VI Expanding Ocean Frontiers Conference, 5-7 July 2021, Barcelona, Spain.-- 25 page

Cossu, Federico

Exarchou, Eleftheria

Grieco, G.

Gómara, Íñigo

King, Gregory P.

Lin, Wenming

Makarova, Evgeniia

Martín-Rey, Marta

Ortega, Pablo

Polverari, Federica

Portabella, Marcos

Rabaneda, Albert S.

Stoffelen, Ad

Trindade, Ana

English

Grieco, Giuseppe

Digital.CSIC

bec.icm.csic.esThe role of scatterometry in ocean model forcingMarcos Portabella (ICM-CSIC)Ana Trindade (ICM-CSIC & UPC)Giuseppe Grieco (ISMAR-CNR)Evgeniia Makarova (ICM-CSIC)Ad Stoffelen (KNMI)Marta Martín-Rey (UCM)Eleftheria Exarchou (BSC)Pablo Ortega (BSC)Íñigo Gómara (UCM)Wenming Lin (NUIS)F. Polverari (NASA-JPL)Federico Cossu (ICM-CSIC)Albert S. Rabaneda (ICM-CSIC)Gregory P. Kingportabella@icm.csic.esbec.icm.csic.esScatterometry• Scatterometers provide high-resolution (25-km), accurate sea surface wind field information up to 15-20 km off the coast• Active microwave sensors, operating at C- & Ku-band, i.e., almost all-weather capabilities• They are used in a wide variety of applications, e.g., assimilation into global and regional NWP, nowcasting, hurricane advisories, climate trend analyses, air-sea fluxes, etc.• They measure the sea surface roughness, which is a good proxy for wind stressbec.icm.csic.es Satellite Wind and Wave  ERS scatterometer observes wave train HiRLAM model (and other NWP models) miss the wave train (too smooth) The MSG clouds are aligned with the wave train, but in themselves provide little dynamical information Next day a forecast burst occurred for cloud and precipitation  in England and the NetherlandsHiRLAMERSERS QCbec.icm.csic.es 16 December 20094Rain-induced dynamicsConvectivedownburstsASCAT-A and ASCAT-B come together. Red arrows:ASCAT-A; Blue arrows:ASCAT-B; color contours: MSG RR.bec.icm.csic.esScatterometry• Scatterometers provide high-resolution (25-km), accurate sea surface wind field information up to 15-20 km off the coast• Active microwave sensors, operating at C- & Ku-band, i.e., almost all-weather capabilities• They are used in a wide variety of applications, e.g., assimilation into global and regional NWP, nowcasting, hurricane advisories, climate trend analyses, air-sea fluxes, etc.• They measure the sea surface roughness, which is a good proxy for wind stressOcean forcing• NWP wind output is generally used as ocean forcing since it’s ubiquitous.• NWP winds resolve up to 100-150 km scales in open ocean, and miss small scale processes like moist convection, wind stress-SST coupling, coastal effects, etc.• Can scatterometers be used to improve current NWP ocean forcing products?• Can they bring higher resolution & more accurate forcing?bec.icm.csic.esHigher Level Wind Processing• Level 3: spatio-temporally consistent wind product from a single wind source• Level 4: spatio-temporally consistent wind product from combined wind sources Optimal interpolation (Bentamy) Bayesian Hierarchical model (Milliff) Local bias corrections method – ERA* (Trindade)DAILY COVERAGE FROM A SINGLE SCATTEROMETER(over ocean)ERA* HOURLY L4 WIND PRODUCTbec.icm.csic.esSYSTEMATIC DIFFERENCES BETWEEN NWP AND SCATTCOLLOCATIONS• ASCAT-A/B/C – ERA5 u10S• 30-d Temporal WindowZonal component (v10S)bec.icm.csic.esCORRECTION ERA5 SURFACE WINDS• How long should the winds be accumulated?• How many scatterometers? N length of the temporal window (d);k Scatterometer combinationsM is the number of scatt. and ERA collocations Applied at every forecast time  𝑆𝐶 𝑖, 𝑗, 𝑡 =1𝑀𝑢 𝑖, 𝑗, 𝑡 − 𝑢 𝑖, 𝑗, 𝑡Trindade et al., TGRS, 2020.