1. 2nd Snow Watch meeting
Ohio State University, Columbus, 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

2. 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

3. 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:

4. 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

5. 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

6. 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
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

7. 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.

8. 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
Most commonly measured electromagnetic parameter is broadband albedo

9. Questionnaire on observations/instrumentation (WG1/2): 92 responses
Other
Other
Other
Other

10. 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?

11. Questionnaires snow data assimilation (WG3) – 26 responses

12. 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):
Welcome input from the international community!
Deadline 23 September 2016

13. Workshop on in-situ snow albedo measurements: toward a snow albedo intercomparison experiment, FMI, August , 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?
Deadline to register: 31 July

14. HarmoSnow COST 29 participating countries:
COST also welcomes:
Near-neighbour countries
International partners

15. 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).

16. 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