The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

Proposal to Ministry of Earth Sciences, Government of India"Monsoon Mission"

Revision 1 – 18 December 2012

Evaluation and Improvement of the Unified Model for Short- and Medium-Range Prediction

of Monsoon Rain Systems

The Centre for Australian Weather and Climate ResearchA partnership between CSIRO and the Bureau of Meteorology

1. Title of the proposed project :

Evaluation and Improvement of the Unified Model for Short- and Medium-Range Prediction of Monsoon Rain Systems

2. Brief information about Principal Investigator (PI) and Co-PI(s) :

PI:Name:- Dr. Elizabeth EbertDate of birth:- 24 February 1960Institution:- CAWCROfficial website:- http://cawcr.gov.au/, http://cawcr.gov.au/staff/eee/ E-mail Id:- e.ebert@bom.gov.au Qualification:- PhD (Meteorology)

Co - PI (1):Name:- Dr. Noel DavidsonDate of birth:- 10 December 1948Institution:- CAWCROfficial website:- http://cawcr.gov.au/E-mail Id:- n.davidson@bom.gov.au Qualification:- PhD (Mathematical Sciences)

Co - PI (2):Name:- Dr. Kamal PuriDate of birth:- 3 August 1945Institution:- CAWCROfficial website:- http://cawcr.gov.au/E-mail Id:- k.puri@bom.gov.au Qualification:- PhD (Physics)

Project Director:Name:- Dr. E.N. RajagopalInstitution:- NCMRWFOfficial website:- http://www.ncmrwf.gov.in E-mail Id:- rajagopal@ncmrwf.gov.in Qualification:- PhD

3. Project Summary (1 page) :

(a) Intellectual merits of the proposed work

Fundamental components of the tropical circulation over India and Australia during summer are the monsoon, tropical cyclones and monsoon depressions. They produce much of the rainfall over these regions, and occasionally are associated with heavy rain and high impact weather. However rainfall, particularly heavy rainfall, is difficult to

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forecast and predictions are sensitive to components of numerical forecast systems. It is thus necessary to study prediction of these events in detail and also quantify the uncertainties in the forecasts.

The aims of this project are to improve prediction of heavy rain events and to provide information on the reliability of the predictions. Even though research has been conducted on these phenomena (e.g., Davidson et al. 1998, Bohra et al. 2006) our understanding and prediction of these weather phenomena are still somewhat limited. It is our belief that the numerical experimentation planned for this project will improve both our prediction and understanding of these weather phenomena.

The proposal described here provides an end-to-end research plan for:

1. Model verification and diagnostic evaluation of the current state-of-the-art of rainfall prediction for the monsoon and embedded weather systems.

2. Numerical experimentation and sensitivity studies of selected rain events (e.g., monsoon onset, monsoon depressions, cyclones).

3. Application of ensemble methods to quantify the uncertainties in prediction of heavy rain.

The numerical system to be used is the UK Met Office's Unified Model (UM) as implemented at NCMRWF, India and CAWCR, Australia. The use of a common modelling framework means that improvements in tropical rainfall prediction achieved through this work will benefit both partners, and indeed, the larger community of UM users. The application of advanced verification methods will better diagnose the sources and nature of the errors, thus providing information that is useful to modellers for targeting model improvements, and to forecasters when interpreting model output as part of the operational forecast process. This proposal also explores the nature of, and potential enhancements to, the predictability of monsoon weather through ensemble prediction.

(b) Broader impacts of the proposed work

Improved prediction of monsoon, tropical cyclones and monsoon depressions will be of social, humanitarian, financial and scientific benefit to India and Australia by reducing the loss of life and property resulting from poor prediction of high impact weather. This will result from model improvements leading to greater accuracy, and also from quantitative uncertainty estimates enabling more informed decision making.

The proposed collaboration will strengthen scientific ties between India and Australia, specifically enabling both NCMRWF and CAWCR to jointly build their capability in numerical weather prediction and monsoon rainfall processes, and more broadly, helping to pave the way to a deep and productive relationship in coming years.

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Project Description:

1. Research Objectives

The summer monsoon, including monsoon lows, depressions, and cyclones, is the main source of rainfall in the tropical regions of India and Australia. However, our ability to accurately forecast these circulations is hampered by gaps in our understanding of these flows, incomplete observations of the atmospheric and surface state, and limitations in the abilities of numerical models to simulate the relevant processes.

The objective of this proposal is to improve the numerical prediction of tropical heavy rain associated with the monsoon circulations in short to medium range (1- to 5-day) forecasts from the Unified Model (UM), which has been adopted by both the NCMRWF and CAWCR for numerical weather prediction (NWP).

The proposed strategy is to first understand the systematic nature of the model's rainfall errors in order to target areas for improvement, then conduct numerical experimentation on a selection of tropical severe weather cases to investigate and improve the model's physical processes. The potential of ensemble forecasting to enhance prediction of tropical heavy rain in the medium range will also be explored. Both the Indian and Australian UM implementations over both countries' tropical domains will be employed to increase the model and observation data available to the project, and ensure that the collaboration provides the greatest benefit for the partner agencies.

Specifically, we propose to address the following questions:

(1) What is the magnitude and nature of rainfall prediction errors from the UM for the monsoon onset, and for organised weather systems such as monsoon depressions and tropical cyclones in Australia and India?

The first step in improving the model is to understand the nature of the errors. This component of the project will implement a suite of diagnostic verification techniques developed in CAWCR (Ebert and McBride 2000; Ebert 2008) and use them to establish a benchmark against which model improvements can be measured.

CAWCR and NCMRWF will jointly examine the performance of the global and regional UM over India and tropical Australia for two monsoon seasons in 2011 and 2012, which is sufficient to get a good picture of systematic errors in the model. The model's rainfall performance will be quantitatively assessed as a function of rain intensity, model lead time, and synoptic type and scale (synoptic, sub-synoptic, mesoscale, orographic), using daily rain gauge analyses as ground truth.

In addition to the traditional metrics normally used in NWP evaluation, diagnostic spatial verification approaches will be applied to analyse the sources of model error (e.g., location errors due to errors in model dynamics, intensity and structural errors related to model physics). Forecasters will be provided with accuracy information on the UM to help guide their use of the model output, and their subjective evaluations of the model rainfall will also be assessed. The evaluation of global and regional models from both centres will also offer insight into the impact of different model resolutions and initalisation approaches on the rainfall performance.

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(2) What is the sensitivity of rainfall prediction in the UM to (a) system resolution, (b) physical parameterizations of moist processes, surface properties (sea surface temperature, soil moisture), boundary layer exchange and radiation?

In order to optimise the performance of the UM, numerical experiments must be conducted to understand its sensitivity to the grid resolution and to the parameterizations used to represent the physical processes involved in convection and rainfall generation. This requires much greater focus on the details of the simulations, and is better done in case study mode. We will select some interesting cases of monsoon heavy rainfall, which will include monsoon depressions and tropical cyclones, and conduct a detailed examination of the structure of the clouds and rainfall. We will use traditional and spatial diagnostic approaches to evaluate surface rainfall, and TRMM, CloudSat and CALIPSO data for validating the model cloud and rain vertical profiles.

The process of closely examining the model output could lead to improved understanding of monsoon rainfall structure and evolution, and to the development of some diagnostics that could be used for characterising and evaluating the simulations.

(3) What additional value, in terms of understanding predictability and providing advance warning and decision support for tropical heavy rain, is possible through the use of ensemble prediction?

For lead times beyond the short range, the predictability of the atmosphere is much lower and single model runs are accompanied by a large amount of uncertainty. Ensemble prediction is a widely used strategy for exploring the predictability of the weather under different conditions, and for generating a suite of uncertainty products to accompany the forecast in order to provide information to assist decision makers in mitigating risk.

NCMRWF plans to implement the MOGREPS (Met Office Global and Regional Ensemble Prediction System), based on the UM, during the time of this proposal. CAWCR has already implemented this ensemble system (called AGREPS) in experimental mode, and is investigating its ability to provide advance warnings of high impact weather in Australia. We will produce scenario and probabilistic forecasts of monsoon rainfall from MOGREPS in hindcast mode, and work with NCMRWF to evaluate its ability to produce reliable and skilful forecasts of tropical heavy rain in the medium range.

1.1 Intellectual merit of the proposed work

This proposal addresses a fundamental need of the Indian government to have access to the most timely and accurate predictions of monsoon weather and rainfall for use in water resource management, public safety, agriculture, industry, etc. A decision has been made to implement the Met Office Unified Model, which is among the top two or three atmospheric models available in the world. However, it is not possible simply to import the model and start running it and expect it to produce accurate forecasts. A significant amount of testing of configurations and settings, as well as development of improved model parameterizations, is required to achieve optimal performance from the model. In the Australian context, CAWCR scientists put in a considerable and continuing effort to improve the ACCESS model (our implementation of the UM), which became operational in 2009 and is now undergoing a major upgrade.

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Beyond the technical aspects of model implementation, which are not insignificant, a large amount of scientific work is involved. There must be continual assessment of the quality of the model's predictions during the development cycle to identify real improvements. This proposal calls for the implementation of state-of-the-art verification methods that go beyond simply quantifying the errors, to better diagnose the sources and nature of the errors, thus providing information that is useful to modellers for targeting model improvements, and to forecasters when interpreting model output as part of the operational forecast process.

Achieving the greatest accuracy from the model calls for experimentation in several areas. Most straightforward are tests of different model resolutions, which enable scientists to evaluate the benefits of finer resolution on the representation of physical processes and their interactions with local topography, as well as the increased computing resources required to achieve those finer scale predictions. Tests of the model's physical parameterizations are more complex, and require scientists to have a strong knowledge of the physical processes themselves. The UM has not been optimised for tropical prediction, so special attention to tropical convection and monsoon processes is needed. As seasonal and intraseasonal predictability is largely driven by low latitude processes, efforts in this area are doubly important. This proposal addresses the need for better simulation of low latitude processes by conducting numerical experimentation to improve the representation of physical processes related to monsoon rainfall.

Forecast uncertainty increases with time into the forecast. This is particularly true at lower latitudes where the scales of meteorological forcing are often much smaller and weaker than in mid-latitudes, making them more difficult for models to predict. Quantifying this uncertainty is important for making best use of the forecasts. Ensemble prediction is the paradigm used by the major global meteorological centres to lengthen the useful duration of a forecast by providing quantitative uncertainty information in the form of scenarios and probabilistic forecasts. This proposal explores how the predictability of monsoon weather could potentially be enhanced through ensemble prediction by assessing the quality of UM-based ensemble rainfall forecasts.

1.2 Broader Impact of proposed work

The direct impacts of this research will be to

provide internal and external users of UM numerical forecasts with quantitative information on the accuracy and uncertainty associated with model forecasts of monsoon rainfall in the short- to medium-range (1-5 days), thus enabling more informed use of UM-based products, and establishing a baseline against which model improvements can be assessed.

focus NCMRWF's and CAWCR's scientific efforts on determining optimum model configurations and improving its physical processes, leading to improved model accuracy of monsoon-related heavy rain,

lengthen the useful lead time of forecasts through ensemble prediction.

