Es#ma#ng the Low La#tude Free Tropospheric Water Vapor Feedback via GPS RO

Transcription

1 Es#ma#ng the Low La#tude Free Tropospheric Water Vapor Feedback via GPS RO E.R Kursinski & A. L. Kursinski Broad Reach Engineering COSMIC Workshop Oct 30- Nov 1, 2012

2 Outline Mo#va#on Approach Comparison of GPS and AIRS humidity ENSO Difference Results Conclusions? 10/31/2012 COSMIC Workshop Kursinski 2

3 The water- vapor feedback is one of the most important in our climate system, which is believed to approximately double the direct warming from greenhouse gas increases [Manabe and Wetherald, 1967; Bony et al., 2006; Randall et al., 2007]. Mo#va#on 10/31/2012 COSMIC Workshop Kursinski 3

4 Approach Dessler et al used AIRS data to es#mate the behavior of atmospheric water vapor and the water- vapor feedback based on ENSO varia#ons in Earth s climate between 2003 and /31/2012 COSMIC Workshop Kursinski&Kursinski 4

5 Feedback Feedback T s = 1/λ R The water vapor feedback represents the enhancement in surface temperature due to water vapor concentra#on increasing in response to radia#ve forcing λ= x,y,z R/ q(x,y,z) q(x,y,z)/ T s Right hand term in sum is measured over ENSO Lea hand term in sum is calculated 10/31/2012 COSMIC Workshop Kursinski 5

6 Status Report We are in the process of making analogous es#mates using COSMIC GPS RO data. Es#mate water vapor from GPS RO via the Simple or Direct method Combine GPS RO refrac#vity data from JPL & Temperature data from ECMWF or NCEP This approach does not use prior humidity from analyses in es#ma#ng water vapor from GPS refrac#vity to avoid NWP model biases 10/31/2012 COSMIC Workshop Kursinski 6

7 Simple Water Vapor Approach Two equa#ons: P (1) Refrac#vity N = a 1 T + a e 2 T 2 (2) Hydrosta#c: P( z i+1 )=P( z i ) ( T i / T i+1 ) m i g i /R T i Given temperature & refrac#vity profiles and water vapor at a star#ng pressure level 1) At the next lower level in the refrac#vity profile, an ini#al guess is made for e(z i+1 ). 2) The average mean molecular mass in the layer is then adjusted based on this value of water vapor. 3) The pressure at z i+1 is then updated via (2). 4) P(z i+1 ) and T(z i+1 ) are used in (1) to update e(z i+1 ). These steps are repeated un#l convergence. 10/31/2012 COSMIC Workshop Kursinski 7

8 GPS RO Al>tude Range & Domain Lower al>tude limit Avoid super- refrac#on problems near PBL top => Focus on free troposphere 725 hpa just above PBL ~2.75 km above surface Upper al>tude limit Can derive accurate water vapor from GPS RO to about the 240 K level 346 hpa is ~9 km about as high as GPS RO WV retrievals work well La#tude range: 30S- 30N so 240 K is an approximately constant al#tude level 10/31/2012 COSMIC Workshop Kursinski 8

9 Moisture Distribu>on Reveal the range of behavior by plopng specific & rela#ve humidity distribu#ons at certain pressure levels In some of the plots that follow, the noise from the GPS measured distribu#on has been deconvolved This removes the nega#ve values while leaving the mean untouched (to avoid biases) It compresses the distribu#on back to something closer to the true distribu#on This also yields es#mates of the errors in the GPS RO moisture, refrac#vity and analysis temperature es#mates 10/31/2012 COSMIC Workshop Kursinski 9

