The influence of tree transmissivity variations in winter on satellite snow parameter observations

Figures & data

Figure 1. The configuration of the radiometer observation experiment (Li et al. 2019).

Figure 2. Time series of snow depth (upper panel) and environmental temperatures (lower panel) in IOA.

Table 1. Estimated parameters, R², and the RMSE of transmissivity model.

	H10	V10	H18	V18	H21	V21	H37	V37
${\mathit{\gamma }}_0(-)$	0.23	0.24	0.18	0.19	0.15	0.14	0.13	0.12
${\mathit{a}}_{\mathit{\gamma }}$ (1/°C)	0.02	0.03	0.02	0.02	0.02	0.02	0.01	0.02

Figure 3. Schematic illustration of the influence of forest biomass on the observation of ground ΔTb.

Figure 4. Schematic illustration of terms in Equation (6).

Figure 5. Radiometer-observed ΔTb of Tb_ground (blue-green-red circle markers) with the (7) simulated results (black solid lines), the blue-green-red bar represents T_air.

Table 2. Estimated parameters, R², and RMSE of Equation (7).

	$\mathit{d}$ (K/cm^2)	$\mathit{e}$ (K/cm)	R^2	RMSE (K)
10-37 V-pol	−0.011	1.64	0.87	6.50
18-37 V-pol	−0.0064	1.18	0.85	6.68

Figure 6. Comparison between ΔTb_RTforest (blue-green-red circle markers) and ΔTb_APPforest which is simulated at $\mathrm{\Delta }T{b}_{fground}$ equal to 10, 20, 30, 40, and 50 K by (4) (lines), the blue-green-red bar represents SD_open.

Table 3. Estimated parameters b_is and c_is, and corresponding R2, and RMSE of (4) against RT model (1) for the model calibration.

	${\mathit{b}}_{\mathit{i}s}$ (1/°C)	${\mathit{c}}_{\mathit{i}s}$ (-)	R^2	RMSE (K)
10-37 V-pol	−0.0073	−0.0071	0.99	0.29
18-37 V-pol	−0.0063	−0.0084	0.99	0.18

Figure 7. Comparison between ΔTb_AMSR (blue-green-red circle markers) and ΔTb_APPsb which is simulated at snow depths equal to 10, 25, 40, 55, and 70 cm (lines), the blue-green-red bar represents SD_AMSR.

Table 4. The estimated parameters b_sb and c_sb, and the corresponding R2, and RMSE of (6) against ΔTb_AMSR during the model calibration with training dataset.

	${\mathit{b}}_{\mathit{s}b}$ (1/°C)	${\mathit{c}}_{\mathit{s}b}$ (-)	R^2	RMSE (K)
10-37 V-pol	−0.019	−0.088	0.85	3.41
18-37 V-pol	−0.014	−0.13	0.75	2.96

Figure 8. ΔTb_APPsbground (blue-green-red circle markers) against T_air, the blue-green-red bar represents SD_AMSR.

Figure 9. Compared ΔTb_APPsbground (blue-green-red circle markers in (a) and (b)) and ΔTb_AMSR (blue-green-red circle markers in (c) and (d)) with the radiometer observed ΔTb of Tb_ground (black cross markers), the blue-green-red bar represents T_air.

Figure 10. Comparison between ΔTb_AMSR (blue-green-red circle markers) and ΔTb_APPsb which is simulated at snow depths equal to 10, 25, 40, 55, and 70 cm (lines), the blue-green-red bar represents SD_AMSR.

Figure 11. Compared ΔTb_APPsbground (blue-green-red circle markers in (a) and (b)) and ΔTb_AMSR (blue-green-red circle markers in (c) and (d)) with the radiometer observed ΔTb of Tb_ground (black cross markers), the blue-green-red bar represents T_air.

Table

Variables of equations	Descriptions	Equation numbers	Measured data	Descriptions
$\uparrow T{b}_{\mathrm{forest}}$	Upwelling emission observed above the forest cover	(1)	Tbground	Radiometer measured ground Tb
$T{b}_{\mathrm{ground}}$	Upwelling ground emission	(1)(2)	↓Tbtree	Radiometer measured downwelling Tb of the specimen tree
$T{b}_{\mathrm{sky}}$	Downwelling sky emission	(1)	Tbsky	Radiometer measured downwelling Tb of the sky
$T$	Air temperature	(1)(3)(4)(6)	TbAMSR	Satellite-observed Tbs
$\gamma$	Transmissivity of the forest	(1)(3)	SDforest	AWS measured snow depth in the forest
$r_{\mathrm{forest}}$	Reflectivity of the forest	(1)	SDopen	AWS measured snow depth in the forest opening
$r_{\mathrm{ground}}$	Reflectivity of the ground	(1)(2)	Tair	The air temperature measured at IOA
$T_{\mathrm{ground}}$	Ground soil temperature	(2)	Tground	The soil temperature measured at IOA
$a_{\gamma }$	Empirical parameter	(3)	Ttree	The measured tree skin temperature
${\gamma }_0$	Mean transmissivity of the forest layer measured when the air temperature is above 0 °C	(3)	Calculated Data	Descriptions
			SDAMSR	The AWS measured snow depth of the AMSR2 footprint (Section 2.2.2, paragraph 1)
$\mathrm{\Delta }T{b}_{\mathrm{forest}}$	ΔTb of the upwelling emission observed above the canopy	(4)(5)	↑TbRTforest	$\uparrow T{b}_{\mathrm{forest}}$ calculated by the equation (1)
$\mathrm{\Delta }T{b}_{\mathrm{fground}}$	ΔTb of the ground emission beneath the forest	(4)	ΔTbRTforest	The ΔTb calculated based on ↑TbRTforest
$b_{is}$	Empirical parameter	(4)	ΔTbAPPforest	$\mathrm{\Delta }T{b}_{\mathrm{forest}}$ estimated by the equation (4)
$c_{is}$	Empirical parameter	(4)	ΔTbAPPsb	the $\mathrm{\Delta }T{b}_{sb}$ estimated by the equation (6)
$\mathrm{\Delta }T{b}_{sb}$	ΔTb of the spaceborne observation	(5)(6)	ΔTbAMSR	the ΔTb of TbAMSR
$\mathrm{\Delta }T{b}_{\mathrm{oground}}$	ΔTb of the ground emission in the forest openings	(5)	ΔTbAPPsbground	$\mathrm{\Delta }T{b}_{\mathrm{sbground}}$ estimated based on the ΔTbAMSR and Tair by the re-arranged equation (6)
$f$	Forest coverage	(5)(6)
$\mathrm{\Delta }T{b}_{\mathrm{sbground}}$	The overall ΔTb of sub-canopy ground emission from the spaceborne AMSR2 observation footprint	(6)
$b_{sb}$	Empirical parameter	(6)
$c_{sb}$	Empirical parameter	(6)
$\mathrm{\Delta }T{b}_{\mathrm{ground}}$	ΔTb of the ground emission	(7)
$SD$	Snow depth	(7)
$c$	Regression coefficient	(7)
$d$	Regression coefficient	(7)

Li, Qinghuan, R. E. J. Kelly, L. Leppanen, J. Vehvilainen, A. Kontu, J. Lemmetyinen, and J. Pulliainen. 2019. “The Influence of Thermal Properties and Canopy-Intercepted Snow on Passive Microwave Transmissivity of a Scots Pine.” IEEE Transactions on Geoscience and Remote Sensing 57 (8). doi:https://doi.org/10.1109/TGRS.2019.2899345.

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