[Insert Table 2 here]
2.2.3 Climate data
To investigate the climate impact of lake water level changes, the
annual and monthly precipitation data for the period 1990-2018 from 10
stations in the TP was collected from the China Meteorological Network
(http://data. cma.cn). The locations of the ten stations are shown in
Fig. 1. In addition, we analyzed the changes of water vapor transport
modes over the TP and its surroundings based on ERA-interim reanalysis
data with a spatial resolution of 0.75°×0.75° (Dee et al. 2011). The sea
surface temperature (SST) from the National Oceanic and Atmospheric
Administration was also applied to investigate the association of the TP
lake level changes and precipitation anomalies driven by El Niño and La
Niña events.
2.3 Methods
2.3.1 Altimetry water level
processing
We retrieved important variables such as time, latitude, longitude,
water level elevation, and geoid from the collected raw data files.
Since the parameter information contained in each altimeter satellite is
not completely consistent, the formulas for calculating water level are
also not the same. Thus, this part of the work also needs to refer to
the data manual for each altimeter satellite. We calculated water levels
by the following the formula below (Hwang et al., 2016):
\(H_{\text{water}}=h_{\text{sat}}-R_{\text{alt}}-C\) (1)
where \(H_{\text{water}}\) refers to ellipsoidal height of the
waterbody, \(h_{\text{sat}}\) refers to ellipsoidal height of the
satellite, \(R_{\text{alt}}\) refers to distance between satellite and
waterbody, and \(C\) refers to the integration of all corrections.
Considered corrections include inverted barometer height correction
(\(C_{\text{inv}}\)), wet and dry tropospheric corrections
(\(C_{\text{wet}}\),\(C_{\text{dry}}\)), ionospheric correction
(\(C_{\text{iono}}\)), solid earth tide (\(C_{\text{solid}}\)), ocean
earth tide (\(C_{\text{ocean}}\)), poletide (\(C_{\text{pole}}\)), sea
state bias correction (\(C_{\text{stb}}\)), and high frequency
fluctuations correction (\(C_{\text{hf}}\)).
2.3.2 Removal of measurement
outliers
For all lakes, the original tracks of the satellite are observed as it
passes through the lake, then the track data falling within the lake
will be selected. As the observations contain outliers, it is necessary
to eliminate them for subsequent work. Outlier elimination for the
selected orbit data was divided into two steps.
Step 1: Apply a median filter with a six-month window size to smooth the
original time series during the study period, and remove the outliers
out of two standard deviations from the median for all the measurements.
Step 2: Remove the data other than twice the standard deviation for
single-day measurements.
2.3.3 Unifying the reference system of different altimetry
sources
In order to reduce the differences caused by different altimeter
instruments, all lake levels from multi-source altimetry satellite were
first converted to the same geographic reference system. The system
biases calculated by the data from different altimetry satellites at the
same period was subtracted from the elevation measurements for each lake
(Crétaux et al. 2011a; Jarihani et al. 2013).
3 Results and discussions
3.1 Long-term lake level variations based on Hydroweb and
DAHITI data archives
The
best way of altimetry data validation is to compare the
altimeter-derived lake level with the in situ data. At present, only a
few lakes such as Qinghai Lake and Nam Co have long-term continuous
water level observations in the TP which are extremely limited compared
with more than 1,200 lakes (>1km2) across
the TP (Zhang et al. 2014). The altimetry data archives, such as
Hydroweb and DAHITI, play an critical role in verifying the lake level
changes obtained by other satellite altimetry data. In order to verify
the reliability of Hydroweb and DAHITI altimetry data archives, the
annual means of water level for Qinghai Lake was validated against the
in situ water levels measured by the hydrological station. As shown in
Fig. 2, the altimetry levels follow a robust linear correlation with in
situ measurement, with a R² value of 0.90. This agreement indicates that
the lake level time series obtained from Hydroweb and DAHITI have a high
reliability, and therefore, were used as a reference for validating our
level time series processed from SARAL and Sentinel-3 altimeters.