𝑢 ∗ 𝑖, 𝑗, 𝑡 = 𝑢 𝑖, 𝑗, 𝑡 + 𝑆𝐶 𝑖, 𝑗, 𝑡bec.icm.csic.esERA* vs. ERA5Meridional component (v10S) 20190215 at 09 UTCERA5bec.icm.csic.esERA* vs. ERA5Meridional component (v10S) 20190215 at 09 UTCERA*bec.icm.csic.esWEST AFRICAN COAST ERA5 stress-equivalent wind(U10S)Meridional component (v10S) 20190215 at 09 UTCbec.icm.csic.esWEST AFRICAN COAST Meridional component (v10S) 20190215 at 09 UTCERA* U10SABCO & 3-day temporal windowABCO:ASCAT-A &ASCAT-B &ASCAT-C & OSCAT2bec.icm.csic.esWEST AFRICAN COAST Meridional component (v10S) 20190215 at 09 UTCERA* U10SABCO & 1-day temporal windowABCO:ASCAT-A &ASCAT-B &ASCAT-C & OSCAT2bec.icm.csic.esERA* PRODUCT VALIDATION: SPECTRAL ANALYSISTropics Middle LatitudesMeridional U10S componentFebuary 2019ABCO:ASCAT-A &ASCAT-B &ASCAT-C & OSCAT2bec.icm.csic.esERA* PRODUCT VALIDATION: VRMS REDUCTIONIndependent verification: HSCAT-B LST (6 am/6 pm) Statistics over monthof February 2019ERA*ABCO-N3 U10S generally has the lowest VRMS scores against HSCAT-BCase study: Warm 2017 North Tropical Atlantic event Technical specifications:• ERA* consists of a scatterometer-based correction of ERA-interim, able to introduce truesmaller scale signal that corresponds to physical processes absent or misrepresented inthe ERA-interim output.• Forced tropical Atlantic region [35°N-35°S, 70°W-20°E] with 4° buffering zone.• Initial conditions on the 1st of February of 2017 from ORA-S4 and ERA-interim• 10 members for each simulation perturbing atmospheric initial conditionsSensitivity experiments with the EC-Earth3 model:• MOD: 11-month initialized forecast simulation from February to December 2017, inwhich the model wind runs free in the tropical Atlantic region.• ERAI: 11-month forecast simulation forced by wind stress from ERA-interim in thetropical Atlantic region from February to December 2017.• ERA*: 11-month forecast simulation forced by wind stress from ERA* in the tropicalAtlantic region from February to December 2017.Case study: Warm 2017 North Tropical Atlantic event New findingsMOD forecast:is not able to correctly capturethe observed 2017 warm patternjust with initialized conditions.Case study: Warm 2017 North Tropical Atlantic event New findings30N30S20S20N10NEQ80W      60W     40W       20W        0          20E10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S- 3.8         - 3       - 2.2       -1.4         -.6    -.2   .2    .6         1.4         2.2         3           3.8AVERAI-MOD  SST  AVERA*-MOD  SST  AVERA*-ERAI  SST  (a) MAM80W      60W     40W       20W        0          20E(d) MJJ80W      60W     40W       20W        0          20E(g) JAS80W      60W     40W       20W        0          20E(j) SON80W      60W     40W       20W        0          20E(b) MAM80W      60W     40W       20W        0          20E MJJ(e)(h) JAS80W      60W     40W       20W        0          20E80W      60W     40W       20W        0          20E(k) SON80W      60W     40W       20W        0          20E(c) MAM80W      60W     40W       20W        0          20E(f) MJJ80W      60W     40W       20W        0          20E(i) JAS80W      60W     40W       20W        0          20E SON(l) ERAI and ERA* (vs MOD):improved SST at eastern NTA andalong Senegal coast. ERA* vs ERAI:ameliorated representation of off-shore NTA. ERAI and ERA* (vs MOD) andERA* vs ERAI:significant improvement ofequatorial 2017 SSTs during summerto