Seminars / Informal seminars / Lectures by ECMWF Staff and Invited Lecturers

Seminars contribute to our ongoing educational programme and are tailored to the interests of the ECMWF scientific community.

Informal seminars are held throughout the year on a range of topics. Seminars vary in their duration, depending on the area covered, and are given by subject specialists. As with the annual seminar, this may be an ECMWF staff member or an invited lecturer.

The following is a listing of seminars/lectures that have been given this year on topics of interest to the ECMWF scientific community.  See also our past informal seminars

2017

11 December
at 14:00

Room: LT

Improved winter Euro-Atlantic atmospheric blocking in high-resolution simulations with EC-Earth

Speaker: Paolo Davini (ISAC-CNR, Torino, Italy)

Abstract

The numerical simulation of atmospheric blocking, in particular over the Euro-Atlantic region, still represents a main concern for the climate modeling community. Here we discuss winter atmospheric blocking representation in a set of atmosphere-only climate simulations produced with EC-Earth during the Climate SPHINX PRACE project. This includes 30-year long runs at five different horizontal resolutions (from T159 to T1279) with several ensemble members (up to 10).

Results show that the usual negative bias in blocking frequency over Europe becomes negligible at T511 and T799. A combined effect by the more resolved orography and by a change in tropical precipitation is identified as the source of an upper tropospheric planetary wave. At the same time, a weakening of the meridional temperature gradient reduces the upper level baroclinicity and the zonal mean winds. Following these changes, in the high resolution configurations the Atlantic eddy-driven jet stream is weakened favoring the breaking of synoptic Rossby waves over the Atlantic ridge and thus increasing the simulated European blocking frequency.

However, at high-resolution the Atlantic jet stream is too weak and the blocking duration is still underestimated. This suggests that the optimal blocking frequencies are achieved through compensation of errors between eddies found at upper levels (too strong) and eddies at lower levels (too weak).

30 November
at 10:30

Room: LT

Dynamically Consistent Parameterization of Mesoscale Eddies

Speaker: Pavel Berloff (Imperial College)

Abstract

This work aims at developing a new approach for parametrizing mesoscale eddy effects for use in non-eddy-resolving ocean circulation models. The idea is to approximate transient eddy flux divergence in a simple way, to find its actual dynamical footprints, and to relate these footprints to large-scale flow properties.

22 November
at 13:30

Room: LT

Statistical post-processing of ensemble forecasts for wind speed

Speaker: Sándor Baran (University of Debrecen, Hungary)

Abstract

Ensemble forecasts often show an underdispersive character and may also be biased, so that some post-processing is needed to account for these deficiencies. We present different versions of two popular methods for calibration of wind speed forecasts, namely the Bayesian model averaging and the ensemble model output statistics (EMOS). Both approaches provide estimates of the probability density functions of the predictable weather quantities, where model parameters are estimated using forecast ensembles and validating observations from a given rolling training period. The presented models are applied to wind speed forecasts of the fifty-member ECMWF ensemble and the eleven-member ALADIN-HUNEPS ensemble of the Hungarian Meteorological Service. The results indicate improved calibration of probabilistic and accuracy of point forecasts in comparison to the raw ensemble and to the climatological forecasts.

We also show two semi-local methods for estimating the EMOS coefficients where the training data for a specific observation station are augmented with corresponding forecast cases from stations with similar characteristics. Similarities between stations are determined using either distance functions or clustering based on various features of the climatology, forecast errors, and locations of the observation stations. In a case study on wind speed over Europe with forecasts from the Grand Limited Area Model Ensemble Prediction System, the proposed similarity-based semi-local models show significant improvement in predictive performance compared to standard regional and local estimation methods. They further allow for estimating complex models without numerical stability issues and are computationally more efficient than local parameter estimation.

21 November
at 15:30

Room: LT

Evolutions and developments of global data assimilation at Météo-France

Speaker: Loïk Berre and Gérald Desroziers

Abstract

The global data assimilation at Meteo-France is based on the IFS/ARPEGE model. The current and next configurations of the deterministic and ensemble components of this system will be briefly reminded. This includes a specific normalisation of the wavelet correlation model, which has been recently implemented.

As the error covariance specification plays a crucial role in the assimilation system, a diagnostic study of error contributions in data assimilation cycling is being conducted. This is based on a linear expansion of forecast error as function of contributions with specific ages (i.e. either old, or recent) and of different types (observations, model, background). Specific perturbations are then activated in the Ensemble Data Assimilation (EDA) system, in order to diagnose error contributions from old background states, and also from recent observations. The contribution of recent model errors is then diagnosed by comparing information provided respectively by a specific EDA experiment and by innovation-based diagnostics.

The growing role of ensembles also motivates the development of the 4DEnVar formulation, which has received increasing interest during recent years. From the beginning, Meteo-France has made the choice to implement this new 4DEnVar scheme within the OOPS (Object Oriented Prediction System) framework, initiated at ECMWF. In particular, with such a system, the background error covariance matrix is an object that can take different forms.

Unlike most implementations of 4DEnVar, the formulation developed at Meteo-France relies on the use of 4D state control variables instead of so-called alpha control variables. It also enables an observation space control variable to be used. Moreover, the use of the 4D state as control variables makes easier the formulation of hybrid 4DEnVar. In this case, the 4D state control variable remains indeed unchanged, while the background error covariance matrix simply becomes a linear combination of ensemble localised covariances and wavelet-based covariances.

Several developments related to 4DEnVar will be presented, such as the diagnosis of horizontal and vertical localisations, and the advection of localisation in order to account for dynamical effects. With the intention of using a common localisation for the different variables, and also in order to account for anisotropic aspects of the mass/wind cross-covariances, scale transformations are applied to wind and surface pressure. A parallelized version of the EDA component of 4DEnVar will also be presented, together with preliminary results.

16 November
at 15:30

Room: LT

Medium-range forecasts with a non-hydrostatic global atmospheric model on a cubed sphere grid

Speaker: Song-You Hong (KIAPS, Seoul, Korea)

Abstract

Korea Institute of Atmospheric Prediction Systems (KIAPS), Seoul, Korea, has embarked a national project in developing a new global forecast system in 2011. The ultimate goal of this 9-year project is to replace the current operational model at Korea Meteorological Administration (KMA), which was adopted from the United Kingdom’s Meteorological Office’s model. Since July 2015, the test version of the Korean Integrated Model (KIM) system that consists of a spectral element non-hydrostatic dynamical core on a cubed sphere and a revised physics package has been running in a real-time testbed. In 2017, an updated KIM with the advanced 4-DEnvar at about 12-km has been launched.  Its performance and operational deployment schedule will be presented, together with a special focus on the aerosol indirect effects on the medium-range forecasts.

30 October
at 10:30

Room: MR1

On the Nexus between Carbon Cycle and Air Quality: Exploring Multiple Constraints on Anthropogenic Combustion and Fires

Speaker: Ave Arellano
(University of Arizona, LATMOS/UPMC)

Abstract

It  is  imperative  that  we  provide  more  accurate  and  consistent  analysis  of  anthropogenic  pollution emissions at scales that is relevant to air quality, energy, and environmental policy.

Here, we present three proof-of-concept studies that explore observational constraints  from  ground, aircraft,  and  satellite-derived measurements of atmospheric composition on bulk characteristics of anthropogenic combustion in megacities and fire regions. We focus on jointly analyzing co-emitted combustion products such as CO2, NO2, CO, SO2, and aerosols from GOSAT, OCO-2, OMI, MOPITT, and MODIS retrievals, in conjunction with USEPA AQS and NASA field campaigns. Each of these constituents exhibit distinct atmospheric signatures that depend on fuel type, combustion technology, process, practices and regulatory policies. Our results show that distinguishable patterns and relationships between the increases in concentrations across the megacity or large fire events due to emissions of these constituents enable us to: a) identify trends in combustion  activity  and  efficiency,  and  b)  reconcile  discrepancies  between  state- to  country-based emission  inventories  and  modeled  concentrations  of  these  constituents. For  example, the  trends  in enhancement ratios of these species reveal combustion emission pathways for China and United States that  are  not  captured  by  current  emission  inventories  and  chemical  reanalysis. Analysis of  their  joint distributions  has considerable  potential  utility  in  current  and  future  integrated  constituent  data assimilation and inverse modeling activities like CAMS for monitoring, verifying, and reporting emissions, particularly for regions with few observations and limited information on local combustion processes. Our targeted evaluation of the global forecast and analysis of CAMS CO and CO2 during KORUS-AQ field campaign in  May  2016 suggests that  CAMS  is  able  to  capture the contrast in combustion efficiency between Chinese outflow and Seoul. Analyses of MOPITT and IASI XCO as well as GOSAT XCO2 column retrievals in  CAMS  better  capture the  variability  in  Seoul but  not  in  the  Chinese  outflow  suggesting insufficient constraints over this region. This work also motivates the need for continuous and preferably collocated  satellite  measurements  of  atmospheric  composition  (including  CH4) and  studies  related  to improving  the  applicability  and  integration  of  these  observations  with ground- and  aircraft-based measurements.

