Observational needs for seasonal to decadal forecasts

Roger Saunders Met Office

Acknowledgements to Adam Scaife and Doug Smith

Seasonal Predictions

ENSO forecasting

2015/16

Nino 3.4

Ensemble prediction systems using a coupled ocean-atmosphere model generate probabilistic forecasts up to six months ahead.

ORCA ¼° ORCA 1°

Higher ocean resolution is important

2 years of monthly mean temperature

at 370m depth

North Atlantic Oscillation The North Atlantic Oscillation (NAO) is a climatic phenomenon in the North Atlantic Ocean of fluctuations in the difference of atmospheric pressure at sea level between the Icelandic low and the Azores high. Many things trigger the NAO.

NAO in Winter now predictable

Sudden stratospheric warming (SSW) and strong polar vortex (SPV) events

SPV

SSW

Observations Ensemble mean

DJF hindcasts started from 1 Nov

Seasonal winter forecasts and the stratosphere

Atmospheric Science Letters 25 OCT 2015 DOI: 10.1002/asl.598

http://onlinelibrary.wiley.com/doi/10.1002/asl.598/full#asl2598-fig-0004

The stratospheric state, which is initialised using satellite data, is crucial to the predictability of the NAO

Atmospheric initial conditions and the predictability of the Arctic Oscillation AO

Stockdale et al 2015

Geophysical Research Letters Volume 42, Issue 4, pages 1173-1179, 26 FEB 2015 DOI: 10.1002/2014GL062681

http://onlinelibrary.wiley.com/doi/10.1002/2014GL062681/full#grl52611-fig-0002

Control uses the correct initial conditions. SHIFT uses only atmosphere initial conditions from the correct date; ocean, sea ice, and land surface are taken from the preceding year. The error bars show the 1 standard deviation uncertainty of the ensemble mean.

Forecasts of the AO from differing initial conditions

Atmospheric initial conditions dominate predictability not the surface

Solar influences on weather

Acknowledgement: Sarah Ineson

Trends in solar spectral irradiance variability in the visible and near infrared

Geophysical Research Letters Volume 36, Issue 7, L07801, 1 APR 2009 DOI: 10.1029/2008GL036797

http://onlinelibrary.wiley.com/doi/10.1029/2008GL036797/full#grl25584-fig-0001

The SIM spectral irradiance data integrated into discrete bands.

Spectral irradiance changes with decreasing solar activity

UV IR

Solar Models not in agreement over solar irradiance distribution

Observations

We need better space based estimates of incoming solar SPECTRAL irradiance to pin down the UV component (200-300nm) of solar variability

Last Winter 2014/15

© Crown copyright Met Office

From October From November Observations

Very clear signals for a westerly winter from October Good agreement with subsequent observations Rossby wave emanating from the tropical Atlantic

Initialisation for seasonal forecasts • Ocean and atmosphere analyses are

currently the main source of initialisation • SST from assimilation in ocean model • Hence satellite data are only indirectly used • Moving to coupled DA and models • The key variables for seasonal forecasts

are: • Sub-surface ocean temperatures • SST, Salinity, Sea-Ice (cover & thickness) • Stratospheric state • Solar spectral irradiance, Soil moisture, Snow cover

Decadal Predictions

© Crown copyright Met Office (Smith et al. 2010)

Impact of initialization on 5 year mean temperature skill

Initialised - Uninitialised Skill of initialised predictions

• Skilful almost everywhere (positive correlations)

• Mostly due to external forcing

• Initialisation gives improved skill mainly in North Atlantic and tropical Pacific

Correlations

Physical basis for improved skill

Robson et al 2012, Yeager et al 2012; also Robson et al 2014, Müller et al 2014 for 1960s cooling

Atlantic sub-polar gyre 500m temp

• Rapid warming of Atlantic sub-polar gyre in mid 1990s • Initialization improves predictions • Increased northward heat transport • Due to ocean dynamics (increased Atlantic overturning circulation)

Observations Initialised (DePreSys) Uninitialised (NoAssim)

Hea

t Con

tent

© Crown copyright Met Office

Predicted cooling of North Atlantic

(Hermanson et al, 2014)

• Atlantic predicted to cool in response to weakening of ocean overturning • Likely to cause climate impacts around the Atlantic basin • Not a reversal, but impacts associated with warm Atlantic less likely: cold winters and wet summers in Europe less likely fewer hurricanes than recent peaks reduced Sahel rainfall reduced risk of drought in SW USA

Temperature Ocean circulation

Atlantic tropical storms

Current decadal forecast

Initialisation for decadal forecasts • Ocean and Atmosphere Reanalyses are

the main source of initialisation and validation of hindcasts

• Upper ocean and SST (HadISST) used • The key variables for decadal forecasts

are: • Upper ocean temperatures and salinity (~500m) • Ocean currents (e.g. RAPID array) • Stratospheric state QBO • Sea-ice thickness • Solar spectral irradiance • Soil moisture? Snow Cover?

