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Different hydrologic impacts Di differently to warming respond very - - PowerPoint PPT Presentation

Jan 10, 2024 390 likes •1.06k views

Different hydrologic impacts Di differently to warming respond very di In observations (historical & paleo) as well as models Jack Scheff (UNC Charlotte), with thanks to many 2018, Current Clim. Change Reports ; 2017, J. Clim. rcp8.5

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SLIDE 1

Di Different hydrologic impacts

respond very di

differently to warming

In observations (historical & paleo) as well as models

Jack Scheff (UNC Charlotte), with thanks to many 2018, Current Clim. Change Reports; 2017, J. Clim.

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SLIDE 2

rcp8.5 CMIP5-median 21st century...

familiar (Stippling = at least 80% of models agree on sign)

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SLIDE 3

rcp8.5 CMIP5-median 21st century...

familiar “global drying” per ecologists (Stippling = at least 80% of models agree on sign)

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SLIDE 4

rcp8.5 CMIP5-median 21st century...

familiar “global drying” per ecologists “global droughting”

d) PDSI = f(P,PET) change

(Stippling = at least 80% of models agree on sign)

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SLIDE 5

rcp8.5 CMIP5-median 21st century...

familiar “global drying” per ecologists “global droughting”

d) PDSI = f(P,PET) change

global topsoil drying (Stippling = at least 80% of models agree on sign)

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SLIDE 6

But why does dryness ma matter?

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SLIDE 7

But why does dryness ma matter?

  • Reductions in water resources (i.e. in P-E or runoff)
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SLIDE 8

But why does dryness ma matter?

  • Reductions in water resources (i.e. in P-E or runoff)
  • Vegetation water stress (less water available to compensate

transpiration losses)

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SLIDE 9

But why does dryness ma matter?

  • Reductions in water resources (i.e. in P-E or runoff)
  • Vegetation water stress (less water available to compensate

transpiration losses)

  • These impacts are the principal motivations for both P/PET (e.g.

Budyko 1974) and PDSI!

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SLIDE 10

But why does dryness ma matter?

  • Reductions in water resources (i.e. in P-E or runoff)
  • Vegetation water stress (less water available to compensate

transpiration losses)

  • These impacts are the principal motivations for both P/PET (e.g.

Budyko 1974) and PDSI!

  • Also - increases in SH at expense of LH – leads to heatwaves &

increased T variance

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SLIDE 11

rcp8.5 CMIP5-median 21st century...

familiar “global drying” per ecologists “global droughting”

d) PDSI = f(P,PET) change

global topsoil drying (Stippling = at least 80% of models agree on sign)

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SLIDE 12

rcp8.5 CMIP5-median 21st century...

familiar (Stippling = at least 80% of models agree on sign)

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SLIDE 13

rcp8.5 CMIP5-median 21st century...

familiar runoff responses vary (Stippling = at least 80% of models agree on sign)

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SLIDE 14

rcp8.5 CMIP5-median 21st century...

familiar runoff responses vary deep-soil responses vary (Stippling = at least 80% of models agree on sign) 3m soil moisture % change (from Berg et al 2017)

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SLIDE 15

rcp8.5 CMIP5-median 21st century...

familiar runoff responses vary deep-soil responses vary (Stippling = at least 80% of models agree on sign) [LH/SH responses similar] 3m soil moisture % change (from Berg et al 2017)

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SLIDE 16

rcp8.5 CMIP5-median 21st century...

familiar runoff responses vary deep-soil responses vary global greening! (Stippling = at least 80% of models agree on sign) [LH/SH responses similar] 3m soil moisture % change (from Berg et al 2017)

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SLIDE 17

Highlights

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SLIDE 18

Highlights

familiar runoff responses vary global greening! (Stippling = at least 80% of models agree on sign) “global droughting”

d) PDSI = f(P,PET) change

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SLIDE 19

Why do the models do this?

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SLIDE 20

Why do the models do this?

  • Greening response is definitely due to direct CO2 effect on plants: they

can fix more CO2 per unit water transpired.

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SLIDE 21

Why do the models do this?

  • Greening response is definitely due to direct CO2 effect on plants: they

can fix more CO2 per unit water transpired.

