Contents S1 Supplementary Figures S–2 On the use of tail-based coincidence metrics as oppossed to correlations-based metrics ................ S–2 Land-atmosphere coupling in individual seasons and alternative metrics for model evaluation ............. S–3 Is land-atmosphere coupling a model-inherent feature? ................................. S–7 5 Global patterns of land-atmosphere coupling in models and observations ........................ S–9 Bivariate T-ET dependence structure in coupling sensitive regions in the warm season ................. S–10 Is there a link between VAC-diagnosed land-atmosphere coupling and (absolute) precipitation or evapotransiration fluxes? ........................................................ S–13 On constraining model-projected warming by land-atmosphere coupling metrics .................... S–14 10 S2 Supplementary Tables S–15 S–1
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Contents
S1 Supplementary Figures S–2On the use of tail-based coincidence metrics as oppossed to correlations-based metrics . . . . . . . . . . . . . . . . S–2Land-atmosphere coupling in individual seasons and alternative metrics for model evaluation . . . . . . . . . . . . . S–3Is land-atmosphere coupling a model-inherent feature? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . S–75Global patterns of land-atmosphere coupling in models and observations . . . . . . . . . . . . . . . . . . . . . . . . S–9Bivariate T-ET dependence structure in coupling sensitive regions in the warm season . . . . . . . . . . . . . . . . . S–10Is there a link between VAC-diagnosed land-atmosphere coupling and (absolute) precipitation or evapotransiration
On the use of tail-based coincidence metrics as oppossed to correlations-based metrics
CMIP5−Models, CEU−JJA: VACc/VACd
Den
sity
0.0 0.5 1.0 1.5 2.0
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Obs.−based, CEU−JJA: VACc/VACd
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CMIP5−Models, CEU−JJA: VACb/VACa
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Obs.−based, CEU−JJA: VACb/VACa
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sity
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Figure S1. (Top) Ratio of V ACc/V ACd occurrences in CMIP5 models (left) and observations (right). (Middle) Ratio of V ACb/V ACa
occurrences in CMIP5 models (left) and observations (right). (Bottom) Comparison of V ACb/V ACc occurrences (left) and V ACa/V ACd
occurrences (right) in models, observations and artificial data. More frequent occurrences of V ACc than would be expected in a symmetricdependence structure (as diagnosed e.g. by correlation-based metrics) indicate that the application of coincidences is appropriate.
S–2
Land-atmosphere coupling in individual seasons and alternative metrics for model evaluation
−150 −100 −50 0 50 100 150
−50
050
Longitude
Latit
ude
DJFMAMJJASON
Figure S2. Definition of “warm season" in this study based on long-term seasonal temperatures in the CRU dataset.
S–3
−0.5 −0.3 −0.1 0.1 0.3 0.5VACcCMIP5, median − VACcBenchmark, median (DJF)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACcCMIP5, median − VACcBenchmark, median (MAM)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACcCMIP5, median − VACcBenchmark, median (JJA)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACcCMIP5, median − VACcBenchmark, median (SON)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACcCMIP5, median − VACcBenchmark, median (warm seas.)
Figure S3. Difference in median V ACc in CMIP5 models and observations in (top left) DJF, (top right) MAM, (middle left) JJA, and (middleright) SON, the warm season (bottom left). (Bottom right) Fraction of models that are within the 5th to 95th percentile of the ensemble ofobservations in the warm season (V ACc).
S–4
−0.5 −0.3 −0.1 0.1 0.3 0.5VACbCMIP5, median − VACbBenchmark, median (DJF)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACbCMIP5, median − VACbBenchmark, median (MAM)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACbCMIP5, median − VACbBenchmark, median (JJA)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACbCMIP5, median − VACbBenchmark, median (SON)
−0.5 −0.3 −0.1 0.1 0.3 0.5VACbCMIP5, median − VACcBenchmark, median (warm seas.)
Figure S4. Difference in median V ACb in CMIP5 models and observations in (top left) DJF, (top right) MAM, (middle left) JJA, and (middleright) SON, the warm season (bottom left). (Bottom right) Fraction of models that are within the 5th to 95th percentile of the ensemble ofobservations in the warm season (V ACb).
Figure S5. Land-atmosphere coupling in Central Europe in CMIP5 models and observations as diagnosed through (top left) V ACb and (topright) V ACc based on 90th percentile thresholds, and (bottom left) the Pearson correlation of T and ET anomalies. (Bottom right) Differencein median Pearson corrrelation in CMIP5 models and observations in the warm season.
