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Enhancement of the consistency ofMODIS thin cirrus with cloud phase byadding 1.6 µm reflectanceY.‐S. Choi a , C.‐H. Ho b , M.‐H. Ahn c & Y.‐S. Kim d

a School of Earth and Environmental Sciences , Seoul NationalUniversity , Seoul, 151–742, Koreab School of Earth and Environmental Sciences , Seoul NationalUniversity , Seoul, 151–742, Korea E-mail:c Korea Meteorological Administration , Meteorological ResearchInstitute , Seoul, Koread Department of Satellite Information Science , Pukyong NationalUniversity , Busan, KoreaPublished online: 24 Jan 2011.

To cite this article: Y.‐S. Choi , C.‐H. Ho , M.‐H. Ahn & Y.‐S. Kim (2005) Enhancement of theconsistency of MODIS thin cirrus with cloud phase by adding 1.6 µm reflectance, InternationalJournal of Remote Sensing, 26:21, 4669-4680, DOI: 10.1080/01431161.2005.10384476

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Enhancement of the consistency of MODIS thin cirrus with cloud phaseby adding 1.6 mm reflectance

Y.-S. CHOI{, C.-H. HO*{, M.-H. AHN{ and Y.-S. KIM"

{School of Earth and Environmental Sciences, Seoul National University,

Seoul 151-742, Korea

{Meteorological Research Institute, Korea Meteorological Administration,

Seoul, Korea

"Department of Satellite Information Science, Pukyong National University,

Busan, Korea

(Received 18 February 2005; in final form 7 June 2005 )

Optically thin cirrus derived from the Moderate-resolution Imaging

Spectroradiometer (MODIS) instrument is examined in connection with its

cloud phase (ice crystal or liquid droplet) for quasi-single layer thin cirrus (either

single-layer thin cirrus or thin cirrus overlying low-level thin clouds) over water

surface conditions. Analysing 142 MODIS data samples during the period 1–16

March 2000, it is found that only about 20% of MODIS thin cirrus having a

total-column cloud optical depth less than 2.0 was detected as ice phase. In the

present study, MODIS cloud phase datasets are newly reproduced by adding the

1.6 mm reflectance to an existing infrared trispectral algorithm of MODIS which

used the 8.7, 11 and 12 mm bands. The percentage of ice phase in the thin cirrus is

estimated at about 80% when new cloud phase is incorporated. The increase is

found for all regions, in particular in mid-latitudes.

Keywords: MODIS cloud; Ice phase; 1.6 mm reflectance; Thin cirrus

1. Introduction

The spatial and temporal variations of optically thin cirrus in the upper troposphere

may be one of the main factors that alter the global radiation budget in the

atmosphere and at the surface. A decrease of thin cirrus will reduce global warmingbecause of its transparency to incoming solar radiation and opaqueness to outgoing

terrestrial radiation. Concerning this issue, there is much contention regarding the

role of thin cirrus in climate feedback processes (e.g. Lindzen et al. 2001, Hartmann

and Michelsen 2002). However, it is also acknowledged that the technique for

detecting thin cirrus from satellite observations still has many uncertainties

(Roskovensky and Liou 2003). Indeed, thin cirrus detection depends on many

error sources such as water vapour (or ice crystal) content, surface conditions,

satellite viewing angle, and so on.Thin cirrus is defined so subjectively that its total fraction is found to vary widely

across the globe. For example, Wylie et al. (1994) suggested that thin cirrus (defined

as cloud optical depth, t,0.7) covers about 20% of the mid-latitude region (30u–60uN) and over 50% of the equatorial region (10u S–10uN). On the other hand, in

*Corresponding author. Email: hoch@cpl.snu.ac.kr

International Journal of Remote Sensing

Vol. 26, No. 21, 10 November 2005, 4669–4680

International Journal of Remote SensingISSN 0143-1161 print/ISSN 1366-5901 online # 2005 Taylor & Francis

http://www.tandf.co.uk/journalsDOI: 10.1080/01431160500239305

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most of the Moderate-resolution Imaging Spectroradiometer (MODIS) cloud mask

retrievals, the global coverage of thin cirrus is estimated to be less than that

demonstrated by Wylie et al. (Roskovensky and Liou 2003). Sassen and Campbell

(2001) documented that thin cirrus in the mid-latitude may be too tenuous to be

effectively sampled using current satellite methods in support of the first

International Satellite Cloud Climatology Project Regional Experiment.