24 October
at 10:30

Room: MR1

GNSS & ATOMMS RO:  New Cubesat-Based Radio Occultation Systems for Weather & Climate

Speaker: E Robert Kursinski (Space Sciences & Engineering, Boulder, CO, USA)

Abstract

Reducing the uncertainty of weather and climate predictions requires better understanding of the hydrological and energy cycles and the intimate coupling and complex interplay between atmospheric water, temperature and stability, dynamics and short and long wave radiation.  Orbiting radar and lidar measurements have greatly increased our understanding of aerosols, clouds and precipitation and Aeolus promises analogous advances on winds in the near future.  Greatly increasing the quantity and information content of radio occultation (RO) profiling promises to provide analogous advances about temperature and water vapor as well as constraints on winds. When taken together, these combined, global, precise and high vertical resolution observations of temperature water vapor, winds, aerosols, clouds, precipitation and energy fluxes would better tie the entire weather-climate system together and yield more observationally constrained global analyses and forecast initialization, better process-related constraints to guide model improvements and reduced uncertainty about GCM realism and predictions.

The ability of GPS RO to profile atmospheric temperature and pressure with very high vertical resolution, precision and accuracy, particularly in the UTLS, is well established. With regard to water vapor, histograms of low latitude specific and relative humidity derived from COSMIC GPS RO data reveal the levels of uncertainty among global analyses and climate models. These results indicate that MERRA water vapor analyses are the best in the middle and upper troposphere while ECWMF (circa 2007) is better in the lower free troposphere. While present RO sampling densities are too sparse to impact global moisture analyses much, greatly increasing the GNSS RO sampling densities via cubesats would more tightly constrain and improve the analyses.  Our cubesat-based GNSS RO constellation, designed to provide several tens of thousands of occultations per day with performance approaching that of COSMIC-2, is scheduled to begin launching at the end of 2018.

A significant advance beyond GPS RO is achievable.  We have been developing the Active Temperature Ozone and Moisture Microwave Spectrometer (ATOMMS) RO system to probe the atmosphere near the 22 & 183 GHz absorption lines of water and 169 & 184 GHz lines of ozone.  By profiling both the speed and absorption of light, ATOMMS will profile water vapor, temperature and pressure simultaneously, which GNSS RO cannot do, from near the surface to the mesopause, with random uncertainties of 1-3% for water vapor and 0.4K for temperature and still better absolute uncertainty over most of the altitude range, with 100 m vertical resolution. Performance in clouds should be within a factor of two of clear air performance. This orbital profiling performance approaches that of radiosondes, but with far better accuracy via RO’s inherent self-calibration.

With funding from NSF, we developed a prototype ATOMMS instrument and demonstrated several key ATOMMS capabilities on the ground including retrieving water vapor to better than 1% in optical depths up to 17 through clear, cloudy and rainy conditions.

While conceived for climate, miniaturization of the ATOMMS instrument and cubesat technology have made NWP sampling densities feasible. A 60 satellite constellation delivering 25,000 ATOMMS and 170,000 GNSS RO occultations each day, providing complete global coverage every 6 hours, could be implemented for a fraction of the cost of a JPSS satellite.  Such a constellation could be implemented in stages, beginning perhaps with 4-6 ATOMMS satellites focused on polar science. This would then be expanded over time via additional satellites with the number of ATOMMS occultations increasing in proportion to the square of the number of satellites.

An ATOMMS observation simulation study would help quantify the impact of large numbers of ATOMMS profiles on NWP analyses and forecasts and move this concept forward.

19 October
at 10:30

Room: LT

LDAS-Monde global capacity assimilation of satellite-derived vegetation and soil moisture products: analysis impact over North America

Speaker: Clement Albergel (Météo-France, France)

Abstract

In this study LDAS-Monde, a land data assimilation system with global capacity, is applied over North America to increase monitoring accuracy for land surface moisture energy and water states and fluxes, including evapotranspiration and stream flow as well as vegetation growth. LDAS-Monde ingests information from satellite-derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) estimates to constrain the Interactions between Soil, Biosphere, and Atmosphere (ISBA) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (ISBA-CTRIP) continental hydrological system. LDAS-Monde uses the CO2-responsive version of ISBA which models leaf-scale physiological processes and plant growth, while transfer of water and heat through the soil rely on a multilayer diffusion scheme. SSM and LAI estimates are assimilated using a Simplified Extended Kalman Filter (SEKF), which uses finite differences from perturbed simulations to generate flow-dependence between the observations and the model control variables (LAI and seven layers of soil: from 1 cm to 100 cm depth).

LDAS-Monde analysis impact over 2007-2016 is assessed over North America using satellite-driven model estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled ground-based observations of gross primary productivity from the FLUXCOM project. Over the US, in-situ measurements of soil moisture from the USCRN network and of turbulent heat fluxes and GPP from FLUXNET-2015 are used in the evaluation, together with river discharges from the USGS. Those data sets highlight the added value of LDAS-Monde compared to an open-loop simulation (i.e. no assimilation). Finally, it has been shown that LDAS-Monde has a strong ability to monitor agricultural drought, by providing improved initial conditions which persist through time, aiding agricultural drought prediction.

6 October
at 10:30

Room: MR1

GEOMETRIC: Geometry and Energetics of Ocean Mesoscale Eddies and Their Rectified Impact on Climate

Speaker: David Marshall (Clarendon Laboratory)

5 October
at 10.30

Room: MZR

A new framework for cumulus parametrization

Speaker: Christian Jakob (Monash University, Australia)

Abstract

The representation of convection in climate model remains a major Achilles Heel in our pursuit of better predictions of global and regional climate. The basic principle underpinning the parametrization of tropical convection in global weather and climate models is that there exist discernible interactions between the resolved model scale and the parametrized cumulus scale. Furthermore, there must be at least some predictive power in the larger scales for the statistical behaviour on small scales for us to be able to formally close the parametrized equations.

The presentation will discuss a new framework for cumulus parametrisation based on the idea of separating the prediction of cloud area from that of velocity. This idea is put into practice by combining an existing multi-scale stochastic cloud model with observations to arrive at the prediction of the area fraction for deep precipitating convection. Using mid-tropospheric humidity and vertical motion as predictors, the model is shown to reproduce the observed behaviour of both mean and variability of deep convective area fraction well. The framework allows for the inclusion of convective organisation and can - in principle - be made resolution-aware or resolution-independent.

When combined with simple assumptions about cloud-base vertical motion the model can be used as a closure assumption in any existing cumulus parametrization. Results of applying this idea in the the ECHAM model indicate significant improvements in the simulation of tropical variability, including but not limited to the MJO.

27 September
at 14:00

Room: Mezzanine

Strengthening the link between meteorological and energy forecasting communities: Datasets and analytics

Speaker: Pierre Pinson (Technical University of Denmark)

Abstract

Renewable energy modelling and forecasting has come a long way since the first work performed and published in the early 80s. However, the underlying analytics has not progressed much, expect for a few breakthrough related to the transition from deterministic to probabilistic forecasting, or to the recent availability of new types of data in large quantity e.g. distributed surface observations, weather radar images, etc. In this talk, we will review and discuss these changes and how they benefit the integration of renewable energy generation in existing power systems and electricity markets. One is left to realize though that much more could be done if high-resolution regional reanalysis data was available for instance, and if developing big-data based approach to the seamless prediction of renewable energy generation at the continental scale. Personal thoughts on which directions such research is to take, and on further collaboration between energy and meteorological communities, will close the talk."

