Regional Activities and Perspectives on GCW: Relevant FMI Activities at Northern Finland and Suggestions for GCW Monitoring Site Requirements

Similar documents
Global SWE Mapping by Combining Passive and Active Microwave Data: The GlobSnow Approach and CoReH 2 O

Soil frost from microwave data. Kimmo Rautiainen, Jouni Pulliainen, Juha Lemmetyinen, Jaakko Ikonen, Mika Aurela

ESA GlobSnow - project overview

Remote Sensing of SWE in Canada

FMI Arctic Space Centre. Jyri Heilimo Finnish Meteorological Institute

SIMULATION OF SPACEBORNE MICROWAVE RADIOMETER MEASUREMENTS OF SNOW COVER FROM IN-SITU DATA AND EMISSION MODELS

Assimilation of GlobSnow Data in HIRLAM. Suleiman Mostamandy Kalle Eerola Laura Rontu Katya Kourzeneva

Remote sensing of snow at SYKE Sari Metsämäki

Snow Cover Applications: Major Gaps in Current EO Measurement Capabilities

Examples on Sentinel data applications in Finland, possibilities, plans and how NSDC will be utilized - Snow

The indicator can be used for awareness raising, evaluation of occurred droughts, forecasting future drought risks and management purposes.

Copernicus Global Land Service

Remote sensing with FAAM to evaluate model performance

Helsinki Testbed - a contribution to NASA's Global Precipitation Measurement (GPM) mission

Validation of satellite derived snow cover data records with surface networks and m ulti-dataset inter-comparisons

Environmental observations over Arctic areas potential for monitoring the spread of infectious diseases

ECMWF. ECMWF Land Surface Analysis: Current status and developments. P. de Rosnay M. Drusch, K. Scipal, D. Vasiljevic G. Balsamo, J.

Prof. Jouni Pulliainen

SEA ICE MICROWAVE EMISSION MODELLING APPLICATIONS

Assimilation of satellite derived soil moisture for weather forecasting

EUMETSAT SAF NETWORK. Lothar Schüller, EUMETSAT SAF Network Manager

REVISION OF THE STATEMENT OF GUIDANCE FOR GLOBAL NUMERICAL WEATHER PREDICTION. (Submitted by Dr. J. Eyre)

Remote Sensing of Snow GEOG 454 / 654

Terrestrial Snow Cover: Properties, Trends, and Feedbacks. Chris Derksen Climate Research Division, ECCC

The Challenge of. Guy Brasseur

CLIMATE CHANGE AND REGIONAL HYDROLOGY ACROSS THE NORTHEAST US: Evidence of Changes, Model Projections, and Remote Sensing Approaches

Snow property extraction based on polarimetry and differential SAR interferometry

Dual-Frequency Ku- Band Radar Mission Concept for Snow Mass

The use of earth observation technology to improve the characterization of ice and snow

LIFE12 ENV/FIN/ st summary report of snow data 30/09/2014

Snow-atmosphere interactions at Dome C, Antarctica

EUMETSAT STATUS AND PLANS

FTS measurements of greenhouse gases over Sodankylä, Finland

Steve Colwell. British Antarctic Survey

Assimilation of ASCAT soil wetness

Lake ice cover and surface water temperature II: Satellite remote sensing

EUMETSAT SAF NETWORK. Lothar Schüller, EUMETSAT SAF Network Manager

C o p e r n i c u s L a n d M o n i t o r i n g S e r v i c e

EUMeTrain Snow Week 2010 Session 3 (MRG069305) (MRG069305)

ECMWF. ECMWF Land Surface modelling and land surface analysis. P. de Rosnay G. Balsamo S. Boussetta, J. Munoz Sabater D.

