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Modes of climate variability can drive significant changes to regional climate affecting extremes such as droughts, floods, and bushfires. The need to forecast these extremes and expected future increases in their intensity and frequency motivates a need to better understand the physical processes that connect climate modes to regional precipitation. Focusing on east Australia, where precipitation is driven by multiple interacting climate modes, this study provides a new perspective into the links between large-scale modes of climate variability and precipitation. Using a Lagrangian backtrajectory approach, we examine how El Niño-Southern Oscillation (ENSO) modifies the supply of evaporative moisture for precipitation, and how this is modulated by the Indian Ocean dipole (IOD) and southern annular mode (SAM). We demonstrate that La Niña modifies large-scale moisture transport together with local thermodynamic changes to facilitate local precipitation generation, whereas below-average precipitation during El Niño stems predominantly from increased regional subsidence. These dynamic-thermodynamic processes were often more pronounced during co-occurring La Niña/negative IOD and El Niño/positive IOD periods. As the SAM is less strongly correlated with ENSO, the impact of cooccurring ENSO and SAM largely depended on the state of ENSO. La Niña-related processes were exacerbated when combined with 1SAM and dampened when combined with 2SAM, and vice versa during El Niño. This new perspective on how interacting climate modes physically influence regional precipitation can help elucidate how model biases affect the simulation of Australian climate, facilitating model improvement and understanding of regional impacts from long-term changes in these modes. [ABSTRACT FROM AUTHOR]

Global climate model simulations inherently contain multiple biases that, when used as boundary conditions for regional climate models, have the potential to produce poor downscaled simulations. Removing these biases before downscaling can potentially improve regional climate change impact assessment. In particular, reducing the low-frequency variability biases in atmospheric variables as well as modeled rainfall is important for hydrological impact assessment, predominantly for the improved simulation of floods and droughts. The impact of this bias in the lateral boundary conditions driving the dynamical downscaling has not been explored before. Here the use of three approaches for correcting the lateral boundary biases including mean, variance, and modification of sample moments through the use of a nested bias correction (NBC) method that corrects for low-frequency variability bias is investigated. These corrections are implemented at the 6-hourly time scale on the global climate model simulations to drive a regional climate model over the Australian Coordinated Regional Climate Downscaling Experiment (CORDEX) domain. The results show that the most substantial improvement in low-frequency variability after bias correction is obtained from modifying the mean field, with smaller changes attributed to the variance. Explicitly modifying monthly and annual lag-1 autocorrelations through NBC does not substantially improve low-frequency variability attributes of simulated precipitation in the regional model over a simpler mean bias correction. These results raise questions about the nature of bias correction techniques that are required to successfully gain improvement in regional climate model simulations and show that more complicated techniques do not necessarily lead to more skillful simulation. [ABSTRACT FROM AUTHOR]

The climate of the eastern seaboard of Australia is strongly influenced by the passage of low pressure systems over the adjacent Tasman Sea due to their associated precipitation and their potential to develop into extreme weather events. The aim of this study is to quantify differences in the climatology of east coast lows derived from the use of six global reanalyses. The methodology is explicitly designed to identify differences between reanalyses arising from differences in their horizontal resolution and their structure (type of forecast model, assimilation scheme, and the kind and number of observations assimilated). As a basis for comparison, reanalysis climatologies are compared with an observation-based climatology. Results show that reanalyses, specially high-resolution products, lead to very similar climatologies of the frequency, intensity, duration, and size of east coast lows when using spatially smoothed (about 300-km horizontal grid meshes) mean sea level pressure fields as input data. Moreover, at these coarse horizontal scales, monthly, interannual, and spatial variabilities appear to be very similar across the various reanalyses with a generally stronger agreement between winter events compared with summer ones. Results also show that, when looking at cyclones using reanalysis data at their native resolution (approaching 50-km grid spacing for the most recent products), uncertainties related to the frequency, intensity, and size of lows are very large and it is not clear which reanalysis, if any, gives a better description of cyclones. Further work is needed in order to evaluate the usefulness of the finescale information in modern reanalyses and to better understand the sources of their differences. [ABSTRACT FROM AUTHOR]

This study investigates the ability of a regional climate model (RCM) to simulate the diurnal cycle of precipitation over southeast Australia, to provide a basis for understanding the mechanisms that drive diurnal variability. When compared with 195 observation gauges, the RCM tends to simulate too many occurrences and too little intensity for precipitation events at the 3-hourly time scale. However, the overall precipitation amounts are well simulated and the diurnal variability in occurrences and intensities are generally well reproduced, particularly in spring and summer. In terms of precipitation amounts, the RCM overestimated the diurnal cycle during the warmer months but was reasonably accurate during winter. The timing of the maxima and minima was found to match the observed timings well. The spatial pattern of diurnal variability in the Weather Research and Forecasting model outputs was remarkably similar to the observed record, capturing many features of regional variability. The RCM diurnal cycle was dominated by the convective (subgrid scale) precipitation. In the RCM the diurnal cycle of convective precipitation over land corresponds well to atmospheric instability and thermally triggered convection over large areas, and also to the large-scale moisture convergence at 700 hPa along the east coast, with the strongest diurnal cycles present where these three mechanisms are in phase. [ABSTRACT FROM AUTHOR]

