levels of reoccurrence 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 subseasonal 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 subseasonal 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. [ABSTRACT FROM AUTHOR]

Daily data from climate models submitted to the Fourth Assessment of the Intergovernmental Panel on Climate Change are compared with daily data from observations over Australia by measuring the overlap of the probability density functions (PDFs). The capacity of these models to simulate maximum temperature, minimum temperature, and precipitation is assessed. The resulting skill score is then used to exclude models with relatively poor skill region by region over Australia. The remaining sample of coupled climate models is then used to determine the seasonal changes in these three variables under a high- (A2) and low- (B1) emission scenario for 2050 and 2100. The authors demonstrate that some projected phenomena, such as the projected drying over southwest Western Australia, are robust and not caused by the inclusion of some weak models in earlier assessments. Some other results, such as the projected change in the monsoon, are more consistent among the good climate models. Consistent with earlier work, a consistent pattern of mean warming is identified in the projections. The amount of warming in the 99.7th percentile is not dramatically higher than the warming in the mean. However, while the mean warming is generally least in the south, the amount of warming in the 99.7th percentile is substantially higher along the southern coast of Australia. This is due to a coupling of the temperature response with reduced rainfall, which causes drying and allows extreme maximum temperatures to increase dramatically. The authors show that, in general, the amount of rainfall is projected to change relatively little, but the frequency of rainfall decreases and the intensity of rainfall at the upper tail of the distribution increases. However, the scale of the increase in extreme rainfall is not large on the time scales analyzed here. The range in projected temperature changes among those climate models with skill in simulating the observations is at least twice as large for the 99.7th/0.3rd percentiles as for the mean. For rainfall, the range among the good models is of order 10 times greater in the 99.7th percentile than in the mean. Since the impact of changes in extremes is increasingly recognized as societally important, this result strongly limits the use of climate model data to explore sectors that are vulnerable to extremes. This suggests an evaluation strategy that focuses on model capacity to simulate whole PDFs since capacity to simulate the mean is a necessary but insufficient criterion for determining a model’s value for future projection. [ABSTRACT FROM AUTHOR]

The Southern Hemisphere storm tracks are commonly simulated too far equatorward in climate models for the historical period. In the latest generation of climate models from phase 6 of the Coupled Model Intercomparison Project (CMIP6), the equatorward bias that was present in CMIP5 models still persists, although it is reduced considerably. A further reduction of the equatorward bias is found in atmosphere-only simulations. Using diagnostic large-scale fields, we propose that an increase in the midlatitude temperature gradients contributes to the reduced equatorward bias in CMIP6 and AMIP6 models, reducing the biases relative to ERA5. These changes increase baroclinicity in the atmosphere and are associated with a storm track that is situated farther poleward. In CMIP6 models, the poleward shift of the storm tracks is associated with an amelioration of cold midlatitude SST biases in CMIP5 and not through a reduction of the long-standing warm Southern Ocean SST bias. We propose that increases in midlatitude temperature gradients in the atmosphere and ocean are connected to changes in the cloud radiative effect. Persistent track density biases to the south of Australia are shown to be connected to an apparent standing-wave pattern originating in the tropics, which modifies the split jet structure near Australia and subsequently the paths of cyclones. [ABSTRACT FROM AUTHOR]

Drought is projected to become more severe and widespread as global warming continues in the twenty-first century, but hydroclimatic changes and their drivers are not well examined in the latest projections from phase 6 of the Coupled Model Intercomparison Project (CMIP6). Here, precipitation (P), evapotranspiration (E), soil moisture (SM), and runoff (R) from 25 CMIP6 models, together with self-calibrated Palmer drought severity index with Penman–Monteith potential evapotranspiration (scPDSIpm), are analyzed to quantify hydroclimatic and drought changes in the twenty-first century and the underlying causes. Results confirm consistent drying in these hydroclimatic metrics across most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, and Australia, although the drying magnitude differs, with the drying being more severe and widespread in surface SM than in total SM. Global drought frequency based on surface SM and scPDSIpm increases by ∼25%–100% (50%–200%) under the SSP2-4.5 (SSP5-8.5) scenario in the twenty-first century together with large increases in drought duration and areas, which result from a decrease in the mean and flattening of the probability distribution functions of SM and scPDSIpm, while the R-based drought changes are relatively small. Changes in both P and E contribute to the SM change, whereas scPDSIpm decreases result from ubiquitous PET increases and P decreases over subtropical areas. The R changes are determined primarily by P changes, while the PET change explains most of the E increase. Intermodel spreads in surface SM and R changes are large, leading to large uncertainties in the drought projections. SIGNIFICANCE STATEMENT: Drought may become more severe and widespread under greenhouse gas (GHG)-induced global warming in the twenty-first century based on model projections. However, there are still large uncertainties in projected future drought changes, especially regarding the extent to which drought changes depend on drought indices and the future emissions scenarios analyzed. The latest projections from CMIP6 models reaffirm the widespread drying and increases in agricultural drought by up to 200% over most of the Americas (including the Amazon), Europe and the Mediterranean region, southern Africa, Southeast Asia, and Australia under moderate-to-high emissions scenarios in the twenty-first century, despite large uncertainties in individual projections partly due to internal variability. Ubiquitous increases in atmospheric demand for moisture under rising temperatures and precipitation decreases over many subtropical regions are the main driver of the projected drying and drought increases. [ABSTRACT FROM AUTHOR]