Interpretation of Polar-orbiting Satellite Observations. Atmospheric Instrumentation

AirCore flights at Sodankylä Rigel Kivi, Pauli Heikkinen, Juha Hatakka, Tuomas Laurila, Leif Backman, Jouni Pulliainen (1), Huilin Chen (2, 3)

Biomes and Biodiversity

ADVANCEMENTS IN SNOW MONITORING

Permafrost: Earth Observation Applications: Introduction

Climate Models and Snow: Projections and Predictions, Decades to Days

Climate Change Service

2015 Fall Conditions Report

Match (one-to-one) the following (1 5) from the list (A E) below.

Evaluation and Assimilation of Remotely- Sensed Lake Surface Temperature in the HIRLAM Weather Forecasting System

Simulations of Lake Processes within a Regional Climate Model

THE EARTH S CLIMATE SYSTEM

Interannual variation of MODIS NDVI in Lake Taihu and its relation to climate in submerged macrophyte region

Observing Snow: Conventional Measurements, Satellite and Airborne Remote Sensing. Chris Derksen Climate Research Division, ECCC

SMAP and SMOS Integrated Soil Moisture Validation. T. J. Jackson USDA ARS

Observed State of the Global Climate

BMKG Research on Air sea interaction modeling for YMC

Remote sensing of sea ice

Course outline, objectives, workload, projects, expectations

Chapter outline. Reference 12/13/2016

The Canadian Land Data Assimilation System (CaLDAS)

Toward improving the representation of the water cycle at High Northern Latitudes

Modelling and Data Assimilation Needs for improving the representation of Cold Processes at ECMWF

Remote Sensing Applications for Land/Atmosphere: Earth Radiation Balance

Snowcover interaction with climate, topography & vegetation in mountain catchments

Canadian Prairie Snow Cover Variability

The Canadian Precipitation Analysis (CaPA) and the Canadian Land Data Assimilation System (CaLDAS)

THE USE OF MERIS SPECTROMETER DATA IN SEASONAL SNOW MAPPING

Development of the Canadian Precipitation Analysis (CaPA) and the Canadian Land Data Assimilation System (CaLDAS)

The Atmosphere and Atmospheric Energy Chapter 3 and 4

Satellite-based Lake Surface Temperature (LST) Homa Kheyrollah Pour Claude Duguay

Studying snow cover in European Russia with the use of remote sensing methods

Assimilation of Globsnow data into HIRLAM. Mostamandy Suleiman Sodankyla August 2011

Climate Modeling Research & Applications in Wales. John Houghton. C 3 W conference, Aberystwyth

Climate and the Atmosphere

Discritnination of a wet snow cover using passive tnicrowa ve satellite data

A R C T E X Results of the Arctic Turbulence Experiments Long-term Monitoring of Heat Fluxes at a high Arctic Permafrost Site in Svalbard

1. The frequency of an electromagnetic wave is proportional to its wavelength. a. directly *b. inversely

Quenching the Valley s thirst: The connection between Sierra Nevada snowpack & regional water supply

The importance of long-term Arctic weather station data for setting the research stage for climate change studies

Instrumentation planned for MetOp-SG

Regional offline land surface simulations over eastern Canada using CLASS. Diana Verseghy Climate Research Division Environment Canada

Recent Data Assimilation Activities at Environment Canada

Central Asia Regional Flash Flood Guidance System 4-6 October Hydrologic Research Center A Nonprofit, Public-Benefit Corporation

GCOM-W1 now on the A-Train

H-SAF Snow products and their use in applications. Matias Takala

USE OF SATELLITE INFORMATION IN THE HUNGARIAN NOWCASTING SYSTEM

Climate Change and Arizona s Rangelands: Management Challenges and Opportunities

OSI SAF Sea Ice products

3. Climate Change. 3.1 Observations 3.2 Theory of Climate Change 3.3 Climate Change Prediction 3.4 The IPCC Process

Land Data Assimilation for operational weather forecasting

ASSESSMENT OF NORTHERN HEMISPHERE SWE DATASETS IN THE ESA SNOWPEX INITIATIVE

CGMS Baseline. Sustained contributions to the Global Observing System. Endorsed by CGMS-46 in Bengaluru, June 2018

Global Climates. Name Date

Improvement of objective analysis of lake surface state in HIRLAM using satellite observations

Status of ESA EO Programmes

Today s Lecture: Land, biosphere, cryosphere (All that stuff we don t have equations for... )

and soils characterizing would be defined.