  • We know this because it vanishes in simulations without these effects:
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SLIDE 22

Why do the models do this?

  • Greening response is definitely due to direct CO2 effect on plants: they

can fix more CO2 per unit water transpired.

  • We know this because it vanishes in simulations without these effects:

1%/yr exp with fert

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SLIDE 23

Why do the models do this?

  • Greening response is definitely due to direct CO2 effect on plants: they

can fix more CO2 per unit water transpired.

  • We know this because it vanishes in simulations without these effects:

1%/yr exp with fert 1%/yr exp nofert global greening is gone!

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SLIDE 24

Why do the models do this?

  • Mismatch of runoff (& deep-soil) responses to dryness index responses

is harder to explain. Smaller in no-fert simulations, but still large.

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SLIDE 25

Why do the models do this?

  • Mismatch of runoff (& deep-soil) responses to dryness index responses

is harder to explain. Smaller in no-fert simulations, but still large.

  • Could be mix of:
  • stomatal closure (due to CO2 & VPD increases) -> less E, thus more runoff (many)
  • increased “flashiness” of P -> more direct runoff (Dai)
  • increased seasonality of P (Chou) -> more runoff
  • PET actually doesn’t depend on temperature at all? (Milly)
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SLIDE 26

But, in any case, this is what the models do.

familiar runoff responses vary global greening! (Stippling = at least 80% of models agree on sign) “global droughting”

d) PDSI = f(P,PET) change

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SLIDE 27

Does this happen when the real world warms?

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SLIDE 28

Does this happen when the real world warms?

  • Yes.
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SLIDE 29

1951-2010 P trend (mm/yr per decade; IPCC 2013)

Ob Observe ved...

familiar (Stippling = trends are significant at 5%)

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SLIDE 30

1951-2010 P trend (mm/yr per decade; IPCC 2013)

Ob Observe ved...

familiar (Stippling = trends are significant at 5%) severe “global droughting” 1950-2012 PDSI trend (PDSI per 50yr; Dai and Zhao 2016)

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SLIDE 31

1951-2010 P trend (mm/yr per decade; IPCC 2013)

Ob Observe ved...

familiar (Stippling = trends are significant at 5%) severe “global droughting” 1950-2012 PDSI trend (PDSI per 50yr; Dai and Zhao 2016) runoff responses vary 1949-2012 runoff trend (0.1mm/day per 50yr; Dai and Zhao 2016)

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SLIDE 32

1951-2010 P trend (mm/yr per decade; IPCC 2013)

Ob Observe ved...

familiar global greening from satellite! (Stippling = trends are significant at 5%) severe “global droughting” 1950-2012 PDSI trend (PDSI per 50yr; Dai and Zhao 2016) runoff responses vary 1949-2012 runoff trend (0.1mm/day per 50yr; Dai and Zhao 2016) 1982-2009 leaf area trend (0.1m2/m2 per decade; Zhu et al 2016)

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SLIDE 33

Does this happen when the real world warms?

  • Yes. At least for the historical anthropogenic warming.
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SLIDE 34

Does this happen when the real world warms?

  • Yes. At least for the historical anthropogenic warming.
  • What about for glacial-to-interglacial warming? Also had a CO2 rise...
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SLIDE 35

Does this happen when the real world warms?

  • Yes. At least for the historical anthropogenic warming.
  • What about for glacial-to-interglacial warming? Also had a CO2 rise...
  • I’ll actually display it as interglacial-to-glacial cooling & CO2 drop (“anti-analog”)
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SLIDE 36

CMIP5-median LGM minus preindustrial...

familiar (Stippling = at least 80% of models agree on sign)

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SLIDE 37

CMIP5-median LGM minus preindustrial...

familiar (Stippling = at least 80% of models agree on sign) more “wetting”, except high lats.

d) PDSI = f(P,PET) change

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SLIDE 38

CMIP5-median LGM minus preindustrial...

familiar runoff responses vary (Stippling = at least 80% of models agree on sign) more “wetting”, except high lats.

d) PDSI = f(P,PET) change

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SLIDE 39

CMIP5-median LGM minus preindustrial...

familiar runoff responses vary global browning! (Stippling = at least 80% of models agree on sign) more “wetting”, except high lats.