The MODIS thin cirrus detection scheme incorporated reflectance at 1.38 mm

(RF1.38) for improving thin cirrus detection under daytime viewing conditions

(Ackerman et al. 2002). The RF1.38 is sensitive to the presence of thin cirrus clouds,

as the strength of this band lies in the strong water vapour absorption region (Gao

et al. 1993, King et al. 1996). In this band, high clouds appear brighter due to a

relatively low specific humidity, that is, reflectance from low and mid-level clouds is

partially attenuated by water vapour absorption (Ackerman et al. 2002).

In spite of the introduction of the band of 1.38 mm to improve the detection of

thin cirrus, its microphysical property may not be coherent yet. Theoretically, the

cloud phase should be ice in the region where single-layer thin cirrus is detected

because it has generally been produced at high altitude (Houze 1993). However, the

present study shows that there are significant circumstances in which single-layer

thin cirrus clouds exist but cannot be detected as ice phase. The reason is that the

current MODIS cloud phase algorithm is composed by brightness temperature

differences (BTDs) among infrared (IR) bands at 8.7, 11 and 12 mm. These bands are

useful for detecting opaque cloud, not for semi-transparent cloud, i.e. thin cirrus.

Especially when the optical depth of thin cirrus is less than 0.5, the BTD thresholds

become inaccurate in distinguishing ice cloud from water cloud (Roskovensky and

Liou 2003). Thus, only the visual high cloud can be well discriminated as ice cloud.

To overcome this limitation, the current retrieval of cloud phase in MODIS is

needed to keep up with the improved thin cirrus detection method.

Baum et al. (2000) recognized that near-IR 1.6 mm band is useful for improving

the phase retrieval accuracy. They pointed out that the IR trispectral algorithm

(using 8.6, 11, and 12 mm) of MODIS cloud phase is found to be less accurate in (1)

regions where more than one cloud phase type occurs, and (2) regions of thin cirrus

overlying a lower-level cloud layer. On the basis of their results, a modified

algorithm for cloud phase retrieval is designed in the present study. In particular, a

threshold test using reflectance at 1.6 mm (RF1.6) is added to the currently used

MODIS cloud phase scheme. The cloud phase retrieved from this new algorithm is

used as a new object to enhance the consistency of MODIS thin cirrus with its phase.

This paper is organized as follows. In §2 the data used in this study are described.

In §3 we examine the consistency of MODIS thin cirrus with current cloud phase

data. In §4 we suggest a new method for cloud phase retrieval adding RF1.6 to

improve the consistency of MODIS thin cirrus detection with its phase and present

the results for the consistency enhanced through the reproduced cloud phase.

Finally, a summary is given in §5.

2. MODIS data description and selection

Three kinds of MODIS datasets of Terra satellite are used: level-1b calibrated

radiances data (MOD02), cloud mask data (MOD35), and cloud product data

(MOD06) for daytime for the period 1–16 March 2000 (see MODIS atmosphere

website: http://modis-atmos.gsfc.nasa.gov). The MOD02 data have calibrated

radiances located at all 36 MODIS bands (both visible and IR regions). In the

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MOD02, reflectance centred at 1.6 mm (band 6) and radiances at 8.6 mm (band 29),

11.0 mm (band 31), and 12.0 mm (band 32) at 1 km61 km nadir resolution are

selectively chosen for this study. The reflectance and radiances were converted into

reflectance and brightness temperature (BT) at 5 km65 km resolution that were

utilized to reproduce a new cloud phase which is expected to be more consistent with

MODIS thin cirrus than current MODIS cloud phase.