Broader impacts of this research include

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providing NCMRWF expertise in tropical processes, as well as data and model improvements, to the consortium of users of the Unified Model, thus improving tropical prediction capability for all users,

strengthening ties between NCMRWF and CAWCR, thus enhancing bilateral scientific exchange,

capacity building through challenging and collaborative research.

social and economic benefit due to reduced loss of life and property through improved prediction of monsoon, tropical cyclones and monsoon depressions.

2. Research methods

2.1 The Unified Model at NCMRWF and CAWCR

Both CAWCR and NCMRWF use the Met Office Unified Model (UM) and data assimilation system which incorporates three-dimensional and four-dimensional variational data assimilation (3DVAR and 4DVAR). The two systems are referred to as the Met Office Unified Modelling Systems (UMS). Detailed justification of the UMS for ACCESS and key references are given in Puri (2012).

The UM forms the atmospheric module of the fully coupled earth system model, the Australian Community Climate and Earth System Simulator (ACCESS), that has been jointly developed by the Bureau of Meteorology and CSIRO within CAWCR. ACCESS takes a national approach to climate and weather prediction model development that is grounded on well-engineered and realistically achievable software and supported by high quality IT infrastructure. For CAWCR the Met Office systems, together with components developed at the Bureau and CSIRO, offer considerable advantages for applications to both weather prediction and climate/climate change research. Some of the key features of the UMS include (i) use of governing equations that are non-hydrostatic, (ii) use of a semi-implicit/semi-Lagrangian scheme to solve the governing equations, (iii) design of the dynamical core that includes conservation of mass, mass-weighted potential temperature and moisture, and angular momentum, and (iv) a number of alternative formulations for the physical parametrisations. Atmospheric data assimilation using a variational scheme (incorporating 3DVAR and 4DVAR) is designed to be used by both global and limited area models. A further key feature of the UMS is that it can be used for both global and limited area domains and hence can be used across space scales ranging from mesoscale to large (climate) scales. Finally the Met Office NWP and climate models are recognized as leading models in the field.

At NCMRWF, Observation Processing System (OPS, Version 27.1.0), four dimensional variational data assimilation system (4D-VAR, Version 27.1.0) and Unified Model (UM, Version 7.7) are the main components of the Unified Model global forecast suite. The OPS prepares quality controlled observations for 4D-VAR in the desired format. 4D-VAR system produces the analysis, which is the best estimate of the atmospheric state, used as the initial condition for the UM forecast. The OPS system processes and packs six hourly data, centered at 00, 06, 12 and 18 UTC for the four data assimilation cycles (00, 06, 12 & 18 UTC cycles). The 4D-VAR data assimilation is carried out for all cycles

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to produce the analysis valid for these cycles. The UM short forecast run are also carried out based on this analysis for all the four cycles, which in turn are used as the background (first guess) for the next cycle in OPS and 4D-VAR. A deterministic 168 hr forecast is prepared everyday based on 00 UTC analysis.

2.2 Diagnostic verification methods for rainfall

When verifying forecasts of rain systems, any error in the location of the rainfall will usually lead to very poor apparent performance using traditional metrics, even if the forecast was otherwise skilful according to a forecaster's or modellers' subjective judgement. As the grid spacing of numerical models has become increasingly finer, the impact of small location errors becomes more pronounced (Mass et al. 2002).

In recent years new verification approaches have been developed to assess gridded forecasts in a spatial sense, to better replicate human judgements about their skill. CAWCR has been active in the development of two types of spatial verification. The Contiguous Rain Area (CRA) method of Ebert and McBride (2000) verifies properties of whole rain systems. After first determining the location error, the total error for the rain system can be decomposed into components due to location, intensity, and pattern errors. Their relative magnitudes give clues as to the sources of forecast errors, whether they are likely due to dynamical errors (incorrect location) or errors in physical processes (intensity and pattern errors). Forecast rain systems can also be classified as "hits", "near hits", "near misses", "misses" and "false alarms" according to their performance, which is a useful and intuitive interpretation for forecasters.

Neighborhood (a.k.a. "fuzzy") verification methods give credit for rain forecasts that are skilful on slightly larger scales, but do not precisely match the grid-scale spatial distribution of rain. By verifying the forecast rain aggregated over increasingly large neighborhoods (grid scale, 3x3 grid boxes, 5x5 grid boxes, etc.) it is possible to diagnose the scale at which the model has sufficient skill to be considered useful. It also allows models at different resolutions to be compared on a common spatial scale. Ebert (2008) combined a large number of neighborhood verification methods from the published literature into a single framework that provides a variety of scale-dependent information on model performance.

NCMRWF has experience in verifying quantitative precipitation forecasts using traditional verification approaches (Ashrit et al. 2009; Iyengar et al., 2010; Ashrit 2012). We will assist with implementing the CRA method and the neighborhood verification framework at NCMRWF and applying them to the UM monsoon rainfall forecasts to provide additional diagnostic information on model performance. Observational data will include rain gauge measurement and analyses over land, and TRMM-based multi-satellite precipitation estimates (over the sea). Merged satellite-gauge gridded data (Mitra et al., 2009) will also be used as observation.

2.3 Numerical investigation of UM

Following detailed objective verification of baseline UM forecasts of the monsoon and associated rainfall, identification of systematic errors in the forecasts, and subjective

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evaluation of potential sources of deficiencies in the forecasts, a set of numerical experiments will be designed to explore sensitivities to (i) model resolution, (ii) initialization for prediction of heavy rain events, and (iii) model parameterizations. This experimentation will focus on specific events that were high impact or poorly forecast. Depending on the nature of the systematic errors, it may involve complete re-runs of whole monsoon seasons. As part of the numerical experimentation, it would also be valuable to revise existing or develop new conceptual models of monsoon rain systems based on detailed diagnostics of monsoon structure and structure change. This would provide under-pinning diagnostics for ongoing evaluation, verification, initialization and prediction.

2.4 Ensemble prediction using MOGREPS

The MOGREPS ensemble prediction system based on the UM is designed to provide advance prediction of high impact weather with quantitative estimates of its associated uncertainty (Bowler et al. 2008). It consists of a 24-member global ensemble that runs to five days, within which is nested a 24-member finer resolution regional ensemble that predicts out to three days. Its spatial resolution is lower than that of the deterministic model to enable multiple runs to be completed in a timely manner. To represent uncertainties in the initial atmospheric state, perturbations to the initial conditions are calculated using an ensemble transform Kalman filter. Model uncertainties are accounted for using stochastic physics, which are random perturbations to the models' internal tendencies.

CAWCR has implemented MOGREPS in experimental mode. Known locally as AGREPS, this ensemble system has been running semi-routinely since 2011. Its spatial resolution is N144 (~80km), currently being upgraded to N216 (~60km) for the global system and 37.5 km, being upgraded to ~20km for the regional system located over a large domain approximately centred over Australia. When a tropical cyclone is forecast, a tracking algorithm is applied to identify the position of the cyclone in each ensemble member, from which maps of strike probability and cyclone tracks can be generated.

3. Statement of Work (methodology to be adopted)

CAWCR will provide

(a) Expertise and code for diagnostic verification of gridded rainfall forecasts

(b) Modelling and data assimilation expertise

(c) Experience using cloud and rainfall profiles from TRMM, CloudSat and CALIPSO

(d) Use of the Australian UM modelling infrastructure (ACCESS)

(e) Supercomputing resources

(f) Rain gauge observations and gridded analyses over Australia

(g) Output from ACCESS global model and AGREPS ensemble

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(h) Logistical support for visits of NCMRWF research staff to CAWCR

NCMRWF will provide

(a) Expertise in tropical meteorology

(b) Experience in model verification

(c) Research scientists to conduct the majority of the research

(d) Use of the Indian UM modelling infrastructure

(e) Supercomputing resources

(f) Rain gauge observations and gridded analyses over India

(g) Output from UM global and regional model, and MOGREPS ensemble if implemented in time for this project, and MOGREPS ensemble if implemented in time for this project

(h) Logistical support for visits of CAWCR research staff to NCMRWF

CAWCR's manpower contribution from PI Ebert and Co-PIs Davidson and Puri will include time spent collaborating on the project in CAWCR, and visits to NCMRWF. We understand that NCMRWF funding for participation in this project will be drawn from another source.

The work package is described below.

Component 1. Comprehensively evaluate UM global and regional model forecasts of rainfall in the monsoon and embedded weather using traditional and spatial verification approaches to diagnose the nature and sources of model error.

Tasks:

(a) Implementation of spatial diagnostic verification methods (CRA and neighborhood techniques) at NCMRWF.

(b) Traditional and spatial verification of model quantitative precipitation forecasts against gridded rainfall from gauges (land) and satellite estimates from TRMM and Megha-Tropiques (sea), for monsoon seasons during 2011-12 (Australia) and 2012 (India).

(c) Analysis of verification results with respect to rain intensity, model lead time, and synoptic type and scale (synoptic, sub-synoptic, mesoscale, orographic).

(d) Interpretation of verification results vis-à-vis model processes in need of improvement and utility of model QPFs in forecast office for short- and medium-range prediction.

Deliverables: Diagnostic verification methods working at NCMRWF. Dataset of verification statistics for global model predictions of tropical heavy rainfall for one wet season each in India and Australia. Journal publication and conference presentation(s) on performance of tropical heavy rainfall predictions from global and regional models.

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Component 2. Perform numerical experiments on selected rain events from Component 1 to document the sensitivity of rainfall prediction to (a) system resolution, (b) physical parameterizations of moist processes, surface properties (sea surface temperature, soil moisture), boundary layer exchange and radiation.

Tasks:

(a) Identification of a small number of cases of observed and forecast monsoon rainfall in India, including tropical cyclones and monsoon depressions.

(b) UM simulations for these cases, varying the model grid spacing and physical parameterization settings to test model sensitivity.

(c) Quantitative assessment of model rainfall output using verification methods implemented in Component 1.

(d) Assessment of modelled vertical rain and cloud profiles against space-based rain and cloud profile data from TRMM, CloudSat and CALIPSO.

(e) Identification of model configuration and settings giving the most realistic simulations for these cases.

Deliverables: Dataset of UM model rainfall spatial fields and vertical profiles, observed rainfall analyses and vertical profiles, and verification statistics for tropical heavy rain cases in India. Optimum UM model configuration and settings.

Component 3. Using the MOGREPS ensemble, investigate the predictability of monsoon heavy rain events, and assess the potential of ensembles to provide advance warning and probabilistic predictions for risk assessment and decision making.

Tasks:

(a) Generation of probabilistic rain forecasts from MOGREPS ensemble output for lead times out to 5 days for monsoon seasons in Component 1.