d) PDSI = f(P,PET) change

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SLIDE 40

LGM vegetation was compiled by BIOME6000

Pollen (& macrofossil) data -> “Biomization” statistical approach: Prentice et al (1996), Clim. Dyn., methods Elenga et al (2000), J. Biogeogr., Africa & W. Europe Takahara et al (2000), J. Biogeogr., Japan Tarasov et al (2000), J. Biogeogr., Former Soviet & Mongolia Thompson and Anderson (2000), J. Biogeogr., Western US Williams et al (2000), J. Biogeogr., Eastern US Yu et al (2000), J. Biogeogr., China Harrison et al (2001), Nature, more China Bigelow et al (2003), JGR, pan-Arctic (>55N) Pickett et al (2004), J. Biogeogr., Australia to SE Asia Marchant et al (2009), Clim. Past, Latin America Mostly downloadable in Excel format

  • Hundreds of sites – determined present potential vegetation for each
  • (Tables S1-S10 in 2017 J. Clim. paper)
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SLIDE 41

On following maps:

( ) : LGM vegetation more open, “drier-looking” than PI. PI rainforest -> LGM seasonal forest, PI forest -> LGM grassland, etc.

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SLIDE 42

On following maps:

( ) : LGM vegetation more open, “drier-looking” than PI. PI rainforest -> LGM seasonal forest, PI forest -> LGM grassland, etc. ( ) : LGM vegetation more closed, “wetter-looking” than PI. PI Seasonal forest -> LGM rainforest, PI grassland -> LGM forest, etc.

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SLIDE 43

On following maps:

( ) : LGM vegetation more open, “drier-looking” than PI. PI rainforest -> LGM seasonal forest, PI forest -> LGM grassland, etc. ( ) : LGM vegetation more closed, “wetter-looking” than PI. PI Seasonal forest -> LGM rainforest, PI grassland -> LGM forest, etc. ( ): PI vegetation looks ~as “wet”/”dry” as LGM.

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SLIDE 44

a) PDSI change with obs vegetation change −5 5 b) NPP change (kg C m−2 yr−1) with obs vegetation change −0.4 −0.2 0.2 0.4 0.6

−1

− − −

−

− − − −

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SLIDE 45

a) PDSI change with obs vegetation change −5 5 b) NPP change (kg C m−2 yr−1) with obs vegetation change −0.4 −0.2 0.2 0.4 0.6

−1

− − −

−

− − − −

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SLIDE 46

a) PDSI change with obs vegetation change −5 5 b) NPP change (kg C m−2 yr−1) with obs vegetation change −0.4 −0.2 0.2 0.4 0.6

−1

− − −

−

− − − −

Near-global browning at LGM, despite “less droughty conditions” but in line with model browning

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SLIDE 47

a) PDSI change with obs vegetation change −5 5 b) NPP change (kg C m−2 yr−1) with obs vegetation change −0.4 −0.2 0.2 0.4 0.6

−1

− − −

−

− − − −

(i.e. near-global greening with warming, despite “drought” but in line with model greening)

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SLIDE 48

Global Lake Status Data Base (direct LGM runoff proxies) (Harrison and Bartlein, 2012, in The Future of the World’s Climate)

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SLIDE 49

−

− − − − − − − −

−

−0.02 − − − − − g) P−E change (mm day−1) −0.4 −0.2 0.2 0.4

− −

− −

Global Lake Status Data Base (direct LGM runoff proxies) (Harrison and Bartlein, 2012, in The Future of the World’s Climate)

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SLIDE 50

−

− − − − − − − −

−

−0.02 − − − − − g) P−E change (mm day−1) −0.4 −0.2 0.2 0.4

− −

− −

Global Lake Status Data Base (direct LGM runoff proxies) (Harrison and Bartlein, 2012, in The Future of the World’s Climate)

real LGM runoff changes resembled model runoff projections (varied), not vegetation (browning)

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SLIDE 51

CMIP5-median LGM minus preindustrial...

familiar runoff responses vary global browning! (Stippling = at least 80% of models agree on sign) more “wetting”, except high lats.

d) PDSI = f(P,PET) change

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SLIDE 52

CMIP5-median LGM minus preindustrial...

familiar runoff responses vary global browning! (Stippling = at least 80% of models agree on sign) more “wetting”, except high lats.

d) PDSI = f(P,PET) change

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SLIDE 53

Does this happen when the real world warms?