The authors propose that a heat-driven circulation from the Zagros Plateau has a significant impact on the climate of the Middle East Plain (MEP), especially summertime winds, air temperature, and aridity. This proposal is examined in numerical experiments with a regional climate model. Simulations in which the Zagros Plateau was assigned a highly reflective, “snowlike” albedo neutralized the heat-driven circulation and produced an extra summertime warming of 1°–2°C in the MEP, measured relative to a control simulation and to the records of the NCEP–NCAR reanalysis project. This effect was largest in midsummer, when heating on the plateau was greatest. Additionally, simulations with high albedo on the Zagros showed reduced subsidence and enhanced precipitation in the MEP. These sensitivities are interesting because the Zagros Plateau lies downwind of the MEP. Analysis of model results indicates that the sensitivity of the upwind subsidence region to Zagros albedo can be understood as a linear atmospheric response to plateau heating, communicated upwind by a steady heat-driven circulation that influences the thermodynamic balance of the atmosphere. This regional phenomenon adds to the large-scale subsidence patterns established by the Hadley circulation and the Asian monsoon. Observed patterns of vertical motion in the Middle East, then, are a combined product of Zagros-induced subsidence and hemispheric-scale circulations. [ABSTRACT FROM AUTHOR]

The Euphrates Plain (EP) experiences large interannual variability in vegetation cover, especially in areas of marginal rain-fed agriculture. Vegetation in this region is primarily limited by available soil moisture, as determined by winter precipitation, spring precipitation, and air temperature. Satellite analyses indicate that the springtime normalized difference vegetation index (NDVI) is negatively correlated with surface albedo, and that interannual variability in albedo in the EP produces an estimated forcing on the radiation balance that peaks at 16.0 W m-2 in May. Simulations with a regional climate model indicate that surface energy fluxes during a drought year (1999) differed substantially from those during a year with normal precipitation (2003). These differences were geographically specific, with the EP exhibiting increased albedo and decreased sensible heat flux while the neighboring Zagros Plateau region showed no albedo effect, a large increase in sensible heat flux, and an offsetting reduction in latent heat flux. In both the EP and the Zagros there was a potential for positive feedbacks on temperature and drought in late spring, though the most likely feedback mechanisms differed between the two regions: in the EP surface brightening leads to cooling and reduced turbulent heat flux, while in the Zagros region reduced latent heat flux leads to warming and a deepening of the planetary boundary layer. [ABSTRACT FROM AUTHOR]

Presently, there is no standardized framework or metrics identified to assess regional climate model precipitation output. Because of this, it can be difficult to make a one-to-one comparison of their performance between regions or studies, or against coarser-resolution global climate models. To address this, we introduce the first steps toward establishing a dynamic, yet standardized, benchmarking framework that can be used to assess model skill in simulating various characteristics of rainfall. Benchmarking differs from typical model evaluation in that it requires that performance expectations are set a priori. This framework has innumerable applications to underpin scientific studies that assess model performance, inform model development priorities, and aid stakeholder decision-making by providing a structured methodology to identify fit-for-purpose model simulations for climate risk assessments and adaptation strategies. While this framework can be applied to regional climate model simulations at any spatial domain, we demonstrate its effectiveness over Australia using high-resolution, 0.5° × 0.5° simulations from the CORDEX-Australasia ensemble. We provide recommendations for selecting metrics and pragmatic benchmarking thresholds depending on the application of the framework. This includes a top tier of minimum standard metrics to establish a minimum benchmarking standard for ongoing climate model assessment. We present multiple applications of the framework using feedback received from potential user communities and encourage the scientific and user community to build on this framework by tailoring benchmarks and incorporating additional metrics specific to their application. Significance Statement: We introduce a standardized benchmarking framework for assessing the skill of regional climate models in simulating precipitation. This framework addresses the lack of a uniform approach in the scientific community and has diverse applications in scientific research, model development, and societal decision-making. We define a set of minimum standard metrics to underpin ongoing climate model assessments that quantify model skill in simulating fundamental characteristics of rainfall. We provide guidance for selecting metrics and defining benchmarking thresholds, demonstrated using multiple case studies over Australia. This framework has broad applications for numerous user communities and provides a structured methodology for the assessment of model performance. [ABSTRACT FROM AUTHOR]