Short bio: Pierre Pinson is a Professor at the Centre for Electric Power and Energy (CEE) of the Technical university of Denmark (DTU, Dept. of Electrical Engineering), also heading a group focusing on Energy Analytics & Markets. He holds a M.Sc. In Applied Mathematics from INSA Toulouse and a Ph.D. In Energy Engineering from Ecole de Mines de Paris (France). He acts (or has acted) as an Editor for the IEEE Transactions on Power Systems, the International Journal of Forecasting and Wind Energy. His main research interests are centered around the proposal and application of mathematical methods for electricity markets and power systems operations, including forecasting. He has published extensively in some of the leading journals in Meteorology, Power Systems Engineering, Statistics and Operations Research. He has been a visiting researcher at the University of Oxford (Mathematical Institute) and the University of Washington in Seattle (Dpt. of Statistics), as well as a scientist at the European Center for Medium-range Weather Forecasts (ECMWF, UK) and a visiting professor at Ecole Normale Superieure (Rennes, France). He is leading a number of initiatives aiming to profoundly rethink electricity markets for future renewable-based power systems and with a more proactive role of consumers. This focus on consumer-centric and community-driven electricity markets translates into proposals for peer-to-peer energy exchange, from mathematical framework to actual demonstration in Denmark.

15 September
at 13.30

Room: LT

Prediction of Arctic sea ice on subseasonal to seasonal time scales

Speaker: Zampieri Lorenzo (AWI, Germany)

Abstract

Sea ice forecasts are becoming a demanding need since human activities in the Arctic are constantly increasing and this trend is expected to continue. In this context, the recent availability of the Subseasonal to Season al Prediction Project (S2S) Dataset has a particularly good timing and provides a solid base to make an initial assessment of the predictive skills of probabilistic forecast systems with dy namical sea ice . In this study , we employ different verification metrics to compare the S2S sea ice forecasts with satellite observations and the models ’ own analys es. In particular , the focus is on the sea ice spatial distribution in the Arctic, which is relevant information for potential final users. The verification metrics, specifically chosen to quantify the quality of the forecasted sea ice edge position , are the Integrated Ice Edge Error (IIEE), the Spatial Probability Score (SPS) and the Modified Hausdorff Distance (MHD).

Despite the early development stage of Arctic sea ice predictions on the seasonal time scale , and the fact that the main focus of the S2S systems is mostly not on sea ice per se, our findings reveal that some of the S2S models are promising , exhibiting better predictive skills than the observation -based climatology and persistence . However, the results also point to critical aspec ts concerning the data assimilation procedure and the tuning of the models , which can strongly affect the forecasts quality . The comparison of different versions of the ECMWF forecast system shows the benefits brought by a coupled dynamical description of the sea ice instead of its prescription based on persistence and climatolog ical records. Moreover, the systematic application of the verification metrics to such a broad pool of forecasts provides useful indications about strengths and limitation of the verification metrics themsel ves. Given the increasing av ailability of new and better sea ice observations and the possible improvement s to coupled seasonal forecast systems, the formulation of reliable Arctic sea ice predictions for the subseasonal to seasonal time scales appears to be a realistic target for the scientific community.

7 September
at 10:30

Room: LT

Recent Developments in Atmospheric River Science, Prediction and Applications

Speaker: F. Martin Ralph (CW3E, Univ. California/ Scripps Institute of Oceanography, USA)

Abstract

A number of key developments have occurred recently on the subject of atmospheric rivers (AR).  These include advances in observations, physical process understanding, predictions, applications and policies.  This presentation will highlight a few of these developments. 

  • Detailed observations of 21 ARs using dropsondes from research aircraft show that an average AR transports, as vapor, roughly 2 times as much water as the Amazon River discharges, as liquid.
  • Extreme precipitation from a series of landfalling ARs led to damage of a spillway of a major flood control dam in February 2017, which triggered an evacuation of 200,000 people in Northern California.
  • Methods are being developed to evaluate AR landfall forecast skill, partly to support potential use of AR forecasts in future reservoir operations.
  • New observations focused on ARs are now available from a specialized mesonet in California and an airborne targeting approach using multi-aircraft dropsonde deployments is under development (including use of research and reconnaissance aircraft normally dedicated to hurricane activities in the warm season).
  • A critical mass of research and experimental forecast capability, with an emphasis on AR science, predictions and applications, has been developed at the Center for Western Weather and Water Extremes.

6 September
at 15.30

Room: LT

Ensemble Seasonal Coupled Streamflow Forecast for Hydropower in Brazil

Speaker: Alberto Assis dos Reis (CEMIG, Brazil)

Abstract

The Brazilian electric system is essentially hydrothermal, with a great weight of hydraulic generation (near 65%). The streamflow forecast can be very beneficial to allow early response in extreme climactic events and for a more efficient operation of the hydro power plants. At this project we aim at using ensemble weather forecasts and ESP-Ensemble Streamflow Prediction technique as a forcing for the hydrological models to develop a robust forecasting. The developments will be conducted within the FEWS-Cemig platform which is already running in operational mode. First we will deal with the uncertainty of the observed precipitation, combining different source of gridded observed precipitation to obtain a better estimative, test different sampling methods to apply the ESP methodology, run the hydrologic models for a group of basins and apply flow data assimilation to improve the models results. Then we will deal with the uncertainty of short term, intra-seasonal and seasonal precipitation forecast models and apply bias correction technics to improve the flow forecasts. Finally we will couple the observed precipitation; flow data assimilation; short term, intra-seasonal and seasonal precipitation forecasts and the ESP technic to obtain a seamless ensemble seasonal flow forecast with the hydrological models.

6 September
at 10:30

Room: LT  

Parameterization of non-orographic gravity-waves: formalism, impact and test against observations

Speaker: François Lott, (LMD, France)

Abstract

A stochastic parameterization of the non orographic gravity waves emitted by convection and fronts is presented.  For the front the formalism is based on a spontaneous adjustment theory where potential vorticity anomalies emit gravity waves in the course of their evolution. The introduction of explicit sources and the use of a stochastic multiwave formalism makes that the momentum fluxes predicted by the scheme are highly intermittent. This intermittent character is one of the key properties of the gravity waves measured by constant level balloons during the vorcore and   concordiasi campaign. It is shown that the scheme can be realistic in representing it. It is also shown  that intermittency in non-orographic gravity waves prediction can be important to predict the final warming in the middle atmosphere of the Southern Hemisphere in early spring. With sources, we can also address how the gravity waves forcing changes when the climate change. The results so far are quite neutral, at least in the middle atmosphere of the LMDz GCM, which probably follows that GWs are strongly filtered by the large scale background winds in the middle atmosphere.

8 August
at 10:30

Room: MR1

Introducing the new Master of Science Degree in Environmental Meteorology

Speaker: Dino Zardi (University of Trento, Italy)

Abstract

The seminar introduces the project of a new programme, leading to an MSc degree in Environmental Meteorology, jointly offered by the Universities of Trento (Italy) and Innsbruck (Austria). The programme aims at preparing experts with a solid background in atmospheric processes relevant for a range of environmental systems and interactions. Courses cover not only typical meteorological subjects - including observational, theoretical, and numerical modelling approaches - but also environmental topics, such as hydrology, renewable energy resource assessment, agricultural and forest interactions with the atmosphere, air quality measurement and modelling, mountain meteorology, environmental physical-chemistry, biogeochemistry. All the lectures will be given in English, partly in Trento and partly in Innsbruck. The programme is going to start in September 2018. Access will be offered to a limited number of selected candidates. During my seminar, I will present this new educational initiative, and will be very happy to hear comments and suggestions from the audience.

25 July
at 10:30

Room: MR1

Seasonal analysis of near-surface biases in ERA-Interim over the Canadian Prairies

Speaker: Alan Betts (Atmospheric Research)

Abstract

We quantify the biases in the diurnal cycle of temperature in ERA-Interim for both warm and cold season using hourly climate station data for four stations in Saskatchewan from 1979-2006. The warm season biases increase as opaque cloud cover decreases, and change substantially from April to October. The bias in mean temperature increases almost monotonically from small negative values in April to small positive values in the fall. Under clear skies, the bias in maximum temperature is of the order of -1 o C in June and July, and -2 o C in spring and fall; while the bias in minimum temperature increases almost monotonically from +1 o C in spring to +2.5 o C in October. The bias in the diurnal temperature range falls under clear skies from -2.5 o C in spring to -5 o C in fall. The cold season biases with surface snow have a different structure. The biases in maximum, mean and minimum temperature with a stable BL reach +1 o C, +2.6 o C and +3 o C respectively in January under clear skies. The cold season bias in diurnal range increases from about -1.8 o C in the fall to positive values in March. These diurnal biases in 2-m temperature and their seasonal trends are consistent with a high bias in both the diurnal and seasonal amplitude of the model ground heat flux, and a warm season daytime bias resulting from the model fixed leaf area index. Our results can be used as bias corrections in agricultural modeling that use these reanalysis data, and also as a framework for understanding model biases.