Stationary wave changes play a significant role in the regional climate change response in Southern Hemisphere (SH) winter. In particular, almost all CMIP5 models feature a substantial strengthening of the westerlies to the south of Australia and enhancement of the subtropical jet over the eastern Pacific in winter. In this study we investigate the mechanisms behind these changes, finding that the stationary wave response can largely be explained via reductions in the magnitude of the upper-level Rossby wave source over the tropical/subtropical east Pacific. The Rossby wave source changes in this region are robust across the model ensemble and are strongly correlated with changes to low-latitude circulation patterns, in particular, the projected southward migration of the Hadley cell and weakening of the Walker circulation. To confirm our mechanism of future changes, we employ a series of barotropic model experiments in which the barotropic model is given a background state identical to a particular CMIP5 model and an anomalous Rossby wave source is imposed. This simple approach is able to capture the primary features of the ensemble-mean change, including the cyclonic anomaly south of Australia, and is also able to capture many of the intermodel differences. These findings will help to advance our understanding of the mechanisms underpinning SH extratropical circulation changes under climate change. [ABSTRACT FROM AUTHOR]

Indices derived from daily rainfall time series are used to measure "burst" features of the northern Australia monsoon, corresponding to one or more days of heavy rainfall. These indices include number of burst days, numbers and durations of burst events, and average intensity. The results using observational data show how these features can vary from one year to the next, and how they can vary from the station scale (Darwin) to the regional scale (northern Australia). The results from Coupled Model Intercomparison Project Phase 5 (CMIP5) climate model simulations under both historical and future greenhouse gas conditions have also been analysed and indicate how well models can capture these features and how they might change by the end of the 21st century under a high emissions scenario. While most models provide a reasonable simulation of present‐day burst features, there is little consensus for a significant change to seasonal rainfall totals when looking at the full CMIP5 ensemble. A subset of models with detectable skills with respect to the Madden‐Julian Oscillation shows evidence for an increase in the seasonal total rainfall amount and most other monsoon metrics, except a slight decrease in the number of burst events. This is consistent with a basic thermodynamic response to warming and consistent with findings elsewhere. However, the Australian monsoon is strongly influenced by the large‐scale circulation and there remains some doubt about whether we can confidently diagnose all the changes to monsoon bursts that could occur given the limited ability of many of the current generation of models to simulate tropical cyclones, the Madden‐Julian Oscillation and other relevant features. [ABSTRACT FROM AUTHOR]

Expansion of the tropics will likely affect subtropical precipitation, but observed and modeled precipitation trends disagree with each other. Moreover, the dynamic processes at the tropical edge and their interactions with precipitation are not well understood. This study assesses the skill of climate models to reproduce observed Australian precipitation variability at the tropical edge. A multivariate linear independence approach distinguishes between direct (causal) and indirect (circumstantial) precipitation drivers that facilitate clearer attribution of model errors and skill. This approach is applied to observed precipitation and ERA-Interim reanalysis data and a representative subset of four models from phase 5 of the Coupled Model Intercomparison Project (CMIP5) and their CMIP3 counterparts. The drivers considered are El Niño-Southern Oscillation, southern annular mode, Indian Ocean dipole, blocking, and four tropical edge metrics (position and intensity of the subtropical ridge and subtropical jet). These models are skillful in representing the covariability of drivers and their influence on precipitation. However, skill scores have not improved in the CMIP5 subset relative to CMIP3 in either respect. The Australian precipitation response to a poleward-located Hadley cell edge remains uncertain, as opposing drying and moistening mechanisms complicate the net response. Higher skill in simulating driver covariability is not consistently mirrored by higher precipitation skill. This provides further evidence that modeled precipitation does not respond correctly to large-scale flow patterns; further improvements in parameterized moist physics are needed before the subtropical precipitation responses can be fully trusted. The multivariate linear independence approach could be applied more widely for practical model evaluation. [ABSTRACT FROM AUTHOR]

