On the computation of mass-change trends from GRACE gravity field time-series

Transcription

1 Geodäsche Woche 0 Nürberg, Sepember 0 O he compuao of mass-chage reds from GRACE gravy feld me-seres Olver Baur Isu für Welraumforschug, Öserrechsche Aademe der Wsseschafe

2 Movao Greelad lear mass-chage reds (jus a few examples... Velcoga ad Wahr (GRL, 005 Ramlle e al. (GPC, 006 Averagg 04/00 07/004 CSR erel 07/00 03/005 Averagg CNES/GRGS erel Che e al. (Scece, 006 Luhce e al. (Scece, /003 07/005 Mascos KBRR 04/00 /005 Forward CSR modelg Wouers e al. (GRL, 008 Baur e al. (JGR, 009 Velcoga (GRL, 009 Che e al. (JGR, 0 0/003 0/008 Forward CSR, modelg GFZ Leaage 08/00 07/008 CSR, quafcao GFZ, JPL 04/00 0/009 Averagg CSR erel 04/00 /009 Forward CSR modelg G/yr Sources of dscrepacy mpac geoceer of GIA geoceer moo sgal from moo SLR Iverso mehod / pre-processg Perod of vesgao Daa used Daa mapulao (c 0, degree-

3 Movao Greelad mass-chage accelerao (aga, jus a few examples... Velcoga ad Wahr (Naure, /00 04/004: -95 ± 50 G/yr 05/004 04/006: -34 ± 6 G/yr Che e al. (JGR, 0 04/00 03/005: -44 ± 5 G/yr 04/005 /009: -48 ± 43 G/yr Velcoga (GRL, 009 Schrama e al. (JGR, 0 Rgo e al. (GRL, G/yr Sources of dscrepacy Iverso mehod / pre-processg Perod of vesgao Daa used Daa mapulao (c 0, degree- Compuao of mass-chage reds 3

4 Coe Lear red modelg No-lear red modelg Model seleco Coclusos Greelad Iverso mehod: Baur e al. (JGR, 009 Perod of vesgao: 05/00 04/0 (ad subses hereof Daa used: CSR (RL04 Daa mapulao : c 0 : SLR, geoceer moo: SLR, GIA: Paulso e al. (007 Compuao of mass-chage reds: varable Amazo bas 4

5 Lear red modelg Model fuco Tred, approxmaed by frs-order polyomal (regresso le y ( 0,,..., Addoal aual sgal y ( A cos( f B s( f 0,,..., F chage rae (G/yr Regresso le -3 ± 5 + aual sgal -3 ± 4 + sem-aual sgal -3 ± 3 + S dal alas -3 ± 3 + K dal alas -30 ± 3 + K dal alas -30 ± 3 5

6 Lear red modelg Model fuco Tred, approxmaed by frs-order polyomal (regresso le y ( 0,,..., Addoal aual ad sem-aual sgal ad dal alases y ( cos( s(,,..., ; 0 A f B f j j j j j j,... F chage rae (G/yr Regresso le -3 ± 5 + aual sgal -3 ± 4 + sem-aual sgal -3 ± 3 + S dal alas -3 ± 3 + K dal alas -30 ± 3 + K dal alas -30 ± 3 6

7 Lear red modelg Model fuco Tred, approxmaed by frs-order polyomal (regresso le y ( 0,,..., Addoal aual ad sem-aual sgal ad dal alases y ( cos( s(,,..., ; 0 A f B f j j j j j j,... F chage rae (G/yr Regresso le -3 ± 5 + aual sgal -3 ± 4 + sem-aual sgal -3 ± 3 + S dal alas -3 ± 3 K + K dal alas -30 ± 3 + K dal alas -30 ± 3 K S 7

8 Lear red modelg Smoohg of me seres Tred, approxmaed by frs-order polyomal (regresso le Addoal aual ad sem-aual sgal ad dal alases Ier-aual varaos 3-moh wdow Lowess fler low-pass fler lowess ± G/yr lowess ± G/yr Velcoga (GRL, 009 8

9 Lear red modelg F chage rae (G/yr Regresso le 50 ± 8 + aual sgal 43 ± 6 + sem-aual sgal 43 ± 6 + S dal alas 43 ± 6 + K dal alas 36 ± 7 + K dal alas 36 ± 7 lowess ± 3 G/yr K K S 9

10 Lear red modelg Mass-chage accelerao Che e al. (JGR, 0 04/00 03/005: -9 ± 38 G/yr 04/00 03/005: -44 ± 5 G/yr 04/005 /009: -48 ± 43 G/yr Re-compuao - ± 4 G/yr -70 ± 3 G/yr -50 ± 8 G/yr 0

11 Lear red modelg Mass-chage accelerao Che e al. (JGR, 0 04/00 03/005: -44 ± 5 G/yr 04/005 /009: -48 ± 43 G/yr Velcoga ad Wahr (Naure, /00 04/004: -95 ± 50 G/yr 05/004 04/006: -34 ± 6 G/yr Velcoga (GRL, /00??/003: -37 G/yr??/007 0/009: -86 G/yr Choce of accelerao po?

12 Lear red modelg Subse perod: 5 years Subse shf: 6 mohs Subse perod: 6 years Subse shf: 6 mohs

13 3,... ;,...,,, (... ( 0 f y j j p p Tred approxmao by p-h order polyomal (regresso polyomal Regresso le Regresso parabola No-lear red modelg Model fuco

14 4 Tred approxmao by p-h order polyomal (regresso polyomal Regresso le Regresso parabola No-lear red modelg Model fuco,... ;,...,,, (... ( 0 f y j j p p

15 Model seleco Whch model s relable / o be preferred?? 5

16 6 (, / 0 ~ / ˆ, 0 :, 0 : p T H H Hypoheses esg of polyomal coeffces (absolue measure Iformao crera (relave measure Leave-oe-ou cross valdao (relave measure CV ˆ CV ( y y Whch model s relable / o be preferred? l( ˆ l( BIC ( AIC AIC, ˆ ˆ, ˆ l( AIC R ( R ( ˆ R c p e - p - - y y σ - R-square Aae IC Bayesa IC Model seleco

17 Model seleco Whch model s relable / o be preferred? Greelad Order ΔR ΔAIC c ΔBIC ΔCV Sgfca parameers all all ercep ercep Secod-order polyomal s superor o oher red fucos accelerao: -5 ± 3 G/yr Amazo bas Order ΔR ΔAIC c ΔBIC ΔCV Sgfca parameers all oe Frs-order polyomal s superor o oher red fucos 7

18 Coclusos I bref I s a mess! More scefcally Treds umbers (ad her error bouds are hghly subjec o he uderlyg processg scheme Ierpreao of mass-chage reds ad mass-chage red varaos over shor perods should be avoded Never ever valdae chage raes agas reds umbers based o dfferg perods Tred model seleco should rouely be accompaed by hypoheses esg ad formao crera evaluao The compuao of mass varao from GRACE has bee becomg creasgly heerogeeous; coveos would mprove cossecy 8

19 Tred model Whch model s relable / o be preferred? CSR Nle bas ITG DMT 9

20 Tred model Subse perod: 5 years Subse shf: 6 mohs Subse perod: 6 years Subse shf: 6 mohs 0