(b) Verification of ensemble spread and probabilistic quantitative precipitation forecasts using standard methods and object-based ensemble verification.

(c) Evaluation of MOGREPS ensemble forecasts for rain cases in Component 2.

(d) Interpretation of results in terms of probabilistic skill and potential usefulness in advance warning context.

Deliverables: Dataset of ensemble rainfall output and verification statistics for Indian and Australian monsoon seasons and selected tropical heavy rain cases in India. Journal publication and conference presentation(s) on performance of ensemble-based forecasts for tropical heavy rainfall. 3.1 Schedule (Year wise)

Year Expected Outcome Deliverables

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Year – 1 UM rainfall performance benchmarked for two wet seasons in India and Australia using traditional and diagnostic spatial verification.

Interaction with forecasters on UM tropical rainfall quality (give/receive feedback).

Preparation of observations and model rain data for selected rainfall cases.

Documentation of results.

Diagnostic verification methods working at NCMRWF.

Dataset of verification statistics for global model predictions of tropical heavy rainfall for one wet season each in India and Australia.

Dataset of UM model rainfall spatial fields and vertical profiles, observed rainfall analyses and vertical profiles, for tropical heavy rain cases in India.

Year – 2 Numerical experimentation with UM to determine model sensitivity to resolution, parameterizations, initialisation.

Probabilistic rainfall forecasts generated from MOGREPS ensemble.

Journal publication and conference presentation(s) on performance of tropical heavy rainfall predictions from global and regional models.

Dataset of verification results for selected Indian tropical heavy rain cases.

Year – 3 Further numerical experimentation to determine optimal model configuration.

Verification of MOGREPS ensemble forecasts.

Documentation of results.

Optimum UM model configuration and settings.

Dataset of ensemble rainfall output and verification statistics for Indian and Australian monsoon seasons and selected Indian tropical heavy rain cases.

Journal publication and conference presentation(s) on performance of ensemble-based forecasts for tropical heavy rainfall.

3.2 Team composition and expertise *

Investigator Qualification ExpertisePI (E. Ebert) PhD, Meteorology Forecast verificationCo-PI (1) (N. Davidson) PhD, Mathematical

SciencesTropical meteorology

Co-PI (2) (K. Puri) PhD, Physics Numerical modellingInvestigator (G. R. Iyengar) MSc, Physics Forecast verificationInvestigator (R. Ashrit) PhD, Atmospheric Sciences Forecast verificationPost-doc (to be named) PhD

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*MoES encourages to include one Indian partner in the project proposal, preferably from MoES institutes.

3.3 Connections to Operational forecast and Human resource development

Improvements to NWP guidance will translate directly to better operational forecasts. Quantifying and communicating the errors in UM predictions of monsoon rainfall, in particular the nature of systematic errors and the magnitude of non-systematic errors, will enable forecasters to interpret the model output in a more informed way, also leading to better operational forecasts. We anticipate that MOGREPS ensemble forecasts will extend the useful lead time for medium-range prediction of synoptic scale events like monsoon depressions and tropical cyclones; this project will quantify the expected benefit of scenario and probabilistic forecasts derived from ensembles.

This project will contribute to the development of scientific skills of participating scientists in NCMRWF and CAWCR in the areas of forecast verification, numerical modelling, and tropical meteorology. In particular, NCMRWF scientists will build expertise in advanced diagnostic verification methods. NCMRWF has identified two project scientists whom they plan to groom as modelling and verification experts; this project would further their development. Working relationships developed during this collaboration may lead to future research opportunities for all concerned.

4. Related works and project assessment :

4.1 National status

4.1.1 ACCESS model development

Development of ACCESS has progressed along the lines laid out in the recommendations made in the Blueprint for ACCESS (Puri, 2005) and Project Plan for ACCESS (Puri, 2005). Significant progress has been made since development started in 2006 and some of the key milestones include:

Operational implementation of the ACCESS NWP system including assimilation of significantly increased number of satellite sounders. Implementation in September 2009 has been marked by a significantly increased skill relative to the previous operational systems, and the system performance is now similar to other major operational centres.

Successful assembly of fully coupled ACCESS and detailed testing of the coupled system. Subsequently the core CMIP5 simulations have been completed with two configurations of ACCESS, one using the Met Office MOSES land surface and a second one using CABLE and upgraded physical parametrizations. Model output data from both configurations has been published on the Earth System Grid (ESG) and will form an important component of the Australian contribution to CMIP5 and the IPCC Fifth Assessment. Preliminary assessment of the ACCESS runs shows

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encouraging performance of the system with ACCESS falling in the top tier of the climate models.

Development of high resolution (1.5km) version for severe weather prediction, including radar data assimilation which has shown encouraging skill in predicting heavy rainfall events.

Implementation in research mode of the ACCESS ensemble prediction system (known as AGREPS).

Commencement of work on using the ACCESS coupled system for seasonal prediction.

Progress in the development of ACCESS infrastructure. Examples include successful porting to both Bureau and National Computational Infrastructure’s (NCI) supercomputers; development, in collaboration with the Centre of Excellence for Climate System Science, of infrastructure to enable ready usage by University researchers; and setting up of a unified repository based at NCI.

The ACCESS NWP implementation and evaluation of its performance has been reported in Puri et al. (2012) and a number of manuscripts describing the assembly of the fully coupled ACCESS and evaluation of the CMIP5/AR5 runs have been submitted for publication (Dix et al., 2012, Bi et al., 2012, Sun et al., 2012).

4.1.2 ACCESS-TC for operations and research

The Australian Community Climate and Earth System Simulator, ACCESS (Puri et al. 2012) has been configured for operational and research applications on Tropical Cyclones. The base system runs at a resolution of 0.11° and 50 levels. The domain is re-locatable and nested in coarser-resolution forecasts. It provides guidance for storms located within the approximate domain: 40°S to 40°N, 70°E to 180°E. Initialization consists of 5 cycles of 4D-VAR assimilation over 24 hours and forecasts to 72 hours are made. Using all available conventional observations and only synthetic surface pressure observations from an idealized vortex to correct the initial location and structure of the storm, the 4DVAR builds a balanced, intense 3-D vortex with a well-developed secondary circulation and maximum wind at the radius of maximum wind. Mean forecast track and intensity errors for Australian region and NW Pacific storms have been encouraging. The system became fully operational at the Australian National Meteorological and Oceanographic Centre in November 2011 (NMOC, 2011). The system has been used effectively to simulate a small number of heavy rain events over Australia.

4.1.3 Australian Climate Change Science Program project on extreme rain events

Amplifying Planetary Rossby Waves and Rain Processes during Extreme Weather Events in Current and Future Climates

The objectives of this project are to:

1. Develop a climatology of extreme rain events over Australia.

2. Develop a classification of extreme rain environments.

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3. Use an index of Rossby wave activity to characterize the mid-latitude circulation over Australia.

4. Document the variability in Rossby wave activity and its association with extreme rain events over Australia.

5. Validate Rossby wave activity and extreme rain events in current and future climates based on CMIP5 and/or available climate simulations.

4.2 International status

4.2.1 US Office of Naval Research (ONR) Award: Rapid Intensification of TCs

Initialization, Prediction and Diagnosis of the Rapid Intensification of Tropical Cyclones using the Australian Community Climate and Earth System Simulator, ACCESS

This is a four-part, interconnected program of

(a) basic research into initialization of realistic TC structures using the state-of-the-art 4-dimensional variational data assimilation system (4D-VAR) from ACCESS (Australian Community Climate and Earth System Simulator)

(b) very high-resolution forecast experiments on prediction of TC structure and intensity, with particular focus on Rapid Intensification, using ACCESS

(c) diagnosis of the mechanisms of TC intensity and structure change (environmental influences, vortex structure, internal processes),

(d) transitioning of a validated TC assimilation and prediction system into operations, to provide forecast guidance on TC track, intensity and structure change.

4.2.2 International High Ice Water Content Study

The International High IWC Study will address engineering and scientific issues related to the failure of jet engines commonly used on commercial aircraft in convective clouds, and a variety of fundamental scientific issues related to the microphysical properties and structure of deep convective cloud systems over land and over the warm tropical ocean. Scientific partners include NASA, the European Union High Altitude Ice Crystal (HAIC) consortium, JMA Meteorological Research Institute, Environment Canada, and NCAR. CAWCR will contribute operationally (through the Darwin Climate Research Facility, and the operational BOM observations and forecasts) and scientifically (as members of the International Science Team and the HAIC consortium). An international field experiment out of Darwin, Australia is planned in January-March 2014.

CAWCR's main objectives in this project are to:

Analyze existing airborne datasets with high IWC and contribute in HAIC to the definition of the payload of the Falcon 20.

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Collect the ground-based and airborne dataset for the characterization of the microphysical properties of high IWC regions, and more generally of tropical oceanic convective systems,

Analyze the ground-based and airborne dataset in order to build a comprehensive picture of the formation and maintenance of high IWC regions in the upper troposphere,

Evaluate and improve ground-based, airborne, and satellite retrieval methods for the characterization of the dynamical and microphysical properties of high IWC regions,

Characterize the frequency of occurrence of high IWC regions at global scale using the newly-developed satellite methods.

Use the knowledge gained from this analysis to evaluate cloud processes within the ACCESS model and inform improvements to the model physics and dynamics.

4.3 The mechanisms adopted in your institute for internal review (assessment) and validation of this Project Proposal.

This proposal initiated by CAWCR scientists was developed through consultation with the partner investigators at NCMRWF to develop the research ideas and define the goals and deliverables. Discussion with the CAWCR Director and Deputy Director to confirm alignment of the project to CAWCR research priorities was also part of the process. After a final draft of the proposal was prepared, a letter of support was obtained from the CAWCR Deputy Director.

A review of potential legal issues and project costings by CAWCR's Business Development and Finance officers was undertaken as well. Staffing costs have been estimated by the Finance officer. Costs associated with proposed travel and journal page charges were estimated from experience and online airline and hotel information. These are indicative at best.

5. Results from prior MoES support (if any)

None

6. Facilities available at the workspace

CAWCR scientists have access to two supercomputer facilities, namely the Bureau’s 4608 core Oracle/Sun constellation system delivering 50 Tflops peak and the National Computational Infrastructure (based at the Australian National University in Canberra) 11936 core Oracle/Sun constellation system delivering 150 Tflops peak. The NCI system will be upgraded to a 1.2 petaflop Fujitsu PRIMERGY system in the first quarter 2013.

Mid-range computing on a high performance research and development Sun cluster (27 nodes, 53 CPUs, 216 cores, 680GB RAM, 32 TB storage) running a large number of applications software packages (IDL, MatLab, NetCDF tools, etc.) is available for analysis of results and other jobs not requiring supercomputing.

NCMRWF has a IBM-P6 based High Performance Computing System having a peak performance of 24 TFlops and has plans to upgrade the existing computing resources.

