Updates of Moderate Resolution Imaging Spectroradiometer on-orbit calibration uncertainty assessments

Xiaoxiong Xiong; Amit Angal; William L. Barnes; Hongda Chen; Vincent Chiang; Xu Geng; Yonghong Li; Kevin Twedt; Zhipeng Wang; Truman Wilson; Aisheng Wu

doi:10.1117/1.JRS.12.034001

16 July 2018 Updates of Moderate Resolution Imaging Spectroradiometer on-orbit calibration uncertainty assessments

Xiaoxiong Xiong, Amit Angal, William L. Barnes, Hongda Chen, Vincent Chiang, Xu Geng, Yonghong Li, Kevin Twedt, Zhipeng Wang, Truman Wilson, Aisheng Wu

Author Affiliations +

Journal of Applied Remote Sensing, Vol. 12, Issue 3, 034001 (July 2018). https://doi.org/10.1117/1.JRS.12.034001

Abstract

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments have successfully operated for more than 18 and 16 years, respectively, on-board the NASA’s Earth Observing System Terra and Aqua spacecraft. Both Terra and Aqua MODIS have significantly contributed to the advance of global Earth remote sensing applications with a broad range of science products that have been continuously produced since the beginning of each mission and freely distributed to users worldwide. MODIS collects data in 20 reflective solar bands (RSB) and 16 thermal emissive bands (TEB), covering wavelengths from 0.41 to 14.4 μm. Its level 1B (L1B) data products, which provide the input for the MODIS high-level science products, include the top of the atmosphere reflectance factors for the RSB, radiances for both the RSB and TEB, and associated uncertainty indices (UI) at a pixel-by-pixel level. This paper provides a brief review of MODIS L1B calibration algorithms, including a number of improvements made in recent years. It presents an update of sensor calibration uncertainty assessments with a focus on several new contributors resulting from on-orbit changes in sensor characteristics, approaches developed to address these changes, and the impact due to on-orbit changes on the L1B data quality. Also discussed are remaining challenges and potential improvements to be made to continuously maintain sensor calibration and data quality, particularly those related to the quality of MODIS L1B uncertainty.

1. Introduction

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of the key instruments for the NASA Earth Observing System (EOS) Terra and Aqua missions that have operated successfully for more than 18 and 16 years since their launches in December 1999 and May 2002, respectively.¹^–⁴ MODIS is a scanning radiometer that collects data in 36 spectral bands, covering wavelengths from visible to long-wave infrared, and at three spatial resolutions (nadir): 250 m (bands 1 to 2), 500 m (bands 3 to 7), and 1 km (bands 8 to 36). It was developed and designed with significant advancements over its heritage sensors, such as the advanced very high resolution radiometer (AVHRR) and the Landsat Thematic Mapper (TM). Methodologies and strategies developed and lessons learned from MODIS design, prelaunch testing, and on-orbit operation and calibration have greatly benefited the development of many follow-on Earth-observing sensors, including the S-NPP and Joint Polar Satellite System visible infrared imaging radiometer suite (VIIRS) instruments and the Landsat-8 operational land imager.⁵^–⁸

Over the course of their entire missions, both Terra and Aqua MODIS instruments have generated an unprecedented amount of data products that are openly distributed to the science community and users worldwide, enabling and supporting a broad range of studies of the Earth’s system that include the short- and long-term changes in its key environmental parameters.⁹^,¹⁰ The quality and calibration uncertainty of MODIS level 1B (L1B) data products are extremely important as they provide key input for generating the high-level science products. The MODIS L1B data products include top of the atmosphere reflectance factors for the reflective solar bands (RSB), radiances for both the RSB and thermal emissive bands (TEB), and the associated uncertainty indices (UI) on a pixel-by-pixel level.¹¹^–¹³

MODIS 36 spectral bands, consisting of a total of 490 individual detectors, are distributed on four focal plane assemblies (FPAs) according to their wavelengths, as shown in Fig. 1: visible (VIS), near-infrared (NIR), short- and midwave infrared (SWIR/MWIR or SMIR), and long-wave infrared (LWIR). The SMIR and LWIR FPAs are nominally controlled at 83 K, thus referred to as the cold FPAs. Bands 1 to 19 and 26 are the RSB, covering wavelengths from 0.41 to $2.3 μ m$ , and bands 20 to 25 and 27 to 36 are the TEB, covering wavelengths from 3.75 to $14.4 μ m$ . Table 1 is a summary of key design parameters of MODIS spectral bands, including their bandwidths, typical spectral radiances, required signal-to-noise ratios (SNRs) or noise equivalent temperature differences at typical radiances, and their primary applications. In addition to extensive prelaunch testing and measurements made to assess instrument performance, MODIS spectral bands are regularly calibrated and characterized on-orbit by a set of on-board calibrators (OBCs). As shown in Fig. 2, MODIS OBCs include a solar diffuser (SD), a solar diffuser stability monitor (SDSM), a blackbody (BB), a spectroradiometric calibration assembly, and a space view (SV) port.

Fig. 1

MODIS FPAs: VIS, NIR, SWIR/MWIR, and LWIR.

Table 1

Key design parameters of MODIS spectral bands.

Primary Use	Banda	Bandwidth (nm)	Spectral radianceb	Required SNR	Primary use	Banda	Bandwidth (nm)	Spectral radianceb	Required NEΔT (K)
Land/cloud/aerosols boundaries	1	620 to 670	21.8	128	Surface/cloud temperature	20	3.660 to 3.840	0.45 (300K)	0.05
Land/cloud/aerosols boundaries	2	841 to 876	24.7	201		21	3.929 to 3.989	2.38 (335K)	0.2
Land/cloud/aerosols properties	3	459 to 479	35.3	243		22	3.929 to 3.989	0.67 (300K)	0.07
	4	545 to 565	29	228		23	4.020 to 4.080	0.79 (300K)	0.07
	5	1230 to 1250	5.4	74	Atmospheric temperature	24	4.433 to 4.498	0.17 (250K)	0.25
	6	1628 to 1652	7.3	275	Atmospheric temperature	25	4.482 to 4.549	0.59 (275K)	0.25
	7	2105 to 2155	1	110	Cirrus clouds water vapor	26	1.360 to 1.390	6	150 (SNR)
Ocean color/ phytoplan kton/ biogeochemistry	8	405 to 420	44.9	880		27	6.535 to 6.895	1.16 (240K)	0.25
	9	438 to 448	41.9	838		28	7.175 to 7.475	2.18 (250K)	0.25
	10	483 to 493	32.1	802	Cloud properties	29	8.400 to 8.700	9.58 (300K)	0.05
	11	526 to 536	27.9	754	Ozone	30	9.580 to 9.880	3.69 (250K)	0.25
	12	546 to 556	21	750	Surface/cloud temperature	31	10.780 to 11.280	9.55 (300K)	0.05
	13	662 to 672	9.5	910	Surface/cloud temperature	32	11.770 to 12.270	8.94 (300K)	0.05
	14	673 to 683	8.7	1087	Cloud top altitude	33	13.185 to 13.485	4.52 (260K)	0.25
	15	743 to 753	10.2	586		34	13.485 to 13.785	3.76 (250K)	0.25
	16	862 to 877	6.2	516		35	13.785 to 14.085	3.11 (240K)	0.25
Atmospheric water vapor	17	890 to 920	10	167		36	14.085 to 14.385	2.08 (220K)	0.35
	18	931 to 941	3.6	57
	19	915 to 965	15	250

^aSpatial resolution: 250 m (B1 to 2), 500 m (B3 to 7), 1000 m (B8 to 36).

^bSpectral radiance unit: W/m2 μm sr.

Fig. 2

MODIS instrument scan cavity showing the location of key OBC and optical components.