MODIS cloud mask data (MOD35) include thin cirrus data determined by the

near-IR 1.38 mm band under daytime viewing conditions at 1 km61 km nadir

resolution (Ackerman et al. 2002). As mentioned in the introduction, RF1.38, a water

vapour absorption channel, is sensitive to the presence of thin cirrus clouds in the

upper troposphere, and its threshold can significantly improve the accuracy of

identifying thin cirrus clouds compared to methods based on Advanced Very High

Resolution Radiometer (AVHRR) data for all types of ground surfaces

(Hutchinson and Choe 1996, King et al. 1996). For the MODIS thin cirrus, low

and high reflectance thresholds (approximately 3.5%) are used to separate thin

cirrus from clear and thick (near-IR cloud optical depth .,0.5) cloud scenes

(Ackerman et al. 2002). Clear-sky pixels are identified if RF1.38 is less than 1.1% that

can be a low reflectance threshold (Roskovensky and Liou 2003). Hence, the

MODIS thin cirrus used in the study can be defined as thin cirrus (near-IR cloud

optical depth ,,0.5) in the upper troposphere. MODIS thin cirrus data are also

converted into thin cirrus at 5 km65 km resolution to be compared with MODIS

cloud phase at the same resolution.

The scenes of thin cirrus identified by RF1.38 in MODIS, in fact, include thin

cirrus overlying lower-level clouds. Those multi-layer cloud scenes should be

removed when cloud phase designed under the assumption of a single-layer cloud

column is compared to thin cirrus. The total-column cloud optical depth data in

MOD06 are used to support the information on the cloud overlap effect. The optical

depth data are determined by the combination of visible channels (0.6, 0.8 or 1.2 mm)

and a near-IR channel (2.1 mm) at 1 km61 km nadir resolution (King et al. 1997).

Using the optical data, either single-layer thin cirrus or thin cirrus overlying low-

level thin clouds (hereafter quasi-single layer thin cirrus) are distinguished from thin

cirrus overlying low-level thick clouds (t.,2.0), which may change near-IR

reflectance from the upper-layer thin cirrus.

Cloud phase data in the MODIS cloud product (MOD06) are used to examine the

proportion of ice phase to the thin cirrus having small total-column cloud optical

depth, i.e. quasi-single layer thin cirrus. The IR trispectral algorithm of MODIS

cloud phase retrieval operates different absorption characteristics of ice and water

clouds within the 8.5–13 mm region: the absorption ratios due to ice and water

clouds of the outgoing terrestrial radiation are nearly equal within the 8.5 and 10 mm

bands but diverge within the 10 and 13 mm bands. In other words, ice clouds have

greater values of absorption than water clouds at 11 and 12 mm (Baum et al. 2000).

Using these different physical properties of ice and water clouds, the MODIS used

BTD 8.6–11 mm and BTD 11–12 mm for detecting ice cloud (Platnick et al. 2003).

The thin cirrus obtained by 1.38 mm band in the MODIS cloud mask (MOD35),

therefore, may not be fairly consistent with the MODIS cloud phase that is accurate

only for thick clouds because of its current IR trispectral algorithm.

The MODIS cloud algorithm (both cloud mask and cloud product) has been

tested continuously since its introduction. As a result, some unresolved problems

have been discovered (see MODIS atmosphere website for detailed information).

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The MODIS cloud algorithm has been updated many times for improved handling

of the problems, but they still remain unresolved. In approaching a thin cirrus study

with awareness of these issues, the spatial and temporal scopes should be carefully

limited. The MODIS cloud algorithm is known to have the problem of the retrieval

of night-time pixels from regions such as coastlines, rivers, inland lakes, some

deserts, shadows, and polar regions (MODIS atmosphere website). However, this

issue is beyond our scope because night-time pixels are not dealt with in this study.

