Abstract

On the night of 27–28 August 1985, a cloud band associated with a cold front dramatically broadened over southeastern Australia, leading to unforecast rain and overforecast daytime temperatures.

This paper presents a detailed synoptic description of this event, describes the vertical circulations leading to cloud band development, and, by means of back trajectory analysis, determines the origins of air parcels entering the cloud band.

The analyses which were used in this diagnostic study were prepared using an intermittent insertion incremental limited-area data assimilation system. The consistency and coherence of the diagnostic quantities calculated from these analyses demonstrates the value of linking the analyses with a dynamic forecast model, even with the relatively coarse resolution of 250 km used in this study.

It is shown that, following the reorganization of the jet patterns over Western Australia (WA), pressure falls lead to an amplification of the surface pressure trough and the acceleration of both the southerly flow west of the trough and the northerly flow east of the trough. The thermal gradient increased over WA in this period under the influence of the increased convergence and increased deformation associated with these flows, which themselves were strongly influenced by the direct vertical transverse circulation at the jet entrance region. Back trajectory analysis shows that air parcels which formed the developing part of the cloud band had their origins in the boundary layer over central Australia and moved into the ascending warm conveyer belt as a northeasterly isallobaric flow towards the rising branch of the vertical circulation at the jet entrance and thereafter ascended at a rate of up to 330 hPa day⁻¹.

Abstract

The data from a 9-day period of SOP-2 were analyzed at 6 h intervals using a fully automatic limited-area variational objective analysis system, with a primitive equations prognosis model providing guess fields for each analysis and thus maintaining time continuity between analyses. It is demonstrated that the scheme produced a set of analyses which showed a stable, consistent evolution of the synoptic systems throughout the period. This would not have been possible without manual intervention prior to FGGE.

Twenty-four hour prognoses based on these analyses showed, on average, equal or slightly greater skill than the equivalent operational prognoses which had access to a similar (although somewhat less timely) data base, as well as having manual input.

The entire experiment was repeated using updated rather than fixed boundary conditions during each 6 h prognosis, with the boundary tendencies being obtained from a hemispheric assimilation experiment. It is shown that this produced a small but significant improvement in the quality of the overall analysis system.

Abstract

A previously reported 9-day limited area data assimilation experiment has been reported, incorporating a recently developed nonlinear vertical mode initialization scheme. It is shown that the initialization scheme significantly reduces surfaces pressure oscillations during the model integration, producing more accurate guess fields for each analysis. It is demonstrated, by means of objective verification statistics and by means of a case study, that these more accurate guess fields result in improved analyses and a small increase in skill of 24 h prognoses based on these analyses.

Abstract

A new limited-area data assimilation system has been developed in the BMRC for operational use by the Australian Bureau of Meteorology. The system analyzes deviations from a primitive equations model forecast, using two-dimensional univariate statistical interpolation (SI) to analyze mass, and three-dimensional univariate SI to analyze wind data. Mass and wind increment analyses may mutually influence the other using variational techniques.

Analysis increments are vertically interpolated to prognosis model sigma surfaces, added to the forecast variables, and the model integrated forward to the next analysis time. This ongoing analysis-forecast cycle is now being implemented operationally.

This paper describes in detail the analysis methodology, and presents results from a 17-day trial period. The analyses are compared with operationally prepared analyses for the same period individually, as means, and by data fitting statistics. It is shown that the assimilated analyses have stronger jet streams and greatly improved detail in the moisture analyses. It is also shown that vertical motion patterns in the guess fields are preserved through the analysis initialization phase of the assimilation cycle, and that these vertical motion fields correlate well with the areas of cloud seen in satellite imagery.

Prognoses from this trial period show a much more rapid spinup of forecast rainfall rate than did a series of control forecasts based on operational analyses, and both mean rainfall for the 17-day period and individual cases are presented to demonstrate improved skill of forecasts from the assimilated analyses. Objective verification of mass-field forecasts showed considerable sensitivity of the forecasts to the particular set of bogus mean sea level pressure data used in the analysis; however, preliminary verification statistics from the first 15 days of operational parallel running showed that the assimilation system produced forecasts of similar skill to operational forecasts of MSLP at 24 hours, but greater skill at the upper levels, and had greater skill at all levels for the 36-hour forecast.

Abstract

Anthropogenic climate change is likely to be felt most acutely through changes in the frequency of extreme meteorological events. However, quantifying the impact of climate change on these events is a challenge because the core of the climate change science relies on general circulation models to detail future climate projections, and many of these extreme events occur on small scales that are not resolved by climate models. This note describes an attempt to infer the impact of climate change on one particular type of extreme meteorological event—the cool-season tornadoes of southern Australia. The Australian Bureau of Meteorology predicts threat areas for cool-season tornadoes using fine-resolution numerical weather prediction model output to define areas where the buoyancy of a near-surface air parcel and the vertical wind shear each exceed specified thresholds. The diagnostic has been successfully adapted to coarser-resolution climate models and applied to simulations of the current climate, as well as future projections of the climate over southern Australia. Simulations of the late twentieth century are used to validate the models’ ability to reproduce the climatology of the risk of cool-season tornado formation by comparing these with similar computations based on historical reanalyses. Model biases are overcome by setting model specific thresholds to define the cool-season tornado risk. The diagnostic, applied to simulations of the twenty-first century, is then used to quantify the impact of the projected climate change on cool-season tornado risk. The sign of the response is consistent across all models: a decrease of the risk of formation during the twenty-first century is projected, driven by the thermodynamical response. The thermal response is modulated by the dynamical response, which varies between models. The projected decrease in tornadoes risk during the cool season is consistent with the projection of positive southern annular mode trends and the known influence of this mode of variability on interannual to intraseasonal time-scale variations in cool-season tornado occurrence.

