Effects of diurnal adjustment on biases and trends derived from inter-sensor calibrated AMSU-A data

doi:10.1007/s11707-017-0671-y

Front. Earth Sci.

2018, Vol. 12

Issue (1) : 1-16 https://doi.org/10.1007/s11707-017-0671-y

RESEARCH ARTICLE

Effects of diurnal adjustment on biases and trends derived from inter-sensor calibrated AMSU-A data

H. CHEN¹, X. ZOU²(

), Z. QIN³

¹. Department of Atmospheric and Oceanic Sciences, University of Colorado, Boulder, Colorado, CO 80309, USA
². Earth System Science Interdisciplinary Center (ESSIC), University of Maryland, College Park, Maryland, MD 20742, USA
³. Joint Center for Data Assimilation Research and Applications, Nanjing University of Information Science and Technology, Nanjing 210044, China

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Abstract

Measurements of brightness temperatures from Advanced Microwave Sounding Unit-A (AMSU-A) temperature sounding instruments onboard NOAA Polar-orbiting Operational Environmental Satellites (POES) have been extensively used for studying atmospheric temperature trends over the past several decades. Inter-sensor biases, orbital drifts and diurnal variations of atmospheric and surface temperatures must be considered before using a merged long-term time series of AMSU-A measurements from NOAA-15, -18, -19 and MetOp-A. We study the impacts of the orbital drift and orbital differences of local equator crossing times (LECTs) on temperature trends derivable from AMSU-A using near-nadir observations from NOAA-15, NOAA-18, NOAA-19, and MetOp-A during 1998−2014 over the Amazon rainforest. The double difference method is firstly applied to estimation of inter-sensor biases between any two satellites during their overlapping time period. The inter-calibrated observations are then used to generate a monthly mean diurnal cycle of brightness temperature for each AMSU-A channel. A diurnal correction is finally applied each channel to obtain AMSU-A data valid at the same local time. Impacts of the inter-sensor bias correction and diurnal correction on the AMSU-A derived long-term atmospheric temperature trends are separately quantified and compared with those derived from original data. It is shown that the orbital drift and differences of LECT among different POESs induce a large uncertainty in AMSU-A derived long-term warming/cooling trends. After applying an inter-sensor bias correction and a diurnal correction, the warming trends at different local times, which are approximately the same, are smaller by half than the trends derived without applying these corrections.

Keywords AMSU-A diurnal adjustment decadal temperature trend

Corresponding Author(s): X. ZOU

Just Accepted Date: 25 September 2017 Online First Date: 14 November 2017 Issue Date: 23 January 2018

Cite this article:

H. CHEN,X. ZOU,Z. QIN. Effects of diurnal adjustment on biases and trends derived from inter-sensor calibrated AMSU-A data[J]. Front. Earth Sci., 2018, 12(1): 1-16.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-017-0671-y
https://academic.hep.com.cn/fesci/EN/Y2018/V12/I1/1

Tab.1 The overlapping AMSU-A time periods for paired satellite datasets

Fig.1 Time series of double difference results for (a) channel 1 and (b) channel 5 of AMSU-A onboard NOAA-15 (N15), NOAA-19 (N19), MetOp-A (MOA) paired with AMSU-A onboard NOAA-18 (N18).

Fig.2 Scatter plots of double differences

(O − B) ‾ sat − (O − B) ‾ NOAA − 18

for AMSU-A channels 1 (left panels) and 5 (right panels). The inter-sensor bias

μ D D, ? sat

and one-standard deviation are indicated by red dot and red box, respectively.

Channel	$μ sat$ /K	$σ sat$ /K
1	0.272	0.241
2	0.085	0.162
3	–0.001	0.145
4	–0.121	0.047
5	–0.081	0.027
6	N/A	N/A
7	0.545	0.037
8	0.232	0.048
9	0.736	0.044
10	0.499	0.056
11	N/A	N/A
12	0.408	0.128
13	0.204	0.215
14	N/A	N/A
15	0.303	0.257

Tab.2 The inter-sensor biases for AMSU-A channels 1- 15 (except for channels 6, 11, 14) between NOAA-15 and NOAA-18. The inter-sensor biases between sat and NOAA-18 are estimated by