12 July
at 14:00

Room: MR3

Robust and transparent planning and operation
of water resource infrastructure

Speaker: Francesca Pianosi (Dept. of Civil. Eng., Bristol Univeristy, UK)

Abstract

Sustainable management of water resources is crucial to underpin population’s health and the economy while increasing resilience against hydro-meteorological hazards such as floods and droughts. In the UK, the water industry faces significant water challenges due to increasing variability of hydrological conditions, changing patterns of water demand and the urgency of reconciling human needs with the protection of the natural environment. In response to such challenges, the UK regulatory frameworks for the water industry (AMP6) has promoted a shift in focus from a ‘capex’ (capital expenditure) to a ‘totex’ (total expenditure) approach and emphasised the need to develop new skills to find ‘no build’ solutions and address supply and quality issues at catchment scale rather than at each individual infrastructure (e.g. treatment plants or pumping station).

To put this priority into practice, two methodological gaps need to be fill in: [1] How to integrate and exploit “built’ infrastructures (e.g. reservoirs, pumping stations, etc.) and “information” infrastructures (e.g. increasingly sophisticated monitoring and forecasting systems) – to promote water efficiency and enhance resilience of water resource systems. [2] How to estimate and compare long-term costs of alternative infrastructure or management options, given the increasingly high uncertainty in future conditions (both on the supply and demand side) induced by unprecedented rate of change in environmental (e.g. climate and hydrology) and socio-economic (e.g. population and consumption behavior) conditions.

The goal of this project is to build the next-generation analytical approaches (simulation and optimisation models and methods) to fill these gaps. These tools will produce actionable information to support both operational (shortterm) and design (long-term) decisions in a robust and transparent way. The project will be carried out in close collaboration with partners representative of the key players of the UK water industry: water suppliers (water companies), knowledge and model providers (consultancy company, government research institutes such as the MetOffice) and regulators (Environment Agency). All methods will be developed and tested on case study applications provided by water companies, so to ensure that they are actually valuable to address the most urgent issues they face, and they will be implemented in open-source software packages so that also other water practitioners besides those directly involved in the project will benefit from its findings and outputs.

10 July 
at 10:30

Room: LT

Representing the stratosphere in atmospheric models (and why it matters)

Speaker: Ted Shepherd (Dept of Meteorology, Reading University)

Abstract

Over the last two decades, it has become apparent that the state of the stratosphere affects the troposphere, and thus that model deficiencies in the stratosphere have tropospheric implications. Whilst stratosphere-troposphere dynamical coupling is a robust phenomenon on many timescales, the lack of a detailed understanding of the mechanisms involved means that model deficiencies in this respect can be difficult to alleviate. This talk will discuss some of the issues involved, as well as highlighting some of the early findings from the Stratosphere Task Force.

6 July
at 10:30

Room: LT

Coupled data assimilation efforts at the US Naval Research Laboratory

Speaker: Sergey Frolov (Naval Research Laboratory, Monterey, California, USA)

Abstract

Data assimilation in coupled models of ocean-atmosphere-ice presents a unique set of challenges. The spatial and temporal scales vary by an order of magnitude between fluids, the covariances between components of the coupled system are poorly known, the assimilation methods tend to differ, and coupled models often do not have tangent linear and adjoint models. In this presentation, we show several algorithmic solutions that allow us to resolve these challenges. Specifically, we introduce the interface solver method that augments existing stand-alone systems for ocean and atmosphere by allowing them to be influenced by relevant measurements from the coupled fluid. To propagate information between fluids, we use coupled ensembles. In this talk we present a combination of development plans for the Navy’s global coupled model, as well as set of preliminary results on the impact of assimilating SST-sensitive radiances in the atmospheric model and first results of hybrid DA in 1/12 degree model of the global ocean

4 July
at 14:00

Room: LT

EuroHPC and domain science driven technologies for exascale

Speaker: Thomas Schulthess (Director of the Swiss Supercomputing Centre, Switzerland)

4 July
at 10:30

Room: LT

An introduction to the European Environment Agency and its work on key thematic areas

Speaker: Hans Bruyninckx (Executive Director, EEA, Belgium)

Abstract

The presentation will provide a summary of the EEA, its governance, networks and member countries. It will look at its 2014-2020 work programme focusing on various thematic areas and relevant European and global policies.

The presentation will also assess anticipated challenges for the Agency.

Moving beyond this general introduction, the presentation will then look at the EEA’s principal areas of work such as air pollution, climate change and energy, water management, marine, and the Copernicus Land monitoring service (CLMS) which the EEA manages. Finally, a summary of the EEA’s interactions with the Copernicus Climate Change Service (C3S) and Copernicus Atmosphere monitoring Service (CAMS) will be provided.

3 July
at 10:30

Room: LT

EC-Earth as a test-bed for climate prediction and services research

Speaker: F J Doblas-Reyes  (ICREA and BSC, Barcelona, Spain)

Abstract

The EC-Earth climate model has the atmosphere and ocean components in common with the ECMWF seasonal forecast system. However, there are many differences between the two models such as the atmosphere and ocean cycles, the resolution, the Earth system components, etc. This talk will discuss these differences using EC-Earth as a climate forecast system and suggest ways in which the differences can be exploited to provide useful feedback to ECMWF. The main ideas will be illustrated in the context of climate services research.

28 June
at 10:30

Room: LT

Self-organization of convection and regulation of tropical climate

Speaker: Marat Khairoutdinov (Stony Brook University, US)

Abstract

Evidence from paleoclimate reconstructions suggests that the tropical climate has been essentially stable with just a few degrees variations in SSTs despite much higher concentration of greenhouse gases than at present. It has been hypothesized that the tropical climate is maintained by self-aggregation or clustering of convection. Idealized cloud-resolving simulations show that warmer SSTs are conducive to aggregation, which has a tendency to dry out the atmosphere reducing the greenhouse effect and, hence, providing powerful negative feedback to warming. Similar mechanism can also operate in response to projected climate warming due to anthropogenic forcing. Recent results from idealized Near-Global (NG) cloud-resolving simulations of tropically centered belt on aquaplanet show that while  the number of small and medium size convective clusters tend to be invariant of warming, the number of super-clusters associated with large-scale equatorially trapped waves such as Kelvin-waves can substantially increase in the warmer climate.  However, contrary to several recent studies, our NG experiments over constant-SST aquaplanet with Earth-like circumference alone the equator show a substantial decrease of MJO variance at warmer SSTs. Possible mechanisms for such behavior will be discussed. Also, some preliminary results of global cloud-resolving simulations of Earth using a newly developed global cloud-resolving model at 4 km grid spacing will be presented.

27 June
at 11:00

Room: MR1

A Case Study of the June 2013 Biomass-Burning Haze Event Using WRF-Chem

Speaker: Andy Chan (University of Nottingham, Malaysia Campus, UK)

23 June
at 10:30

Room: MR1

Bias correction of tropical cyclone size and structure in the ECMWF global ensemble prediction system

Speaker: Jeff Kepert (Bureau of Meteorology, Australia)

Abstract

Global EPS systems provide very valuable warning of severe weather risk, including tropical cyclones. One limitation arises because the spatial resolution of the EPS is necessarily too coarse to capture the fine details of the tropical cyclone's core circulation, resulting in the predicted storms having systematic biases in structure and intensity. In particular, the cyclones are too weak and the radius to maximum winds is too large, with these biases increasing with forecast length. Ocean waves are a major impact mechanism of tropical cyclones, but these atmospheric biases result in errors in the predicted ocean wave field also. While these biases to not affect users who respond purely to the expected risk of a tropical cyclone in their vicinity, they are important for users who wish to make more quantitative use of the wind or wave predictions.

We have developed a method for bias correcting tropical cyclone structure and intensity in EPS systems, and applied it to cyclones off north west Australia in the ECMWF global EPS. The method diagnoses the properties of forecast storms within the EPS, and replaces them in the surface wind and pressure field with parametric vortices with the corrected intensity and structure. The correction scheme is statistical, based on regression analysis of historical errors. The bias-corrected wind field ensemble is then used to force a wave model ensemble.

This work was supported by Woodside, Shell, Inpex and Chevron, who operate in the waters off north west Australia.

22 June
at 11.15

Room: MZR

A statistical-dynamical ensemble approach to forecasting water hazards

Speaker: Louise Slater (Loughborough University, UK)

Abstract

Traditional hydrologic forecasting approaches are either statistical, relating climate precursors to streamflow/stage, or dynamical, forcing hydrologic models with meteorological forecasts. In contrast, hybrid statistical-dynamical techniques benefit from different strengths: they are computationally efficient, can integrate and ‘learn’ from a broad selection of input data (GCM forecasts, Earth Observation time series, teleconnection patterns), and can benefit from recent progress in machine learning (e.g. multi-model blending, post-processing and ensembling techniques). 