MODIS radiometric calibration uncertainty requirements are 2% in reflectance and 5% in radiance for the RSB and 1% in radiance for the TEB, with exceptions of 0.5% for surface temperature spectral bands 31 and 32 at 11 and $12 μ m$ , 0.75% for band 20 at $3.75 μ m$ , and 10% for band 21 (used for fire detection) at $3.95 μ m$ . These requirements are specified at typical scene radiance levels of individual spectral bands and for the observations made at scan angles within $\pm 45 \deg$ . At other radiances between 0.3 typical radiance (0.3 $L_{typ}$ ) and 0.9 maximum radiance (0.9 $L_{\max}$ ), an additional 1% uncertainty is added to those specified at the typical radiance levels.¹⁴

MODIS RSB and TEB calibration uncertainty algorithms were reported previously in a number of Refs. 15 16.–17. Since then a number of updates have been made due to changes in sensor on-orbit performance and improvements of calibration algorithms. As expected, the calibration uncertainty is scene dependent. It is described in MODIS L1B by an uncertainty index (UI) at a pixel-by-pixel level. The UI in the L1B uncertainty product holds eight-bit unsigned integers. The four least significant bits of these integers are currently effective, with UI values ranging from 0 to 15. The other four bits are reserved for future use. Each UI value represents an interval of uncertainty values that cover the estimated uncertainty. A log scaling is used to convert the calculated uncertainty to UI in the L1B processing to allow a broad range of uncertainty to be covered while an adequate resolution for small uncertainties is still retained. To convert the UI back to the percentage uncertainty, the required parameters are provided for L1B users in the attributes associated with each UI dataset.¹¹^,¹²

Before collection 6, the UI had only a few time-dependent terms and most contributors were determined from prelaunch measurements or estimates. Starting from C6, RSB response versus scan-angle (RVS) characterization has included the use of pseudoinvariant ground targets to track changes in sensor responses at multiple angles of incidence (AOIs). Application of a detector-dependent RVS is also made to several VIS spectral bands. These, coupled with other changes made in C6, led to modifications of MODIS L1B uncertainty estimates and therefore the L1B uncertainty product. Similar to RSB calibration coefficients, several time-dependent look-up tables (LUTs) are now provided as the input for generating the L1B uncertainty product.

This paper provides an overview of MODIS on-orbit calibration and uncertainty algorithms and the latest updates resulting from changes in sensor characteristics, such as RVS for the RSB and electronic crosstalk for the long-wave TEB. It serves as an update to our previous references on MODIS calibration uncertainties, including key contributors to the current L1B uncertainty product and strategies developed to implement the changes in the L1B algorithm for its uncertainty estimation. Remaining challenges and future improvements that have impact on the quality of MODIS L1B uncertainty product are also discussed in this paper. Like its calibration algorithms, the MODIS L1B calibration uncertainty approach has also been applied to other Earth-observing sensors, including its follow-on VIIRS instruments.¹⁸^,¹⁹

2. Calibration Algorithms

MODIS RSB on-orbit calibration is reflectance based using an on-board SD panel with its bidirectional reflectance factor (BRF) determined prelaunch by the instrument vendor with traceability to the NIST reflectance standard.²⁰ For a given Earth view (EV) pixel, the calibration is performed for each band, detector, subsample, and mirror side. The MODIS L1B primary deliverable product for the RSB is the EV reflectance factor that can be expressed as

Eq. (1)

ρ_{EV} \cos (θ_{EV}) = m_{1} d n_{EV}^{*} d_{ES_EV}^{2} / {RVS}_{EV},

where

ρ_{EV}

is the EV scene BRF,

θ_{EV}

is the EV solar illumination angle,

d {n^{*}}_{EV}

is the EV digital response corrected for background and instrument temperature,

d_{ES_EV}

is the Earth–Sun distance at the time of the EV measurement in astronomical units (AU),

{RVS}_{EV}

is the RVS angle at the EV AOI, and

m_{1}

is the calibration coefficient for the reflectance factor that is determined from SD calibration

Eq. (2)

m_{1} = \frac{ρ_{SD} \cos (θ_{SD})}{d n_{SD}^{*} \cdot d_{ES_SD}^{2}} \cdot Γ_{SDS} \cdot Δ_{SD},

where

ρ_{SD}

is the SD BRF determined from prelaunch measurements,

θ_{SD}

is the SD solar illumination angle,

d {n^{*}}_{SD}

is the SD digital response corrected for background and instrumental temperature,

d_{ES_SD}

is the Earth–Sun distance at the time of the SD measurement in AU,

Δ_{SD}

is SD BRF on-orbit degradation determined by the SDSM, and

Γ_{SDS}

is the SDS vignetting function used for calibration of the high gain bands (B8-16). Specifically, the corrected digital responses in Eqs. (1) and (2) can be expressed as

Eq. (3)

d n_{EV}^{*} = d n_{EV} [1 + k_{INST} (T_{INST_EV} - T_{INST_REF})]

and

Eq. (4)

d n_{SD}^{*} = d n_{SD} [1 + k_{INST} (T_{INST_SD} - T_{INST_REF})],

where

d n_{EV}

and

d n_{SD}

are the EV and SD view responses with the background SV response (averaged over the frames within a scan) subtracted,

k_{INST}

is an instrument temperature correction coefficient determined prelaunch,

T_{INST_EV}

and

T_{INST_SD}

are the instrument temperatures at the time of EV and SD observations, and

T_{INST_REF}

is the reference temperature. The calibration coefficients are determined off-line and updated as necessary to the L1B calibration algorithms via LUTs.

The RVS is normalized at the AOI of the SD—the primary calibration target for the RSB. For other AOIs, the RVS was measured prelaunch and is updated on orbit. The RVS on-orbit variation at the AOI of the SV is tracked by comparing the results of near-monthly lunar calibration events to the results from the SD calibration events. In practice, the inverse of the corrected digital signal from the moon is calculated for each lunar calibration event and then normalized to the mission start value to determine the on-orbit change, $m_{1}^{moon, oo}$ . This is divided from the on-orbit change in the SD, $m_{1}^{oo}$ , to get the on-orbit change in the RVS

Eq. (5)

{RVS}_{SV} = {RVS}_{SV, prl} \frac{m_{1}^{oo}}{m_{1}^{moon, oo}},

where

{RVS}_{SV, prl}

is the prelaunch RVS at the SV AOI.

For most RSB, the RVS on-orbit variation at other AOI is derived using the SD and lunar data and assumes a linear AOI dependence. This approach works well at the mission beginning and for spectral bands with small on-orbit changes in their responses. However, after many years of on-orbit operations, there was sufficient evidence to suggest that the linear approximation used to track the on-orbit variation in the RVS might be inadequate, especially for the VIS bands that have experienced large on-orbit changes in their responses. In addition, the SD has experienced significant degradation in the VIS wavelengths that might lead to an inaccurate estimation of the gain at the SD AOI. However, the moon, being an extremely stable calibration target, is still considered a reliable source for tracking the gain at the SV AOI and nearby scan angles. To overcome the limitations mentioned above, a new RVS approach, that includes the use of pseudoinvariant EV targets, was developed and implemented starting from C6.¹³ This approach uses lunar measurements and response trending from pseudoinvariant desert targets at multiple AOIs. The combination of $m_{1}$ and RVS derived using this approach is currently applied in both C6 and C6.1 for Terra bands 1 to 4 and 8 to 10 and Aqua bands 1 to 4, 8, and 9, respectively. In this case, we can write

Eq. (6)

\frac{m_{1}}{{RVS}_{EV}} = (\frac{m_{1} (t_{0})}{{RVS}_{EV, prelaunch}}) {(\frac{m_{1}}{{RVS}_{EV}})}_{on-orbit},

where

{(\frac{m_{1}}{{RVS}_{EV}})}_{on-orbit}

is normalized to 1 at the time when the instrument nadir door was first opened.

MODIS TEB are calibrated on-orbit using an on-board BB. The calibration is performed on a scan-by-scan basis via a quadratic algorithm. The MODIS L1B deliverable product for the TEB is the EV radiance $L_{EV}$ given by the following equation:

Eq. (7)

{RVS}_{EV} \cdot L_{EV} + ({RVS}_{SV} - {RVS}_{EV}) \cdot L_{SM} = a_{0} + b_{1} \cdot d n_{EV} + a_{2} \cdot d n_{EV}^{2},

where

L_{SM}

is the radiance due to scan mirror (SM) emission,

{RVS}_{EV}

and

{RVS}_{SV}

are the system RVS angles at the EV and SV. The EV digital response

{dn}_{EV}

is corrected for the instrument background using the sensor’s SV response. The offset and quadratic calibration coefficients (

a_{0}

and

a_{2}

) are determined from BB warm-up and cool-down, whereas the linear coefficient (

b_{1}

) is computed each scan using the sensor’s response to the BB

Eq. (8)

{RVS}_{BB} \cdot ϵ_{BB} \cdot L_{BB} + ({RVS}_{SV} - {RVS}_{BB}) \cdot L_{SM} + {RVS}_{BB} \cdot (1 - ϵ_{BB}) \cdot ϵ_{CAV} \cdot L_{CAV} = a_{0} + b_{1} \cdot d n_{BB} + a_{2} \cdot d n_{BB}^{2},

where

L_{BB}

and

L_{CAV}

are the BB and scan cavity (CAV) radiances and

ϵ_{BB}

and

ϵ_{CAV}

are their emissivities.