Some errors in the level-1b data are also known to be problematic in most of the

land areas (MODIS atmosphere website, in their known problems of the cloud

product). Particularly, band 26 (1.38 mm) has cross-talking problems, that is, a

fraction of 4–5 mm thermal radiation leaks into the 1.38 mm band; a fraction of the

1.24 mm radiation leaks into the 1.38 mm band, as well. Since the land surface is

bright at 1.24 mm, almost all the pixels over land have a 1.38 mm band apparent

reflectance greater than 0.5%. Thus, the pixels over the land can be mistakenly

classified as thin cirrus (MODIS atmosphere website). We dealt, therefore, with the

pixels over only a water surface background. Furthermore, we selected level 2 pixel

data to exclude the averaging effect and grid bias. We also sampled 693 data points

(spatial domains of about 1165 km61165 km) during 16 days in early–mid March

2000, which could be enough to eliminate the dependence on temporal and spatial

variations.

Meanwhile, most of the MODIS data are assigned to different validation levels by

quality checks. For the sampled data, the validation levels are relatively high. Cloud

mask data (MOD35) is validated stage 2 and cloud product data (MOD06) is

validated stage 1 for the selected date in this study (MODIS atmosphere website).

Validated stage 2 indicates that accuracy is assessed over a widely distributed set of

locations and time periods via several ground-truth and validation efforts. Validated

stage 1 indicates that the accuracy is estimated using a small number of independent

measurements obtained from selected locations and time periods and ground-truth/

field program efforts. Hence, our cloud mask data which will mainly be dealt with in

our study can be considered as having relatively accurate cirrus detection

information. In summary, rigorous conditions such as the validation level, land

surface effect, temporal or spatial variation, as well as grid or averaging bias are

carefully considered in the selection of the data for this study.

3. Current MODIS thin cirrus versus cloud phase

Figure 1 shows the Terra-MODIS images of RF1.38, thin cirrus by the RF1.38

threshold test, and total-column cloud optical depth. For example, three cases (0220

UTC 7, 0325 UTC 6 and 0310 UTC 1 March 2000) are selected and shown on panels

A, B and C, respectively. Panel A (east Asia, located in 34u–45uN and 118u–154uE)

is the scene of cirrus that may be formed by the upward motion of a mountain wave.

Panel B (the western Pacific, located in 5u–16uN and 99u–124uE) is the scene of

cirrus that may be detrained from the convection core. Panel C (the western Pacific,

located in 2u S–9uN and 100u–125uE) is the scene of cirrus that may also be

detrained from the eastward convection cluster. Areas A, B and C in the panels

indicate widely-spread thin cirrus scenes having small optical depth (figures 1(b) and

1(c)). We assumed that these scenes represent quasi-single layer thin cirrus clouds

(named in the data section) as the effect of overlying clouds is negligible. The pixels

corresponding to quasi-single layer thin cirrus take as much as 50% of the total

MODIS thin cirrus used in this study on average.

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The scenes of quasi-single layer thin cirrus are compared with their thermo-

dynamic phases which are retrieved by the MODIS IR trispectral algorithm. For the

areas A, B and C shown in figure 1, most clouds are identified as water or an

unknown phase, whereas they are distinguished as thin cirrus (see figure 4(b) later).

Besides, the large thin cirrus region over area A may not be considered as a cloud

region for the retrieval of cloud phase. This is because the possibility of cloud

existing in the region is determined as low through cloud mask tests performed

before the cloud phase retrieval. To develop these findings into generalized results,

we analysed quantitative features of the ice phase in quasi-single layer thin cirrus in

extended samples over 16 days as mentioned in the data section.