Using climate forecasts from the North American Multi Model Ensemble (NMME: CCSM3, CCSM4, CanCM3, CanCM4, GFDL2.1, FLORb01,GEOS5, and CFSv2), we conduct systematic probabilistic forecasting of monthly-seasonal streamflow and water levels in several hundred catchments across the U.S. and U.K, over weekly to decadal timescales. In heavily urbanised or agricultural catchments, we find that changing land use is a key predictor of streamflow and water levels. While our current approach uses various proxies to model the effects of land cover, this work opens up new possibilities for combining Earth Observation time series with GCM forecasts to predict a variety of hazards (incl. low/high water levels and water pollution) from space using data science techniques.

20 June
at 14:00

Room: LT

Porting IFS physics cloud scheme (CLOUDSC) to GPUs with OpenACC

Speaker: Huadong Xiao (ECMWF, UK)

Abstract

A physics cloud scheme is an important component of a numerical weather/climate prediction model which represents the cloud processes in it. The IFS physics cloud scheme (CLOUDSC) solves five prognostic equations for water vapour, cloud liquid water, rain, cloud ice and snow mixing ratios in an implicit numerical framework. It is a computationally intensive part in the ECMWF model. GPU computing has been extensively applied in scientific and engineering computing recently due to the progress of GPU hardware and related programming models such as CUDA/OpenCL and OpenACC. Given the advantages with respect to code portability and simplicity with OpenACC over CUDA we implement an accelerated CLOUDSC with OpenACC. It combines MPI, OpenMP and OpenACC to fully exploit the power of GPUs across a single or multiple nodes, together with various optimizations. The results show that in terms of the total GPU runtime the obtained performance of 4 NVIDIA GK210 GPUs (2 NVIDIA K80) on a single node for a single time-step is comparable to that of a whole node of 2 Intel Xeon Haswell CPU with 24 cores if the workload saturates GPUs; but without taking into account the GPU data transfer and other overheads, the GPU actual calculation time with a single GPU is about 17% less than that of a whole CPU node with 24 cores for the same problem size. In an operational forecast where multiple time-steps are taken data can be resident on GPU and need to be communicated to CPU only during an I/O step. Therefore, based on the results of this implementation, we conclude that a GPU adaptation of the CLOUDSC can be competitive in terms of performance with respect to CPU.

20 June
at 10:30

Room: MZR

WAVE2NEMO: A regional WAM-NEMO model setup

Speaker: Øyvind Breivik (Norwegian Meteorological Institute, Norway)

Abstract

The WAVE2NEMO project, funded by CMEMS, aims to implement a number of wave effects in a regional NEMO version. The project builds on work started at ECMWF and implements Coriolis-Stokes forcing, wave-induced mixing by breaking waves and wave-modified momentum fluxes in forced mode with wave fields taken from a regional WAM model. A wave-forced model of the North Sea and the Baltic Sea is found to have improved water level representation during two wind storms in the autumn of 2013. The model also shows slightly improved SST biases in the Baltic Sea compared to a control run. Recent work on approximate Stokes drift profiles (Breivik et al, 2016, Li et al, 2017) has led to a new layer-averaged Stokes drift profile which is now being tested in the regional NEMO setup. We hope to collaborate with ECMWF on the implementation of these wave effects in the most recent version of NEMO.

19 June
at 14:00

Room: MR1

Atmospheric Rivers in Europe: from moisture sources to impacts and future climate scenarios

Speaker: Alexandre Ramos (Instituto Dom Luiz, Portugal)

Abstract

An atmospheric river (AR) detection algorithm is used for the North Atlantic ocean basin, allowing the identification of the major ARs affecting western European coasts between 1979 and 2014. The western coast of Europe was divided into five domains, namely the Iberian Peninsula, France, UK, Southern Scandinavia and the Netherlands, and Northern Scandinavia. Following the identification of the main ARs that made landfall in western Europe, a Lagrangian analysis was then applied in order to identify the main areas where the moisture uptake was anomalous and contributed to the ARs reaching each domain.

There is a strong relationship between extreme precipitation across Europe and ARs.  In the particular case of the Iberian Peninsula, the major AR events that affected the region were studied in detailed. It was analyzed if the extreme precipitation days in the Iberian Peninsula are association (or not) with the occurrence of ARs. Results show that the association between ARs and extreme precipitation days in the western river basins is noteworthy, while for the eastern and southern basins the impact of ARs is reduced.

Since the ARs are associated with high impact weather it is of most importance to assess changes in the ARs frequency in future climate changes. Regarding Europe, changes in the vertically integrated horizontal water transport were analyzed using six global climate models. There is an increase in the vertically integrated horizontal water transport which lead to an increase in the ARs frequency for the 2074- 2099 period when compared with the historical simulation (1980-2005). This increase in  future ARs frequency is estimated to be more visible in the high emission scenarios (RCP8.5) when it can more than double the annual mean of ARs obtained for the historical simulation, as shown in Figure 2 for the “Southern Scandinavia and The Netherlands” domain.

8 June at 13:00-18:00

Symposium on dynamic meteorology and numerical weather prediction

Speakers:

  • Raymond T. Pierrehumbert (Halley Professor of Physics at the University of Oxford)
  • Nedjeljka Žagar (Associate Professor of Meteorology at the University of Ljubljana)
  • Hans Huang (Head of Weather Modelling and Prediction at the Centre for Climate Research Singapore)
  • Stephen Belcher (Chief Scientist at the UK Met Office)
  • David Burridge (Director of ECMWF 1991–2004)
  • Erland Källén (Director of Research at ECMWF)
  • Florence Rabier (Director-General of ECMWF)

Abstract: Raymond Pierrehumbert

Raymond Pierrehumbert will speak on multiple equilibria, bifurcations and climate regimes. Professor Pierrehumbert’s research on climate has spanned timescales from billions of years in the past to billions of years in the future. His work on atmospheric dynamics has included contributions to theories of weather regimes and blocking, baroclinic instability, stratified flow (with applications to mountain meteorology), atmospheric mixing problems and dynamical control of atmospheric humidity.

Abstract: Nedjeljka Žagar

Nedjeljka Žagar will talk about data assimilation in the context of tropical dynamics. Professor Žagar’s research interests range from modelling mid-latitude mesoscale weather to large-scale tropical variability and data assimilation. Her research has highlighted the role of large-scale equatorial waves in tropical data assimilation. She applies normal modes for the scale-dependent evaluation of the global unbalanced circulation and the growth of forecast uncertainties in ensemble prediction.

Abstract: Hans Huang

Hans Huang’s lecture will be devoted to high-resolution forecast modelling in the context of tropical dynamics. Dr Huang has extensive experience of data assimilation research, observation system design and assessment, and NWP system development. He was the lead scientist for data assimilation in the forecast system developed by the European HIRLAM programme, and the manager of the US-based Weather Research and Forecasting (WRF) Model data assimilation system.

Abstract: Stephen Belcher

Stephen Belcher will talk about climate change. Since 1990, Professor Belcher has published over 100 peer-reviewed papers on the fluid dynamics of atmospheric and oceanic turbulence. Between 2007 and 2010, he was the Head of the School of Mathematical and Physical Sciences at the University of Reading. In 2012, he joined the Met Office as Director of the Met Office Hadley Centre for Climate Science and Services before becoming the Met Office Chief Scientist in November 2016.

Abstract: David Burridge

David Burridge will speak on the past evolution of numerical weather prediction at ECMWF. Dr Burridge was the Head of Research at ECMWF from 1982 to 1991 and the Centre’s Director from 1991 to 2004. Subsequently he shaped and steered the implementation of THORPEX, a ten-year international research and development programme set up by the World Meteorological Organization to improve one-day to two-week forecasts of high-impact weather.

Abstract: Erland Källén

Erland Källén’s lecture will be about the Centre’s research and operations today. Between 1983 and 2009, Professor Källén was first an associate professor and later professor in dynamic meteorology at Stockholm University. His research areas are large-scale dynamics of the atmosphere, NWP and climate modelling. He has worked as a project leader for the HIRLAM programme and was responsible for initiating and heading the first Swedish climate modelling programme in the 1990s.

Abstract: Florence Rabier

Florence Rabier will talk about what the future holds for numerical weather prediction and related services at ECMWF. Dr Rabier has greatly contributed to delivering major operational changes at ECMWF and Météo-France. She is especially well known within the meteorological community for her key role in implementing a new data assimilation method (4DVar) in 1997. She was ECMWF’s Director of Forecasts before she became the Centre’s Director-General in January 2016.