S–6
Is land-atmosphere coupling a model-inherent feature?
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VACc
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−1.0 −0.6 −0.2 0.2 0.6 1.0Correlation between VACc_present and VACc_future (CMIP5)
Figure S6. (Top) V ACc occurrences in Central Europe (JJA) in individual models. (Bottom) Correlation between present-day and futureland-atmosphere coupling reveal that occurrences of V ACc are largely model-inherent features.
S–7
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VACc
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Figure S7. V ACc occurrences in Central North America (JJA) in individual models.
S–8
Global patterns of land-atmosphere coupling in models and observations
0.00 0.20 0.40 0.60 0.80 1.00VACbCMIP5, median (warm seas.)
0.00 0.20 0.40 0.60 0.80 1.00VACbBenchmark, median (warm seas.)
0.00 0.20 0.40 0.60 0.80 1.00VACcCMIP5, median (warm seas.)
0.00 0.20 0.40 0.60 0.80 1.00VACcBenchmark, median (warm seas.)
Figure S8. Global patterns in land-atmosphere coupling as diagnosed through (top) V ACb and (bottom) V ACc: ensemble medianV ACb/V ACc in CMIP5 models (left) and ensemble median of the observations-based datasets (right).
S–9
Bivariate T-ET dependence structure in coupling sensitive regions in the warm season
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ET standardized anomalies (1989−2005)
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CEU−Benchmark
r = 0.46VACb−rate = 54.9%VACc−rate = 14.8%
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CEU−CMIP5−original
r = 0.08VACb−rate = 34.6%VACc−rate = 28.4%
●
●
VACb−indiv.VACc−indiv.
−3 −2 −1 0 1 2 3
−3
−2
−1
0
1
2
3
ET standardized anomalies (1989−2005)
Tem
pera
ture
, sta
ndar
dize
d an
omal
ies
(198
9−20
05)
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CEU−CMIP5−constraint
r = 0.48VACb−rate = 53.3%VACc−rate = 13.4%
●
●
VACb−indiv.VACc−indiv.
Figure S9. Bivariate kernel density estimates of T-ET relationship in Central Europe in the observations-based benchmarking datasets (Top),the original (middle) and constrained (bottom) CMIP5 ensemble.
S–10
−3 −2 −1 0 1 2 3
−3
−2
−1
0
1
2
3
ET standardized anomalies (1989−2005)Te
mpe
ratu
re, s
tand
ardi
zed
anom
alie
s (1
989−
2005
)
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CNA−Benchmark
r = 0.03VACb−rate = 30.4%VACc−rate = 31.3%
●
●
VACb−indiv.VACc−indiv.
−3 −2 −1 0 1 2 3
−3
−2
−1
0
1
2
3
ET standardized anomalies (1989−2005)
Tem
pera
ture
, sta
ndar
dize
d an
omal
ies
(198
9−20
05)
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CNA−CMIP5−original
r = −0.34VACb−rate = 17.3%VACc−rate = 47.5%
●
●
VACb−indiv.VACc−indiv.
−3 −2 −1 0 1 2 3
−3
−2
−1
0
1
2
3
ET standardized anomalies (1989−2005)
Tem
pera
ture
, sta
ndar
dize
d an
omal
ies
(198
9−20
05)
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CNA−CMIP5−constraint
r = 0.02VACb−rate = 30.3%VACc−rate = 30.3%
●
●
VACb−indiv.VACc−indiv.
Figure S10. Bivariate kernel density estimates of T-ET relationship in Central North America in the observations-based benchmarkingdatasets (Top), the original (middle) and constrained (bottom) CMIP5 ensemble.
S–11
−3 −2 −1 0 1 2 3
−3
−2
−1
0
1
2
3
ET standardized anomalies (1989−2005)Te
mpe
ratu
re, s
tand
ardi
zed
anom
alie
s (1
989−
2005
)
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AMZ−Benchmark
r = 0.29VACb−rate = 39.9%VACc−rate = 18.4%
●
●
VACb−indiv.VACc−indiv.
−3 −2 −1 0 1 2 3
−3
−2
−1
0
1
2
3
ET standardized anomalies (1989−2005)
Tem
pera
ture
, sta
ndar
dize
d an
omal
ies
(198
9−20
05)
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AMZ−CMIP5−original
r = −0.11VACb−rate = 23.3%VACc−rate = 36.9%
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VACb−indiv.VACc−indiv.