  • Yes. At least for the historical anthropogenic warming.
  • And for the glacial-to-interglacial warming (as far as we can tell.)
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SLIDE 54

Does this happen when the real world warms?

  • Yes. At least for the historical anthropogenic warming.
  • And for the glacial-to-interglacial warming (as far as we can tell.)
  • (Quaternary-to-Pliocene warming was also green/wet, but for other reasons.)
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SLIDE 55

So, what to take away from this?

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SLIDE 56

So, what to take away from this?

  • For modern/future climate scientists:
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SLIDE 57

So, what to take away from this?

  • For modern/future climate scientists:
  • Be very careful with words like “wetting” and “drying”
  • Stick to “precipitation increase”, “runoff decrease”, “deep-soil

moisture increase”, “Bowen ratio decrease” unless context is clear...

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SLIDE 58

So, what to take away from this?

  • For modern/future climate scientists:
  • Be very careful with words like “wetting” and “drying”
  • Stick to “precipitation increase”, “runoff decrease”, “deep-soil

moisture increase”, “Bowen ratio decrease” unless context is clear...

  • For both historical and orbital warming, ”drought” & “aridity” indices

were too pessimistic for runoff & especially vegetation impacts.

  • Direct model runoff & vegetation output did much better.
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SLIDE 59

So, what to take away from this?

  • For modern/future climate scientists:
  • Be very careful with words like “wetting” and “drying”
  • Stick to “precipitation increase”, “runoff decrease”, “deep-soil

moisture increase”, “Bowen ratio decrease” unless context is clear...

  • For both historical and orbital warming, ”drought” & “aridity” indices

were too pessimistic for runoff & especially vegetation impacts.

  • Direct model runoff & vegetation output did much better.
  • Indices are perhaps more relevant for fuel moisture/fire, if ~topsoil moisture.
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SLIDE 60

So, what to take away from this?

  • For paleoclimate scientists:
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SLIDE 61

So, what to take away from this?

  • For paleoclimate scientists:
  • Simultaneous greening and hydrological drying is expected in many

places when CO2 rises! And vice versa when CO2 falls

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SLIDE 62

So, what to take away from this?

  • For paleoclimate scientists:
  • Simultaneous greening and hydrological drying is expected in many

places when CO2 rises! And vice versa when CO2 falls

  • e.g. LGM Eastern Mediterranean (brown/wet) is not weird. In fact,

the models explicitly predict it.

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SLIDE 63

So, what to take away from this?

  • For paleoclimate scientists:
  • Simultaneous greening and hydrological drying is expected in many

places when CO2 rises! And vice versa when CO2 falls

  • e.g. LGM Eastern Mediterranean (brown/wet) is not weird. In fact,

the models explicitly predict it.

  • So if you have a veg proxy (e.g. pollen, plant fossils, !13C), it tells you

about vegetation but not necessarily hydrology

  • Likewise if you have a water proxy (e.g. lake level, water isotopes), it

tells you about hydrologic system but not necessarily plants/life

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SLIDE 64

So, what to take away from this?

  • This stuff is particularly a concern for paleoclimate changes

associated with major global-temperature and/or CO2 changes (e.g. deep-time, glacial-interglacial, abrupt.)

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SLIDE 65

So, what to take away from this?

  • This stuff is particularly a concern for paleoclimate changes

associated with major global-temperature and/or CO2 changes (e.g. deep-time, glacial-interglacial, abrupt.)

  • Much less of a concern for e.g. precession, centennial variability.
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SLIDE 66

1951-2010 P trend (mm/yr per decade; IPCC 2013)

Ob Observe ved...

familiar global greening from satellite! (Stippling = trends are significant at 5%) severe “global droughting” 1950-2012 PDSI trend (PDSI per 50yr; Dai and Zhao 2016) runoff responses vary 1949-2012 runoff trend (0.1mm/day per 50yr; Dai and Zhao 2016) 1982-2009 leaf area trend (0.1m2/m2 per decade; Zhu et al 2016)