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7. Total Budget ( $ ) requirements ** (with justifications)

S.No Item Name 1st Year 2nd Year 3rd Year Total Justification

A) Man Power

1) Key personnel 45,000 46,000 47,000 138,000 Staff costs for Ebert, Davidson, Puri @ 0.05 FTE each, for three years

2) Other personnel (e.g. Research Assistants)

3) Technical Assistant

Total budget for Manpower

45,000 46,000 47,000 138,000

B) Travel1) Foreign Travel 6,000 6,000 6,000 18,000 One two-week visit of CAWCR scientist to

NCMRWF each year (flight, accommodation, food and incidentals)

Total budget for Travel 6,000 6,000 6,000 18,000

Grand Total (for each year) 51,000 52,000 53,000 156,000

** As per MoES guidelines, we will not be paying any additional overheads for international proposals. Funding is available only for manpower (not exceeding $1, 00,000/- per year/per person) and travel.

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8. Bio-data (CV) of the Investigators :

8.1 PI Biography (Dr. Elizabeth Ebert)

Name:- Dr. Elizabeth EbertDate of birth:- 24 February 1960Institution:- CAWCR, Bureau of MeteorologyAddress (Residence):- 46 Henry Street, Windsor, Victoria 3181, AUSTRALIA Tel. No: +61-3-9510-5293 Mob No: +61-406-763-248 E-mail Id: e.ebert@bom.gov.au

Address (Office):- 700 Collins Street, Docklands, Victoria 3008, AUSTRALIA Tel. No: +61-3-9669-4688 FAX: +61-3-9669-4660 Official E-mail Id: e.ebert@bom.gov.au

Official website address: http://cawcr.gov.au/, http://cawcr.gov.au/staff/eee/

Educational Qualification:-

School/College/

University

Degree Year Main subjects Division/Class

University of California B.S. 1981 Atmospheric Science

University of Wisconsin M.S. 1984 MeteorologyUniversity of Wisconsin Ph.D. 1987 Meteorology

Awards / Honors / Fellowships, etc.:

Bureau of Meteorology Award for Individual Excellence, 12 March 2008WMO recognition of contribution toward initiation and development of validation

efforts within the International Precipitation Working Group, 3rd IPWG Workshop, 23-27 October 2006, Melbourne.

AMS Committee on Probability and Statistics, 2007-2009THORPEX GIFS/TIGGE Working Group, 2005-2011GPM Ground Validation Steering Committee, 2003-presentWWRP/WGNE Joint Working Group on Forecast Verification Research, 2003-present;

co-chair 2008-presentWWRP Beijing 2008 FDP Team, 2005-2009International Precipitation Working Group (IPWG), 2002-presentWWRP Sydney 2000 FDP Verification Team, 2001-2002Global Precipitation Climatology Project (GPCP) Science Advisory Team, 1998-2001Australian Academy of Science Atmospheric and Oceanic Sciences Committee, 1997-

2000Associate editor, Monthly Weather Review, 2006-2008Associate editor, Weather and Forecasting, 2004-2007

Appointments (Professional experience/employment record):

Organization Designation / Position Duration (Year / date)

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Bureau of Meteorology Research Centre

Professional Officer 1989-1995

Bureau of Meteorology Research Centre

Senior Professional Officer 1995-2007

Bureau of Meteorology, Centre for Australian Weather & Climate Research

Research Team Leader, NWP Applications Team

2007-2009

Bureau of Meteorology, Centre for Australian Weather & Climate Research

Research Program Leader, Weather and Environmental Prediction Program

2009-present

Ten most relevant research publications: (most recent first)

Brown, B.G., E. Gilleland and E.E. Ebert, 2011: Forecasts of spatial fields. In I.T. Jolliffe and D.B. Stephenson (eds), Forecast Verification: A Practitioner's Guide in Atmospheric Science. 2nd ed., Wiley.

Ebert, E.E., M. Turk, S.J. Kusselson, J. Yang, M. Seybold, P.R. Keehn, R.J. Kuligowski, 2011: Ensemble tropical rainfall potential (eTRaP) forecasts. Wea. Forecasting, 26, 213-224.

Bougeault, P., Z. Toth, C. Bishop, B. Brown, D. Burridge, D.H. Chen, B. Ebert, M. Fuentes, Tom Hamill, K. Mylne, J. Nicolau, T. Paccagnella, Y.-Y. Park, D. Parsons, B. Raoult, D. Schuster, P. Silva Dias, R. Swinbank, Y. Takeuchi, W. Tennant, L. Wilson and S. Worley, 2010: The THORPEX Interactive Grand Global Ensemble (TIGGE). Bull. Amer. Met. Soc., 8, 1059-1072.

Gilleland, E., D.A. Ahijevych, B.G. Brown and E.E. Ebert, 2010: Verifying forecasts spatially. Bull. Amer. Met. Soc., 91, 1365-1373.

Ebert, E.E., 2008: Fuzzy verification of high resolution gridded forecasts: A review and proposed framework. Meteorol. Appl., 15, 51-64.

Ebert, E.E., J.E. Janowiak, and C. Kidd, 2007: Comparison of near real time precipitation estimates from satellite observations and numerical models. Bull. Amer. Met. Soc., 88, 47-64.

Ebert, E.E., U. Damrath, W. Wergen and M.E. Baldwin, 2003: The WGNE assessment of short-term quantitative precipitation forecasts. Bull. Amer. Met. Soc., 84, 481-492.

Ebert, E.E., 2001: Ability of a poor man's ensemble to predict the probability and distribution of precipitation. Mon. Wea. Rev., 129, 2461-2480.

Ebert, E.E. and J.L. McBride, 2000: Verification of precipitation in weather systems: Determination of systematic errors. J. Hydrology, 239, 179-202.

McBride, J.L. and E.E. Ebert, 1999: Verification of quantitative precipitation forecasts from operational numerical weather prediction models over Australia. Wea. Forecasting, 15, 103-121.

Other publications:

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De Maria, E.M.C., D.A. Rodriguez, E.E. Ebert, F. Su, and J.B. Valdes, 2011: Evaluation of mesoscale convective systems in South America using multiple satellite products and an object-based approach. J. Geophys. Res., 116, D08103, doi:10.1029/2010JD015157.

Schuster, G., E.E. Ebert, M.A. Stevenson, R.J. Corner, C.A. Johansen, 2011: Application of satellite precipitation data to analyse and model relationships between Murray Valley encephalitis virus and rainfall in Western Australia. Int. J. Health Geographics, 10:8 doi:10.1186/1476-072X-10-8.

Dance, S., E. Ebert and D. Scurrah, 2010: Thunderstorm strike probability nowcasting. J. Atmos. Oceanic. Tech., 27, 79-93.

Ahijevych, D., E. Gilleland, B. Brown, and E. Ebert, 2009: Application of spatial verification methods to gridded precipitation forecasts. Weather and Forecasting, 24, 1485–1497.

Ebert, E.E., 2009: Neighborhood verification of high resolution precipitation products. In Hossain, F. and M. Gebremichael (eds), Satellite Rainfall Applications for Surface Hydrology. Springer.

Ebert, E.E., 2009: Neighborhood verification of high resolution precipitation forecasts. Weather and Forecasting, 24, 1498-1510.

Ebert, E.E. and W.A. Gallus, 2009: Toward better understanding of the contiguous rain area (CRA) verification method. Weather and Forecasting, 24, 1401-1415.

Gilleland, E., D. Ahijevych, B.G. Brown, B. Casati, and E.E. Ebert, 2009: Inter-comparison of spatial verification methods. Weather and Forecasting, 24, 1416–1430.

Turk, F.J., B.-J. Sohn, J.-J. Oh, E.E. Ebert, V. Levizzani, and E.A. Smith, 2009: Validating a rapid-update satellite precipitation analysis across telescoping space and time scales. Meteorol. Atm. Phys., 105, 99-108.

Casati, B., L.J. Wilson, D.B. Stephenson, P. Nurmi, A. Ghelli, M. Pocernich, U. Damrath, E.E. Ebert, B.G. Brown and S. Mason, 2008: Forecast verification: current status and future directions. Meteorol. Appl., 15, 3-18.

Rossa, A., P. Nurmi, and E. Ebert, 2008: Overview of methods for the verification of quantitative precipitation forecasts. In Michaelides, S. (ed), Precipitation: Advances in Measurement, Estimation and Prediction, pp. 417-450.

Turk, F.J., P.Arkin, E. Ebert and M. Sapiano, 2008: The First Workshop of the Program for the Evaluation of High Resolution Precipitation Products. Bull. Amer. Met. Soc., 89, 1911-1916.

Engel, C. and E. Ebert, 2007: Performance of hourly operational consensus forecasts (OCFs) in the Australian region. Weather and Forecasting, 22, 1345-1359.

Ebert, E.E., 2006: Methods for verifying satellite precipitation estimates. In Levizzani, V., P. Bauer and F.J. Turk (eds), Measuring Precipitation from Space. EURAINSAT and the Future.

Grams, J.S., W.A. Gallus, L.S. Wharton, S. Koch, A. Loughe, and E.E. Ebert, 2006: The use of a modified Ebert-McBride technique to evaluate mesoscale model QPF

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as a function of convective system morphology during IHOP 2002. Weather and Forecasting, 21, 288–306.

Ebert, E., S. Kusselson and M. Turk, 2005: Validation of NESDIS operational tropical rainfall potential (TRaP) forecasts for Australian tropical cyclones. Aust. Meteorol. Mag., 54, 121-135.

Ebert, E., L.J. Wilson, B.G. Brown, P. Nurmi, H.E. Brooks, J. Bally, and M. Jaeneke, 2004: Verification of nowcasts from the WWRP Sydney 2000 Forecast Demonstration Project. Weather and Forecasting, 19, 73-96.

May, P.T., T. Keenan, R. Potts, R. Webb, A. Treloar, E. Spark, S. Lawrence, E. Ebert, J. Bally, J. Wilson, and P. Joe, 2004: The Sydney observing network during the Sydney 2000 Olympic Games Forecast Demonstration Project: Addressing forecast issues and nowcasting requirements. Weather and Forecasting, 19, 115-130.

Pierce, C.E., E.E. Ebert, A. Seed, N. Fox, M. Sleigh, C.G. Collier, N. Donaldson, J. Wilson, R. Roberts and C. Mueller, 2004: The nowcasting of precipitation during Sydney 2000: An appraisal of the QPF algorithms. Weather and Forecasting, 19, 7-21.

Wilson, J.W., E. Ebert, T. Saxen, C. Pierce, M. Sleigh, A. Seed, R. Roberts and C. Mueller, 2004: Sydney 2000 Forecast Demonstration Project: Convective storm nowcasting. Weather and Forecasting, 19, 131-150.