{RVS}_{BB}

is the system RVS at the BB view. The sensor’s response to BB,

d n_{BB}

, is also corrected for the instrument background. Equations (7) and (8) are nearly identical except a cavity term included in the BB calibration equation. This is due to the scan cavity emission (

L_{CAV}

) reflected from the BB surface with an equivalent reflectivity of

1 - ϵ_{BB}

. In MODIS TEB calibration, the entire RVS curve is normalized to the BB view at an angle of incidence of 26.5 deg. The calibration is band, detector, and mirror side dependent. The radiance terms in the calibration equations (

L_{BB}

,

L_{SM}

, and

L_{CAV}

) are computed using Planck’s equation weighted over each detector’s relative spectral response at their corresponding temperatures. The BB, SM, and instrument cavity temperatures are provided in the instrument telemetry records.

Details of Terra and Aqua MODIS RSB and TEB calibration algorithms can be found in a number of Refs. 21 22.23.–24. In addition to the baseline algorithms described above, MODIS RSB calibration has included a correction to mitigate the impact due to a thermal leak and electronic crosstalk in the SWIR bands 5 to 7 and 26.²⁵ For the TEB, an optical leak correction is applied for Terra MODIS photoconductive (PC) bands 32 to 36 from the beginning of its mission,²² and, recently, an electronic crosstalk correction is also applied to its photovoltaic (PV) bands 27to 30.²⁶ Band 21 is used for fire detection with a low gain setting, and its on-orbit calibration is performed with fixed linear gain provided in the calibration LUTs.

3. Reflective Solar Bands Calibration Uncertainty

Combining Eqs. (1)–(4), the EV reflectance factor at the SD AOI can be written as

Eq. (9)

{[ρ_{EV} \cos (θ_{EV})]}_{SD} = ρ_{SD} \cos (θ_{SD}) Γ_{SD S} Δ_{SD} \frac{d n_{EV} d_{ES, EV}^{2} [1 + k_{inst} (T_{I N ST_EV} - T_{I N ST_REF})] {RVS}_{SD}}{d n_{SD} d_{ES, SD}^{2} [1 + k_{inst} (T_{I N ST_SD} - T_{I N ST_REF})] {RVS}_{EV}} .

Therefore, the total uncertainty of the reflectance factor at the SD AOI can be written as the root mean square (RMS) summation of the uncertainty associated with the parameters on the right-hand side of Eq. (9)

Eq. (10)

{[\frac{δ ρ_{EV} \cos (θ_{EV})}{ρ_{EV} \cos (θ_{EV})}]}_{SD}^{2} = {[\frac{δ ρ_{SD}}{ρ_{SD}}]}^{2} + {[\frac{δ Γ_{SD S}}{Γ_{SD S}}]}^{2} + {[\frac{δ Δ_{SD}}{Δ_{SD}}]}^{2} + {[\frac{δ d n_{SD}}{d n_{SD}}]}^{2} + {[\frac{δ d n_{EV}}{d n_{EV}}]}^{2} + {[\frac{δ {RVS}_{EV}}{{RVS}_{EV}}]}^{2} + {[δ k_{inst} (T_{INST_EV} - T_{INST_SD})]}^{2} + {[k_{inst} δ (T_{INST_EV} - T_{INST_SD})]}^{2},

where the terms related to Earth–Sun distance and SD solar illumination angle have negligible contributions to the uncertainty and therefore have been dropped. Also ignored in Eq. (8) is the

{RVS}_{SD}

term as RSB RVS is normalized to the SD AOI. The covariance terms are all expected to be small and are not considered here.

The dominant contributor to the RSB calibration uncertainty is related to the SD BRF uncertainty that includes its characterization uncertainty determined from prelaunch measurements and that from on-orbit calibration and characterization. Table 2 shows a summary of uncertainty elements related to SD calibration. The first 6 terms in Table 2 are the uncertainties derived from prelaunch BRF characterization. On-orbit SD uncertainty contributors include items 7 to 9. Items 10 to 12 are related to the stray light and Earthshine elements that could also impact the on-orbit SD calibration. The second column of Table 2 has listed original uncertainty elements (error sources) reported by the instrument vendor (SBRS). Based on the independent uncertainty analysis performed by the MODIS Characterization Support Team (MCST), we increased the SD screen uncertainty term (item 8) from 0.2% to 0.5%. This adjustment was made due to the fact that no prelaunch characterization was made for the SD screen transmittance (or vignetting function $Γ_{SDS}$ ). This term only applies to the bands that are calibrated with the SDS in place. We have also combined the stray light term with the Earthshine term as their contributions are always in the same direction. The magnitude of Earthshine related uncertainty used in the MCST uncertainty analysis is strongly wavelength dependent. As MODIS SD calibration is performed when the instrument is on the dark side of the terminator, we have dropped the term related to the Earthshine through the EV nadir aperture door (0.1%). Based on our on-orbit characterization of SD BRF and how the SD panel is used in RSB calibration, we believe that the SD uniformity impact on the calibration uncertainty is smaller than prelaunch assessment. Additional information on the uncertainty elements listed in Table 2 can be found in these Refs. 27 and 28. Note that the first term on the right-hand side of Eq. (10) includes the combined uncertainty of all elements in the second column of Table 2, in addition to the band-dependent Earthshine uncertainty.

Table 2

Summary of MODIS solar diffuser characterization uncertainty elements (k=1).

	Error sources	SBRS	MCST (I)	MCST (II)
1	NIST reference:	0.50	0.50
2	SBRS scattering goniometer:	0.70	0.70
3	NIST BRF scale to MODIS SD reference:	0.50	0.50
4	MODIS SD characterization:	0.50	0.50
5	SD spatial non-uniformities:	0.70	0.35
6	Interpolation angular / spectrally:	0.10	0.10
7	Prelaunch to on-orbit SD BRF change:	0.50	0.50
8	SD screen (SDS):	0.20		0.50
9	SDSM and SDS impact:	0.50	0.50
10	Solar illumination of the SD surrounds	0.30		0.50–0.80
11	Earthshine through the SD door	0.30		0.50–0.80
12	Earthshine through nadir aperture door	0.10	0.00
	RSS	1.57	1.37

The SD degradation, $Δ_{SD}$ , is determined from SDSM measurements, and the uncertainty in this term is simply taken to be the standard deviation of fitting residuals of the SDSM trends. The last two terms in Eq. (10) represent the uncertainty associated with the prelaunch characterization of the RSB temperature correction coefficients $k_{inst}$ and instrument temperature $T_{inst}$ . These terms are derived using the assumption $k_{inst} (T_{inst} - T_{ref}) ≪ 1$ . The impact of these two terms is relatively small, each typically $< 10^{- 3}$ . Finally, the terms $[\frac{δ d n_{SD}}{d n_{SD}}]$ and $[\frac{δ d n_{EV}}{d n_{EV}}]$ are the uncertainties related to the sensor’s SD response noise and EV response noise at typical signal levels. The value of $δ d n$ is calculated as a function of dn using a linear approximation to obtain the fitting coefficients ( $c_{0,1}$ ). The data from every SD calibration event are fitted to obtain values for these coefficients for each band, detector, mirror side, and subframe. The noise is then calculated at the typical signal level of the SD calibration to determine the $[\frac{δ d n_{SD}}{d n_{SD}}]$ term. For the $[\frac{δ d n_{EV}}{d n_{EV}}]$ term, the value depends on the dn_EV and is thus evaluated for every EV pixel using the coefficients $c_{0, 1}$ . This uncertainty term can be significant for very low radiance scenes.²⁹