Accurate estimates of terrestrial water and energy cycle components are needed to better understand climate processes and improve models' ability to simulate future change. Various observational estimates are available for the individual budget terms; however, these typically show inconsistencies when combined in a budget. In this work, a Conserving Land–Atmosphere Synthesis Suite (CLASS) of estimates of simultaneously balanced surface water and energy budget components is developed. Individual CLASS variable datasets, where possible, 1) combine a range of existing variable product estimates, and hence overcome the limitations of estimates from a single source; 2) are observationally constrained with in situ measurements; 3) have uncertainty estimates that are consistent with their agreement with in situ observations; and 4) are consistent with each other by being able to solve the water and energy budgets simultaneously. First, available datasets of a budget variable are merged by implementing a weighting method that accounts both for the ability of datasets to match in situ measurements and the error covariance between datasets. Then, the budget terms are adjusted by applying an objective variational data assimilation technique (DAT) that enforces the simultaneous closure of the surface water and energy budgets linked through the equivalence of evapotranspiration and latent heat. Comparing component estimates before and after applying the DAT against in situ measurements of energy fluxes and streamflow showed that modified estimates agree better with in situ observations across various metrics, but also revealed some inconsistencies between water budget terms in June over the higher latitudes. CLASS variable estimates are freely available via https://doi.org/10.25914/5c872258dc183. [ABSTRACT FROM AUTHOR]

Six weather types (WTs) are computed for tropical Australia during the wet season (November–March 1979–2015) using cluster analysis of 6-hourly low-level winds at 850 hPa. The WTs may be interpreted as a varying combination of at least five distinct phenomena operating at different time scales: the diurnal cycle, fast and recurrent atmospheric phenomena such as transient low pressure, the intraseasonal Madden–Julian oscillation, the annual cycle, and interannual variations mostly associated with El Niño–Southern Oscillation. The WTs are also strongly phase-locked onto the break/active phases of the monsoon; two WTs characterize mostly the trade-wind regime prevalent either at the start and the end of the monsoon or during its breaks, while three monsoonal WTs occur mostly during its core and active phases. The WT influence is strongest for the frequency of wet spells, while the influence on intensity varies according to the temporal aggregation of the rainfall. At hourly time scale, the climatological mean wet intensity tends to be near-constant in space and not systematically larger for the monsoonal WTs compared to other WTs. Nevertheless, one transitional WT, most prevalent around late November and characterized by weak synoptic forcings and overall drier conditions than the monsoonal WTs, is associated with an increased number of high hourly rainfall intensities for some stations, including for the interior of the Cape York Peninsula. When the temporal aggregation exceeds 6–12 h, the mean intensity tends to be larger for some of the monsoonal WTs, in association with more frequent and also slightly longer wet spells. [ABSTRACT FROM AUTHOR]

Two questions motivated this study: 1) Will meteorological droughts become more frequent and severe during the twenty-first century? 2) Given the projected global temperature rise, to what extent does the inclusion of temperature (in addition to precipitation) in drought indicators play a role in future meteorological droughts? To answer, we analyzed the changes in drought frequency, severity, and historically undocumented extreme droughts over 1981–2100, using the standardized precipitation index (SPI; including precipitation only) and standardized precipitation-evapotranspiration index (SPEI; indirectly including temperature), and under two representative concentration pathways (RCP4.5 and RCP8.5). As input data, we employed 103 high-resolution (0.44°) simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX), based on a combination of 16 global circulation models (GCMs) and 20 regional circulation models (RCMs). This is the first study on global drought projections including RCMs based on such a large ensemble of RCMs. Based on precipitation only, ~15% of the global land is likely to experience more frequent and severe droughts during 2071–2100 versus 1981–2010 for both scenarios. This increase is larger (~47% under RCP4.5, ~49% under RCP8.5) when precipitation and temperature are used. Both SPI and SPEI project more frequent and severe droughts, especially under RCP8.5, over southern South America, the Mediterranean region, southern Africa, southeastern China, Japan, and southern Australia. A decrease in drought is projected for high latitudes in Northern Hemisphere and Southeast Asia. If temperature is included, drought characteristics are projected to increase over North America, Amazonia, central Europe and Asia, the Horn of Africa, India, and central Australia; if only precipitation is considered, they are found to decrease over those areas. [ABSTRACT FROM AUTHOR]

The Middle East and southwest Asia are a region that is water stressed, societally vulnerable, and prone to severe droughts. Large-scale climate variability, particularly La Niña, appears to play an important role in regionwide droughts, including the two most severe of the last 50 years-1999-2001 and 2007/08-with implications for drought forecasting. Important dynamical factors include orography, thermodynamic influence on vertical motion, storm-track changes, and moisture transport. Vegetation in the region is strongly impacted by drought and may provide an important feedback mechanism. In future projections, drying of the eastern Mediterranean region is a robust feature, as are temperature increases throughout the region, which will affect evaporation and the timing and intensity of snowmelt. Vegetation feedbacks may become more important in a warming climate. There are a wide range of outstanding issues for understanding, monitoring, and predicting drought in the region, including dynamics of the regional storm track, the relative importance of the range of dynamical mechanisms related to drought, the regional coherence of drought, the relationship between synoptic-scale mechanisms and drought, the predictability of vegetation and crop yields, the stability of remote influences, data uncertainty, and the role of temperature. Development of a regional framework for cooperative work and dissemination of information and existing forecasts would speed understanding and make better use of available information. [ABSTRACT FROM AUTHOR]