Keenan, T., P. Joe, J. Wilson, C. Collier, B. Golding, D. Burgess, P. May, C. Pierce, J. Bally, A. Crook, D. Sills, L. Berry, I. Bell, N. Fox, R. Pielke Jr., E. Ebert, M. Eilts, K. O'Loughlin, R. Webb, R. Carbone, K. Browning, R. Roberts, C. Mueller, 2002: The Sydney 2000 World Weather Research Programme Forecast Demonstration Project: Overview and current status. Bull. Amer. Met. Soc., 84, 1041–1054.

Ebert, E.E. and G.T. Weymouth, 1999: Incorporating satellite observations of "no rain" into an Australian daily rainfall analysis. J. Appl. Meteor., 38, 44-56.

Ebert, E.E. and M.J. Manton, 1998: Performance of satellite rainfall estimation algorithms during TOGA COARE. J. Atmos. Sci., 55, 1537-1557.

Weymouth, G., G.A. Mills, D. Jones, E.E. Ebert, and M.J. Manton, 1998: A continental-scale daily rainfall analysis system. Aust. Meteorol. Mag., 48, 169-179.

Schramm, J.L., M.M. Holland, J.A. Curry and E.E. Ebert, 1997: Modeling the thermodynamics of a sea ice thickness distribution. Part I: Sensitivity to ice thickness resolution. J. Geophys. Res., 102, 23,079-23,092.

Ebert, E.E., M.J. Manton, P.A. Arkin, R.J. Allan, G.E. Holpin, and A.J. Gruber, 1996: Results from the GPCP Algorithm Intercomparison Programme, Bull. Amer. Met. Soc., 77, 2875-2887.

Curry, J.A., J.L. Schramm, M.C. Serreze and E.E. Ebert, 1995: Water vapor feedback over the Arctic Ocean, J. Geophys. Res., 100, 14,223-14,229.

Curry, J.A., J.L. Schramm and E.E. Ebert, 1995: Sea ice-albedo climate feedback mechanism, J. Climate, 8, 240-247.

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Ebert, E.E. and J. Le Marshall, 1995: An evaluation of infrared satellite rainfall estimation techniques over Australia, Aust. Meteorol. Mag., 44, 177-190.

Ebert, E.E., J.L. Schramm and J.A. Curry, 1995: Disposition of solar radiation in sea ice and the upper ocean. J. Geophys. Res., 100, 15,965-15,975.

Curry, J.A., E.E. Ebert and J.L. Schramm, 1993: Impact of clouds on the surface radiation balance of the Arctic Ocean, Meteorol. Atmos. Phys., 51, 197-217.

Ebert, E.E. and J.A. Curry, 1993: An intermediate one-dimensional thermodynamic sea ice model for investigating ice-atmosphere interactions, J. Geophys. Res., 98, 10,085-10,109.

Curry, J.A. and E.E. Ebert, 1992: Annual cycle of radiation fluxes over the Arctic Ocean: Sensitivity to cloud optical properties, J. Climate, 5, 1267-1280.

Ebert, E.E. and J.A. Curry, 1992: A parameterization of ice cloud optical properties for climate models. J. Geophys. Res., 97, 3831-3836.

Ebert, E.E. and G.J. Holland, 1992: Observations of record cold cloud top temperatures in tropical cyclone Hilda (1990). Mon. Wea. Rev, 120, 2240-2251.

Ebert, E.E., 1991: Pattern recognition analysis of polar clouds during summer and winter. Int. J. Remote Sensing, 13, 97-109.

Curry, J.A. and E.E. Ebert, 1990: Sensitivity of the thickness of Arctic sea ice to the optical properties of clouds. Annals of Glaciology, 14, 43-46.

Curry, J.A., F.G. Meyer, L.F. Radke, C.A. Brock, and E.E. Ebert, 1990: Occurrence and characteristics of lower tropospheric ice crystals in the Arctic. Int. J. Climatol., 10, 749-764.

Ebert, E.E., 1989: Analysis of polar clouds from satellite imagery using pattern recognition with a statistical cloud analysis scheme. J. Appl. Meteor., 28, 382-399.

Curry, J.A., G.F. Herman and E.E. Ebert, 1988: Mean and turbulence structure of the summertime Arctic cloudy boundary layer. Q. J. R. Meteorol. Soc., 114, 715-746.

Ebert, E.E., U. Schumann and R.B. Stull, 1988: Nonlocal turbulent mixing in the convective boundary layer evaluated from large-eddy simulation. J. Atmos. Sci., 46, 2178-2207.

Eloranta, E.W., R. B. Stull and E. Ebert, 1988: Test of a calibration device for airborne Lyman-alpha hygrometers. J. Atmos. Ocean Tech., 6, 129-139.

Ebert, E.E., 1987: A pattern recognition technique for distinguishing surface and cloud types in the polar regions. J. Clim. Appl. Meteor., 26, 1412-1427.

Participation in Conference/Seminar/Workshop/Summer Schools

Chair, 5th International Verification Methods Workshop, 1-7 December 2011, Melbourne, Australia.

Trainer at 14 WMO training courses and Asia-Pacific Satellite Applications coursesInvited speaker at 20 international workshops and conferences

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Presenter or participant at many other workshops and conferences

Recent collaborations:

Intercomparison of satellite precipitation estimates (with NASA, NOAA, NRL, UCI, JAXA; 2000-present).

Spatial Verification Methods Intercomparison Project (with NCAR, UK Met Office, universities; 2007-2009)

WWRP Beijing 2008 Olympics Forecast Demonstration Project (with CMA, NCAR, Env. Canada, HKO)

Research Guidance:

No. of Ph.D. students enrolled/ completed: 3 completed, 1 current

Synergistic Activities:

Operational implementation in the Bureau

Poor Man's Ensemble (PME) of NWP rainfall predictions, 2006

RAINVAL, a tool for automated and interactive verification of gridded quantitative precipitation forecasts, 2000

Operational implementation outside Bureau

Real Time Forecast Verification (RTFV) system implemented at Beijing Meteorological Bureau for use in WWRP 2008 Beijing Olympics Forecast Demonstration Project, July 2008.

Ensemble TRaP (eTRaP) implemented at NOAA/NESDIS Satellite Analysis Branch, May 2008.

Cyclone XML (CXML) v.1.0 released for TIGGE exchange of ensemble tropical cyclone tracks, 4 June 2008.

Weather XML (WxML) v.1.0 released for exchange of nowcasts as part of the WWRP 2008 Beijing Olympics Forecast Demonstration Project, August 2006.

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8.2 Co-PI (1) Biography (Dr. Noel Davidson)

Name: Noel E. DavidsonDate of birth: 10 December 1948Institution: CAWCR, Bureau of MeteorologyAddress (Residence): 8 Pryde Court, Wheelers Hill, Melbourne, Australia. 3150 Tel. No. : +61-3-9561-2864 Mob No: E-mail Id: n.davidson@bom.gov.au

Address (Office):- 700 Collins Street, Docklands, Victoria 3008, AUSTRALIA Tel. No: +61-3-9669-4416 FAX: +61-3-9669-4660 Official E-mail Id: n.davidson@bom.gov.au

Official website address: http://cawcr.gov.au/

Educational Qualification:School/College/University Degree Year Main subjects Division/ClassMonash University B.Sc.

(Hons)1970 Astrophysics,

Atmospheric Science

Monash University PhD 1995 The Monsoon and Tropical Cyclones

Awards / Honors / Fellowship etc.:

1. Lead Principal Investigator, US National Oceanographic Partnership Program (NOPP) and the US Office of Naval Research (ONR) Award (2010 – 2012):

“Initialization, Prediction and Diagnosis of the Rapid Intensification of Tropical Cyclones, using the Australian Community Climate and Earth System Simulator, ACCESS”

Co-Principal Investigators: Michael J. Reeder, Craig H. Bishop, Jeffrey D. Kepert, Peter Steinle and Kevin J. Tory.

2. Lead Principal Investigator, 2010-2012 Australian Climate Change Science Program (ACCSP) Proposal:

“Amplifying Planetary Rossby Waves and Rain Processes during High Impact Weather Events in Current and Future Climates”

Co-Principal Investigators: Hongyan Zhu, Harry Hendon and Michael J. Reeder.

3. Lead Principal Investigator, US Office of Naval Research (ONR) Project (2002-2005):

"Research and Development Towards Improved Operational Prediction of Tropical Cyclone Behavior and Associated Significant Weather"

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Member Australian Meteorological and Oceanographic SocietyMember American Meteorological Society (AMS)Member AMS Committee on Tropical Meteorology and Hurricanes, 2000 - 2002Member Editorial Board of the Australian Meteorological Magazine, Associate Editor,

1999-2005.Visiting Research Scientist, Meteorological Research Institute, Japan Meteorological

Agency, Tsukuba, Japan. Visiting Research Scientist, Supercomputer Computations Research Institute and the

Department of Meteorology, Florida State University, with Prof. T.N. Krishnamurti. Leader, IWTC Working Group on Tropical Cyclone Prediction, 2002. Recipient of the Priestley Award, (1982) from the Australian Meteorological and

Oceanographic Society, for excellence in meteorological or oceanographic research, for Davidson, N.E. and B.J. McAvaney, 1981: The ANMRC tropical analysis scheme. Aust. Met. Mag., 29, 155-168.

Appointments (Professional experience/employment record):

Organization Designation / Position Duration ( Year / date)Bureau of Meteorology

Professional Officer (Meteorologist)

1975-1977

Australian Numerical Meteorology Research Centre

Senior Professional Officer (Research)

1978 - 1984

Bureau of Meteorology Research Centre (BMRC)

Senior Professional Officer (Research)

1985 - 1998

BMRC Senior Research Scientist 1998 – 2008CAWCR Senior Research Scientist 2008 - 2011CAWCR Principal Research Scientist 2011 - 2012

List of important and relevant research publications:

Davidson, N.E. and Y. Ma, 2012: Surface Pressure Profiles, Vortex Structure and Initialization for Hurricane Prediction. Part II: Numerical Simulations of Track, Structure and Intensity, Meteorol. Atmos. Phys, 117, 25-45.

Wang, X., Y. Ma and N.E. Davidson, 2012: Secondary eyewall formation and eyewall replacement cycles in a simulated hurricane: Effect of unbalanced forces in the atmospheric boundary layer, J.Atmos. Sci., under revision.

Nguyen, C.M., M.J. Reeder, N.E. Davidson, M.T. Montgomery and R.K. Smith, 2011: Vacillation cycles during the intensification of Hurricane Katrina. Quart. J. Roy. Met. Soc., 137, 829–844.

Tory, K. J., N. E. Davidson and M. T. Montgomery 2007: Prediction and diagnosis of tropical cyclone formation in an NWP system. Part III: Developing and non-developing storms. J. Atmos. Sci. 64, 3195 – 3213.