25 May
at 10.30

Room: LT

20th Century trends in potential predictability and the role of land surface

Speaker: Bart van den Hurk (KNMI, The Netherlands)

Abstract:

Climate change does give rise to shifts in patterns of risks of high-impact extreme events. An important means to adapt to extreme events is early warning, based on skilful forecasts. The ability to forecast any signal is inherently limited by the chaotic nature of the system. A change in the variability patterns in the climate system may or may not impose shifts in the inherent potential predictability of phenomena at monthly to seasonal time scales, which may or may not change our ability to prepare to these phenomena.

 

During a short sabbatical stay I've explored signatures of trends in potential predictability and the role of land surface processes in this. Use was made of earlier 20th century reforecasts by Antje Weisheimer, where at 4 startdates per year an ensemble of 51 4-month forecasts was produced initialized from ERA20C. In order to explore the role of the land surface, a duplicate experiment was performed in which the land surface in each of the ensemble members was initialized from different states, removing the source of predictability arising from this component in the climate system.

 

The seminar will review some related studies reported earlier in the literature, and will present early results of the experiments carried out at ECMWF. Suggestions for further analyses from the audience are more than welcome.

22 May
at 9:30

Room: CC

Statistical postprocessing of multi-model ensemble
precipitationforecasts in the US National Weather Service

Speaker: Tom Hamill (NOAA Earth System Research Lab, USA)

Abstract

Taking concepts developed in programs such as THORPEX/TIGGE, the US NWS is embracing the use of multi-model ensembles and their statistical postprocessing using short training data sets.  The intended goal is to produce dramatically improved forecasts of important weather elements such as temperature, winds, and precipitation, both deterministic and probabilistic.  Generating reliable and skillful forecasts of precipitation will be the focus of this talk.  Postprocessing of precipitation is especially challenging since forecast bias depends on precipitation amount, and a short training sample (here, the previous 60 days) is often insufficient to estimate this conditional, often location-dependent bias. 

This talk will discussed a sequential algorithm for precipitation postprocessing over the US for forecast leads of +1 to +10 days using US and Canadian global ensemble data, an algorithm that provides a workaround for limitations imposed by using a short training data set. The steps in the postprocessing include: (a) pre-specification of "supplemental locations" for each model grid point -- i.e., the specification of other grid points with similar precipitation climatologies and terrain characteristics that are likely to have similar forecast biases. (b) generating forecast and analyzed cumulative distribution functions (CDFs) for each grid point using the last 60 days of forecasts, including data from supplemental locations. (c) Quantile mapping of each member forecast at each grid point; (d) Dressing each quantile-mapped forecast with amount-dependent noise to account for the under-spread character of ensemble forecasts; (e) estimation of probabilities from the ensemble relative frequency; and (f) Savitzky-Golay smoothing of forecasts in regions with little variation in terrain height.  The resulting forecasts are shown to be highly reliable and skillful

19 May
at 14:00

Room: LT

Application of a CubeSat-Based Passive Microwave Constellation to Operational Meteorology

Speaker: Al Gasiewski (University of Colorado, USA)

Abstract

In their most recent decadal assessment (Earth Application from Space, 2007) of Earth science space missions the U.S. National Research Council identified the Precipitation and Allweather Temperature and Humidity (PATH) mission as one of ten recommended medium cost missions. Based on the NRC’s outlined goals, PATH would have the unique capability of providing allweather temperature and moisture soundings and cloud and raincell imagery at spatial scales comparable to AMSU-A/B or ATMS, but at sub-hourly temporal resolution. The essential need is to provide the atmospheric penetrability and spatial resolution of operational microwave sensors but with temporal resolution commensurate with the natural rate of evolution of convectively driven weather. This seminar will focus on the merits of a constellation of passive microwave sounding and imaging CubeSats for achieving PATH goals from the multiple viewpoints of calibration accuracy, data assimilation and global sampling, downlink capability and latency, and orbital lifetime and launch availability. Microwave spectral imagery at 50, 118, and 183 GHz with spatial resolution of ~10-30 km and temporal resolution of ~15-60 minutes from such a fleet could be expected to significantly enhance forecasting of mesoscale convective weather and hurricane rain band evolution, along with provide valuable temporal gap-filling data for synoptic weather forecasting. It is argued that from a joint technology, science, and operational standpoint that a cost-effective realization of the PATH goals, but with the additional features of global coverage and improved NWP sensitivity, can be achieved by a low-cost random-orbit constellation of CubeSats supporting the ATMS and 118 GHz bands. The CU PolarCube mission will be discussed as a basis for this fleet concept.

18 May
at 10:30

Room: MR1

"How do I know if I’ve improved my continental scale flood early warning system?"

Speaker: Hannah Cloke (University of Reading, UK)

Abstract

Flood early warning systems mitigate damages and loss of life and are an economically efficient way of enhancing disaster resilience. The use of continental scale flood early warning systems is rapidly growing. The European Flood Awareness System (EFAS) is a pan-European flood early warning system forced by a multi-model ensemble of numerical weather predictions. Responses to scientific and technical changes can be complex in these computationally expensive continental scale systems, and improvements need to be tested by evaluating runs of the whole system. It is demonstrated here that forecast skill is not correlated with the value of warnings. In order to tell if the system has been improved an evaluation strategy is required that considers both forecast skill and warning value. The combination of a multi-forcing ensemble of EFAS flood forecasts is evaluated with a new skill-value strategy. The full multi-forcing ensemble is recommended for operational forecasting, but, there are spatial variations in the optimal forecast combination. Results indicate that optimizing forecasts based on value rather than skill alters the optimal forcing combination and the forecast performance. Also indicated is that model diversity and ensemble size are both important in achieving best overall performance. The use of several evaluation measures that consider both skill and value is strongly recommended when considering improvements to early warning systems.

16 May
at 10:30

Room: LT

Mesoscale aggregation of shallow marine cumulus convection

Speaker: Christopher Bretherton (University of Washington, USA)

Abstract

Over the oceans, shallow cumulus convection, often mixed with patchy stratocumulus, is a common cloud type.  It is usually 'aggregated' into mesoscale patches or polygons of deeper cumuli, with possible consequences for the mean vertical structure of cloud cover and cloud-precipitation-aerosol interaction.  Large-eddy simulations (LES) covering domains 50 km or more across also exhibit mesoscale aggregation of shallow cumulus convection, but it is not fundamentally well understood.   To further that understanding, we analyze the development of convective aggregation in multiday LES of a 108x108 km doubly periodic domain simulating mean summertime conditions at a location east of Hawaii.  The simulated convection aggregates within 12 hours.  Vertically resolved heat and moisture budgets on mesoscale subdomains elucidate this process.  Shallow cumulus deepen preferentially in more humid regions of the boundary layer, stimulating net moisture convergence into those regions.  Sensitivity studies show that the aggregation does not require precipitation.  Aggregation is weakened but not prevented if radiative cooling and surface fluxes are horizontally homogenized.  A unifying conceptual model explains these findings.

15 May
at 13:30

Room: LT

Measuring Large Scale Divergence and Vorticity by Aircraft

Speaker: Bjorn Stevens (MPI, Germany)

Abstract

During NARVAL-2 an extensive array of dropsondes were launched over the tropical Atlantic, near the ITCZ, to test methods for measuring large scale vertical velocity.  These measurements have been evaluated and show that as few as 12 dropsondes launched by an aircraft are well suited to estimating divergence on the scale of a flight leg.  Analysis of high-resolution (1-2 km) simulations over the tropical Atlantic during the ICON period are used to evaluate the credibility of the measurements, and the richness of the vertical structure observed, as well as to characterize the spatial and temporal correlation of divergence as a function of scale. The analysis and measurements open a new chapter in observing diabatic processes in the tropical atmosphere and underpin a major new field initiative planned for 2020.