The uncertainty at the SD AOI is determined by considering all of the terms in the SD calibration as just described. This approach has been used in all previous descriptions of MODIS RSB uncertainty. Starting from $C 6$ , we split $m_{1} / RVS$ uncertainty terms into those determined prelaunch and those used to capture on-orbit changes. The prelaunch determined uncertainties at the SD AOI represent a baseline uncertainty that is present for all time and AOI, and the uncertainties in the parameters that have on-orbit changes are added to this baseline. For most RSB, the on-orbit $m_{1}$ and RVS are derived solely based on the on-board measurements from the SD and moon (viewed via the SV port). Based on Eqs. (1)–(5) and similar to Eq. (10), the total uncertainty of the reflectance factor at the AOI of the SV can be expressed as follows:

Eq. (11)

{[\frac{δ ρ_{EV} \cos (θ_{EV})}{ρ_{EV} \cos (θ_{EV})}]}_{SV}^{2} = {[\frac{δ ρ_{SD}}{ρ_{SD}}]}^{2} + {[\frac{δ Γ_{SD S} (t_{0})}{Γ_{SD S} (t_{0})}]}^{2} + {[\frac{δ Δ_{SD} (t_{0})}{Δ_{SD} (t_{0})}]}^{2} + {[\frac{δ d n_{SD} (t_{0})}{d n_{SD} (t_{0})}]}^{2} + {[\frac{δ d n_{EV}}{d n_{EV}}]}^{2} + {[δ k_{inst} (T_{inst, EV} - T_{inst, SD})]}^{2} + {[k_{inst} δ (T_{inst, EV} - T_{inst, SD})]}^{2} + {[\frac{δ {RVS}_{SV, prl}}{{RVS}_{SV, prl}}]}^{2} + {[\frac{δ m_{1}^{moon, oo}}{m_{1}^{moon, oo}}]}^{2},

where the

(t_{0})

indicates the values of uncertainty at mission start,

[\frac{{δ RVS}_{SV, prl}}{{RVS}_{SV, prl}}]

is the prelaunch RVS measurement uncertainty, which is band dependent, and

[\frac{δ m_{1}^{moon, oo}}{m_{1}^{moon, oo}}]

is the uncertainty in the measurement of the lunar calibration. This lunar uncertainty is calculated from the standard deviation of the fitting residuals after fitting the

m_{1}^{moon, oo}

time series to an empirically determined piece-wise function. The other terms in Eq. (11) are the same as in Eq. (10).

At other AOI, the $m_{1} / RVS$ is determined by assuming a linear dependence of the RVS between the SD and SV (lunar) calibration results. Correspondingly, the uncertainty at arbitrary AOI is a combination of the uncertainties in the on-orbit changes at the SD and SV AOI. For some bands, mirror side ratio data obtained from Earth-view targets are used to supplement the on-board data in calculating the $m_{1} / RVS$ for mirror side 2. Thus, an additional uncertainty term is also applied to mirror side 2 that accounts for the typical uncertainty in the EV observations. We note that this results in mirror side 2 having a larger uncertainty than mirror side 1 for these bands, which is clearly not appealing as the mirror side labeling is an arbitrary choice. This is an issue that will be addressed in future algorithm changes.

As stated in Sec. 2, on-orbit changes in both the $m_{1}$ and $RVS$ for select RSB (Terra bands 1 to 4, 8 to 10, and Aqua bands 1 to 4, 8, and 9) are computed using the lunar measurements and measurements from select EV desert sites.³⁰^,³¹ In this EV-based approach, the EV reflectance factor can be expressed as follows:

Eq. (12)

{[ρ_{EV} \cos (θ_{EV})]}_{α} = \frac{d n_{EV} d_{ES, EV}^{2} [1 + k_{inst} (T_{inst, EV} - T_{inst, ref})] m_{1} (t_{0})}{{RVS}_{prl}} {(\frac{m_{1}}{RVS})}_{EV, on-orbit},

where the

α

subscript indicates arbitrary AOI. The total uncertainty of the reflectance factor is

Eq. (13)

{[\frac{δ ρ_{EV} \cos (θ_{EV})}{ρ_{EV} \cos (θ_{EV})}]}_{α}^{2} = {[\frac{δ ρ_{SD}}{ρ_{SD}}]}^{2} + {[\frac{δ Γ_{SDS} (t_{0})}{Γ_{SDS} (t_{0})}]}^{2} + {[\frac{δ Δ_{SD} (t_{0})}{Δ_{SD} (t_{0})}]}^{2} + {[\frac{δ d n_{SD} (t_{0})}{d n_{SD} (t_{0})}]}^{2} + {[\frac{δ d n_{EV}}{d n_{EV}}]}^{2} + {[δ k_{inst} (T_{inst, EV} - T_{inst, SD})]}^{2} + {[k_{inst} δ (T_{inst, EV} - T_{inst, SD})]}^{2} + {[\frac{δ {RVS}_{prl}}{{RVS}_{prl}}]}^{2} + {[\frac{δ {(\frac{m_{1}}{R V S})}_{EV, on-orbit}}{{(\frac{m_{1}}{RVS})}_{EV, on-orbit}}]}^{2} .

All of the terms in this equation have been previously discussed, except for the last one. The uncertainty in the EV-based $m_{1} / RVS$ for all AOI is determined from two sets of fitting residuals. First, the normalized reflectance trends from the desert sites are fit to a piecewise polynomial function of time at several select AOI. Then, the results of the time fitting are fit to a quadratic or quartic function over AOI, depending on the band. The uncertainty due to on-orbit change in the EV $m_{1} / RVS$ is taken to be the summation of the standard deviation of the fitting residuals of these two fits.

The various components contributing to the MODIS RSB uncertainty algorithm are organized in five different terms ( $U_{1}$ , $U_{2}$ , $U_{3}$ , $U_{4}$ , and $U_{5})$ when computing the uncertainty of RSB L1B product. The organization is based on each term’s dependence of band ( $B$ ), detector ( $D$ ), mirror side ( $M$ ), subframe (SF), time ( $t$ ), AOI ( $θ$ ), and scene

Eq. (14)

{[\frac{δ ρ_{EV} \cos (θ_{EV})}{ρ_{EV} \cos (θ_{EV})}]}_{α}^{2} = U_{1} {(B, D)}^{2} + U_{2} {(B, D, M, α, t)}^{2} + U_{3} {(B, D, M)}^{2} + U_{4} {(B, D, M, S F, t, scene)}^{2} + U_{5} {(B, D, M, S F, t, scene)}^{2} .

The first term, $U_{1}$ , contains the terms of the SD calibration uncertainty, which are considered to be constant in time, including the earthshine impact. The second term, $U_{2}$ , represents the RVS uncertainty as well as uncertainty in the $m_{1}$ not accounted for in $U_{1}$ . The $U_{2}$ term is both time- and AOI-dependent and varies depending on the band and whether the on-board RVS algorithm or the EV-based RVS algorithm is used. The third term, $U_{3}$ , represents the uncertainty in the instrument temperature correction, which is based on prelaunch measurements and is band, detector, and mirror-side dependent. The fourth term, $U_{4}$ , contains the scene-dependent uncertainty in $d n_{EV}$ and is derived from the SD calibration measurements. The final term, $U_{5}$ , is an additional term, not derived from the above equations, that accounts for uncertainty due to optical leak and electronic crosstalk in the SWIR bands. It is assigned to be equal to one-fourth of the SWIR $d n_{EV}$ correction ( $Δ d n_{EV} / d n_{EV}$ ). At typical radiance levels for both sending and receiving bands, this term (averaged over operable detectors and sub-frames) could be from 0.2% to 2.0% for Terra MODIS SWIR bands with the largest uncertainty for band 5. With less optical leak and electronic crosstalk, the Aqua SWIR band uncertainty is smaller than for Terra MODIS.

The total uncertainty for the Terra and Aqua MODIS RSB is shown for multiple years in Fig. 3. The results shown are for mirror side 1 and averaged over all operable detectors (i.e., excluding noisy and inoperable). The contributions from the uncertainty due to optical leak and electronic crosstalk in the SWIR bands ( $U_{5}$ term) are not included in the results in this figure. This term is scene dependent and can add significantly to the displayed uncertainty of the SWIR bands for low radiance scenes. As seen for the nadir case in Fig. 3, most Terra MODIS RSB continue to meet the 2% specification after multiple years on-orbit. The bands that use EV-based calibration (1 to 4 and 8 to 10) have relatively high uncertainty compared with the other RSB due to the larger variances in the retrieved EV data compared with the SD and lunar data. It is also observed that bands 5, 7, and 18 marginally exceed the 2% specification. In comparison with other RSB, the typical radiance values for these bands (see Table 1) are relatively low. This translates to a lower SNR and a larger uncertainty ( $U_{4}$ term).