Downscaled climate model projections from phase 5 of the Coupled Model Intercomparison Project (CMIP5) were used to force a dynamic vegetation agricultural model (Agro-IBIS) and simulate yield responses to historical climate and two future emissions scenarios for maize in the U.S. Midwest and wheat in southeastern Australia. In addition to mean changes in yield, the frequency of high- and low-yield years was related to changing local hydroclimatic conditions. Particular emphasis was on the seasonal cycle of climatic variables during extreme-yield years and links to crop growth. While historically high (low) yields in Iowa tend to occur during years with anomalous wet (dry) growing season, this is exacerbated in the future. By the end of the twenty-first century, the multimodel mean (MMM) of growing season temperatures in Iowa is projected to increase by more than 5°C, and maize yield is projected to decrease by 18%. For southeastern Australia, the frequency of low-yield years rises dramatically in the twenty-first century because of significant projected drying during the growing season. By the late twenty-first century, MMM growing season precipitation in southeastern Australia is projected to decrease by 15%, temperatures are projected to increase by 2.8°-4.5°C, and wheat yields are projected to decline by 70%. Results highlight the sensitivity of yield projections to the nature of hydroclimatic changes. Where future changes are uncertain, the sign of the yield change simulated by Agro-IBIS is uncertain as well. In contrast, broad agreement in projected drying over southern Australia across models is reflected in consistent yield decreases for the twenty-first century. Climatic changes of the order projected can be expected to pose serious challenges for continued staple grain production in some current centers of production, especially in marginal areas. [ABSTRACT FROM AUTHOR]

The influence of a warming climate on the occurrence of severe thunderstorms over Australia is, as yet, poorly understood. Based on methods used in the development of a climatology of observed severe thunderstorm environments over the continent, two climate models [Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6) and the Cubic-Conformal Atmospheric Model (CCAM)] have been used to produce simulated climatologies of ingredients and environments favorable to severe thunderstorms for the late twentieth century (1980-2000). A novel evaluation of these model climatologies against data from both the ECMWF Interim Re-Analysis (ERA-Interim) and reports of severe thunderstorms from observers is used to analyze the capability of the models to represent convective environments in the current climate. This evaluation examines the representation of thunderstorm-favorable environments in terms of their frequency, seasonal cycle, and spatial distribution, while presenting a framework for future evaluations of climate model convective parameters. Both models showed the capability to explain at least 75% of the spatial variance in both vertical wind shear and convective available potential energy (CAPE). CSIRO Mk3.6 struggled to either represent the diurnal cycle over a large portion of the continent or resolve the annual cycle, while in contrast CCAM showed a tendency to underestimate CAPE and 0-6-km bulk magnitude vertical wind shear (S06). While spatial resolution likely contributes to rendering of features such as coastal moisture and significant topography, the distribution of severe thunderstorm environments is found to have greater sensitivity to model biases. This highlights the need for a consistent approach to evaluating convective parameters and severe thunderstorm environments in present-day climate: an example of which is presented here. [ABSTRACT FROM AUTHOR]

The influence of a warming climate on the occurrence of severe thunderstorm environments in Australia was explored using two global climate models: Commonwealth Scientific and Industrial Research Organisation Mark, version 3.6 (CSIRO Mk3.6), and the Cubic-Conformal Atmospheric Model (CCAM). These models have previously been evaluated and found to be capable of reproducing a useful climatology for the twentieth-century period (1980-2000). Analyzing the changes between the historical period and high warming climate scenarios for the period 2079-99 has allowed estimation of the potential convective future for the continent. Based on these simulations, significant increases to the frequency of severe thunderstorm environments will likely occur for northern and eastern Australia in a warmed climate. This change is a response to increasing convective available potential energy from higher continental moisture, particularly in proximity to warm sea surface temperatures. Despite decreases to the frequency of environments with high vertical wind shear, it appears unlikely that this will offset increases to thermodynamic energy. The change is most pronounced during the peak of the convective season, increasing its length and the frequency of severe thunderstorm environments therein, particularly over the eastern parts of the continent. The implications of this potential increase are significant, with the overall frequency of potential severe thunderstorm days per year likely to rise over the major population centers of the east coast by 14% for Brisbane, 22% for Melbourne, and 30% for Sydney. The limitations of this approach are then discussed in the context of ways to increase the confidence of predictions of future severe convection. [ABSTRACT FROM AUTHOR]

