Monday 25/01/2016

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Fig. 1: The LH flux anomaly time series over the global ocean and central eastern Pacific (20oN-20oS, 210oE-282oE from different data sets.
from OAFLUX between two periods (2001-2008 minus 1986-2000). It shows mean negative trend over the central Eastern Pacific. The solid black box over the eastern Pacific is from 20oN-20oS and 210oE to the west coast of Central America marked by Liu et al [2015]. The dashed box is from 8oN-8oS and 220oE to the west coast of Central America where there are 27 buoy stations in it.



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Fig. 2: (a) is monthly buoy data points over central eastern Pacific. (b) is the composite LH flux anomaly from buoys. (c) is the LH flux anomaly time series from different data sets. The period means (1986-2000 and 2001-2008) are displayed in the plaot as well.



Monday 18/01/2016

New plots

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Fig. 1: The is LH flux difference from OAFLUX between two periods (2001-2008 minus 1986-2000). It shows mean negative trend over the central Eastern Pacific. The solid black box over the eastern Pacific is from 20oN-20oS and 210oE to the west coast of Central America marked by Liu et al [2015]. The dashed box is from 8oN-8oS and 220oE to the west coast of Central America where there are 27 buoy stations in it.



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Fig. 2: Since data recorded at each buoy station have breaks and different starting time, we build a composite time series over the eastern Pacific (over the dashed box). The data are simply the mean of all stations in the box.



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Fig. 3: Anomaly time series at each of 27 buoy stations in the dashed box of central Eastern Pacific.



Wednesday 13/01/2016

Surface tubulent flux comparison with buoy data

1. Introduction

After reconstruction of TOA (top of atmosphere) radiation fluxes (FT) [Allan et al. 2014], the surface net energy fluxes are estimated by Liu et al. [2015] combining FT and the atmospheric energy transport (divergence) from ERA-Interim atmospheric reanalysis [Dee et al. 2011; Berrisford et al. 2011] (hereafter ERAINT).

The estimated surface fluxes need to be cross checked with other data sets derived using different methods, particularly with "observations", such as flux data from object analysis (OAFLUX [Yu et al ????]) and buoy stations.

This study focus on the turbulent flux comparison and it includes two parts:

2. Data


3. Results

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Fig. 1: Spatial distribution of (a) correlation coefficient, (b) bias and (c) RMSE. They are all calculated from turbulent flux anomalies between WB and OAFLUX.



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Fig. 2: Statistics of comparisons of turbulent fluxes between WB, WA, OAFLUX and buoy stations.



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Fig. 3: Scatter plot of turbulent flux anomalies. The anomalies are collections of individual anomaly time series from each buoy stations.



3.1 RMSE at buoy stations



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Fig. 4: (a) TAO buoy station locations, (b) RMSE (between OAFLUX and buoy data), (c) RMSE (between WB and buoy data), (d) RMSE (between WA and buoy data).



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Fig. 5: As Fig. 4, but for RAMA data in Indian Ocean.



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Fig. 6: As Fig 4, but for PIRATA data in central Atlantic.



3.2 Variability


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Fig. 7: Top row is the anomaly time series at three buoy stations, and the lower row is their corresponding scatter plot.



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Fig. 8: Area mean turbulent flux anomaly time series.


Table 2: Correlation coeffcients between WB, WA, OAFLUX and buoy station data.
Area
Number of buoy stations
WB
WA
OAFLUX
F
12
0.61
0.51
0.28
G
21
0.43
0.42
0.44
H
15
0.40
0.36
0.34
K
5
0.22
0.24
0.19

4. Conclusions

Through the comparison with observations, though there are systematic biases between our estimates and observations, there are very good correlations in the variability. The effect of total column water vapor content correction on the derived products is small.