fallContours: significance at 95%Case study: Warm 2017 North Tropical Atlantic event Martín-Rey et al 2021a, to be submittedNew findings30N30S20S20N10NEQ80W      60W     40W       20W        0          20E10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S- 3.8         - 3       - 2.2       -1.4         -.6    -.2   .2    .6         1.4         2.2         3           3.8AVERAI-MOD  SST  AVERA*-MOD  SST  AVERA*-ERAI  SST  (a) MAM80W      60W     40W       20W        0          20E(d) MJJ80W      60W     40W       20W        0          20E(g) JAS80W      60W     40W       20W        0          20E(j) SON80W      60W     40W       20W        0          20E(b) MAM80W      60W     40W       20W        0          20E MJJ(e)(h) JAS80W      60W     40W       20W        0          20E80W      60W     40W       20W        0          20E(k) SON80W      60W     40W       20W        0          20E(c) MAM80W      60W     40W       20W        0          20E(f) MJJ80W      60W     40W       20W        0          20E(i) JAS80W      60W     40W       20W        0          20E SON(l) ERAI and ERA* (vs MOD):improved SST at eastern NTA andalong Senegal coast. ERA* vs ERAI:ameliorated representation of off-shore NTA. ERAI and ERA* (vs MOD) andERA* vs ERAI:significant improvement ofequatorial 2017 SSTs during summerto fallContours: significance at 95%Case study: Warm 2017 North Tropical Atlantic event New findings30N30S20S20N10NEQ80W      60W     40W       20W        0          20E10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S30N30S20S20N10NEQ10S- 3.8         - 3       - 2.2       -1.4         -.6    -.2   .2    .6         1.4         2.2         3           3.8AVERAI-MOD  SST  AVERA*-MOD  SST  AVERA*-ERAI  SST  (a) MAM80W      60W     40W       20W        0          20E(d) MJJ80W      60W     40W       20W        0          20E(g) JAS80W      60W     40W       20W        0          20E(j) SON80W      60W     40W       20W        0          20E(b) MAM80W      60W     40W       20W        0          20E MJJ(e)(h) JAS80W      60W     40W       20W        0          20E80W      60W     40W       20W        0          20E(k) SON80W      60W     40W       20W        0          20E(c) MAM80W      60W     40W       20W        0          20E(f) MJJ80W      60W     40W       20W        0          20E(i) JAS80W      60W     40W       20W        0          20E SON(l) ERAI and ERA* (vs MOD):improved SST at eastern NTA andalong Senegal coast. ERA* vs ERAI:ameliorated representation of off-shore NTA. ERAI and ERA* (vs MOD) andERA* vs ERAI:significant improvement ofequatorial 2017 SSTs during summerto fallContours: significance at 95%Case study: Warm 2017 North Tropical Atlantic event (e) SSH 2N-4N ERA*-ERAI (f)  SSH EQ ERA*-ERAI-8    -7     -6     -5     -4     -3     -2     -1      0      1      2      3      4      5      6      7      8OCTGJUNAYAPRMAR10E       0     10W    20W    30W   40W      40W    30W     20W   10W       0      10Ecm(a) SSH 2N-4N ERAI-MOD (b) SSH EQ ERAI-MODOCTSEPAUGJULJUNMAYAPRMAR(c) SSH 2N-4N ERA*-MOD (d) SSH EQ ERA*-MODOCTSEPAUGJULJUNMAYAPRMAR10E       0     10W    20W    30W   40W        40W    30W    20W   10W      0      10E10E       0     10W    20W    30W   40W       40W    30W    20W    10W      0      10EdRW (BM2~ 0.49m/s) propagateswestward and is boundary-reflectedin JulydKW (BM1~ 2.97m/s) propagatesalong the equator during July-AugustdKWdRWRW-reflected mechanism:Contours: significance at 