Implications for Observing System 1. Note satellite data assimilation for coupled global ocean

and atmosphere models underpins seasonal and decadal prediction

2. SST and deeper layer ocean temperatures and salinity essential

3. Ocean basin circulation important currents

4. Sea-ice thickness and snow observations should be continued and improved relative to the current operational satellites (e.g. treatment of melt ponds)

5. Continue and enhance? observations of stratospheric state limb view measurements?

6. Initiate long term measurements of spectral solar irradiance

7. Maintain and improve soil moisture measurements

Data Provision 1. Observations and analyses required < few days delay

of real time for seasonal forecasts

2. Observations and analyses required < 1 month of real time for decadal forecasts

3. Global coverage of observations at <1 deg resolution for ocean for large scale anomalies but model needs to be at 0.25 deg for ocean circulation.

4. Daily sampling

5. The solar irradiance is not required close to real time as we just need the amplitude of the 11year solar cycle

6. “Observations” • ARGO, RAPID • HadISST • ERA (Ocean/Atmosphere) • GLOSEA

Satellite Observational capabilities GCOS ECV 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 Sensors

Atmospheric Surface precip SSMIS, AMSR, MWRI, TRMM, GPM, ATMS, GEO Vis/IR Surface wind ASCAT, OSCAT, HY-2, RapidScat, WindRAD TOA radn budget CERES, EarthCARE, SCARAB, RBI Solar irradiance TSIS, ACRIM, SORCE, Picard Temp profile Sounder radiances, GPS-RO Water vapour profile Sounder radiances, GPS-ZTD, [Column SSMIS, OLCI] Wind profile AMVs, ADM

Cloud properties Cloudsat, EarthCare, VIS/IR imagers (GEO/LEO) Carbon dioxide AIRS, IASI,OCO-2/3,CRIS, GOSAT, GAS Methane AIRS, IASI, GOSAT, CrIS, MTG-IRS, Schiamachy, MOPPIT Ozone GOME-2,IASI,AIRS,CRIS, IR, UV limb, OMPS, OMI Other GHG IASI, GOME-2, UV/IR limb, GOSAT, Sentinel-5 Aerosols AVHRR, VIIRS, GOME-2, MERIS, MODIS, Sent-4/5, MTG

Oceanic SST AATSR, SLSTR, AVHRR, AMSR-2, MODIS, VIIRS, GeoIR Surface salinity SMOS, Aquarius, SMAP Sea level TOPEX,Jason-1,2,3, Sentinel-3 ALT, Sentinel-6 Sea state Jason-1,2 Sentinel 3 ALT

Sea-ice SSM/I, AMSR, SSMI(S) [Thickness Cryosat-2, ICESAT-2, SMOS] Currents Jason-1,2,3?, Sentinel-3 ALT Ocean colour MERIS, MODIS, VIIRS, OLCI

Terrestrial LST AATSR, SLSTR, AVHRR, AMSR, MODIS, VIIRS, CrIS, IASI Lake levels Jason-1,2,3, Sentinel 3 ALT Snow cover and SWE SSMIS, AMSR, AVHRR, MODIS, Geo Imagers Glaciers and ice caps GRACE, Cryosat-2, ICESat, ASTER, Landsat Permafrost MODIS, VIRSS,SAR Albedo AVHRR, MODIS, VIRSS Land cover (inc veg) Sentinel-2, MODIS, VIRSS, Landsat, TerraSAR fAPAR MODIS, VIRSS, MERIS, Sentinel-2 LAI MODIS, VIRSS, MERIS, Sentinel-2 Biomass Sentinel-1 SAR, BIOMASS Fire Geo imagers, ATSR, AVHRR, VIIRS, Sentinel-3 Soil moisture ASCAT, SMOS, SMAP Ground water GRACE, GRACE-2

Key Good capability Some capability but needs improvement Poor capability Capability lost No capability

Loss of limb view stratospheric measurements

Recommendations

1. Ensure continuity and improvement of following satellite measurements:

– Ocean salinity and temperatures

– Sea-Ice thickness

– Stratospheric temperature and winds

– Solar spectral irradiance

– Soil moisture? Snow?

2. Develop capability to measure ocean currents

Any questions? Latest Met Office seasonal forecast