10 Deconvolu#on Example: 346 hpa Specific Humidity c 10/31/2012 COSMIC Workshop Kursinski 10

11 Deconvolu#on Example: 547 hpa Specific Humidity c 10/31/2012 COSMIC Workshop Kursinski 11

12 Deconvolu#on Example: 725 hpa Specific Humidity c 10/31/2012 COSMIC Workshop Kursinski 12

13 Es>ma>ng GPS Water Vapor Error Es#mate water vapor error from nega#ve tail of distribu#on Deconvolved distribu#on represented as Gaussian + exponen#al distribu#ons Resul#ng errors somewhat smaller than those of Kursinski & Hajj 2001 Presumably because temperature & refrac#vity errors are smaller Best fit error shape Kursinski & Hajj 01stdev of error Deconvolu>on: 346 mb 547 mb 725 mb Gauss. Expon. Gauss. Expon. Gauss. Expon. 80% 20% 90% 10% 94% 6% 0.24 g/kg 0.31 g/kg 0.47 g/kg stdev of error 0.14 g/kg 0.20 g/kg 0.26 g/kg Kursinski & Hajj: est. error contribu>ons Deconvolu>on: Likely error contribu>ons N T P ref N T P ref N T P ref error error error error error error error error error 0.2% 1.5 K 0.3% 0.5% 1.5 K 0.3% 0.9% 1.5 K 0.3% 0.2% 0.9 K 0.15% 0.42% 0.9 K 0.15% 0.62% 0.9 K 0.15% 10/31/2012 COSMIC Workshop Kursinski 13

14 Comparisons of GPS & AIRS Distribu>ons 10/31/2012 COSMIC Workshop Kursinski 14

15 346 hpa Specific Humidity Annual c 10/31/2012 COSMIC Workshop Kursinski 15

16 547 hpa Specific Humidity c 10/31/2012 COSMIC Workshop Kursinski 16

17 547 hpa Specific Humidity c Analyses don t like dry air 10/31/2012 COSMIC Workshop Kursinski 17

18 GPS v. AIRS: 725 hpa Specific Humidity AIRS underes#mates low & high ends of distribu#on 10/31/2012 COSMIC Workshop Kursinski 18

19 General tendency for GPS RO to observe more very dry and wet air than AIRS and global analyses Now, divide 30S- 30N la#tude interval into 6 bands to berer understand the distribu#on 10/31/2012 COSMIC Workshop Kursinski 19

20 GPS 725 hpa Specific Humidity c Asymmetry: Northern Hemisphere werer Southern Hemisphere drier 10/31/2012 COSMIC Workshop Kursinski 20

21 GPS 725 hpa Rela>ve Humidity 10/31/2012 COSMIC Workshop Kursinski 21

22 AIRS 725 hpa Rela#ve Humidity 10/31/2012 COSMIC Workshop Kursinski 22

23 725 hpa RH Equator to 10N 10/31/2012 COSMIC Workshop Kursinski 23

24 725 hpa Specific Humidity 30S- 20S 10/31/2012 COSMIC Workshop Kursinski 24

25 Quick Summary GPS RO observes higher percentage of extremely high and low moisture than AIRS, despite long horizontal averaging interval Very dry air is gepng to top of PBL, par#cularly in southern subtropics 10S- 10N is principal interval of rising air Lirle of the very dry air is gepng down to 725 hpa in 10S- 10N (despite Walker circula#on) 10/31/2012 COSMIC Workshop Kursinski 25

26 Es>ma>ng the Water Vapor Feedback To es#mate the water vapor feedback observa#onally, one must measure the water vapor varia#ons as the surface temperature varies An obvious choice is to examine varia#ons over the ENSO cycle Not without problems since the warm phase of ENSO, El Nino, is the warm phase of an oscilla#on, not a warm secular change Dessler et al. (2008) es#mated the water vapor feedback examining ENSO varia#ons in AIRS temperature and water vapor data spanning We now have 6 years of COSMIC GPS data from /31/2012 COSMIC Workshop Kursinski 26 to present

27 ENSO Index during AIRS & COSMIC Era ENSO MEI Year DJF JFM FMA MAM AMJ MJJ JJA JAS ASO SON OND NDJ /31/2012 COSMIC Workshop Kursinski 27

28 Free Tropospheric Water Vapor Changes over ENSO Looked previously at free tropospheric precipitable water vapor between El Nino and La Nina Overall, the mean of the water vapor does increase in the warm ENSO phase by mm But, the median was nega+ve and the areal extent of the dry air increased 10/31/2012 COSMIC Workshop Kursinski 28