Figure 2 shows the ratios of MODIS ice clouds to the corresponding quasi-single

thin cirrus clouds. Considering such a case in which cloud phase retrieval is not

performed in the thin cirrus region, the ratio is calculated only for thin cirrus pixels

having cloud phase data. The 142 bars represent 5-min data (also called granules)

during 16 days in early–mid March. The granule has a spatial domain of about

2330 km63493 km as the swath width of MODIS is 2330 km. The granules are

sorted in ascending order by their thin cirrus fractions on the horizontal axis of

figure 2. The thin cirrus fraction is calculated as the ratio of quasi-single layer thin

cirrus to total area in the granule. In figure 2, no case has 1.0 (100%) ice phase. This

is because some thin cirrus clouds are identified as unknown phase instead of ice

phase. Only five cases have over 0.8 (80%) ice phase among 142 cases, and most

cases have less than 0.2 (20%). More than 30 cases have approximately 0% ice phase.

Figure 1. Terra-MODIS images of 1.38-mm reflectance (a), thin cirrus (b) and cloud opticaldepth (c) for 0220 UTC 7 (Panel A), 0325 UTC 6 (Panel B) and 0310 UTC 1 March 2000(Panel C). Areas A, B and C indicate where widely spread thin cirrus exists, and also the cloudoptical depth is less than 2.0.

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This illustrates well that MODIS thin cirrus still has severe inconsistency with its

phase.

This inconsistency is also shown in subdivided domains. Figure 3 shows the ratios

of MODIS ice phase to the corresponding quasi-single layer thin cirrus clouds for

their fractions in the subdivided domains. The ratio is also calculated only for thin

cirrus pixels having cloud phase data. For the thin cirrus fraction, the horizontal

axis is calculated in the same manner as for figure 2, so that a fractional value of

unity means that the sector is full of quasi-single layer thin cirrus clouds. This time,

693 cases are collected over 16 days in spatial domains of about 1165 km61165 km.

All cases are separated by location to confirm positional features. Thin cirrus may

have different dynamics in its occurrence, depending on location. The retrieval

accuracy of thin cirrus may also be affected by location as mentioned in the

introduction. Hence, the cases with latitude .60u, 30u–60u, ,30u in both

Figure 2. The ratios of MODIS ice phase to the corresponding quasi-single layer thin cirrusclouds. The bars represent 142 5-min data points over 16 days. The bars are sorted by theirthin cirrus fractions from the left to the right.

Figure 3. Scatterplots of the ratios of the MODIS ice phase to the corresponding MODISthin cirrus clouds versus their fractions. The 693 data points are plotted. The diamonds,squares, and circles indicate high latitude (60u. latitude), mid-latitude (30u–60u latitude) andthe tropics (,30u latitude), respectively.

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hemispheres are defined as high-latitude, mid-latitude, and tropical regions,

respectively. The numbers of cases examined are 58, 108, and 527 for high-latitude,

mid-latitude, and tropics, respectively. Most of the cases crowd around zero for the

ratio of MODIS ice phase in thin cirrus. This implies that the consistency of the

quasi-single layer thin cirrus with its phase needs to be strongly enhanced to attain a

1.0 ratio. The cases over the high latitudes are widely distributed. This is because

some pixels are quite contaminated by snow or ice and the quality of the phase

retrieval is not uniform. The cases over the tropics are also spread as widely as for

the high latitudes, but more values of the ratio are around zero. In the mid-latitudes,

most of the cases have relatively small ratios (about 0–0.3). This is because the

amount of thin cirrus overlying lower-level clouds may be smaller in the mid-

latitudes than in the tropics and its cloud phase is mostly detected as unknown

phase. As a result, the MODIS thin cirrus has the inconsistency with its phase

regardless of location. Moreover, the inconsistency is clearly revealed for any thin

cirrus fraction.

Likewise, through the analysis of daily MODIS gridded atmospheric data

(MOD08) obtained in 2000, it could be confirmed that the average of the ratio of ice

phase to cirrus is about 0.8 for the extreme cases in which the cirrus fraction is 1.0

for 1u61u resolution (not shown in this paper). However, its deviation is also very

large, that is, the current MODIS cirrus detection cannot lead to determination of

microphysical properties regardless of the cirrus fraction.