Climate Roles of Land Surface

Extreme Weather and Climate Change: the big picture Alan K. Betts Atmospheric Research Pittsford, VT NESC, Saratoga, NY

Transcription:

Regional Activities and Perspectives on GCW: Relevant FMI Activities at Northern Finland and Suggestions for GCW Monitoring Site Requirements Jouni Pulliainen 21 November 2011

Suggestions for GCW monitoring sites: Case of sub-arctic and boreal forest zone Supersites with detailed integrated monitoring - Soil-snow-vegetation-atmosphere interaction - CAL-VAL of satellite instruments (including satellite reference systems) - Open data delivery and archiving Regular sites with a relaxed monitoring programme - Monitoring of key variables of the cryospheric processes - Coverage over different snow regimes needed - Open data delivery and archiving

Suggestions for GCW monitoring sites: Coverage over different snow regimes Snow cover class Typical characteristics Indicative range of max. SWE before melt (mm) Tundra A thin, cold and wind blown snow cover; high density 40-280 Taiga Thin/moderate depth cold snow cover with low density, depth hoar typical 80 300 Alpine A deep snow pack with intermediate to cold temperatures, some wind crust and some melt-refreeze effects 200 750 Maritime A warm deep snow cover, melt features very common 250 1700 Ephimeral A thin, very warm snow cover 0 150 Prairie A thin (except in drifts) moderately cold snow cover. Wind effects. 0 180 Mountain (special class) Highly variable snow cover -

Preliminary suggestions for GCW monitoring sites: Supersite requirements (a) Continuous automatic data (distributed observations covering e.g. different ecosystems/soil/land cover types) Soil moisture profiles (distributed) Soil temperature/soil frost profiles (distributed) Snow depth and/or SWE (distributed) Snow temperature profiles (distributed) Automatic synoptic weather station observations (including temperature 2 m, temperature ground, dew point temperature, air pressure, air relative humidity, wind speed, wind direction, precipitation, cloud height, amount of clouds, visibility, snow depth, prevailing weather code) Radiation observations (incoming and reflected) Distrometer observations on precipitation Atmospheric soundings (troposphere and stratosphere) CO2 and/or methane fluxes between the atmosphere and soil-vegetation system (preferably for different ecosystems) Water table depth on wetlands

Preliminary suggestions for GCW monitoring sites: Supersite requirements (b) Regular manual observations SWE and snow depth on snow pits (forest and bog sites) Snowpack layering and snow grain size on snow pits (visible snow grain size observations/photography and/or SSA measurements) Soil frost depth Snow surveys (snow courses with a preferable length of some kilometers) Optionally Specific reference measurements for Earth Observation (EO) instruments (e.g. reference systems of cryosphere monitoring satellite instruments) Aerosol optical depth Energy fluxes (sensible, latent and soil heat), evaporation/transpiration and soil respiration.

Preliminary suggestions for GCW monitoring sites: Regular site requirements Continuous automatic data Soil moisture profiles Soil temperature/soil frost profiles Snow depth and SWE Snow temperature profiles Automatic synoptic weather station observations Radiation observations (incoming and reflected) Regular manual observations SWE and snow depth on snow pits (forest and bog sites) Snowpack layering and snow grain size on snow pits (visible snow grain size observations) Snow surveys (snow courses with a preferable length of some kilometers)

Example of Feasible Regional Monitoring: Case of Northern Finland (Cryospheric) Monitoring Programme A proposed contribution to GCW