Fig. 3

Terra and Aqua MODIS RSB uncertainty at typical radiance and three scan-angles (nadir, $- 45 \deg$ and $+ 45 \deg$ ).

Differences in uncertainty across different scan angles (nadir, $- 45 \deg$ and $+ 45 \deg$ ) are due entirely to the uncertainty in RVS, which is contained in the $U_{2}$ term. As discussed earlier, the bands that use EV-based calibration tend to have larger uncertainty, and this is particularly true for the short-wavelength VIS bands (3, 8, 9, and 10). In addition, on-orbit polarization sensitivity of the Terra MODIS SM is known to have changed especially for these short wavelength bands 8 and 9 at the end of scan (high scan angles), and this is likely the reason that the uncertainties for these bands are much larger at higher scan angles. In general, the uncertainty at the SV scan angle (close to the case at scan angle of $- 45 \deg$ ) calculated using lunar measurements has much smaller magnitude than other angles that rely on the EV desert targets. In the case of bands 1 and 2, the EV data are used at all the scan angles due to disagreement between the on-orbit lunar and EV measurements; hence the uncertainty at all angles is between 1.8% and 2.4%. In general, the uncertainty results observed in Aqua MODIS RSB are very similar in trend, but of a slightly lower magnitude, in comparison with Terra MODIS. Unlike Terra MODIS, the on-orbit change in the polarization sensitivity of Aqua MODIS is known to be minimal, which is reflected in the results at $+ 45 \deg$ scan angle for the short wavelength bands 8 and 9.

Figure 4 shows the uncertainty of the Terra MODIS RSB (nadir) at two ends of the dynamic range, i.e., $0.3 L_{typical}$ and $0.9 L_{\max}$ . As discussed earlier, the scene-dependent term $U_{4}$ increases at lower scene radiances, resulting in greater uncertainties for all RSB. It should be noted that the specified uncertainty requirement of 2% in reflectance for the RSB is for observations at typical scene radiance level. An extra 1% uncertainty is added to specified requirements for observations made at different radiance levels from 0.3 $L_{typ}$ to 0.9 $L_{\max}$ . With this criterion, only bands 5, 7, and 18 are seen to exceed the specification for reasons discussed earlier. Similar results for Aqua MODIS are shown in Fig. 5.

Fig. 4

Terra MODIS RSB uncertainty (nadir) at specified 0.3 typical radiance and 0.9 maximum radiance levels.

Fig. 5

Aqua MODIS RSB uncertainty (nadir) at specified 0.3 typical radiance and 0.9 maximum radiance levels.

4. Thermal Emissive Bands Calibration Uncertainty

From TEB calibration Eqs. (7) and (8), the EV radiance can be expressed as

Eq. (15)

L_{EV} = \frac{1}{{RVS}_{EV}} {(a_{0} + a_{2} \cdot d n_{EV}^{2}) + [{RVS}_{BB} \cdot ϵ_{BB} \cdot L_{BB} + ({RVS}_{SV} - {RVS}_{BB}) \cdot L_{SM} + {RVS}_{BB} \cdot (1 - ϵ_{BB}) \cdot ϵ_{CAV} \cdot L_{CAV} - a_{0} - a_{2} \cdot d n_{BB}^{2}] \cdot \frac{d n_{EV}}{d n_{BB}} - ({RVS}_{SV} - {RVS}_{EV}) \cdot L_{SM}} .

It is a function of several parameters determined from prelaunch and on-orbit observations

Eq. (16)

L_{EV} = L_{EV} {a_{0}, a_{2}, {RVS}_{BB}, {RVS}_{SV}, {RVS}_{EV}, ϵ_{BB}, ϵ_{CAV}, λ, T_{BB}, T_{SM}, T_{CAV}, d n_{EV}, d n_{BB}} .

The TEB calibration uncertainty is determined by combining the contributions from all of the parameters involved in the calibration and retrieval. In our analysis, the contributions from higher order and cross-product terms are not considered as they are either much smaller than the first-order terms or uncorrelated. With these assumptions, the total uncertainty of $L_{EV}$ can be computed using a small perturbation approach

Eq. (17)

{(\frac{d L_{EV}}{L_{EV}})}^{2} = \sum_{i} {[\frac{L_{EV} (x_{i} + d x_{i}) - L_{EV} (x_{i})}{L_{EV} (x_{i})}]}^{2},

where

x_{i}

represents a given contributing parameter in Eq. (16) and

d x_{i}

represents the measurement error or estimated uncertainty for parameter

x_{i}

. Tables 3 and 4 provide examples of Terra and Aqua MODIS TEB calibration uncertainties implemented in the C6 L1B with contributions from individual parameters. The uncertainties (for year 2008) are expressed as a percentage of the typical radiance level and at nadir AOI. With the exception of Terra LWIR PV bands (27 to 30), the uncertainties listed in Tables 3 and 4 are nearly identical to that used for C6.1 L1B.

Table 3

Terra MODIS TEB calibration uncertainties (at typical radiance, nadir AOI, year 2008, C6).

Band	T_BB	T_SM	T_CAV	CW	RVS_EV	RVS_SV	ϵ_BB	ϵ_CAV	dn_BB	dn_EV	a0	a2	PCX	RSS (%)
20	0.23	0.00	0.01	0.43	0.08	0.02	0.11	0.02	0.02	0.11	0.00	0.02	0.00	0.52
21	0.00	0.00	0.00	0.00	2.19	0.26	0.00	0.00	0.00	0.49	0.00	0.00	0.00	2.34
22	0.22	0.00	0.01	0.38	0.08	0.02	0.11	0.02	0.02	0.11	0.00	0.03	0.00	0.47
23	0.21	0.00	0.02	0.36	0.07	0.02	0.16	0.02	0.02	0.09	0.00	0.03	0.00	0.47
24	0.18	0.01	0.02	0.26	0.23	0.27	0.19	0.03	0.01	0.67	0.04	0.05	0.00	0.84
25	0.19	0.00	0.02	0.26	0.01	0.05	0.15	0.03	0.02	0.22	0.01	0.02	0.00	0.42
27	0.13	0.03	0.02	0.14	0.19	0.22	0.12	0.03	0.01	0.50	0.23	0.07	0.00	0.67
28	0.11	0.02	0.02	0.09	0.05	0.07	0.16	0.04	0.01	0.18	0.05	0.22	0.00	0.37
29	0.10	0.03	0.02	0.04	0.03	0.01	0.11	0.05	0.01	0.05	0.01	0.10	0.00	0.21
30	0.09	0.06	0.01	0.01	0.10	0.15	0.14	0.04	0.02	0.25	0.09	0.42	0.00	0.56
31	0.08	0.01	0.01	0.02	0.02	0.01	0.06	0.03	0.01	0.04	0.00	0.03	0.00	0.12
32	0.07	0.01	0.01	0.03	0.02	0.01	0.03	0.02	0.01	0.05	0.00	0.03	0.00	0.11
33	0.07	0.03	0.01	0.04	0.04	0.06	0.03	0.03	0.02	0.22	0.00	0.06	0.11	0.28
34	0.07	0.04	0.01	0.04	0.31	0.33	0.06	0.03	0.03	0.32	0.00	0.11	0.16	0.60
35	0.07	0.05	0.01	0.04	0.16	0.18	0.03	0.03	0.03	0.46	0.00	0.09	0.22	0.59
36	0.07	0.07	0.01	0.04	0.40	0.42	0.06	0.03	0.05	1.01	0.00	0.10	0.52	1.28

Table 4

Aqua MODIS TEB calibration uncertainties (at typical radiance, nadir AOI, year 2008, C6).