−3 −2 −1 0 1 2 3
−3
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−1
0
1
2
3
ET standardized anomalies (1989−2005)
Tem
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AMZ−CMIP5−constraint
r = 0.24VACb−rate = 36.8%VACc−rate = 19.6%
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VACb−indiv.VACc−indiv.
Figure S11. Bivariate kernel density estimates of T-ET relationship in the Amazon region in the observations-based benchmarking datasets(Top), the original (middle) and constrained (bottom) CMIP5 ensemble.
S–12
Is there a link between VAC-diagnosed land-atmosphere coupling and (absolute) precipitation or evapotransirationfluxes?
−1.0 −0.6 −0.2 0.2 0.6 1.0Correlation between VACc and Precip (CMIP5)
−1.0 −0.6 −0.2 0.2 0.6 1.0Correlation between VACc and ET (CMIP5)
Figure S12. Pearson correlation between (top) V ACc and rainfall, and (bottom) V ACc and evapotranspiration across the CMIP5 multi-model ensemble.
S–13
On constraining model-projected warming by land-atmosphere coupling metrics
Figure S13. Correlation between V ACc and the "excess" warming in the warm season (difference between warm season warming andannual mean warming). In boreal regions, the "summer excess warming", is not related to V ACc.
S–14
S2 Supplementary Tables
Table S1. CMIP5 models used for analysis
Model name Variable Ensemble member ScenarioACCESS1-0 T, ET, TXx r1i1p1 Historical, RCP8.5ACCESS1-3 T, ET, TXx r1i1p1 Historical, RCP8.5bcc-csm1-1 T, ET, TXx r1i1p1 Historical, RCP8.5bcc-csm1-1-m T, ET, TXx r1i1p1 Historical, RCP8.5CanESM2 T, ET, TXx r1i1p1 Historical, RCP8.5CCSM4 T, ET, TXx r1i1p1 Historical, RCP8.5CESM1-BGC T, ET, TXx r1i1p1 Historical, RCP8.5CESM1-CAM5 T, ET, TXx r1i1p1 Historical, RCP8.5CMCC-CESM T, ET, TXx r1i1p1 Historical, RCP8.5CMCC-CM T, ET, TXx r1i1p1 Historical, RCP8.5CMCC-CMS T, ET, TXx r1i1p1 Historical, RCP8.5CNRM-CM5 T, ET, TXx r1i1p1 Historical, RCP8.5CSIRO-Mk3 T, ET, TXx r1i1p1 Historical, RCP8.5EC-EARTH T, ET, TXx r2i1p1 Historical, RCP8.5FGOALS-g2 T, ET, TXx r1i1p1 Historical, RCP8.5FIO-ESM T, ET r1i1p1 Historical, RCP8.5GFDL-CM3 T, ET, TXx r1i1p1 Historical, RCP8.5GFDL-ESM2G T, ET, TXx r1i1p1 Historical, RCP8.5GFDL-ESM2M T, ET, TXx r1i1p1 Historical, RCP8.5GISS-E2-H T, ET, TXx r6i1p1 Historical, RCP8.5GISS-E2-R T, ET, TXx r6i1p1 Historical, RCP8.5HadGEM2-AO T, ET, TXx r1i1p1 Historical, RCP8.5HadGEM2-CC T, ET, TXx r1i1p1 Historical, RCP8.5HadGEM2-ES T, ET, TXx r1i1p1 Historical, RCP8.5inmcm4 T, ET, TXx r1i1p1 Historical, RCP8.5IPSL-CM5A-LR T, ET, TXx r1i1p1 Historical, RCP8.5IPSL-CM5A-MR T, ET, TXx r1i1p1 Historical, RCP8.5IPSL-CM5B-LR T, ET, TXx r1i1p1 Historical, RCP8.5MIROC-ESM T, ET, TXx r1i1p1 Historical, RCP8.5MIROC-ESM-CHEM T, ET, TXx r1i1p1 Historical, RCP8.5MIROC5 T, ET, TXx r1i1p1 Historical, RCP8.5MPI-ESM-LR T, ET, TXx r1i1p1 Historical, RCP8.5MPI-ESM-MR T, ET, TXx r1i1p1 Historical, RCP8.5MRI-CGCM3 T, ET, TXx r1i1p1 Historical, RCP8.5MRI-ESM1 T, ET, TXx r1i1p1 Historical, RCP8.5NorESM1-M T, ET, TXx r1i1p1 Historical, RCP8.5NorESM1-ME T, ET r1i1p1 Historical, RCP8.5
