Temporal and spatial variations in radiation and energy fluxes across Lake Taihu

Transcription

1 Temporal and spatial variations in radiation and energy fluxes across Lake Taihu Wang Wei YNCenter Video Conference May 10, 2012

2 Outline 1. Motivation 2. Hypothesis 3. Methodology 4. Preliminary results 5. Discussion 6. Next steps

3 List of Symbols H: sensible heat flux, LE: latent heat flux, S: heat storage, β: Bowen ratio, λ: latent heat of vaporization, γ: psychrometric constant, C D : drag coefficient, C p : specific heat at constant pressure. T a : air temperature, T s : skin temperature, ΔT= T s T a, RH: relative humidity, U: wind speed, e a : vapor pressure, e s : saturation vapor pressure, Δe= e s e a, ρ v : water vapor density, ρ w : water density, h: water depth. UR: reflected short wave radiation, DR: incident radiation, ULR: upward long wave radiation, DLR: downward long wave radiation, R n : net radiation, α: albedo; ε: emissivity, σ: Stefan Boltzmann constant.

4 Abbreviation EC: Eddy Covariance MET: meteorological EBC: Energy Balance Closure NWP: Numerical Weather Prediction GCMs: Global Climate Models GMR: Geometric Mean Regression IRGA: Infrared Gas Analyzer

5 1. Motivation Lakes, ponds and impoundments cover >3% of Earth s continent (Downing et al., 2006), about 0.9% of China s land area (Ma et al., 2011); The domain averaged H was reduced, LE was enhanced with the inclusion of lakes (Bonan, 1995; Nagarajan et al., 2004); Accurate measurements of lake atmosphere exchanges are imperative for improving NWP and GCMs performance (Herderson Sellers, 1986); Existing models treated lake as a whole bulk, without considering the spatial variations in radiation and energy fluxes (Spence et al., 2011).

6 2. Hypothesis Variations in radiation and energy fluxes exist across Lake Taihu; Behaving different H and LE, lake and land contribution to local heat, moisture source may vary; Local climate changes can result from lake reclamation and lake side enclosure associated with anthropogenic activities.

7 3. Methodology

8 3.1 Experimental sites

9 Sites description Type Site Measurement Data coverage Location Elevation(m) land DS EC, MET gradient, Radiation,Soil Apr.15, 2011~now ' E, 31 04' N 17.5 MLW EC, MET, Radiation,Tw Jun 13, 2010~now ' E, 31 24' N lake DPK EC, MET, Radiation,Tw Aug.17, 2011~now ' E, 31 16' N BFG1 EC, MET, Radiation,Tw Dec.15, 2011~now ' E, 31 10' N Research period: Apr. 16, 2011 to now

10 30min average data De-spike Daily mean ( 40 points) ρ v IRGA correction coefficient Bulk transfer coefficient Filling approach Gap filling MET data Radiation data Tw data Flux data LE correction Monthly mean Results β R n S Adjusting H, LE

11 3.2 Equations involved Energy balance equation Rn S H LE QB QF QP Energy balance closure H LE EBC 100% Rn S Heat storage in water S C w pw h h Tw2 dh2 Tw 1 dh1 h h h h t Skin temperature T s Bowen ratio H LE ULR (1 ) DLR 1 4 (Nordbo et al., 2011)

12 3.3 Bulk mass transfer approach H C C U( T T ) a a D s a aca LE CD U( es ea) (Binyamin et al., 2006)

13 H

14 LE

15 3.4 ρ v IRGA correction by ρ v RH through GMR vrh a virga b w w ( a b) aw vrh virga virga (GMR by Trujillo Ortiz and Hernandez Walls, 2010 )

16

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18 3.5 Adjusting H and LE Lack of EBC results from several complicated reasons (Foken, 2006, 2008); Forcing closure can be done by assuming β is correctly measured by EC and available energy is representative of footprint (Twine et al., 2000) ; The objective is to get accurate H and LE.

19 4. Preliminary results

20 4.1 MET variables

21 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Annual DS T a MLW DPK BFG DS P a MLW kpa DPK BFG DS RH MLW % DPK BFG DS U MLW m.s -1 DPK BFG

22 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Annual DS T s MLW DPK BFG e s MLW kpa DPK BFG DS ΔT MLW DPK BFG Δe MLW kpa DPK BFG

23 4.2 Radiation components

24 UR W.m -2 DR W.m -2 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Annual DS MLW DPK BFG DS MLW DPK BFG DS ULR MLW W.m -2 DPK BFG DS DLR MLW W.m -2 DPK BFG

25 α R n (W.m -2 ) Month DS MLW DPK BFG1 DS MLW DPK BFG1 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Annual

26 4.3 Energy fluxes

27 Heat storage

28 Bowen ratio

29 EBC

30 H adjusted

31 LE adjusted

32 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Annual DS H MLW W.m -2 DPK BFG DS LE MLW W.m -2 DPK BFG DS R n MLW W.m -2 DPK BFG DS S MLW W.m -2 DPK BFG

33 H/(R n S)

34 LE/(R n S)

35 H/(R n -S) LE/(R n -S) DS MLW DPK BFG1 DS MLW DPK BFG1 Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Annual

36 Summary UR, DR, ULR, DLR peaked in Apr., Apr., Jul., Jul., reached the minimum in Feb., Jan., Jan., Dec. respectively; Equal DR, ULR and DLR among four sites; Annual mean UR_MLW 1/3*UR_DS [α_ds 3*α_MLW(0.07)], BFG1 with the highest UR and MLW reflected the lowest among lake sites; Annual mean R n _DS 69%*R n _MLW.

37 Little variations in energy fluxes over lake Taihu; At MLW, the footprint average LE doubled (97%) and H was halved (52%) as compared with DS; Land behaved the major local heat source especially in summer(>70%), lake evaporation contributed >70% of local atmospheric moisture source in winter; About 89% of lake available energy fueled the evaporation loss, 33% of land available energy was used to heating atmosphere; Lake reclamation and lake side enclosure can accelerate (even double) the warming drying trend.

38 5. Discussion The effect of lake land interaction (horizontal transport); Difference in energy fluxes between lake and land when atmospheric conditions vary (clear sky, overcast ); The lake land water cycle; Local warming drying effect of lake reclamation.

39 Measured (mm) Calculated (mm) DS MLW

40 (Ma et al., 2010)

41 6. Next steps Evaluating the uncertainty in H, LE calculation and bias propagating; Investigating the driven forces for UR and energy fluxes spatial variations; Comparison with findings published for lake; Assessing the local climate effect of lake reclamation and lakeside enclosure in China during the past half century.

42 Thank you! Suggestions and questions are welcome.