Band	t_bb	t_sm	t_cav	CW	rvs_ev	rvs_sv	ϵ_BB	s_CAV	dn_BB	dn_EV	a0	a2	RSS (%)
20	0.23	0.00	0.00	0.44	0.01	0.01	0.26	0.00	0.03	0.10	0.09	0.03	0.58
21	0.00	0.00	0.00	0.00	0.08	0.02	0.00	0.00	0.00	0.64	0.00	0.00	0.64
22	0.22	0.00	0.00	0.39	0.02	0.01	0.25	0.00	0.02	0.08	0.08	0.08	0.54
23	0.22	0.00	0.00	0.37	0.01	0.01	0.25	0.00	0.02	0.08	0.09	0.09	0.52
24	0.19	0.03	0.00	0.27	0.04	0.05	0.19	0.00	0.02	0.60	0.30	0.09	0.78
25	0.20	0.01	0.00	0.27	0.00	0.01	0.19	0.00	0.02	0.17	0.06	0.06	0.43
27	0.13	0.03	0.00	0.14	0.21	0.24	0.15	0.00	0.01	0.35	0.21	0.09	0.58
28	0.12	0.02	0.00	0.10	0.03	0.03	0.15	0.01	0.01	0.13	0.15	0.11	0.32
29	0.10	0.01	0.01	0.04	0.04	0.02	0.14	0.02	0.01	0.03	0.03	0.07	0.20
30	0.09	0.03	0.01	0.01	0.08	0.07	0.13	0.04	0.01	0.17	0.17	0.15	0.35
31	0.08	0.01	0.00	0.01	0.00	0.00	0.12	0.00	0.00	0.02	0.00	0.04	0.16
32	0.07	0.01	0.00	0.02	0.00	0.00	0.12	0.01	0.01	0.04	0.00	0.02	0.15
33	0.08	0.03	0.00	0.04	0.00	0.01	0.10	0.00	0.02	0.17	0.03	0.05	0.23
34	0.07	0.04	0.00	0.04	0.01	0.01	0.09	0.00	0.02	0.20	0.07	0.09	0.26
35	0.08	0.05	0.00	0.04	0.02	0.02	0.10	0.01	0.03	0.30	0.05	0.08	0.34
36	0.07	0.08	0.00	0.04	0.05	0.03	0.12	0.01	0.03	0.52	0.21	0.21	0.63

The Terra MODIS PC bands, 32 to 36, have an additional uncertainty imposed due to signal contamination from an optical leak (PCX). This is not the case for Aqua MODIS. As expected, the Terra MODIS TEB uncertainty for these five bands is generally higher than Aqua MODIS. MODIS band 21 (for fire detection), with a calibration uncertainty requirement of 10%, has been calibrated in the L1B using a fixed linear coefficient. Its calibration uncertainties shown in Tables 3 and 4 are not adequate and need to be determined separately.

Although the same uncertainty values of the BB (50 mK), SM (1.0 K), and CAV (1.0 K), temperatures are used for all TEB, their impacts on the calibration uncertainties are spectral band and retrieval radiance-level dependent. The center wavelength (CW) uncertainty was determined from prelaunch spectral characterization.³² The BB spectral emissivity and its uncertainty were characterized prelaunch using thermal vacuum calibration datasets.³³^,³⁴ Meanwhile, the scan cavity emissivity and its uncertainty values were estimated based on the instrument design and characteristics. The impact of this term on the total calibration uncertainty is usually very small. For a given spectral band, several contributors in Eq. (17) are constant and in general their impact on the total uncertainty is relatively small. The $a_{0}$ , $a_{2}$ , $d n_{EV}$ , and $d n_{BB}$ terms are time dependent and can have large impact on the total uncertainty, depending on the detector performance and calibration quality. It should also be noted that some TEB on-orbit calibrations are made with the $a_{0}$ terms set to zero. Table 5 shows the TEB calibration uncertainty at different radiance levels. Except for a few bands in Terra MODIS at lower radiance levels, most TEB continue to meet the calibration requirements.

Table 5

Summary of Terra and Aqua MODIS TEB calibration uncertainty (C6) in percentage at different radiance levels (nadir view, year 2008, C6).

	Terra			Aqua
Bands	Ltyp	0.3 Ltyp	0.9 Lmax	Ltyp	0.3 Ltyp	0.9 Lmax
20	0.52	0.61	0.56	0.58	0.68	0.63
22	0.47	0.57	0.51	0.54	0.60	0.63
23	0.47	0.55	0.50	0.52	0.58	0.65
24	0.84	2.73	0.56	0.78	2.36	0.54
25	0.42	0.92	0.40	0.43	0.85	0.41
27	0.67	2.34	0.34	0.58	1.88	0.30
28	0.37	0.88	0.26	0.32	0.91	0.24
29	0.21	0.45	0.33	0.20	0.32	0.25
30	0.56	1.47	0.31	0.35	1.25	0.22
31	0.12	0.25	0.14	0.16	0.23	0.19
32	0.11	0.27	0.13	0.15	0.22	0.17
33	0.28	0.98	0.22	0.23	0.58	0.19
34	0.60	3.29	0.43	0.26	0.88	0.22
35	0.59	2.08	0.46	0.34	0.94	0.29
36	1.28	4.31	1.02	0.63	2.01	0.50

The uncertainty values for Terra MODIS bands 27 to 30 (Tables 3 and 5) are inadequately estimated as no correction for electronic crosstalk was included in $C_{6}$ . The latest L1B (C6.1) calibration algorithm has included an electronic crosstalk correction for these bands. As shown in Fig. 6 are examples of Terra and Aqua MODIS TEB on-orbit calibration uncertainties in C6.1 for select years at their typical radiances and three scan-angles (nadir, $- 45 \deg$ and $+ 45 \deg$ ). The updated results indicate a significant reduction of uncertainty, particularly in Terra bands 27 and 30 after 2015, which is due to improvement of the stability in $a_{0} / a_{2}$ and detector noise after the crosstalk correction. Figures 7 and 8 show the uncertainties at 0.3 of typical and 0.9 of maximum radiances for Terra and Aqua MODIS, respectively. As expected, at the 0.3 typical radiance there is a significant increase in uncertainty for bands with low typical temperatures.

Fig. 6

Terra and Aqua MODIS TEB uncertainty (C6.1) at typical radiance and three scan-angles (nadir, $- 45 \deg$ and $+ 45 \deg$ ).

Fig. 7

Terra MODIS TEB uncertainty (C6.1, nadir) at specified 0.3 typical radiance and 0.9 maximum radiance levels.

Fig. 8

Aqua MODIS TEB uncertainty (C6.1, nadir) at specified 0.3 typical radiance and 0.9 maximum radiance levels.

To account for the electronic crosstalk correction in the calculation of the L1B radiance uncertainty, we apply an additional penalty term at the pixel level for each detector ( $i$ ) in these bands, as given by

Eq. (18)

P_{i} = \frac{Δ d n}{d n} β_{i},

where

Δ d n

is the magnitude of the signal correction,

d n

is the corrected signal level, and

β_{i}

is the uncertainty penalty coefficient for a given detector. The appropriate value for

β_{i}

is found by comparing the long-term drift in the band-averaged, corrected radiance to a relatively stable reference, in this case band 31, over warm ocean scenes where the radiance is relatively high. For bands 27 to 30, the drift in corrected radiance relative to band 31 is on the order of 1% over the course of the mission. We then choose a value

β_{i}

such that the band-averaged value of the applied penalty is equal to that of the measured radiance drift after correction for selected scenes late in the mission.

For bands 28 to 30, we calculated $β_{i}$ to be 0.040, 0.095, and 0.021, respectively. The same values are applied to each detector within the band. For band 27, $β_{i} = 0.025$ for detectors 3to 8 and 0.0375 for detectors 1, 2, 9, and 10 due to the higher levels of contamination for these detectors relative to the rest of the band. As the applied penalty is proportional to the magnitude of the corrected signal, the uncertainty penalty is dependent on the detector, scene, and time during the mission, with the assessed penalty generally increasing as the mission progresses. For high-radiance scenes late in the mission, most detectors are generally assessed an uncertainty penalty of 1% to 2%, with some detectors in band 27 having a 3% to 5% penalty. Early in the mission, the uncertainty penalty is negligible for all detectors.