5 May
at 10:30

Room: LT

Improved Climate Forecasting Service of Australian Bureau of Meteorology

Speaker: William Wang (Bureau of Meteorology, Australia)

Abstract

Australia Bureau of Meteorology has started seasonal climate outlook service since 1989 based purely on statistical methods using tropical SST conditions as predictors. In May 2013 the Bureau of Meteorology Climate Information Services has started issuing climate outlooks based on the Predictive Climate Ocean Atmosphere Model for Australia, a dynamical climate model developed by the Bureau of Meteorology and CSIRO Marine and Atmospheric research division. Since 2016, we have been developing our next generation of climate forecasting system and products based on UKMO Glosea5 or ACCESS-S. This talk is to give an overall picture of the climate prediction services in Australia through the following aspects:

  1. A very brief introduction of our Bureau’s climate forecast service history; why we did what we did, experiences and lessons we obtained from the past;
  2. The current dynamic climate forecasting system
    • A very brief introduction of (POAMA)
    • The revolutionary transition from statistic to dynamic and how did we make such a CHANGE;
    • What we investigate when we develop a new climate forecasting system and how, including verification metrics, such as percent consistence, LEPS, ROC skill, Brier skill score etc. and some major results as the benchmarks of a system;
    • The current services and the online products and relevant issues.
  3. The development of the next generation of Bureau’s climate forecasting system
    • The new ACCESS-S/UK Met Office Glosea5 model and why it was chosen;
    • Development of new forecasting system and products– the concept of seamless forecasting from weather to annual climate prediction.
    • Primary results of this development
  4. A brief introduction of a new verification metric, the so called weighted percent consistence

26 April
at 10:30

Room: LT

Compatible finite element methods for numerical weather prediction

Speaker: Jemma Shipton (Imperial College, UK)

Abstract

We present recent work on developing a compatible finite element model for numerical weather prediction. This work has been motivated by the requirement for numerical discretisations that are stable and accurate on nonorthogonal grids (such as icosahedral or equiangular cubed sphere grids) without sacrificing properties of conservation, balance and wave propagation that are important for accurate atmosphere modelling on the scales relevant to weather and climate (Staniforth et. al. 2012).

Compatible finite element methods are a type of mixed finite element method (where different finite element spaces are used for different fields) where the divergence of the velocity space maps on to the pressure space. This necessitates the use of div-conforming finite element spaces for velocity, such as Raviart-Thomas and Brezzi-Douglas-Marini, and discontinuous finite element spaces for pressure. The main reason for choosing compatible finite element spaces is that they have a discrete Helmholtz decomposition of the velocity space; this means that there is a clean separation between divergence-free and rotational velocity fields. Cotter and Shipton (2012) used this decomposition to demonstrate that compatible finite element discretisations for the linear shallow water equations satisfy the basic conservation, balance and wave propagation properties listed in Staniforth and Thuburn (2012).

In the talk we will show the progress we have made towards extending this approach to the fully 3D equations via a vertical slice model. Many current atmospheric models use a staggered Charney Phillips grid in the vertical to ensure a good representation of hydrostatic balance. In the finite element context the equivalent staggering requires the temperature field to be discontinuous in the horizontal direction but continuous in the vertical. We present a stable and accurate advection scheme for this field. The success of this approach is illustrated by benchmarking results from our model, implemented in Firedrake (www.firedrake.org).

25 April
at 10:30

Room: LT

Developments in ensemble variational data assimilation at Météo-France

Speaker: Benjamin Ménétrier (Météo-France, France)

Abstract

A brief overview of the work that is being carried out at Meteo-France in data assimilation will be presented. Short term developments include a better resolution for the ensemble of global 4DVars, whose size might double. Significant steps are also made towards the operational implementation of an ensemble of 3DVars for the regional model. Long-term plans for both global and regional models are based on a transition from 3D/4DVar to 3D/4DEnVar algorithms. After 3 years of development within the OOPS framework, numerous improvements for the EnVar methods are now available: enhanced localisation, faster distribution of members, hybrid background error covariance matrix, block-Krylov methods, etc. The implementation of all observation operators in the OOPS framework has been recently completed, enabling deeper investigations about the EnVar behaviour in an operational-like setup.

A crucial aspect of ensemble methods, and especially of EnVar algorithms, is the need for an efficient and well-tuned localisation. Affordable methods are now available to diagnose localisation functions objectively, using the ensemble only. A detailed presentation of both mathematical background and practical implementation of these methods will be given, showing consistent results for several atmospheric and oceanic models. Extensions of the theory towards hybrid covariance matrices and 4D localisation have been developed recently. All these diagnostics are publicly available in an open-source, easily operable code that works for any kind of model grid.

 

5 May
at 10:30

Room: LT

Improved Climate Forecasting Service of Australian Bureau of Meteorology

Speaker:  William Wang (Bureau of Meteorology, Australia)

Abstract

 

Australia Bureau of Meteorology has started seasonal climate outlook service since 1989 based purely on statistical methods using tropical SST conditions as predictors. In May 2013 the Bureau of Meteorology Climate Information Services has started issuing climate outlooks based on the Predictive Climate Ocean Atmosphere Model for Australia (POAMA), a dynamical climate model developed by the Bureau of Meteorology and CSIRO Marine and Atmospheric research division. Since 2016, we have been developing our next generation of climate forecasting system and products based on UKMO Glosea5 or ACCESS-S. This talk is to give an overall picture of the climate prediction services in Australia through the following aspects:

  1. A very brief introduction of our Bureau’s climate forecast service history; why we did what we did, experiences and lessons we obtained from the past;
  2. The current dynamic climate forecasting system
    1. A very brief introduction of (POAMA)
    2. The revolutionary transition from statistic to dynamic and how did we make such a CHANGE;
    3. What we investigate when we develop a new climate forecasting system and how, including verification metrics, such as percent consistence, LEPS, ROC skill, Brier skill score etc. and some major results as the benchmarks of a system;
    4. The current services and the online products and relevant issues.
  3. The development of the next generation of Bureau’s climate forecasting system
  4. The new ACCESS-S/UK Met Office Glosea5 model and why it was chosen;
    1. Development of new forecasting system and products– the concept of seamless forecasting from weather to annual climate prediction.
    2. Primary results of this development
    3. A brief introduction of a new verification metric, the so called weighted percent consistence

 

25 April
at 14:00

Room: LT

Non-oscillatory Forward-in-Time Unstructured-Mesh Models for Fluid Flows

Speaker: Joanna Szmelter (Loughborough Univ., UK)

Abstract

The presentation will summarize the development of a fully unstructured (and hybrid) mesh class of models for multi-physics applications with emphasis on simulating inertia gravity waves. Global and limited area atmospheric models will be discussed. The methodology employs an edge-based, finite volume discretisation within the non-oscillatory forward-in-time (NFT) framework. The edge-based data structure allows integration of the generic physical form of the governing PDE over arbitrarily-shaped cells. Aspects of unstructured meshes flexibility, such as optimal point distribution, adaptivity and multigrid will be discussed together with different options of applying the general NFT framework based on the unstructured mesh Multidimensional Positive Definite Advection Transport Algorithm (MPDATA) and elliptic (Krylov) solvers. This approach will be evaluated for a range of models from soundproof and compressible nonhydrostatic to engineering flow solvers. Simulations of stratified orographic flows and the associated gravity-wave phenomena in media with uniform and variable dispersive properties will be presented. They verify the developments and demonstrate the efficacy of the implicit large eddy simulation operating on unstructured meshes for study of stratified turbulent flows.  Numerical examples for engineering problems will include coastal flows, gas dynamics at Mach numbers from zero to supersonic, and solutions from Arbitrary Lagrangian Eulerian (ALE) codes using conservative MPDATA based remapping techniques.

 

21 April
at 10:30

Room: LT

SODA3 (Simple Ocean Data Assimilation ocean/sea ice reanalysis) and a step toward a coupled reanalysis?

Speaker: James Carton (Univ. Maryland, USA)

Abstract

Atmospheric reanalyses produce surface fluxes as a residual of their update cycle. These fluxes should be consistent with estimates of ocean heat and freshwater storage and divergence of transports.  Here we compare the ERA-Int, MERRA2, and JRA-55 fluxes with the imbalances apparent in the increments produced by the SODA3 ocean reanalysis system during the data-rich eight year period 2007-2014.   The heat flux comparison reveals that the regional imbalance falls in the range of 10-30 W/m2 in time mean with even larger imbalances on seasonal time scales.  In the vertical the corresponding temperature imbalances are concentrated in the mixed layer.  We argue that in the interior gyres these imbalances are the result of seasonal errors in the atmospheric reanalysis representation of surface heat and freshwater fluxes (the problem is the atmosphere).  In other regions such as the Gulf Stream we show evidence of substantial ocean model error. Elsewhere errors in momentum fluxes appear to dominate the temperature and salinity increments.  We also examine the impact on fluxes of the choice of bulk parameterization used to calculate surface fluxes from atmospheric state variables.

In the second part of the talk we present a strategy for correcting surface fluxes based on the ocean observations and we then discuss the results of experiments testing this strategy.  Examination of the results confirms that in the interior gyres our bias-correction strategy reduces the seasonal error in surface heat flux to less than 5 W/m2.  We conclude with a discussion of the changes that are needed to address biases at high latitude.