Pallas-Sodankylä GAW Station, northern Finland Pallas: tropospheric air chemistry atmosphere/ biosphere interactions (also in Sodankylä) Sodankylä: stratosphere ionosphere column measurements satellite observations (CAL-VAL)

Long term times series from the meteorological observatory First thermo-/barometer based records in 1856 Met station during the 1st IGY 1882/83 Continuous homogenized synoptic weather records from 1908 onwards Upper air soundings from 1949 onwards Solar radiation observations since 1957/58 (1st IPY) Radioactivity monitoring since 1963 Air quality observations since 1970s Ozone and UV-observations 1988 Stratospheric Aerosol/Humitidy mid 1990s Micrometeorological tower 1999 Weather radar at Luosto 2000 Satellite data processing 1998 Satellite data reception 2003

The measurements at Sammaltunturi include reactive gases (ozone, sulphur dioxide and nitrogen oxides) greenhouse gas concentrations (carbon dioxide, methane, nitrous oxide and sulphur hexafluoride) aerosol particle number concentration and size distribution PM 10 particle mass concentration aerosol scattering coefficient black carbon volatile organic compounds (ethane, propane etc.) stable isotopes radon-222 meteorological parameters

Pallas-Sodankylä GAW Station, northern Finland

Relevant Sodankylä-Pallas Activities: Satellite CAL-VAL Sodankylä site: Reference instruments for various EO missions: ELBARA-II of ESA : Reference for SMOS (global soil moisture and ocean salinity) SnowScat of ESA: Reference for the planned CoReH2O SWE mapping SAR mission SodRad: Reference for SSMI/I and AMSR-E Mast-based spectrometer: Reference for MODIS, MERIS etc. ELBARA-II SMOS

SodRad and ESA-Elbara-II: References for space-borne radiometers

Sodankylä-Pallas satellite CAL-VAL-site (Satellite Pixel) Providing in situ data on atmospheric and surface parameters for remote sensing instruments Co-operation e.g. with NASA,ESA and EUMETSAT) Globally unique CAL-VAL site at (northern) boreal forest region 0.08 Measured spectrum from mast 30.6.06 0.07 0.06 0.05 0.04 0.03 Radiance [ W/m^2] Measured reference spectrum Measured forest spectrum Measured open land spectrum 0.02 0.01 Wavelenght 0.00 350 442 534 626 718 810 902 994 1086 1178 1270 1362 1454 1546 1638 1730 1822 1914 2006 2098 2190 2282 2374 2466

ESA CoReH2O preparation work at Sodankylä Cold Regions Hydrology Highresolution Observatory Dual frequency (X / Ku band) SAR for cryospheric mapping ESA Earth Explorer candidate - Phase A (decision for launch early 2012) Large ongoing ESA campaign activities (NOSREX 1,2&3 with participation from Finland, Canada, USA, Switzerland, Austria, France, UK )

ESA NoSREx campaign: Reference instruments for space-borne monitoring of the cryosphere Extensive ESA campaign activities at Sodankylä Reference instrument for the planned CoReH 2 O Earth Explorer - Dual frequency SAR for the global investigation of snow cover (Snow Water Equivalent) for NWP, hydrology and climate modeling - Coordinated activities with Canadian experiments at Churchill (Univ. of Waterloo and Environment Canada) Reference instruments for ESA SMOS and operational microwave radiometers of USA and Japan

Sodankylä Intensive Observation Area (IOA) 67 21.712 N 26 38.270 E Site typical boreal coniferous forest on mineral soil FMI Arctic Research Centre, Sodankylä, Finland Average permanent snow cover: 6th Nov 25 May (1971 2000) Average maximum snow depth: 80 cm Easy access and technical support 1.12.2011 17

IOA instrumentation Elbara-II SodRad radiometer 10, 18, 36, and 90 GHz SodRad2 21 and 150 GHz radiometer installed during coming winter SnowScat 10-18 GHz scatterometer ASD spectrometer 400-2500 nm spectrophotometer Reference measurements soil moisture and temperature snow parameters meteorological parameters CO2 flux etc.