95%• NTA-equatorial linkage in the 2017 event via wind-induced remote ocean waves• RW-reflected mechanism arises when realistic surface stress is used• Despite stronger ERA* wind curl, similar dRW w.r.t ERAi• Enhanced dKW for ERA* experiment w.r.t. ERAi  bec.icm.csic.esERA* product - summary • Due to the persistence of the ERA5 local biases, it is possible to add smaller scale information, i.e., include some of the physical processes that are missing or misrepresented in ERA5, and still keep the large scale circulation patterns.• ERA* shows a significant increase in small-scale true wind variability, due to oceanic features such as wind changes over SST gradients and ocean currents.• Short temporal windows are preferred, to avoid over smoothing of the forcing fields and to address persistence effects.• From the statistical and spectral analyses, the optimal configuration to introduce the oceanic mesoscale is the use of complementary scatterometers and a temporal window of three days.• ERA* effectively resolves spatial scales of about 50 km, substantially smaller than those resolved by global NWP output (about 100-150 km).• Overall, ERA* ABCO 3-day product shows the best performance with a global error variance reduction of 9.1% w.r.t. ERA5 U10S performance.bec.icm.csic.esERA* impact on simulations - 2017 warm event • During extreme 2017 warm event, NTA and equatorial SST variability were connected.• Realistic wind stress required to improve the simulation of SSTs in eastern NTA, along Senegalese coast and at the Equator.• The ocean wave activity is highly sensitive to realistic wind stress products: only ERAI and ERA* winds are able to reproduce the RW-reflected mechanism linking NTA and EQ regions.• ERA* does provide an enhanced propagation of the downwelling equatorial Kelvin wave in the boreal summer.bec.icm.csic.esFUTURE WORK• ERA* developments:• Test in ERA* the upcoming OSI SAF OSCAT2 version, with reduced across-track biases• Test new scatt-ERA5 outlier rejection strategies• Test ERA* quality as a function of scatterometer sampling• Verify ERA* (notably ERA*ABC-N3) against buoy U10S• Test optimal configuration in the period 2010-2018 to complete the 10-year ERA* dataset (ESA WOC project)• ERA* impact experiments• Test ERA* impact on improved surge prediction capabilities in the Adriatic Sea (in collaboration with ISMAR & NIB)• Test new ERA* product on, e.g., ENSO predicting capabilities or stress/SST coupling• Test ERA* impact on improved ocean current products in the context of WOCCGMS-48 May 25-29, 2020 25CEOS OSVW-VC current status and outlook 25Note: Near real-time and open data access not assured for all missions listed16 17 18 19 20 21 22 23 24 25 26 27 28 29 30ASCAT / Metop-A (launch 19.10.2006)ASCAT / Metop-B (launch 17.09.2012)ASCAT / Metop-CSCA / Metop-SG B1 + B2 + B3C-bandC and Ku-bandKu-bandWindRad / FY-3EScatsat-1Oceansat-3SCAT + SWIM/ CFOSATHY-2A HY-2BHY-2E / HY-2F / HY-2GHY-2D OperationalApprovedDevelopedSCATSAT-1AConsideredHY-2CMeteor-MP N1Meteor-MP N2Meteor-MP N3Source: CEOS / WMO OSCAR database, 08/2018(launched 2011)SWIM+SCAT / CFOSAT follow-onOperational = on orbit but does not distinguish between research and operational  missionPlannedHY-2 Next Generation 

The role of scatterometry in ocean model forcing

https://digital.csic.es/bitstream/10261/257885/1/Portabella_et_al_2021.pdf

The role of scatterometry in ocean model forcing

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