5. Future Improvements

In addition to changes with on-orbit calibration algorithms, several enhancements can be made to improve the assessments of MODIS calibration uncertainties. The MODIS SD panel’s BRF was characterized prelaunch by the instrument vendor using reference samples traceable to NIST reflectance standards at a number of wavelengths up to $1.7 μ m$ . No direct BRF measurements were made at $2.1 μ m$ due to low SNR and hence an extrapolation is used, contributing an additional 0.5% uncertainty at $2.1 μ m$ (band 7) that is not accounted for in our current SD BRF uncertainty estimate (Table 2). Also considered are the improvements of SWIR on-orbit calibration for both Terra and Aqua MODIS by applying correction for the SD degradation, and the use of a different sending band for Terra MODIS SWIR optical leak and electronic crosstalk correction as several detectors in the current sending band (B28) have also been significantly impacted by the electronic crosstalk from the other LWIR PV bands.³⁵ Other improvements are listed in the following for future considerations

• RSB mirror side 2 uncertainty for bands using mirror side 1 as reference
As discussed in Sec. 3, some of the bands that use the on-board based RVS calibration use additional mirror side ratio data from EV ocean targets to correct the RVS of mirror side 2 relative to mirror side 1. This is currently applied to Aqua bands 10 to 16 and Terra bands 11 to 16. As a result, an additional uncertainty term is included only for mirror side 2, which is not desirable. One option for resolving this is to change the RVS calibration such that the EV mirror-side ratio correction is applied equally to the RVS of both mirror sides (while maintaining the ratio). Then, the additional uncertainty term should also be applied equally to both mirror sides.

• RSB RVS uncertainty for bands that have been impacted by the changes in sensor polarization sensitivity
Current RSB calibration coefficients are derived under the assumption that the impact due to instrument polarization sensitivity is small and can be ignored. Several Terra MODIS VIS spectral bands (e.g., bands 8 and 9), however, have seen large changes (increases) in their polarization sensitivity, especially at the large AOIs.³⁶ Because of this, the RVS derived using EV targets at different AOIs is affected due to an increase in the instrument polarization sensitivity. As a potential improvement, the EV based RVS should be derived after removing the polarization effect.

• TEB uncertainty for bands using fixed calibration coefficients during BB warm-up and cool-down (WUCD)
Fixed gain coefficients, i.e., default $b_{1}$ , are used for Aqua bands 33, 35, and 36 during BB warm-up and cool-down when the detector responses saturate over certain high BB temperatures. During this period, the default $b_{1}$ values are predetermined using BB measurements from three consecutive orbits generally 10 days before each BB WUCD. As these values are not computed from instantaneous scan–by–scan measurements, an extra, small uncertainty term needs to be considered when the default $b_{1}$ is used.

• B21 calibration uncertainty
Unlike most TEB, band 21 uses a simple linear calibration algorithm. Its $b_{1}$ coefficients are provided via an LUT with its values derived from BB WUCD. As this low-gain band is primarily used for fire detection with a specified maximum temperature of 500 K, its response to the BB nominal temperature (290 K for Terra and 285 for Aqua) is at the low end of its dynamic range. Because of this, the calibration uncertainty could be very large when scene temperatures are considerably high (e.g., for fire scene).

• TEB RVS uncertainty for Terra MODIS using new deep space maneuver data sets
Terra MODIS TEB RVS used in the current L1B product is based on the results derived from a deep space maneuver performed in 2003. In August 2017, Terra conducted another deep space maneuver. A comparison of the TEB RVS derived from these two maneuvers shows that the differences are generally within 0.2% except for the bands 27 to 30 that in recent years have large electronic crosstalk. The differences are small but comparable with the RVS uncertainties currently assigned for most TEB. As a future improvement, a better estimate of the TEB RVS can be made by combing the RVS results from both maneuvers and relative long-term trends (time series) using other stable targets.

6. Summary

The MODIS instruments have been successfully operating on-orbit making continuous global observations for various science applications. In comparison with its predecessors, MODIS has a more stringent requirement on its calibration accuracy and data product quality. A sustained instrument characterization program has led to timely upgrades to the L1B algorithm, resulting in well calibrated science products that continue to meet the overall science requirements. Algorithms used to estimate the calibration uncertainties on-orbit for both the RSB and TEB are discussed in detail. This paper serves as an update to our previous uncertainty analysis results reflecting the calibration algorithm updates performed over the mission of each instrument. With a few exceptions, most RSB and TEB calibration uncertainties are within the specified uncertainty requirements. Due to the significant on-orbit degradation observed in the short wavelength bands, the OBC measurements are supplemented with EV data from time-invariant desert sites. The changing polarization sensitivity of short wavelength Terra MODIS bands (3, 8, 9, and 10) at large AOIs has contributed to the increased uncertainty as the RVS for these bands, which is derived from the EV measurements. With the addition of the electronic crosstalk correction for bands 27 to 30 in Terra MODIS C6.1, our assessment of the uncertainty in these bands also needed to be re-evaluated. With the algorithm change and correction applied in C6.1, the uncertainty for these bands was reduced significantly during the more recent years of the mission. Several enhancements to the current approach were also identified and will be considered for a future L1B version.

Acknowledgments

The authors would like to thank all current and past members of MCST for their many and varied contributions over the years. They would also like to thank the Science Team members they have collaborated with, leading to greater understanding of instrument performance, impacts on the science products, and improvements in their calibration methodologies. This manuscript is an extension of an SPIE conference proceedings paper, Xiong, X., A. Angal, W. Barnes, H. Chen, V. Chiang, X. Geng, Y. Li, K. Twedt, Z. Wang, T. Wilson, et al., “Updates of MODIS on-orbit calibration uncertainty assessments,” Proc. SPIE—Earth Observing Systems XXII, vol. 10402, no. 104020M, 2017.

References

1.

W. L. Barnes and V. V. Salomonson, “MODIS: a global image spectroradiometer for the earth observing system,” Crit. Rev. Opt. Sci. Technol., 47 285 –307 (1993). CROTE2 Google Scholar

2.

W. L. Barnes et al., “Development, characterization, and performance of the EOS MODIS sensors,” Proc. SPIE, 5151 337 –345 (2003). https://doi.org/10.1117/12.504818 PSISDG 0277-786X Google Scholar

3.

X. Xiong et al., “NASA EOS terra and aqua MODIS on-orbit performance,” Adv. Space Res., 43 413 –422 (2008). https://doi.org/10.1016/j.asr.2008.04.008 ASRSDW 0273-1177 Google Scholar

4.

X. Xiong, B. N. Wenny and W. L. Barnes, “Overview of NASA earth observing systems terra and aqua moderate resolution imaging spectroradiometer instrument calibration algorithms and on-orbit performance,” J. Appl. Remote Sens., 3 032501 (2009). https://doi.org/10.1117/1.3180864 Google Scholar

5.

C. Schueler et al., “NPOESS VIIRS sensor design overview,” Proc. SPIE, 4483 11 –23 (2001). https://doi.org/10.1117/12.453451 PSISDG 0277-786X Google Scholar

6.

R. P. Murphy et al., “The visible infrared imaging radiometer suite,” Earth Science Satellite Remote Sensing, 1 199 –223 Springer-Verlag, Berlin, Heidelberg (2006). Google Scholar

7.

E. J. Knight and G. Kvaran, “Landsat-8 operational land imager design, characterization and performance,” Remote Sens., 6 10286 –10305 (2014). https://doi.org/10.3390/rs61110286 Google Scholar

8.

B. Markham, “Landsat-8 operational land imager radiometric calibration and stability,” Remote Sens., 6 12275 –12308 (2014). https://doi.org/10.3390/rs61212275 Google Scholar

9.

V. V. Salomonson, “An overview of the earth observing system MODIS instrument and associated data systems performance,” in IEEE Int. Geoscience and Remote Sensing Symp., 1174 –1176 (2002). https://doi.org/10.1109/IGARSS.2002.1025812 Google Scholar

10.

V. Salomonson, X. Xiong, “MODIS instrument characteristics, performance, and data for climate studies,” Satellite-Based Applications on Climate Change, 31 –48 Springer, Dordrecht (2013). Google Scholar

11.

X. Xiong, A. Isaacman, W. L. Barnes, “MODIS level-1B products,” Earth Science Satellite Remote Sensing: Science and Instrument, 1 33 –49 Springer, Berlin, Heidelberg (2006). Google Scholar

12.

G. Toller, “Status of EOS terra and aqua MODIS L1B algorithm,” J. Appl. Remote Sens., 2 023505 (2008). https://doi.org/10.1117/1.2839442 Google Scholar

13.

