WWRP Implementation Plan Reporting

Transcription

1 WWRP Implementation Plan Reporting This report will form the basis of the WWRP report to the upcoming session of the WMO Commission for Atmospheric Sciences. As you respond to this request please think in terms of the activities of your working group, project or expert team being included in a presentation summarising all WWRP activities. Which highlights of your activities would you want to see in such a summary presentation? What would demonstrate the value of your activities to the member states? Where do you see the key future activities? We will be asking for a more detailed report by mid September as input to the SSC meeting. Please send you report to Paolo Ruti (pruti@wmo.int) and Sarah Jones (sarah.jones@dwd.de) by 21 July. Note that we have reserved the week of July 24 to work on the documents for the CAS session so we really need your input by then. High Impact Weather and its socio economic effects in the context of global change. Dust storms represents high impact weather for numerous countries in the vicinity of dust sources, affecting a wide range of socio economic aspects and activities (i.e., aviation, energy, health). Dust modeling is a key tool for predicting the process in a seamless manner from very short term (day or shorter) to medium and climate scale. With respect to climate, desert dust afects Earth s global energy balance through direct interactions with radiation, and through indirect interactions with clouds and ecosystems. How has your WG or Project contributed to addressing this Societal Challenge since the last CAS session in 2013? (Please provide highlights and challenges) The spatial resolution of the dust models has followed a similar evolution as that of the numerical weather prediction (NWP) models. The development of nonhydrostatic models, with the transport equation of mineral dust added as on line component, allows substantial improving of the horizontal resolution from several tens of km to less than 10 km. The current challenge consists of improving the representation of the model dynamics and the physical processes of dust emission and deposition, necessary to run the models at finer resolutions, and allowing to properly simulate local scale phenomena such as haboobs, density currents, cloud resolving thermodynamics and squall lines. In May 2013, in view of the demand of many national meteorological services and the

2 good results obtained by the SDS WAS, which proves the feasibility and the need to begin developing operational services beyond the scope of R&D, the Sixty fifth Session of the WMO Executive Council (EC 65) designates the consortium formed by the Spanish State Meteorological Agency (AEMET) and the Barcelona Supercomputing Center (BSC) to create in Barcelona the first Regional Specialized Meteorological Center with activity specialization on Atmospheric Sand and Dust Forecast (RSMC ASDF). The Barcelona Dust Forecast Center was created in February 2014 to be this RSMC ASDF. It operationally generates and distributes dust predictions for Northern Africa (north of equator), Middle East and Europe. A second RSMC ASDF has been created in 2017, hosted by the China Meteorological Administration. This second RSMC ASDF generates and distributes dust forecasts for Asia. These activities are successful stories of transferring research to technology. Dust information obtained from current observation and prediction systems is, in most cases, not in a form and content appropriate for the community of potential users. SDS WAS intends to transfer basic dust observation and model parameters into non specialized user oriented products. The recently approved EU COST Action CA16202 (International Network to Encourage the Use of Monitoring and Forecasting Dust Products), promoted from SDS WAS is aimed at establishing a network involving research institutions, service providers and potential end users of information on airborne dust. It will search, in close coordination with SDS WAS, to coordinate and harmonize the process of transferring dust observation and prediction data to users as well as to assist the diverse socio economic sectors affected by the presence of high concentrations of airborne mineral dust. Address limitations The simulation of a haboob dust storm over Phoenix (USA) generated by local dust hot spots and driven by a cold convective storm down burst was not successful predicted before the following modeling components were introduced (Vukovic et al, 2014): dust model downscaled to 4 km, non hydrostatic solver, explicit cloud resolution and definition of the dust source mask based on combined use of the most recent satellite data on land cover and normalized difference vegetation index data. This study provides guidance to possible developments of a new generation of high resolution dust models. An in depth case study of the small scale extreme dust storm occurred in Tehran on 2nd June 2014 is currently being conducted. This study is a response to the fact that eight dust models, routinely operated within the SDS WAS Northern Africa, Middle East and Europe NAMEE Regional Node, predicted increase of dust concentration in a wider area of northern Iran, but none of them were able to predict the dust storm over Tehran due to the fact that their coarse resolution could not resolve the small