Figure 4. Cloud phase results obtained by the MODIS scheme (b) and the algorithm withadditional reflectance at 1.6 mm (a and c) for the corresponding periods of figure 1. Red, blue,white, yellow and black in figures 4(b) and 4(c) indicate ice, water, unknown, mixed phasesand clear sky, respectively.

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4. Assessment of MODIS thin cirrus with the reproduced cloud phase

Baum et al. (2000) presented that RF1.6 tends to be lower for single-layer ice clouds

than for water clouds in their radiative transfer calculations. Specifically, RF1.6 can

have a value less than about 0.1 (10%) for cirrus (ice) clouds regardless of changes in

the ice particle properties, while none has this for water clouds (Baum et al. 2000).

Besides, a recent study pointed out that RF1.6 for ice clouds can increase due to

overlying low-level water clouds (Pavolonis and Heidinger 2004). However, they

also showed that thin cirrus overlying low-level thin clouds (t,,2.0), i.e. quasi-

single layer clouds used in this study still have RF1.6 less than 0.1 (10%) with ascattering angle of 31.4u over the water surface (Pavolonis and Heidinger 2004, in

their figure 2). Hence, the criterion, 2.0 of total-column cloud optical depth to

identify quasi-single layer ice clouds in this study will prevent the original feature

shown in Baum et al. (2000) from increasing RF1.6 by the cloud overlap effect. Using

this feature, we added a simple test (equation (1)) to the MODIS IR trispectral

algorithm for the cloud phase:

RF1:6vsci ð1Þ

where sci is the threshold for determination of the ice phase. The threshold (roughly

0.1) is determined by the radiative transfer calculation by Baum et al. (2000). Thus,

the equation (1) is performed to identify the ice phase from cloudy pixels in

combination with BT 11 mm, BTD 8.6–11 mm and BTD 11–12 mm tests.

For preprocessing tests such as a scene type and a solar zenith angle check, input

data are provided from MODIS cloud mask data (MOD35). First of all, clear-skypixels are identified by the clear sky probability (.95%) in MOD35. Then, among

the cloudy pixels, the solar zenith angles in MOD35 are considered to filter out

night-time, shadow, dawn and twilight pixels. Next, the filtered cloudy pixels need to

undergo the combined cloud phase algorithm (IR trispectral and RF1.6 test). The

reflectance and the brightness temperatures for the algorithm are extracted in

MODIS calibrated radiance datasets (MOD02). Finally, the reproduced cloud phase

data have the same categories as MODIS such as ice, water, mixed and unknown

phases. Figure 4 shows RF1.6 (a), MODIS cloud phase retrieved by IR trispectralmethod (b) and the reproduced cloud phase by both IR trispectral method and

equation (1) (c), for the three cases of thin cirrus shown in figure 1.

Comparing the MODIS cloud phase with the one reproduced in the areas in

figure 4, it is clear that the new cloud phase has more ice cloud than that found by

MODIS (figures 4(b) and 4(c)). For thick cloud scenes, this increment is meaningless

because the threshold of equation (1) is not valid for a value of RF1.6 increased by

the cloud overlap effect. However, the areas A, B and C represent quasi-single layer

thin cirrus cases where RF1.6 may not be contaminated within the scope of 0.1. Inother words, the RF1.6 threshold is valid because the reflectance does not increase

noticeably (less than 0.1) due to overlying lower-level clouds as demonstrated by

Pavolonis and Heidinger (2004). This implies that the new phase retrieval algorithm

renders ambiguous pixels clearly and distinguishes the ice phase from the MODIS-

retrieved water phase for single-layer thin cirrus. In all areas where quasi-single layer

thin cirrus clouds exist over the ocean, the pixels are fairly well identified as ice

(figures 1 and 4(c)). On the other hand, MODIS cloud phases are detected as water

or unknown phases (figure 4(b)). The results give a great opportunity to improve theconsistency of thin cirrus detection because, theoretically, thin cirrus clouds must be

composed of ice crystals that originate from the freezing of supercooled water

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droplets. They can be analysed to verify the microphysical characteristic using the

recalculated cloud phase information.