29 ΔPW free trop vs ΔSST DATA: Warm - Cold ASO thru MAM Each point is a 1º zonal mean Median ΔPW free trop = mm For more than half of the zonal mean points, the PW free trop decreases with the warm phase SST increase Mean ΔPW free trop /ΔSST = 0.065mm/0.28C = 0.24 mm/c Mean frac#onal ΔPW free trop /ΔSST = 3.3%/C < Sat. Vap.(T) October 31, 2012 COSMIC

30 Driest air PDFs Jan 2007 minus 2008 El Nino La Nina March 5, 2009 NCAR

31 ENSO Circula>on Change dpw/dlat slope steeper in El Nino => faster overturning circula#on Physics: overturning circula#on slower in a warmer climate ENSO oscillates => nega#ve feedback: Warm ENSO cools more rapidly Not clear how good ENSO is for es#ma#ng the WV feedback 10/31/2012 COSMIC Workshop Kursinski 31

32 Warm vs Cold Phase differences c 10/31/2012 COSMIC Workshop Kursinski 32

33 Warm vs Cold Phase differences C 10/31/2012 COSMIC Workshop Kursinski 33

34 Es#mate Water Vapor Feedback Frac#onal Change in specific humidity DJF minus (Dessler et al., 2008) 10/31/2012 COSMIC Workshop Kursinski 34

35 GPS vs AIRS Frac>onal Δq vs. Al>tude DJF minus DJF in % AIRS Similar overall parerns AIRS is muted by x2-3 rela#ve GPS 10/31/2012 COSMIC Workshop Kursinski 35 to GPS (which is up to 30%)

36 GPS v. AIRS Profiles of Low La>tude <Δq> Rapid increase in q with al#tude GPS sees much smaller increase GPS sees larger increase below 670 hpa 10/31/2012 COSMIC Workshop Kursinski 36

37 Specific Humidity Changes Above 400 hpa level: GPS and AIRS see rapid increase with al#tude At 425 hpa: GPS minimum +0.2% vs. AIRS 4% Above 675 hpa: Δq measured by GPS is less posi#ve than AIRS Just above PBL: GPS sees 50% larger posi#ve delta 10/31/2012 COSMIC Workshop Kursinski 37

38 AIRS Rela#ve Humidity DJF07- DJF08 c 10/31/2012 COSMIC Workshop Kursinski 38

39 GPS vs AIRS Frac>onal ΔRH vs. Al>tude DJF minus DJF in % AIRS GPS 725 Similar parerns 10/31/2012 COSMIC Workshop Kursinski 39 GPS is larger by x2-3

40 Preliminary Conclusions GPS RO sees more water vapor varia#on than AIRS Higher percentage of extremely wet and dry air based on histograms GPS RO sees more change over ENSO cycle than AIRS Next step in WV feedback es#ma#on is to do the radia#ve kernel calcula#ons 10/31/2012 COSMIC Workshop Kursinski 40

41 Addi>onal Thoughts My guess: Water vapor feedback results will be similar to AIRS, despite much larger moisture varia#ons observed by GPS RO Reason is linear behavior assump#on built into the WV feedback approach Real world radia#ve response is not linear Changes in RH in regions of high RH will change cloud behavior and may not produce much radia#ve influence directly via water vapor Changes in humidity in dry regions will have direct water vapor radia#ve impact 10/31/2012 COSMIC Workshop Kursinski 41

42 PWV FT vs. OLR for 07DJF - 08DJF DJF + Zonally Averaged + Water Vapor - DJF Warm 2007 DJF Cold PWV FT OLR Warm 2007 DJF OLR 2 Latitude OLR 250 OLR Cold 2008 DJF July 1, LASP 0 2 latitude

43 Future Look at the rela#on between changes in humidity, the clouds and the OLR over the ENSO cycle 10/31/2012 COSMIC Workshop Kursinski 43