3 scales of the storm. Ensemble prediction is another approach to improve the forecast of high impact dust events. Multi model forecasting intends to alleviate the shortcomings of individual models while offering an insight on the uncertainties associated with a single model forecast. Moreover, an exhaustive comparison of different models with each other and against multi model products as well as observations can reveal weaknesses of individual models and provide an assessment of model uncertainties in simulating the dust cycle. The SDS WAS Regional Centre for NAMEE coordinates the exchange of forecast products generated by twelve dust models and conducts a model intercomparison and evaluation within its geographic scope. Ensemble products describing centrality and spread are calculated and are daily available at products/dust forecasts/ensemble forecast Verification The first problem for the evaluation/verification of dust models is the scarcity of routine dust observations. As far as now, sun photometric measurements and satellite retrievals are used for the routine forecast verification in the framework of SDS WAS. However, these measurements allow verification of total column products, whereas dust surface concentration (DSC), which is a relevant parameter for many application fields, cannot be evaluated. As a pilot study (Garcia Castrillo and Terradellas, 2017), forecasts of DSC released by seven models are compared with PM10 observations recorded by the Air Quality Control and Monitoring Network of the Canary Islands (Spain). Since PM10 measurements integrate particles of different origin, including anthropogenic and natural aerosols, the contribution of mineral dust to the total PM10 is estimated using different methods. Finally, the verification of vertical profiles is addressed in Binietoglou et al (2015), where dust concentration forecast by different numerical models is compared with retrievals from lidar profilers co located with sun photometers using the Lidar/Radiometer Inversion code (LIRIC) algorithm. LIRIC permits retrieval of the volume concentration profiles of various atmospheric aerosol components, based on the synergy of a multi wavelength lidar and an AERONET sun photometer. The limitation of this verification approach is the fact that in most cases lidar sites do not function operationally. How do you see your WG or Project contributing to the Action Areas in the next 2 years?

4 Water: modelling and predicting the water cycle for improved disaster risk reduction and resource management. Not applicable to SDS WAS How has your WG or Project developed this Societal Challenge since the last CAS session in 2013? (Please provide highlights and challenges) How do you see your WG or Project advancing in the next 2 years? (Please provide with detailed based on Action Areas) Urbanization: research and services for megacities and large urban complexes. How has your WG or Project developed this Societal Challenge since the last CAS session in 2013? (Please provide highlights and challenges) No action for the moment No action for the moment No action for the moment How do you see your WG or Project advancing in the next 2 years? (Please provide with detailed based on Action Areas) Given that dust storms have a very negative impact on air quality in heavily populated urban areas, including some megacities, particularly in North Africa, the Middle East and East Asia, SDS WAS plans to create synergies with the expertise of the Global Atmosphere Watch (GAW) Urban Research Meteorology and Environment

5 (GURME) project. This collaboration will improve the connection between research and operations, prompting the implementation of services and products that can be used by citizens living in these urban areas. Evolving Technologies: their impact on science and their use. How has your WG or Project developed this Societal Challenge since the last CAS session in 2013? (Please provide highlights and challenges) Advanced methods Nowadays, one of the most active fields in dust research is data assimilation. While the general assimilation tools can be ported in a straightforward manner to any variable, there are some specific challenges in dust assimilation, which are mainly related to the paucity of suitable dust observations available for assimilation and the complexity of extracting specific dust signals from satellite radiances. In particular, in the SDS WAS Regional Center for NAMEE, a local ensemble transform Kalman filter has been used to optimally combine model background and satellite retrievals and to build the future operational data assimilation scheme of the Barcelona Dust Forecast Center (Di Tomaso et al., 2017). The implementation is based on known uncertainties in the physical parameterizations of the dust emission scheme. Another cross sutting SDS WAS activity is research addressed at predicting the impact of dust to cold cloud formation (Nickovic et al, 2016) as a promising approach to improve performance of NWP models. How do you see your WG or Project advancing in the next 2 years? (Please provide with detailed based on Action Areas) Cross cutting activities What are the key achievements in your WG or Project since the last CAS session in 2013 that cut across two or more societal challenges? SDS WAS maintains close cooperation with the GAW programme, specifically

6 participating in the Scientific Advisory Group (SAG) for Aerosols. In this close relationship with GAW, the importance of incorporating new observations that account for the mineral dust, and which are not contemplated in the current GAW aerosol monitoring programme, has become evident. In addition, after transition from R&D to operations, SDS WAS has put on the table its urgent need for near realtime atmospheric aerosol data that can be used for data assimilation and validation of dust models. How have you linked to other WGs, Projects and International initiatives for crosscutting activities? SDS WAS has established extensive collaboration with a number of international organizations, such as WHO, UNEP, UNFCC, UNCCD, and GEO. These international organizations, external to WMO, have dust storms as a key issue in their programs. In addition, some of them have complementary information and observation networks (I. e. air quality monitoring stations) to those under the umbrella of WMO. The access to the information provided by these networks and, in some cases, the redefinition of some of their characteristics, might facilitate the development of dust products adapted to the particular needs of different socio economic stakeholders. What will be the key cross cutting activities in the next 2 years? Defining and implementing, in some cases, new initiatives, and reinforcing and consolidating existing cooperation, by systematizing the exchange of information in a routine and non exceptional way.