G. Toller et al., “Terra and aqua moderate-resolution imaging spectroradiometer collection 6 level 1B algorithm,” J. Appl. Remote Sens., 7 073557 (2013). https://doi.org/10.1117/1.JRS.7.073557 Google Scholar

14.

“Specification for the moderate resolution imaging spectroradiometer,” (1993). Google Scholar

15.

J. Esposito, “MODIS reflective solar bands uncertainty analysis,” Proc. SPIE, 5542 448 –458 (2004). https://doi.org/10.1117/12.558106 PSISDG 0277-786X Google Scholar

16.

K. Chiang et al., “MODIS thermal emissive bands calibration uncertainty analysis,” Proc. SPIE, 5542 437 –447 (2004). https://doi.org/10.1117/12.558072 PSISDG 0277-786X Google Scholar

17.

X. Xiong et al., “Terra and aqua MODIS calibration algorithms and uncertainty analysis,” Proc. SPIE, 5978 59780V (2005). https://doi.org/10.1117/12.627631 PSISDG 0277-786X Google Scholar

18.

K. Chiang, J. McIntire and X. Xiong, “VIIRS thermal emissive bands L1B calibration uncertainty,” in IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), 4197 –4200 (2017). https://doi.org/10.1109/IGARSS.2017.8127927 Google Scholar

19.

N. Lei et al., “SNPP VIIRS RSB Earth view reflectance uncertainty,” in IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS), 5916 –5919 (2017). https://doi.org/10.1109/IGARSS.2017.8128355 Google Scholar

20.

X. Xiong and J. Butler, “MODIS solar reflective calibration traceability,” Proc. SPIE, 7452 74520K (2009). https://doi.org/10.1117/12.824761 PSISDG 0277-786X Google Scholar

21.

X. Xiong et al., “Multi-year on-orbit calibration and performance of terra MODIS reflective solar bands,” IEEE Trans. Geosci. Remote Sens., 45 (4), 879 –889 (2007). https://doi.org/10.1109/TGRS.2006.890567 IGRSD2 0196-2892 Google Scholar

22.

X. Xiong et al., “Multiyear on-orbit calibration and performance of terra MODIS thermal emissive bands,” IEEE Trans. Geosci. Remote Sens., 46 (6), 1790 –1803 (2008). https://doi.org/10.1109/TGRS.2008.916217 IGRSD2 0196-2892 Google Scholar

23.

X. Xiong et al., “Aqua MODIS thermal emissive bands on-orbit calibration, characterization, and performance,” IEEE Trans. Geosci. Remote Sens., 47 (3), 803 –814 (2009). https://doi.org/10.1109/TGRS.2008.2005109 IGRSD2 0196-2892 Google Scholar

24.

X. Xiong et al., “On-orbit calibration and performance of aqua MODIS reflective solar bands,” IEEE Trans. Geosci. Remote Sens., 48 (1), 535 –546 (2010). https://doi.org/10.1109/TGRS.2009.2024307 IGRSD2 0196-2892 Google Scholar

25.

X. Xiong et al., “MODIS correction algorithm for out-of-band response in the short-wave IR bands,” Proc. SPIE, 5234 605 –613 (2004). https://doi.org/10.1117/12.510261 PSISDG 0277-786X Google Scholar

26.

T. Wilson et al., “Development and implementation of an electronic crosstalk correction for bands 27-30 in terra MODIS collection 6,” Remote Sens., 9 (6), 569 (2017). https://doi.org/10.3390/rs9060569 Google Scholar

27.

M. Pavlov, M. Byers and J. A. Walker, “Bidirectional reflectance factor (BRF) characterization of the MODIS flight solar diffuser, earth observing systems III,” Proc. SPIE, 3439 257 –268 (1998). https://doi.org/10.1117/12.325631 PSISDG 0277-786X Google Scholar

28.

X. Xiong et al., “On-orbit characterization of a solar diffuser’s bidirectional reflectance factor using spacecraft maneuvers, earth observing systems VIII,” Proc. SPIE, 5151 375 –383 (2003). https://doi.org/10.1117/12.504802 PSISDG 0277-786X Google Scholar

29.

A. Angal et al., “On-orbit noise characterization of MODIS reflective solar bands,” J. Appl. Remote Sens., 9 094092 (2015). https://doi.org/10.1117/1.JRS.9.094092 Google Scholar

30.

J. Sun et al., “Time-dependent response versus scan angle for MODIS reflective solar bands,” IEEE Trans. Geosci. Remote Sens., 52 (6), 3159 –3174 (2014). https://doi.org/10.1109/TGRS.2013.2271448 IGRSD2 0196-2892 Google Scholar

31.

A. Angal et al., “On-orbit performance and calibration improvements for the reflective solar bands of terra and aqua MODIS,” Proc. SPIE, 9881 98811F (2016). https://doi.org/10.1117/12.2223912 PSISDG 0277-786X Google Scholar

32.

J. B. Young, “MODIS calibration and accuracy areas,” (1997). Google Scholar

33.

X. Wang et al., “MODIS OBC emissivity extracted from RC02 and MFI09 data sets,” (1999). Google Scholar

34.

A. Wu and X. Xiong, “Re-evaluation of MODIS OBC BB emissivity uncertainty,” (2005). Google Scholar

35.

K. Twedt et al., “MODIS solar diffuser degradation at short-wave infrared band wavelengths,” Proc. SPIE, 10402 104022K (2017). https://doi.org/10.1117/12.2274272 PSISDG 0277-786X Google Scholar

36.

A. Wu et al., “Assessment of terra MODIS on-orbit polarization sensitivity using pseudo-invariant desert sites,” IEEE Trans. Geosci. Remote Sens., 55 (7), 4168 –4176 (2017). https://doi.org/10.1109/TGRS.2017.2689719 IGRSD2 0196-2892 Google Scholar

Biography

Xiaoxiong Xiong is an optical physicist at NASA/GSFC, currently serving as the MODIS Project Scientist and the MODIS and VIIRS Calibration Scientist. He received his BS degree in optical engineering from Beijing Institute of Technology, Beijing, China and his PhD in physics from University of Maryland, College Park, Maryland, USA. In addition to remote sensing, he had also worked in the fields of optical instrumentation, nonlinear optics, laser/atomic spectroscopy, and mass spectrometry, http://science.gsfc.nasa.gov/sed/bio/xiaoxiong.xiong-1.

Biographies for the other authors are not available.

Citation Download Citation

Xiaoxiong Xiong, Amit Angal, William L. Barnes, Hongda Chen, Vincent Chiang, Xu Geng, Yonghong Li, Kevin Twedt, Zhipeng Wang, Truman Wilson, and Aisheng Wu "Updates of Moderate Resolution Imaging Spectroradiometer on-orbit calibration uncertainty assessments," Journal of Applied Remote Sensing 12(3), 034001 (16 July 2018). https://doi.org/10.1117/1.JRS.12.034001

Received: 27 April 2018; Accepted: 26 June 2018; Published: 16 July 2018

Access the abstract

JOURNAL ARTICLE
18 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY

GET CITATION

CITATIONS

Cited by 39 scholarly publications.

Explore citations on Lens.org

RIGHTS & PERMISSIONS

Get copyright permission Get copyright permission on Copyright Marketplace

KEYWORDS

Calibration

MODIS

Sensors

Spectral calibration

Reflectivity

Mirrors

Short wave infrared radiation

1.

Introduction

Fig. 1

Table 1

Fig. 2

2.

Calibration Algorithms

Eq. (1)

Eq. (2)

Eq. (3)

Eq. (4)

Eq. (5)

Eq. (6)

Eq. (7)

Eq. (8)

3.

Reflective Solar Bands Calibration Uncertainty

Eq. (9)

Eq. (10)

Table 2

Eq. (11)

Eq. (12)

Eq. (13)

Eq. (14)

Fig. 3

Fig. 4

Fig. 5

4.

Thermal Emissive Bands Calibration Uncertainty

Eq. (15)

Eq. (16)

Eq. (17)

Table 3

Table 4

Table 5

Fig. 6

Fig. 7

Fig. 8

Eq. (18)

5.

Future Improvements

6.

Summary

Acknowledgments

References

Biography

Show All Keywords

Keywords/Phrases

Search In:

Publication Years