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Davidson, N.E., K.J. Tory, M. J. Reeder and W.L. Drosdowsky, 2007: Extratropical-tropical interaction during onset of the Australian Monsoon: Re-analysis diagnostics and idealized dry simulations. J. Atmos. Sci., 64, 3475-3498.

Dare, R.A and N.E. Davidson, 2004: Characteristics of tropical cyclones in the Australian Region. Mon. Wea. Rev., 132, 3049-3065.

Davidson, N.E. and S.K. Kar, 2002: Upper tropospheric flow transitions during rapid tropical cyclone intensification. Quart. J. Roy. Met. Soc., 128, 861-891.

Davidson, N.E. and H.C. Weber, 2000: The BMRC high resolution tropical cyclone prediction system: TC-LAPS. Mon. Wea. Rev., 128, 1245-1265

Davidson, N.E., K. Kurihara, T. Kato, G. Mills and K. Puri, 1998: Dynamics and prediction of a mesoscale, extreme rain event in the Baiu front over Kyushu, Japan. Mon. Wea. Rev. , 126, 1608-1629.

Davidson, N.E. and K. Puri, 1992: Tropical prediction using dynamical nudging, satellite-defined convective heat sources and a cyclone bogus. Mon. Wea. Rev., 120, 2501-2522.

Davidson, N.E. and H.H. Hendon, 1989: Downstream development in the Southern Hemisphere monsoon during FGGE/WMONEX. Mon. Wea. Rev., 117, 1458-1470.

Davidson, N.E. and G.J. Holland, 1987: A diagnostic analysis of two intense monsoon depressions over northern Australia. Mon. Wea. Rev., 115, 380-392.

Davidson, N.E., J.L. McBride, and B.J. McAvaney, 1983: The onset of the Australian monsoon during winter MONEX: Synoptic aspects. Mon. Wea. Rev., 111, 496-516.

Other publications:

Tory, K.J., R. A. Dare, N. E. Davidson, J. L. McBride, and S. S. Chand, 2012: The importance of low-deformation vorticity in tropical cyclone formation, Atmos. Chem. Phys. Discuss., 12, 1–43, 2012, www.atmos-chem-phys-discuss.net/12/1/2012/ doi:10.5194/acpd-12-1-2012

Davidson, N. E. and Y. Ma, 2012: Surface Pressure Profiles, Vortex Structure and Initialization for Hurricane Prediction. Part II: Numerical Simulations of Track, Structure and Intensity, Meteorol. Atmos. Phys, 117, 25-45.

Luo, Z., N.E. Davidson, F. Ping and W. Zhou, 2011: Multi-scale interactions affecting tropical cyclone track changes. Adv. Mech. Eng.,

Davidson, N.E., 2010: On the intensification and recurvature of Tropical Cyclone Tracy (1974). Austr. Meteorol. Oceanogr. J., 60, 169-177

Ma, L., J. C. Chan, N. E. Davidson and J. Turk, 2008: Initialization with diabatic heating from satellite-derived rainfall. Atmospheric Research, 85,148-158.

Tory K. J., M. T. Montgomery, N. E. Davidson, and J. D. Kepert, 2006: Prediction and diagnosis of tropical cyclone formation in an NWP system. Part II: A diagnosis of Tropical Cyclone Chris formation. J. Atmos. Sci., 63, 3091–3113.

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Tory, K. J., M. T. Montgomery and N. E. Davidson, 2006: Prediction and diagnosis of tropical cyclone formation in an NWP system. Part I: The critical role of vortex enhancement in deep convection. J. Atmos. Sci., 63, 3077 - 3090.

Paterson, L., B. Hanstrum, N.E. Davidson and H.C. Weber, 2005: Influence of environmental wind shear on the intensity of hurricane-strength tropical cyclones in the Australian region. Mon. Wea. Rev., 133, 3644-3660.

Davidson, N.E., H. Stern, G. Mills and T. Leggett, 2001: Forward-backward assimilation, prediction and dynamics for the southeast Australia floods of October 1993. Aust. Met. Mag., 50, 205-224

Li, J., N.E. Davidson, D. Hess and G. Mills, 1997: A high resolution prediction study of two typhoons at landfall. Mon. Wea. Rev. , 125, 2856-2878.

Davidson, N.E., 1995a: Vorticity Budget for AMEX. Part I : Diagnostics. Mon. Wea. Rev., 123, 1620-1635.

Davidson, N.E., 1995b: Vorticity Budget for AMEX. Part II : Simulations of monsoon onset, mid-tropospheric lows and tropical cyclone behaviour. Mon. Wea. Rev., 123, 1636-1659.

Kurihara, K., N. Davidson, K. Puri, R. Bowen and M. Ueno, 1995: Simulations of Tropical Cyclone Connie during AMEX Phase II. Aust. Met. Mag., 45, 101-111.

McBride, J.L., N. Davidson, K. Puri and G. Tyrell, 1995: The flow during TOGA-COARE as diagnosed by the BMRC tropical analysis and prediction system. Mon. Wea. Rev., 123, 717-736.

Puri, K. and N.E. Davidson, 1993: The use of satellite data as proxy data for moisture and diabatic heating in data assimilation. Mon. Wea. Rev., 121, 2329-2341.

Davidson, N.E. and K. Puri, 1992: Limited area tropical prediction for AMEX. Aust. Met. Mag., 40, 179-190.

Davidson, N.E., J. Wadsley, K. Puri, K. Kurihara, and M. Ueno, 1992: Implementation of the JMA typhoon bogus in the BMRC tropical prediction system. J. Met. Soc. Japan, 71, 437-467.

Puri, K., N.E. Davidson, L.M. Leslie, and L.W. Logan, 1992: The BMRC tropical limited area model. Aust. Met. Mag.,40, 81-104.

Davidson, N.E., G.J. Holland, J.L. McBride, and T.D. Keenan, 1990: On the formation of AMEX tropical cyclones Irma and Jason. Mon. Wea. Rev., 118, 1981-2000.

Davidson, N.E. and A. Kumar, 1990: Numerical simulation of the development of AMEX tropical cyclone IRMA. Mon. Wea. Rev., 118, 2001-2019.

Krishnamurti, T.N., A. Kumar, K-S. Yap, A.P. Dastoor, N. Davidson and J. Sheng, 1990: Performance of a high resolution meso-scale tropical prediction model. Advances in Geophysics, 32, 133-286.

Gunn, B.W., J.L. McBride, G.J. Holland, T.D. Keenan, N.E. Davidson, and H.H. Hendon, 1989: The Australian summer monsoon circulation during AMEX Phase II. Mon. Wea. Rev., 117, 2554-2574.

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Hendon, H.H., N.E. Davidson, and B.W. Gunn, 1989: Australian summer monsoon onset during AMEX 1987. Mon. Wea. Rev., 117, 370-390.

Keenan, T.D., J.L. McBride, G.J. Holland, N.E. Davidson, and B.W. Gunn, 1989: Diurnal variations during the Australian monsoon experiment (AMEX) Phase II. Mon. Wea. Rev., 117, 2535-2552.

McBride, J.L., B.W. Gunn, G.J. Holland, T.D. Keenan, N.E. Davidson, and W.M. Frank, 1989: Time series of total heating and moistening over the Gulf of Carpentaria radiosonde array during AMEX. Mon. Wea. Rev., 117, 2701-2713.

Mills, G.A. and N.E. Davidson, 1987: Tropospheric moisture profiles from digital IR satellite imagery: System description and analysis/forecast impact. Aust. Met. Mag., 35, 109-118.

Keenan, D.W., N.E. Davidson, and G.A. Kelly, 1986: Analysis of screen level temperature and dewpoint in the Australian region. Aust. Met. Mag, 34, 155-161.

Davidson, N.E., J.L. McBride, B.J. McAvaney, 1984: Divergent circulations during the onset of the 1978-79 Australian monsoon. Mon. Wea. Rev., 11, 1684-1696.

Davidson, N.E., 1984: Short term fluctuations in the Australian monsoon during winter MONEX. Mon. Wea. Rev., 112, 1697-1708.

Davidson, N.E., J.L. McBride, and B.J. McAvaney, 1983: The onset of the Australian monsoon during winter MONEX: Synoptic aspects. Mon. Wea. Rev., 111, 496-516.

Davidson, N.E., 1982: Diagnostic capabilities of objective analysis schemes: areal mean vertical motion fields of some weather regimes over Australia. Aust. Met. Mag., 30, 211-221.

Davidson, N.E. and B.J. McAvaney, 1981: The ANMRC tropical analysis scheme. Aust. Met. Mag., 29, 155-168.

Participation in Conference/Seminar/Workshop/ Summer Schools

Invited Presentations:

WMO World Weather Research Programme (WWRP) and Tropical Cyclone Programme (TCP), International Workshop on Rapid Change Phenomena in Tropical Cyclones. Haikou, Hainan, China. 5-9 November 2012.

Advanced Indo-US Training Workshop and Colloquium on Modeling and Data Assimilation for Tropical Cyclone Predictions, 9-14 July, 2012, Indian Institute of Technology, Bhubaneswar, Odisha, India.

IUGG, Symposium on Tropical Cyclones, Montreal, Canada, 19-29 July 2009.

International Meeting on South Atlantic Cyclones, Track Prediction and Risk Evaluation, Cooperative Institutions of Brazil, Rio de Janeiro, May 19 – 21, 2008.

Regional Research Workshop on Tropical Cyclones. Meteo France. RSMC La Reunion. May 26 -30, 2008.

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Planning Workshop for the THORPEX Pacific Asian Regional Campaign (T-PARC), Tropical Cyclone Structure (TCS08) and other Collaborative Experiments. Princeville, Kauai, Hawaii, 4-6 December 2007.

Recent Advances in Understanding Tropical Cyclones, Monash University, 23 March 2007.

IUGG, Symposium on Intense Vortices, Sapporo, Japan, 30 June – July 11, 2003

International Workshop on Tropical Cyclone Intensity Change, SanDiego, USA, 3 – 5 May,2002.

WMO Workshop on Typhoon Forecasting Research. Cheju, Korea, 25 - 28 September , 2001.

International Workshop on the Dynamics and Forecasting of Tropical Weather Systems. Darwin, Australia, 22 - 26 January, 2001.