Abstract

The output from the Australian operational regional numerical weather prediction model has been used to provide input thermodynamic and kinematic fields to a decision tree designed to diagnose the likelihood of thunderstorms and whether the thunderstorm environment is conducive to the development of severe, supercell, or tornadic supercell thunderstorms. On targeted cases of observed severe weather described in this paper the system successfully diagnoses severe thunderstorms and appears to discriminate between tornadic and nontornadic cases.

It is shown that the thunderstorm decision tree of Colquhoun has considerable potential, when coupled with a regional NWP model, to provide forecast guidance of areas of thunderstorms, severe thunderstorms, tornadic thunderstorms, and whether these storms are likely to be associated with flash floods, downbursts, strong winds, etc. The results from targeted severe weather case studies show a very good degree of correspondence with the location and type of severe weather observed, and if these results were to be replicated in operational practice, the system would be of great benefit to weather forecast teams. The results of a 33-day trial indicate that the results from the case studies did not occur due to excessive overprediction, with a relatively low number of false alarms and relatively high number of hits based on the admittedly fairly loose subjective criterion for a hit.

These results indicate that the system may provide a useful alerting system to form the basis of the definition of thunderstorm watch areas in operational practice in Australia.

Abstract

The Model output Statistics (MOS) technique has been used to produce forecasts of both the probability of precipitation and the rain amount for seven major Australian cities in subtropical and middle latitudes. Single station equations were generated using data from the current objective analysis, together with some surface observations for the same time, and a 24 h prognosis based on that analysis, to predict the rainfall in the 24 h beyond the prognosis validity time.

In order to increase the usefulness and acceptability of the MOS predictions, transformations were applied that reduced the biases of the final forecasts throughout the forecast ranges. The skid with which large rainfall totals were predicted was particularly enhanced in this manner the MOS forecasts showed much greater skill in the prediction of large totals than was achieved by either the operational or persistence forecasts, while predicting small totals with comparable proficiency.

The MOS probability forecasts were better able to predict rainfall occurrence than were the quantitative MOS forecasts, and additionally were superior in this regard to both subjective forecasts produced operationally and predictions based on persistence. The overall skill of the quantitative precipitation forecasts was further enhanced by using the probability estimates to provide a categorical prediction of rain occurrence such that a rain amount was only forecast if the predicted probability of precipitation exceeded 50%.

Routine issuance of the MOS guidance to the operational forecasters commenced in January 1984.

To test the impact of high-resolution Nimbus-6 sounding data on Australian region forecasts, two parallel analysis/forecast cycling experiments were carried out, using data for 14 days during August and September 1975. In one of these cycles, only conventional data and manual interpretation of satellite imagery were used as input, while the other cycle used conventional and Nimbus-6 sounding data. A manual mean sea level pressure analysis was used in each cycle to provide reference level information over the oceans.

Two series of 24 h limited area prognoses were prepared from these two sets of analyses, using the primitive equations prognosis model developed at the Australian Numerical Meteorology Research Centre. An average improvement in geopotential forecasts of more than 5 skill score points was achieved at all levels over the Australian continent when the Nimbus-6 data were included in the base analyses. Also, significant reductions were obtained in 24 h forecast root-mean-square (rms) temperature errors.

Abstract

The World Urban Database and Access Portal Tools (WUDAPT) is an international community-based initiative to acquire and disseminate climate relevant data on the physical geographies of cities for modeling and analysis purposes. The current lacuna of globally consistent information on cities is a major impediment to urban climate science toward informing and developing climate mitigation and adaptation strategies at urban scales. WUDAPT consists of a database and a portal system; its database is structured into a hierarchy representing different levels of detail, and the data are acquired using innovative protocols that utilize crowdsourcing approaches, Geowiki tools, freely accessible data, and building typology archetypes. The base level of information (L0) consists of local climate zone (LCZ) maps of cities; each LCZ category is associated with a range of values for model-relevant surface descriptors (roughness, impervious surface cover, roof area, building heights, etc.). Levels 1 (L1) and 2 (L2) will provide specific intra-urban values for other relevant descriptors at greater precision, such as data morphological forms, material composition data, and energy usage. This article describes the status of the WUDAPT project and demonstrates its potential value using observations and models. As a community-based project, other researchers are encouraged to participate to help create a global urban database of value to urban climate scientists.

Abstract

The Observing System Research and Predictability Experiment (THORPEX) was a 10-yr, international research program organized by the World Meteorological Organization’s World Weather Research Program. THORPEX was motivated by the need to accelerate the rate of improvement in the accuracy of 1-day to 2-week forecasts of high-impact weather for the benefit of society, the economy, and the environment. THORPEX, which took place from 2005 to 2014, was the first major international program focusing on the advancement of global numerical weather prediction systems since the Global Atmospheric Research Program, which took place almost 40 years earlier, from 1967 through 1982. The scientific achievements of THORPEX were accomplished through bringing together scientists from operational centers, research laboratories, and the academic community to collaborate on research that would ultimately advance operational predictive skill. THORPEX included an unprecedented effort to make operational products readily accessible to the broader academic research community, with community efforts focused on problems where challenging science intersected with the potential to accelerate improvements in predictive skill. THORPEX also collaborated with other major programs to identify research areas of mutual interest, such as topics at the intersection of weather and climate. THORPEX research has 1) increased our knowledge of the global-to-regional influences on the initiation, evolution, and predictability of high-impact weather; 2) provided insight into how predictive skill depends on observing strategies and observing systems; 3) improved data assimilation and ensemble forecast systems; 4) advanced knowledge of high-impact weather associated with tropical and polar circulations and their interactions with midlatitude flows; and 5) expanded society’s use of weather information through applied and social science research.