μ sat = (O − B) ‾ sat − (O − B) ‾ NOAA − 18 ‾

σ sat

is the standard deviation

Channel	$μ sat$ /K	$σ sat$ /K
1	–0.172	0.175
2	–0.231	0.112
3	–0.105	0.121
4	–0.016	0.028
5	–0.162	0.017
6	0.231	0.017
7	0.437	0.041
8	N/A	N/A
9	0.485	0.037
10	0.463	0.039
11	0.502	0.056
12	0.381	0.095
13	0.594	0.147
14	0.218	0.173
15	0.319	0.179

Tab.3 Same as Table 2 except for NOAA-19 and NOAA-18

Channel	$μ sat$ /K	$σ sat$ /K
1	0.165	0.194
2	0.069	0.127
3	–0.041	0.122
4	0.041	0.034
5	–0.034	0.024
6	0.162	0.027
7	N/A	N/A
8	0.205	0.031
9	0.442	0.043
10	0.485	0.050
11	0.459	0.076
12	0.123	0.144
13	–0.651	0.241
14	–0.786	0.329
15	0.367	0.184

Tab.4 Same as Table 3 except for MetOp-A and NOAA-18

Fig.3 Monthly mean of observational local times of multiple AMSU-As near-nadir observations from ascending nodes (solid lines) and descending nodes (dashed lines) over Amazon rainforest during 1998–2014.

Fig.4 Brightness temperature observations from AMSU-A channel 1 on (a) the descending nodes of NOAA-19, NOAA-18, NOAA-15 and MetOp-A which passed over Amazon rainforest around 0141 LT, 0227 LT, 0443 LT and 0949 LT January 1, 2012. AMSU-A FOV center locations are shown in black crosses; (b) the ascending nodes of NOAA-19, NOAA-18, NOAA-15 and MetOp-A over the Amazon rainforest around 1257 LT, 0227 LT, 0443 LT and 0949 LT.

Fig.5 Brightness temperature observations at FOVs 15 and 16 of channels 1, 5, 8 and 10 from NOAA-19, NOAA-18, NOAA-15 and MetOp-A under the “no-rain” conditions over Amazon rainforest in January (open circles) from 1999 to 2013. The monthly mean of near-nadir observations from descending nodes (down triangle) and ascending nodes (up triangle) are used for estimating the Fourier coefficients of the diurnal variation of brightness temperatures (black curve).

Fig.6 Time series of brightness temperature observations of channel 1 from NOAA-15 at its ascending (red, nighttime, early morning) and descending (blue, daytime, later afternoon) nodes (a) without and (b) with a diurnal correction using 1200 LT as reference local time. The linear trend of brightness temperature observations is indicated by black line. Regression equations are added in the upper right corner, the unit of T is day.

Fig.7 Same as Fig. 6 except for channel 5.

Fig.8 Time series of monthly mean brightness temperature observations of NOAA-15 AMSU-A channel 1 (a) without and (b)–(d) with a diurnal correction using a reference local time at (b) 0600 LT, (c) 0900 LT or (d) 1200 LT. The linear trend of brightness temperature observations is indicated by a black line. The data counts are indicated in grey shading. Regression equations are added in the upper right corner, the unit of T is month.

Fig.9 Monthly data counts of NOAA-15 AMSU-A observations under the “no-rain” (grey) and “raining” (red) conditions over Amazon rainforest during the time period from October 1998 to June 2012.

Fig.10 Linear trends of brightness temperatures derived from monthly mean of NOAA-15 AMSU-A channel 1 before (black) and after applying diurnal correction with three different reference local times of 0600 LT (red), 0900 LT (blue), and 1200 LT (green).

Fig.11 Time series of channel 1 near-nadir observations from NOAA-19, NOAA-18, NOAA-15 and MetOp-A (a) without any inter-sensor bias correction nor diurnal correction and with (b) inter-sensor bias correction only (c) with both the inter-sensor bias correction and diurnal correction using a reference time at 1200 LT. The black solid line indicates the linear trend. Regression equations are added in the upper right corner, the unit of T is day.

Fig.12 Decadal linear trends of brightness temperature observations for all AMSU-A channels from (a) NOAA-15 only and (b) NOAA-15, -18, -19 and MetOp-A.

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