2nd Snow Watch meeting Ohio State University, Columbus, 13-14 June 2016 HarmoSnow COST action Ali Nadir Arlsan (FMI), Patricia de Rosnay (ECMWF), Sam Pullen (UKMO), Juergen Helmert (DWD), Roberta Pirazzini (FMI) and the HarmoSnow COST action Team

HarmoSnow COST Action COST is an intergovernmental framework for European Cooperation. It supports networking activities within the COST action. COST Action on Snow (ES1404): “A European network for a harmonised monitoring of snow for the benefit of climate change scenarios, hydrology and numerical weather prediction”. HarmoSnow 2015-2018

HarmoSnow COST Action This COST Action on SNOW aims at building a better connection between: snow measurements and models, snow observers, researchers and forecasters for the benefit of various stakeholders and the entire society Web Pages: http://www.cost.eu/COST_Actions/essem/Actions/ES1404 http://costsnow.fmi.fi/

HarmoSnow Objectives Establish a European-wide science network on snow measurements for their optimum use and applications benefitting on interactions across disciplines and expertise. Assess and harmonise practices, standards and retrieval algorithms applied to ground, air- and space-borne snow measurements. Develop a rationale and long term strategy for snow measurements, dissemination and archiving. Advance snow data assimilation in European NWP and hydrological models and show its benefit for relevant applications. Establish a validation strategy for climate, NWP and hydrological models against snow observations and foster its implementation within the European modelling communities. Training of a new generation of scientists on snow science and measuring techniques with a holistic perspective linked with the various applications. I tried to edit into simpler sentences

HarmoSnow activities Web data portal of snow observations and links to existing NRT snow databases Synthesis and strategic recommendations report Catalogue of snow measurement instrumentation and best practices Review and practical guide on snow measurements for users needs Review on snow data assimilation in European NWP and hydrological models Multi-disciplinary articles in scientific journals Three Working Groups: WG1: Physical characterization of snow properties WG2: Instrument and method evaluation WG3: Snow data assimilation and validation methods for NWP and hydrological models

NRT data on the GTS: Ongoing action with Bulgaria Outcome of the COST action to improve snow depth data exchange Action from ECMWF and NIMH following November 2015 meeting Tested in the ECMWF data Assimilation (1 month test in oper config) Suitable for operational use Recommendation to NIMH to make the data available on the GTS de Rosnay et al., ECMWF Res Memo RD16-178, June 2016 Operational ECMWF Test ECMWF 0.05 0.2 0.5 19 January 2016 Snow depth in m 39 more stations provided by NIMH, in the dedicated BUFR (more red obs values) Lack of observations in Bulgaria

COST ES1404 WG1-WG2 Questionnaire Questionnaires Questionnaire on observations/instrumentation (WG1/2) - What are the snow parameter-instrument pairs used in the measurements? - What is the landscape of the measurements, the applied measurement protocols, and the purpose/s of the measurements? COST ES1404 WG1-WG2 Questionnaire Description of measured snow parameter - Description of snow instrument The purpose of the questionnaire is to make a survey on the measured snow parameters and applied instrumentation/techniques. The questionnaire only addresses general information, and should be filled just once for ALL measured parameters. For each parameter, the applied instrument should be selected among the available choices or specified with text in the free space.

Questionnaire on observations/instrumentation (WG1/2): 92 responses Most commonly measured macrophysical parameters are: snow presence, snow depth, SWE, and snow density Most commonly measured microphysical parameters are: grain size and grain shape https://docs.google.com/forms/d/12tmJ0mep9t7-pMsDhjlOgZKhzJJkqN8b6MdNP53dAJo/viewanalytics Most commonly measured electromagnetic parameter is broadband albedo

Questionnaire on observations/instrumentation (WG1/2): 92 responses Other Other https://docs.google.com/forms/d/12tmJ0mep9t7-pMsDhjlOgZKhzJJkqN8b6MdNP53dAJo/viewanalytics Other Other

Questionnaires Questionnaire on snow data assimilation (WG3) - How many and which kind of snow observations are assimilated in numerical weather prediction and hydrological models? - What are the data assimilation methods used in meteorology and hydrology for snow observations?

Questionnaires snow data assimilation (WG3) – 26 responses

Synergies between SnowWatch and COST action: Status and improvement of NRT snow depth on the GTS Reporting practices harmonization (e.g. zero snow depth) Relevance of the Questionnaires on observations/instrumentation (WG1/2) and snow data assimilation (WG3): http://costsnow.fmi.fi/index.php?page=Questionnaires Welcome input from the international community! Deadline 23 September 2016

Workshop on in-situ snow albedo measurements: toward a snow albedo intercomparison experiment, FMI, August 24 - 25, 2016 Organisers: R. Pirazzini (FMI), G. Picard (LGGE) et al. What is the accuracy that spectral and broadband albedo measurements can achieve? What is, presently, the standard calibration and characterization of the instruments? Which calibration and characterization of the instruments would be required in order to allow a meaningful comparison of the measurements obtained with different instruments, and under different environmental conditions? http://costsnow.fmi.fi/index.php?page=24%20-%2025.08.2016,%20Helsinki Deadline to register: 31 July

HarmoSnow COST 29 participating countries: COST also welcomes: Near-neighbour countries International partners http://www.cost.eu/participate

Snow Data Assimilation WG3  snow data assimilation and validation methods for NWP and hydrological models - An overview assessment for understanding the future perspectives of how the various snow observations are used in NWP, hydrology and climate studies. - Development of methods to update non-observed forecasted physical snow properties (such as snow temperature, wetness, density profiles, and mechanical properties) based on the observed ones (such as snow depth and extent). - Advance in the assimilation of new and developing satellite observations of different snow properties and combination with in-situ snow measurements. - Finding ways towards more extended usage of conventional snow observations in NWP, hydrological and climate models, including observations from high-resolution national networks. - Reaching better knowledge on model and observational errors relevant for data assimilation (links with WG1 and WG2).

Snow Data Assimilation WG3  snow data assimilation and validation methods for NWP and hydrological models Models WG3 Snow schemes NWP Hydrology Climate Observations Assimilation Conventional Remote Sensing WG1 WG2 High-res networks