Workshop on Spatial Objective Analysis for Diagnostic Studies in Meteorology and Oceanography. Menorca, Spain, 18 - 22 September 2000

Recent collaborations outside of CAWCR:

Prof. Michael Montgomery, Naval Postgraduate School, MontereyProf. Roger Smith, University of MunichDr. Craig Bishop, Naval Research Laboratory, MontereyDr. Harry Weber, University of MunichDr. Mathieu Plu, Meteo-FranceProf. Zhexian Luo, Chinese Academy of ScienceProf. Ping Fan, Chinese Academy of ScienceProf. Michael Reeder, Monash University.Dr. Alex Pezza, University of Melbourne

Research Guidance:

No. of Ph.D. students enrolled/ completed: 5

Chi Mai Nguyen, Monash University. Inner-core vacillation cycles during the rapid ntensification of Hurricane Katrina. PhD dissertation, Department of Mathematical Sciences, Monash University, (accepted January 2011) (with Prof. M.J. Reeder)

Luke A. Garde, University of Melbourne. Tropical and Extratropical Transition of Tropical Cyclones in the Australian Region. PhD Candidate, School of Earth Sciences, University of Melbourne. (with Dr. A. Pezza)

Marie-Dominique Leroux, Meteo-France. Based on research she completed while an Intern at CAWCR, she successfully applied to continue this work as part of her PhD. Funding for her PhD comes from a Meteo-France Scholarship. (with Mathieu Plu, Frank Roux and David Barbary, Meteo-Franc)

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Lili Liu, Institute of Atmospheric Physics, Beijing, China. Downstream Development during the Extratropical Transition of Tropical Cyclones: Observational Evidence and Influence on Storm Structure. Her PhD was based on research she commenced and mostly completed while an Intern at CAWCR, working on a project defined and supervised by Noel Davidson and Hongyan Zhu. (accepted September 2010).

Ying Jun Chen, University of Melbourne. PhD student. Rainfall in Tropical Cyclones. (With Drs. Kevin Walsh and Beth Ebert).

No. of Graduate/Postgraduate students enrolled/ completed: 2

Charlie Lok, Monash University. Landfall of Typhoons near Hong Kong. MSc Student. (accepted June 2012) (with Prof. M.J. Reeder)

Joan Fernon, Monash University. The Australian Monsoon. MSc student. (With Prof. M.J. Reeder)

Synergistic Activities:Activity 1

Recent Developments of Advanced Operational NWP Systems

TC-LAPS (2004-2010): This system is built around a unique initialization technique which (a) builds the inner-core structure (central pressure, maximum wind at the radius of maximum wind) based on observed storm structure, (b) re-locates the circulation to the observed location, (c) imposes a steering flow consistent with the current motion, and (d) preserves the analysed primary circulation, while initializing the secondary circulation using model dynamics, physical process and satellite imagery to redefine the vertical motion field and asymmetries in convection. Balanced initial conditions are crucial for accurate prediction of TCs and this technique enabled TC-LAPS to achieve track and intensity forecasting skill competitive with the very best available.

ACCESS-TC (2011 - ): Like TC-LAPS, the initialization (a) builds the inner-core structure (central pressure, maximum wind at the radius of maximum wind) based on observed storm structure, (b) re-locates the circulation to the observed location, and (c) imposes a steering flow consistent with the current motion. Then based on a minimal distribution of only synthetic surface pressure observations, the power of the 4DVAR is used to build the horizontal and vertical structure of the inner core, and initializes the secondary circulation. The system was declared operational in November 2011.

Activity 2

Leading three major projects: (i) ACCESS-TC for operations and research, (ii) the NOPP/ONR Project on rapid intensification of TCs, and (iii) an ACCSP Project on Rossby Wave Activity and Extreme Weather. These mostly define my current interests.

ACCESS-TC for operations and research Initialization, prediction and understanding of the rapid intensification of

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tropical cyclones Impact of initial vortex structure on track, intensity and structure change Mechanisms of extratropical transition of tropical cyclones Influence of amplifying, propagating Rossby waves on tropical cyclone structure

change Extratropical-tropical interaction during the Australian summer monsoon Rossby wave activity and rain processes during extreme weather events in the

Australian Region Prediction and diagnosis of TC genesis.

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8.4 Co-PI (2) Biography (Dr. Kamal Puri)

Name: Kamal PuriDate of birth:Institution:Address (Residence): 89 Glenburnie Road, Vermont, Victoria 3133, Australia Tel. No. : +61-3-9874-5168 Mob No: +61 438324953 E-mail Id: K.Puri@bom.gov.au

Address (Office): 700 Collins Street, Docklands, Victoria 3008, AUSTRALIA Tel. No. :- +61-3-9669-4433 FAX:- +61-3-9669-4660 Official E-mail Id:- K.Puri@bom.gov.au Official website address:- http://cawcr.gov.au/

Educational Qualification:School/College/University Degree Year Main subjects Division/ClassUniversity of Manchester, UK

B.Sc. Hons 1968 Physics 2.1

University of Manchester, UK

Diploma of Advanced Studies in Science

1969 Physics Distinction

University of Manchester, UK

PhD 1972 Physics

Awards / Honors / Fellowship etc.:

1992-1994 Associate Editor, Monthly Weather Review1992-1996 Associate Editor, Quarterly Journal of the Royal Meteorological

Society (QJRMS)1987-1990 Member, WMO/CAS Working Group on Tropical Meteorology1988-Present Member, WMO/CAS Working group on Limited Area

Modelling/Tropics1990-2000 Chairman, WMO/CAS Long term Asian/African Monsoon Studies

(Project M2)1991-1995 Member, WMO/CAS Monsoon Experimentation Group (MONEG)1995 - 2000 Member WMO/CAS Research Initiative on East Asian Monsoon

(Project M1)1995 -2009 Member WMO/CAS Working Group on Numerical Experimentation

(WGNE)1998 - 2004 Chairman, WMO/CAS Working Group on Numerical Experimentation

(WGNE)2001- Member, Scientific Advisory Group of the GEWEX Coordinated

Enhanced Observing Period (CEOP)2001 - Member, THORPEX International Core Steering Committee (ICSC)2005 - Member, THORPEX Science Advisory Board

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2005 - Member, THORPEX Executive Board2005 - Co-Chair, Southern Hemisphere THORPEX Regional Committee2005 - Member, UK Met Office Science Advisory Committee2008 - Member, Government of India Ministry of Earth Sciences International

Advisory Panel (IAP)2011 - Member, Science Advisory Committee, Korea Institute of Atmospheric

Prediction Systems (KIAPS).

Appointments (Professional experience/employment record):

Organization Designation / Position Duration ( Year / date)CSIRO RS, SRS, PRS 1974 - 1984BMRC PRS, SPRS 1985 - 2005CAWCR SPRS 2005 -

List of publications:

Puri, K., and W.P. Bourke, 1974: Implications of horizontal resolution in spectral model integrations. Mon. Wea. Rev., 102, 33-47.

Bourke, W.P., B.J. McAveney, K. Puri, and R.J. Thurling, 1977: Global modelling of atmospheric flow by spectral methods. Methods in Computational Physics, Vol 17, General Circulation models of the Atmosphere, Academic Press, 267-324.

McAveney, B.J., W.P. Bourke, and K. Puri, 1978: A global spectral model for simulation of the general circulation. J. Atmos. Sci., 35, 1557-1583.

Wells, N.C., and K. Puri, 1979: Atmospheric feedback in a coupled ocean-atmosphere model. J. Geophys. Res., 84, 4985-4997.

Daley, R., and K. Puri, 1980: Four-dimensional data assimilation and the slow manifold. Mon. Wea. Rev., 108, 85-99.

Puri. K., 1981: Extended range forecasts for the Southern Hemisphere with the ANMRC spectral model. Mon. Wea. Rev., 109, 286-305.

Kasahara, A., and K. Puri, 1981: Spectral representation of three-dimensional global data by expansion in normal model functions. Mon. Wea. Rev., 109, 37-51.

Bourke, W.P., K. Puri, and R. Seaman, 1982: Numerical weather prediction studies from FGGE Southern Hemisphere data base. Mon. Wea. Rev., 110, 1787-1800.

Puri K., W.P. Bourke, and R. Seaman, 1982: Incremental linear normal mode initialisation in four dimensional assimilation. Mon. Wea. Rev., 110, 1773-1784.

Bourke, W.P., K. Puri, R. Seaman, B. McAveney, and J. Le Marshall, 1982: ANMRC data assimilation for the Southern Hemisphere. Mon. Wea. Rev., 110, 1749-1771.

Puri, K., and W.P. Bourke, 1982: A scheme to retain the Hadley circulation during non-linear normal model initialisation. Mon. Wea. Rev., 110, 327-335.

Puri, K., 1983: Some experiments in variational normal mode initialisation in data assimilation. Mon. Wea. Rev., 111, 1208-1218.

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Puri, K., 1983: The relationship between convective adjustment, Hadley circulation and normal modes of the ANMRC spectral model. Mon. Wea. Rev., 111, 23-33.

Pitcher, E.J., R.C. Malone, V. Ramanathan, M.L. Blackmon, K. Puri, and W.P. Bourke, 1983: January and July simulations with a spectral general circulation model. J. Atmos. Sci., 40, 580-604.

Malone, R.C., E.J. Pitcher, M.L. Blackmon, K. Puri, and W.P. Bourke, 1984: The simulation of stationary and transient geopotential-height eddies in January and July with a spectral general circulation model. J. Atmos. Sci., 41, 1394-1419.Puri, K., 1984: The ANMRC data assimilation system - the impact of normal mode initialisation techniques. The 1984 ECMWF Seminar, Data Assimilation Systems and Observing System Experiments with particular emphasis on FGGE, Vol 1, 235-279.

Puri, K., and W. Stern, 1984: Investigations to reduce noise and improve data acceptance in the FGGE 4-dimensional analysis system.. The 1984 ECMWF Seminar, Data Assimilation Systems and Observing System Experiments with particular emphasis on FGGE, Vol 2, 157-190.

Frederiksen, J.S., and K. Puri, 1985: Nonlinear instability and error growth in Northern Hemisphere three-dimensional flows: Cyclogenesis, onset of blocking and mature anamolies. J. Atmos. Sci., 42, 1374-1397.

Bourke, W.P., R. Seaman, and K. Puri, 1985: Data assimilation. Advances in Geophys., 28B, Atmospheric and Oceanic Modelling, Academic Press, 123-155.

Puri, K., 1985: Sensitivity of low-latitude velocity potential field in a numerical weather prediction model to initial conditions, initialisation and physical processes. Mon. Wea. Rev., 113, 449-466.

Puri, K., and D.J. Gauntlett, 1987: Numerical weather prediction in the tropics. J. Met. Soc. Japan, Special Volume, Ed. T. Matsuno, 605-631.

Puri, K., 1987: Some experiments on the use of tropical diabatic heating information for initial state specification. Mon. Wea. Rev., 115, 1394-1406.

Heckley, W.A., and K. Puri, 1988: The Winter Monsoon during AMEX. A quick look atlas 10 January - 15 February 1987. ECMWF Publication, 169pp.

Puri, K., 1988: On the importance of low frequency gravity modes for the evolution of large scale flow in a general circulation model. J. Atmos. Sci., 45, 2523-2544.

Puri, K., P. Lonnberg, and M.J. Miller, 1990: The ECMWF analysis-forecast system during AMEX. ECMWF Tech. Report No. 65, 166pp.

Puri, K., and M.J. Miller, 1990: Use of satellite data in the specification of convective heating for diabatic initialisation and moisture adjustment in numerical prediction models. Mon. Wea. Rev., 118, 67-93.