Manual snow measurements Weekly observed parameters Stratigraphy Density profile (snow fork and snow scale) Grain size profile Temperature profile Snow moisture Bulk values for SD, SWE, density Detailed snow measurements (one campaign period each year) Snow depth/swe distribution SSA measurements/ NIR photography High resolution penetromety Instruments in continuous observation mode (diurnal change observation)

Automated measurements snow depth and snow water equivalent (acoustic and gamma ray measurements) soil moisture vertical profile soil temperature profiles and frost depth snow temperature profile weather (AWS) and radiation measurements

Northern Finland test area Northern Finland test area 300x300 km Sodankylä-Pallas CAL/VAL area 150x150 km Other 0.8 % Open ( barren ) 1.2 % Bog 23.3 % Forest 70.9 % Lakes & rivers 3.7 % Sodankylä

New SM / ST vertical profile stations

Sodankylä area in-situ measurements Continuous automatic soil/snow measurements Soil moisture vertical profile + top layer measurements Soil temperature vertical profile + top layer measurements Snow depth and snow water equivalent Snow temperature profiles Manual in-situ measurements Snow pits on three locations Frost tubes on forest, open area and bog

CoReH 2 O MAG, Innsbruck, Austria 1.12.2011 27

Connecting in situ observations and satellite data: Products and observations for GCW

New Sodankylä Processing Facility Data processing Archiving Delivery (already open database operational litdb.fmi.fi)

Finnish Meteorological Institute 1.12.2011 30

EUMETSAT: H-SAF FMI is responsible to the development of real-time snow mapping services for Europe SWE mapping approach is based on the further development of GlobSnow system EC: CryoLand Multinational EC project carrying partially on with GlobSnow efforts Development of operational satellite-based snow & land ice products

EC SnowCarbo estimation of CO2 balance of Northern areas Weather station data: Synoptic weather data Satellite data: Snow Covered Area Snow Depth/Water equivalent REMO JSBACH Model System REMO Regional Climate Model JSBACH Biosphere-Atmosphere Model Product validatio n Validation and error estimation Output: CO2 flux maps with error estimates CO2 consentration maps with error estimates Direct validation: CO2 flux measurements CO2 consentration measurements In direct validation: NDVI time series driven features Spring increase in photosynthesis Vegetation summer maximum Beginning of dormancy Timing of soil freezing Snow melt onset Snow clearance

Daily CO 2 balances at the spruce forest site in 2003 mean PPFD (μmol m -2 s -1 ) Daily CO 2 balance (mgco 2 m -2 d -1 ) 600 400 200 0 10 5 0-5 -10-15 Soil temperature Air temperature PPFD CO 2 balance 25 20 15 10 5 0-5 -10-15 -20-25 -30-35 Temperature (C) -20 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2003

30 year-long Climate Data Record (CDR) on snow conditions of Northern Hemisphere (ESA-GlobSnow) First time reliable daily map information on snow: - Snow Water Equivalent (SWE) - Snow Extent and melt Spaceborne passive microwave radiometer data combined with ground-based synoptic snow observations - Variational data-assimilation Part of Sodankylä Cryospheric Data Archive -system - 30-year-long time-series Continuous real-time hemispehirical processing started on October 2010

Trend in the snow melt date based on GlobSnow 30-year long product (change in days/decade) Satellite retrieval ECHAM5 (Obs. SST) INTAS-SCONE data Melts earlier Melts later Conclusion: Confidence on the climate model s ability to represent Eurasian snow cover with reasonable accuracy

Seasonal behaviour and hemispherical trend of snow mass 1995 Finnish Meteorological Institute 1.12.2011 36

Thank You for Your Attention!