11 April
at 14:00

Room:LT

Dataflow for Geocomputing

Speaker: Georgi Gaydadjiev (Maxeler, London, UK)

Abstract

Ever since Von Neuman, predicting the weather has been one of humanities top computing challenges. The challenge can be split into two parts: (1) writing the software to predict the weather and (2) running the software to predict the weather. Running the software includes deciding on discretisation, data sizes, and building custom configurations of computing, memory and storage components. 

A key question arises. Should we build computers that are easy to program or should we build computers that are efficient in running the largest models we can conceive. Of course in the initial decades, software, math and models need to be developed. However in the steady state, we will need to transition to optimising the operational aspects of running complex models. 

Maxeler Multiscale Dataflow Computing addresses the steady-state challenge of optimising operational efficiency in Space, Time and Value (STV). We re-evaluate choices in discretisation of space, time and value, and build optimal computational arithmetic pipelines to compute PDE solutions in minimal time and with minimal cost. 

Maxeler Dataflow computing has been demonstrated in Italy to compute a local weather model 60x faster and in China, to be 14x faster than a Tianhe 1a (dual GPU node) on a node-2-node basis. The UK government purchased a significant Maxeler machine for Daresbury labs. Still programming challenges remain and we are looking forward to continuing the dialogue with the geoscientists on how this new computational paradigm can be deployed with minimal impact on programming and code maintenance.

23 March
at 10:30

Room: MR1

Uncertainties in simulated evapotranspiration from land surface models over a 15-year Mediterranean crop succession

Speaker: Sebastien Garrigues (CEH/UoR/INRA)

Abstract

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6 March
at 14:00

Room: LT

Water Information in Australia - The Post Millennium Drought Experience

Speaker: Dr Dasarath Jayasuriya (BoM, Australia)

Abstract

Water data and information are needed for planning, managing and meeting the sustainable development goals related to water resources taking into account climate changes, population growth and other drivers impacting supply security. The Australian National Plan for Water Security (2007) postulated that better water information was essential for providing water security during Australia's periodic droughts. After the Millennium Drought which lasted from 1996 to 2007, the Government and the policy bureaucracy understood that they were facing a water crisis, but had no nationally consistent and accessible data to make informed decisions. Water data were held by approximately 200 organisations across state and local governments with no standardisation, transparency, and accessibility. Parochial interests often led to ‘gaming’.

The presentation lays out the Australian experience and its response to the water data and information challenge and shares the Government’s Water Information Program initiative over the last 10 years. Highlights relate to socialising the universal availability of water data, water information products and water forecasting services. Collectively they provide water intelligence to Bureau’s stakeholders including Government, industry and community.

Dr Dasarath Jayasuriya

23 February
at 10:30

Room: LT

Subseasonal forecasting – a battle between damped persistence and tropical forcing?

Speaker: Warwick Norton (CUMULUS, UK)

Abstract

Cumulus
 
We review some of the forecast performance across the 2016/17 winter where the seasonal forecasts expected a negative NAO state yet this not really played out. Rather there has been significant forecast volatility, with no forecast skill past week 2 for Europe (or in forecasting the NAO). In the southern hemisphere Australia has experienced an extremely hot summer which was also poorly forecast in the subseasonal range. We discuss sources of forecast error particularly associated with underestimating maritime continent convection but also other factors that may have led to poor forecast skill this year such as lack of MJO activity. 
 
We examine what could be predicted with perfect knowledge of the tropics from relaxation experiments. We compare this year to other recent years where skill in predicting the NAO has been higher. Results based on Rossby wave source analysis suggest that tropical teleconnections are too weak in the ECMWF model - this can lead to periods of under confidence in forecasting predictable extratropical signals. We conjecture that current subseasonal models contain too much damped persistence of the initial conditions and not enough forcing from the tropics.

15 February
at 10:30

Room: MR1

Flood forecast sensitivity to temperature using ECMWF ensembles for 145 catchments in Norway

Speaker: Trine Jahr Hegdahl (NVE, Norway)

Abstract

The Norwegian flood forecasting service is based on a flood-forecasting model run on 145 basins. The basins are located all across Norway and differ in both size and hydrological regime. Current flood forecasting system is based on deterministic meteorological forecasts, and uses an auto-regressive procedure to achieve probabilistic forecasts. An alternative approach is to use meteorological and hydrological ensemble forecasts to quantify the uncertainty in forecasted streamflow. The aim of our study is to establish and assess the performance of both meteorological and hydrological ensembles for 145 catchments in Norway, which differ in size, elevation and hydrological regime. We identify regional differences and improvements in performance for preprocessed meteorological forecasts. A separate study further investigates the sensitivity to forecasted temperature for specific snowmelt induced floods. In Norway, snowmelt and combined rain and snowmelt floods are frequent. Hence, temperature is important for correct calculations of snowmelt. Temperature and precipitation ensembles are derived from ECMWF covering a period of nearly three years (01.03.2013 to 31.12.2015). To improve the spread and reduce bias we used standard methods provided by the Norwegian Meteorological Institute. Precipitation is corrected applying a zero-adjusted gamma distribution method (correcting the spread), and temperature is bias corrected using a quantile-quantile mapping (using Hirlam (RCM) 5 km temperature grid as a reference). Observed temperature and precipitation data are station data for all of Norway, interpolated to a 1×1 km2 grid (SeNorge.no). Streamflow observations are available from the NVE database. The hydrological model is the flood-forecasting operational HBV model, run with daily catchment average values. The results show that the methods applied to meteorological ensemble data reduce the cold bias present in the ECMWF temperature ensembles. Catchments on the western coast, having a lower initial performance, show the highest improvement by the temperature corrections, whereas some inland catchments in southeastern Norway show reduced performance. Ensemble spread for precipitation improves, but is not recognized in the discharge performance measures. Both precipitation and temperature show an east-west divide in performance. Corrected temperature ensemble lead to improved performance in discharge for some western catchments. Overall, the regional analyzes including all data, show that catchments have different sensitivity to temperature correction and will benefit from regional or catchment specific bias correction. Spring flood events, in catchments located west and southeast, showed different discharge response to temperature correction (more than 2°C). For the western catchment the increased temperature, led to higher discharge, whereas there were minor change for the southeastern catchment.

 

12 January
at 14:00

Room: LT

The global ICON Ensemble at DWD

Speakers: Michael Denhard and Cristina Primo (DWD, Germany)

Abstract

Since October 2015 DWD runs an experimental ICON ensemble suite with 40 members and approx. 40km horizontal resolution on the global scale up to +168h lead time twice a day (00/12UTC). The global grid contains a 20km two-way nested area over Europe. The ensemble is initialized by analyses from our ensemble data assimilation system (ICON EDA) which is a combination of a Local Ensemble Transform Kalman Filter (LETKF) with a hybrid ensemble/3D-Var variational system for the high-resolution deterministic model. At the time there is no stochastic physics implemented and the error growth properties of the ensemble are determined by the diverse co-variance inflation techniques in the LETKF such as multiplicative inflation factors, relaxation to the prior and stochastic SST perturbations.  Moreover, the static NMC Background error co-variances are added to the flow dependent ensemble co-variances to rescale the innovations. In the first part we show verification results for the ICON-EPS forecasts in comparison to the ECMWF-EPS and analyze the spread skill relation for both ensembles. The second part introduces techniques for predicting the error growth properties along trajectories in the state space of a model. We use the "Broyden family" methods to iterate a Broyden matrix in state space of the Lorenz63 and 95 models. During iteration the Broyden matrix gains information on the error growth properties of the dynamical system. We discuss, if the information in the Broyden matrices along a trajectory can be used as an approximation of the singular vector approach.

11 January
at 10:30

Room: LT

How good (or bad) is the circulation of the stratosphere and mesosphere in the IFS?

Speaker: Inna Polichtchouk (University of Reading, UK)

Abstract

Accurate representation of the stratospheric circulation is important for tropospheric predictability on intraseasonal timescales, because of the downward influence of the stratosphere on the troposphere.  The “downward control” principle states that the stratospheric Brewer Dobson circulation (BDC) is primarily driven by the wave breaking/saturation aloft. Thus, the stratospheric circulation in turn depends on the representation of the mesospheric momentum budget. This talk reviews the state of the middle atmosphere in the IFS, with a focus on the BDC and the semi-annual oscillation. I will compare the middle-atmosphere circulation to reference datasets and assess the impact of 1) the parametrized non-orographic gravity wave drag; 2) treatment of the sponge layer; 3) the cubic octahedral discretization; and, 4) stochastic physics.

LT = Lecture Theatre, LCR = Large Committee Room, MZR = Mezzanine Committee Room,
CC = Council Chamber