Puri, K., and M.J. Miller, 1990: Sensitivity of ECMWF analyses-forecasts of tropical cyclones to cumulus parameterization. Mon. Wea. Rev., 118, 1709-1741.

Puri, K., 1990: Tropical numerical weather prediction studies for the 1987 Australian summer monsoon. Mausam, 41, 257-264.

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Puri, K., and P. Lonnberg, 1991: Use of high resolution structure functions and modified quality control in the analysis of tropical cyclones. Mon. Wea. Rev., 119, 1151-1167.

Puri, K., N.E. Davidson, L.M. Leslie, and L.W. Logan, 1992: The BMRC tropical limited area model. Aust. Met. Mag., 40, 81-104.

Puri, K., and N.E. Davidson, 1992: The use of satellite data as proxy data for moisture and diabatic heating in data assimilation. Mon. Wea. Rev., 120, 2329-2341.

Davidson, N.E., and K. Puri, 1992: Tropical prediction using dynamical nudging, satellite-defined convective heat sources, and a cyclone bogus. Mon. Wea. Rev., 120, 2501-2522.

Davidson, N.E., J. Wadsley, K. Puri, K. Kurihara, and M. Ueno, 1992: Implementation of the JMA typhoon bogus in the BMRC tropical prediction system. J. Met. Soc. Japan, 71, 437-467.

Puri, K., N.E. Davidson, and P. Steinle, 1995: Assimilation of information on moisture and diabatic heating from satellite imagery. The 1993 ECMWF Seminar, Developments in the use of satellite data in numerical weather prediction, 349-398.

Puri, K., 1995: Modelling studies on the Australian summer monsoon. Mon. Wea. Rev., 122, 2816-1837.

McBride, J.L., N.E. Davidson, K. Puri, and G.C. Tyrell, 1995: The flow during TOGA COARE as diagnosed by the BMRC Tropical Analysis and Prediction System. Mon. Wea. Rev., 123, 717-736.

Kurihara, K., N.E. Davidson, K. Puri, R. Bowen, and M. Ueno, 1996: Simulations of tropical cyclone Connie from the Australian Monsoon Experiment. Aust. Met. Mag., 45, 101-111.

Puri, K., and G.A. Mills, 1996: Initial state specification for mesoscale applications. J. Met. Soc. Japan, 75 No.1B, 286-413.

Davidson, N.E., K. Kurihara, T. Kato, G. Mills, and K. Puri, 1998: Dynamics and prediction of a mesoscale, extreme rain event in the Baiu front over Kyushu, Japan. Mon. Wea. Rev., 126, 1608-1629.

Puri, K., G.S. Dietachmayer, G.A. Mills, N.E. Davidson, R.A. Bowen, and L.W. Logan, 1998: The new BMRC Limited Area Prediction System, LAPS. Aust. Met. Mag. , 47, 203-223.

Saito, K., T. Keenan, G.J. Holland, and K. Puri, 2000: Diurnal evolution of tropical island convection over the maritime continent. Mon. Wea. Rev., 121, 378-400.

Puri, K., J. Barkmeijer, and T.N. Palmer, 2001: Ensemble prediction of tropical cyclones using diabatic singular vectors. Q .J. R. Met. Soc., 127, 709,731.

Barkmeijer, J., R. Buizza, T.N. Palmer, K. Puri and J.-F. Mahfouf, 2001: Tropical singular vectors computed with linearized diabatic physics. Q. J. R. Met. Soc., 127, 685-708.

Sperber, K.R., C. Brankovic, M. Deque, C.S. Frederiksen, R. Graham, A. Kitoh, C. Kobayashi, T. Palmer, K. Puri, W. Tennant and E. Volodin, 2001: Dynamical

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seasonal predictability of the Asian summer monsoon. Mon. Wea. Rev., 129, 2226-2248.

Cope, M.E., G.D. Hess, S. Lee, K. Tory, M. Azzi, J. Carras, W. Lilley, P.C. Manins, P. Nelson, L. Ng, K. Puri, N. Wong, S. Walsh and M. Young, 2003: The Australian Air Quality Forecasting System. Part I. Project description and early outcomes. J. App. Met., 43, 649-662.

Hess, G.D., K.J. Tory, M.E. Cope, S. Lee, K. Puri, P.C. Manins and M. Young, 2003: The Australian Air Quality Forecasting System. Part II. Case study: Sydney 7-day photochemical-smog event. J. App. Met., 43, 663-679.

Tory, K.J., M.E. Cope, G.D. Hess, S. Lee, K. Puri, P.C. Manins and N. Wong, 2003: The Australian Air Quality Forecasting System. Part III. Case study: Melbourne 4-day photochemical-smog event. J. App. Met., 43, 680-695.

Puri, K., 2005. Blueprint for ACCESS. Unpublished Bureau of Meteorology report.

Puri, K., 2005. Project plan for ACCESS. Unpublished Bureau of Meteorology report.

Puri, K., 2012. The Australian Community Climate and Earth System Simulator: Scientific justification and options for System development. Accepted for publication to Aust. Met. Oceanog. J.

Puri, K., Dietachmayer, G., Steinle, P., Dix, M., Rikus, L., Logan, L., Naughton, M., Tingwell, C., Xiao, Y., Barras, V., Bermous, I., Bowen, R., Deschamps, L., Franklin, C., Fraser, J., Glowacki, T., Harris, B., Lee, J., Le, T., Roff, G., Sulaiman, A., Sims, H., Sun, X., Sun, Z., Zhu, H., Chattopadhyay, M., and Engel C. 2012, Implementation of the initial ACCESS Numerical Weather Prediction system. Submitted for publication to Aust. Met. Oceanog. J.

Dix, M., Vohralik, P., Bi, D., Rashid, H., Marsland, S., O’Farrell, S, Uotila, P., Hirst, A., Kowalczyk, E., Sullivan, A, Yan, H., Franklin, C., Sun, Z., Watterson, I., Collier, M., Noonan, J., Rotstayn, L., Stevens, L., Uhe, P. and Puri, K., 2012. The ACCESS Coupled Model: Documentation of core CMIP5 simulations and initial results. Submitted for publication to Aust. Met. Oceanog. J.

Bi, D., Dix, M., Marsland, S., O’Farrell, S., Rashid, H., Uotila, P., Hirst, A., Kowalczyk, E., Golebiewski, M., Sullivan, A, Yan, H., Hannah, N., Franklin, C., Sun, Z., Vohralik, P., Watterson, I., Zhou, X., Fiedler, R., Collier, M., Ma, Z., Noonan, J., Stevens, L., Uhe, P., Zhu, H., Griffies, S., Hill, R., Harris, C., and Puri, K., 2012. The ACCESS Coupled Model: Description, control climate and evaluation. Submitted for publication to Aust. Met. Oceanog. J.

Sun, Z., Franklin, C., Zhou, X, Ma, Y., Okely, P., Bi, D., Dix, M., Hirst, A., Shonk, J.K.P, and Puri, K., 2012. Modifications in atmospheric physical parameterization aimed at improving SST simulation in the ACCESS coupled-model. Submitted for publication to Aust. Met. Oceanog. J.

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9. List of supplementary documents :( e.g., authorization letter from the Head of the organization, endorsements etc.)

Letter of support from Dr. Peter May, Deputy Director of CAWCR

10. References cited:

Ashrit, R.G., E.N. Rajagopal, G.R. Iyengar, A.K. Mitra and A.K. Bohra, 2009: Rainfall forecast verification during Monsoon 2008: T254 Vs UKMO. NCMRWF Research Report NMRF/RR/2/2009.

Ashrit, R.G., 2012: Inter-comparison of Rainfall forecasts: Global (UKMO) and Regional (SAMU) Models. Report in preparation.

Bohra, A.K., Swati Basu, E. N. Rajagopal, G. R. Iyengar, M. Das Gupta, R. Ashrit and B. Athiyaman, 2006: Heavy rainfall episode over Mumbai on 26 July 2005: Assessment of NWP guidance. Current Science, 90, 1188 -1194.

Bowler, N.E., A. Arribas, K.R. Mylne, K.B. Robertson, S.E. Beare, 2008: The MOGREPS short-range ensemble prediction system. Quart. J. Royal Meteorol. Soc., 134, 703–722.

Davidson, N.E., K. Kurihara, T. Kato, G. Mills and K. Puri, 1998: Dynamics and prediction of a mesoscale, extreme rain event in the Baiu front over Kyushu, Japan. Mon. Wea. Rev. , 126, 1608-1629.

Ebert, E.E., 2008: Fuzzy verification of high resolution gridded forecasts: A review and proposed framework. Meteorol. Appl., 15, 51-64.

Ebert, E.E. and J.L. McBride, 2000: Verification of precipitation in weather systems: Determination of systematic errors. J. Hydrology, 239, 179-202.

Iyengar, Gopal R., R.G. Ashrit, M. Das Gupta, Manjusha Chourasia, Kuldeep Sharma, V.S. Prasad, E.N. Rajagopal, A.K. Mitra, Saji Mohandas and L. Harenduprakash, 2010: NCMRWF & UKMO Global Model Forecast Verification: Monsoon 2010

Mass, C.F., D. Ovens, K. Westrick and B.A. Colle, 2002: Does increasing horizontal resolution produce more skillful forecasts? Bull. Amer. Met. Soc., 83, 407-430.

Mitra, A.K., A.K. Bohra, M.N. Rajeevan and T.N. Krishnamurti, 2009: Daily Indian precipitation analyses formed from a merged of rain-gauge with TRMM TMPA satellite derived rainfall estimates, J. Met. Soc. Japan, 87A, 265-279

NMOC, 2011: Operational implementation of the ACCESS-TC tropical cyclone numerical weather prediction system. NMOC Operational Bulletin No 90. Available from http://www.bom.gov.au/australia/charts/bulletins/apob90.pdf.

Puri, K., 2005. Blueprint for ACCESS. Unpublished Bureau of Meteorology report.

Puri, K., 2005. Project plan for ACCESS. Unpublished Bureau of Meteorology report.

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Puri, K., 2012. The Australian Community Climate and Earth System Simulator: Scientific justification and options for System development. Accepted for publication in Aust. Met. Oceanog. J.

Puri, K., Dietachmayer, G., Steinle, P., Dix, M., Rikus, L., Logan, L., Naughton, M., Tingwell, C., Xiao, Y., Barras, V., Bermous, I., Bowen, R., Deschamps, L., Franklin, C., Fraser, J., Glowacki, T., Harris, B., Lee, J., Le, T., Roff, G., Sulaiman, A., Sims, H., Sun, X., Sun, Z., Zhu, H., Chattopadhyay, M., and Engel C. 2012, Implementation of the initial ACCESS Numerical Weather Prediction system. Submitted for publication to Aust. Met. Oceanog. J.

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