The consistency of MODIS thin cirrus was examined with the reproduced cloud

phase. In the same manner as in figure 2, the ratios of the reproduced ice clouds to

the corresponding quasi-single thin cirrus of MODIS were represented by the

shaded bars in figure 5. In comparison with the ratios from the MODIS ice phase

(expressed as a white bar in figure 2), the ratios of the reproduced ice particles

increased to a great extent for all 142 cases. Specifically, about 0.60 (60%) were

enhanced from 0.18 (18%) to 0.78 (78%) on average (table 1). However, there is no

change regarding the standard deviation. The ratio of the reproduced ice phase

attains 1.0 (100%) for 13 cases, whereas no cases have 1.0 (100%) for the MODIS ice

phase (figures 2 and 5). The ratio also reaches 0.8 (80%) for 82 cases, while the

MODIS ice phase does so for only five cases (figures 2 and 5). The ratio increased by

more than a factor of 2 for 125 cases. The results can be regarded as having greatly

enhanced the consistency of the MODIS thin cirrus, allowing for the serious

inconsistency of that with MODIS ice phase.

In the same manner as in figure 3, the ratios of the reproduced ice phases in the

corresponding quasi-single layer thin cirrus clouds are calculated for the 693 cases

(not shown in the figure). The ratios increase without depending on location and

thin cirrus fraction. While the ratios obtained by the MODIS cloud phase crowded

around zero, the ratios calculated by the reproduced cloud phase have more values

Figure 5. The ratios of the reproduced ice phase to the corresponding quasi-single layer thincirrus clouds. The bars are depicted in the same manner as figure 2.

Table 1. Results from comparisons of the consistency of quasi-single layer thin cirrus withMODIS ice phase and the reproduced ice cirrus over the ocean. The number of samplesexamined is 58 for high latitude, 108 for mid-latitude, and 527 for the tropics. The parentheses

indicate maximum minus minimum values for the ranges.

ParameterMODIS icecirrus (A)

Reproduced icecirrus (B) B minus A

Average 0.183 0.782 0.599Average for high latitude 0.597 0.975 0.378Average for mid-latitude 0.035 0.772 0.737Average for tropics 0.155 0.701 0.546

Range 0–1 (1) 0–1 (1) (0)Range for high latitude 0–1 (1) 0.680–1 (0.320) (20.68)Range for mid-latitude 0–1 (1) 0–1 (1) (0)Range for tropics 0–0.950 (0.950) 0–1 (1) (0.050)

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spreading toward 1.0 for several cases. Table 1 shows the statistical results of the

distribution of the ratios calculated by the MODIS ice phase and the reproduced

one, respectively. Especially for the mid-latitudes, the shift is conspicuous. Most of

the ratios for the mid-latitudes were less than 0.3, but the newly calculated ratios by

the reproduced ice phase are widely distributed up to 1.0 (table 1). The increase of

the total average of the ratios is 0.599. This represents a remarkable enhancement

for the ratio of ice particles in quasi-single layer thin cirrus. Locally, the averages of

the ratios for the high-latitude, mid-latitude and tropical regions are increased by

0.378, 0.737 and 0.546, respectively (see table 1 for more details). Thus, most of the

cases have a similar size of increment on average.

However, an increase cannot be found for all cases, as can be demonstrated by

examining the range of the values. The range of the ratios of the MODIS ice phase is

the same as that of the reproduced ice phase (table 1). Although the averages of the

ratios increase, their ranges are not much changed. Since the minimum value of the

ratio for the high latitudes is somewhat increased from 0 to 0.68, the range is solely

decreased. This is because the enhancement may not be sufficient for the zero ratios

(table 1). Some cases that have no MODIS ice phase in thin cirrus cannot be

improved in their reproduced ice phase. Eventually, the shift in the range is hardly

shown.