The east coast of Australia is a region of the world where a particular type of extratropical cyclone, known locally as an east coast low, frequently occurs with severe consequences such as extreme rainfall, winds, and waves. The likelihood of formation of these storms is examined using an upper-tropospheric diagnostic applied to three reanalyses and three global climate models (GCMs). Strong similarities exist among the results derived from the individual reanalyses in terms of their seasonal variability (e.g., winter maxima and summer minima) and interannual variability. Results from reanalyses indicate that the threshold value used in the diagnostic method is dependent on the spatial resolution. Results obtained when applying the diagnostic to two of the three GCMs are similar to expectations given their spatial resolutions, and produce seasonal cycles similar to those from the reanalyses. Applying the methodology to simulations from these two GCMs for both current and future climate in response to increases in greenhouse gases indicates a reduction in extratropical cyclone occurrence of about 30% from the late twentieth century to the late twenty-first century for eastern Australia. In addition to the absolute risk of formation of these extratropical cyclones, spatial climatologies of occurrence are examined for the broader region surrounding eastern Australia. The influence of large-scale modes of atmospheric and oceanic variability on the occurrence of these storms in this region is also discussed. [ABSTRACT FROM AUTHOR]

Cutoff lows are an important source of rainfall in the mid-latitudes that climate models need to simulate accurately to give confidence in climate projections for rainfall. Coarse-scale general circulation models used for climate studies show some notable biases and deficiencies in the simulation of cutoff lows in the Australian region and important aspects of the broader circulation such as atmospheric blocking and the split jet structure observed over Australia. The regional climate model conformal cubic atmospheric model or CCAM gives an improvement in some aspects of the simulation of cutoffs in the Australian region, including a reduction in the underestimate of the frequency of cutoff days by more than 15 % compared to a typical GCM. This improvement is due at least in part to substantially higher resolution. However, biases in the simulation of the broader circulation, blocking and the split jet structure are still present. In particular, a northward bias in the central latitude of cutoff lows creates a substantial underestimate of the associated rainfall over Tasmania in April to October. Also, the regional climate model produces a significant north-south distortion of the vertical profile of cutoff lows, with the largest distortion occurring in the cooler months that was not apparent in GCM simulations. The remaining biases and presence of new biases demonstrates that increased horizontal resolution is not the only requirement in the reliable simulation of cutoff lows in climate models. Notwithstanding the biases in their simulation, the regional climate model projections show some responses to climate warming that are noteworthy. The projections indicate a marked closing of the split jet in winter. This change is associated with changes to atmospheric blocking in the Tasman Sea, which decreases in June to November (by up to 7.9 m s), and increases in December to May. The projections also show a reduction in the number of annual cutoff days by 67 % over the century, together with an increase in their intensity, and these changes are strongest in spring and summer. [ABSTRACT FROM AUTHOR]

The simulation characteristics of the Asian-Australian monsoon are documented for the Community Climate System Model, version 4 (CCSM4). This is the first part of a two part series examining monsoon regimes in the global tropics in the CCSM4. Comparisons are made to an Atmospheric Model Intercomparison Project (AMIP) simulation of the atmospheric component in CCSM4 [Community Atmosphere Model, version 4, (CAM4)] to deduce differences in the monsoon simulations run with observed sea surface temperatures (SSTs) and with ocean-atmosphere coupling. These simulations are also compared to a previous version of the model (CCSM3) to evaluate progress. In general, monsoon rainfall is too heavy in the uncoupled AMIP run with CAM4, and monsoon rainfall amounts are generally better simulated with ocean coupling in CCSM4. Most aspects of the Asian-Australian monsoon simulations are improved in CCSM4 compared to CCSM3. There is a reduction of the systematic error of rainfall over the tropical Indian Ocean for the South Asian monsoon, and well-simulated connections between SSTs in the Bay of Bengal and regional South Asian monsoon precipitation. The pattern of rainfall in the Australian monsoon is closer to observations in part because of contributions from the improvements of the Indonesian Throughflow and diapycnal diffusion in CCSM4. Intraseasonal variability of the Asian-Australian monsoon is much improved in CCSM4 compared to CCSM3 both in terms of eastward and northward propagation characteristics, though it is still somewhat weaker than observed. An improved simulation of El Niño in CCSM4 contributes to more realistic connections between the Asian-Australian monsoon and El Niño-Southern Oscillation (ENSO), though there is considerable decadal and century time scale variability of the strength of the monsoon-ENSO connection. [ABSTRACT FROM AUTHOR]

The article focuses on ranking the AR4 climate models over the Murray-Darling Basin using simulated maximum temperature, minimum temperature and precipitation. It states that assessment is taken on the capacity of models submitted for Intergovernmental Panel on Climate Change (IPCC) Fourth Assessment Report (AR4), to simulate maximum and minimum temperatures and precipitation the Murray-Darling Basin in Australia. The team use daily data from AR4 to calculate the mean of three quantities, but also derive probability density functions (PDFs) for each variable. It notes that to demonstrate skill in simulating the daily derived PDFs is more challenging than simulating the mean.