5. Summary and discussion

MODIS thin cirrus is thought to be quite improved by using near-IR 1.38 mm

because the reflectance is sensitive to high ice clouds including semi-transparent

clouds. The thin cirrus appears bright in the 1.38 mm band, which possesses different

spectral features such as attenuation of radiance by water vapour absorption. Even

though the presence of thin cirrus becomes more accurate owing to the complement

of the RF1.38, it is still inadequate to explain the consistency of thin cirrus with its

phase retrieved by the MODIS algorithm. The MODIS algorithm of cloud phase

consists of three IR window bands, which weakly work for semi-transparent cloud.

Also, the IR trispectral cloud phase algorithm is designed to determine what the

most dominant cloud phase is within a single cloud column. Accordingly its results

may have good consistency with opaque cloud retrieved by the IR bands, but weak

consistency with thin cirrus by RF1.38 or thin cirrus overlying low-level clouds.

To eliminate thin cirrus overlying low-level clouds, only thin cirrus pixels having

total-column cloud optical depth less than 2.0 are dealt with in this study. Those

pixels take about 50% of the total cirrus clouds detected by the 1.38 mm band in the

MODIS cloud mask used in this study on average, so that the inconsistency related

to them is not negligible. As a result, only about 20% of the quasi-single layer thin

cirrus clouds have ice phases on average for the cases chosen in this study over 16

days. Therefore, these thin cirrus clouds need to be compared with the newly

reproduced cloud phase.

The newly retrieved ice phase compensates for the inconsistency of the MODIS

single layer thin cirrus detection with its phase. Through the addition of the RF1.6

test to MODIS IR trispectral methods for the reproduced cloud phase, about 80% of

the thin cirrus pixels could be identified as ice phase (table 1). Comparing with the

percentage by MODIS cloud phase, approximately 60% of the ice fraction in thin

cirrus is increased by the new phase. The increase is revealed for subdivided domains

with smaller size as well as the original domain of MODIS 5-min data. The

increase can also be shown for all locations over a water surface: the high latitudes,

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the mid-latitudes and the tropics (table 1). The new scheme adding the RF1.6 may

not be fully tested or effective for all cloudy pixels because we do not focus on the

development of the new algorithm but the consistency between two cloud products

in this study. Also, the consistency between two products does not guarantee that

these products are correct.

The range of the ratio still remains from 0 to 1 because some extremely poor cases

that have no ice phase in thin cirrus clouds may not be enhanced by the reproduced

ice phase (table 1). This lack of enhancement for the extreme cases requires highly

sensitive work to have great confidence in the calculation. Moreover, there still

remains a 20% increase in the ice phase in the single-layer thin cirrus and the

consideration of the cloud overlap effect for further study.

Thin cirrus combined with the newly calculated cloud phase may have a greater

impact on the global radiation budget in comparison with recent climate or cloud

dynamics studies mentioned in the previous section. By considering other onboard

satellite sensors and algorithms, it may not only improve the consistency of MODIS

results but also present a bias towards other satellite products. Besides, the

increment of the new ice phase is not proportional to the present MODIS data. In

other words, it does not increase linearly due to the addition of the 1.6 mm band

because it depends so much on spectral and atmospheric conditions. Hence, further

work is needed to clarify such a credible relationship between thin cirrus and other

cloud products such as cloud top properties, cloud optical depth and effective

radius.

Acknowledgments

This study was undertaken for the project Technical Development for Remote

Sensing Meteorology and the Communication, Oceanography and Meteorology

Satellite funded by the Korean Meteorological Administration. The first author is

supported by the BK21 project of the Korean government. The MODIS data were

provided by the Earth Observing System Data and Information System, Distributed

Active Archive Center, at Goddard Space Flight Center, which archives, manages

and distributes these data. The authors especially thank Dr M. D. Chou and Dr H.

J. Lutz for support and advice.

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