The transition of cloud types from stratocumulus to cumulus over ocean has ... we only present results for the Atlantic regions, which were within the Meteosat-9.
MULTI-SENSOR ANALYSIS OF CLOUD-TOP HEIGHT ALONG SC TO CU TRANSITION TRAJECTORIES Elke Ludewig and Ákos Horváth Max Planck Institute for Meteorology, Bundesstraße 53, 20146 Hamburg, Germany Abstract Cloud-top height (CTH) retrievals by different satellite instruments were analysed over stratocumulus (Sc) to cumulus (Cu) transition regions in the Atlantic and Pacific Ocean. Our analysis along representative Sc to Cu transition trajectories calculated the difference statistics between the CALIOP, MODIS, MISR, and SEVIRI sensors. With the exception of MODIS Collection 5, all datasets showed an increase in CTH from stratocumulus to cumulus. We introduced modifications to MODIS and MISR retrievals that lead to improved CTHs compared to the reference CALIOP data. The correlation between CALIOP and SEVIRI were comparable to those between CALIOP and modified MODIS and MISR, but SEVIRI CTHs were mostly biased high.
INTRODUCTION The transition of cloud types from stratocumulus to cumulus over ocean has recently aroused the interest of the modeling community (Sandu et al., 2010), because these clouds have a significant effect on the earth‘s radiation budget. Prompted by this, we analyzed satellite retrieved cloud-top heights along trajectories from unbroken sheets of Sc to fields of scattered Cu. Such transitions systematically occur in the northeast and southeast Atlantic and Pacific as boundary-layer air masses are advected equatorward by the trade winds, mostly during the summer months. We evaluated a suite of satellite sensors comprising CALIOP, MODIS, MISR, and SEVIRI on Meteosat-9 and also tested different methods to improve the retrieved CTHs. The Sc to Cu transition (SCT) was represented by a median trajectory computed by HYSPLIT, along which the CTHs were statistically compared. Here, we only present results for the Atlantic regions, which were within the Meteosat-9 coverage. First, we give a short overview of the study areas and time periods. Then, description of the used sensors and datasets follow, including retrieval and sampling issues. Finally, we summarize our main results.
STUDY AREAS Following Sandu et al. (2010) and based on the availability of Meteosat-9 CTH data, our investigation time period included the summer months of 2006-2009: June, July, August (JJA) for the north Atlantic (NA) investigation area and September, October, November (SON) for the south Atlantic (SA) region (see Figure 1). To evaluate CTH retrievals, we calculated 1°x1° mean-maps over these time periods and regions, and from each map we selected the CTHs that corresponded to the longitude and latitude positions of the Sc to Cu transition trajectory. Figure 1. Mean MODIS cloud fraction for JJA and SON 2006-2009 over our stratocumulus to cumulus transition areas.
STRATOCUMULUS TO CUMULUS TRANSITION TRAJECTORIES As in Sandu et al. (2010), the Hybrid Single-Particle Langragian Integrated Trajectory (HYSPLIT) model was used to compute the stratocumulus to cumulus transition trajectories (SCTT). More than 10,000 trajectories of individual air parcels were calculated, all placed within the boundary layer, started at 11 am local time and tracked for six days (144 hours). It was found that results from individual trajectories could be well represented by a single median trajectory. Therefore, the median of these trajectories for each area defined our SCTT along which the analysis of satellite CTHs was performed.
SENSORS AND DATASETS The multi-sensor analysis included CTH Level 2 data from CALIOP, MISR, SEVIRI on Meteosat-9, and MODIS, described below. CALIOP aboard CALIPSO obtains high vertical-resolution lidar profiles at two wavelengths: 1064nm and 532 nm. The instrument only allows nadir viewing with a footprint of 70 m and sampling distance of 330 m along the track. Here, the Level 2 cloud layer classification product with a horizontal resolution of 1 km and vertical resolution of 60 m was used (Version 1 for 2006 and Version 2 for 2007-2009). Due to its active and highly accurate retrieval technique, CALIOP provided our reference CTHs. The persistence of the Sc to Cu transition during the summer months and the small day-night contrast in retrievals allowed the combination of day and night time data, which reduced noise due to the relatively poor sampling of CALIOP [Ludewig, 2010]. The Multi-angle Imaging Spectroradiometer, MISR, is a pushbroom scanner aboard Terra. MISR consists of nine discrete cameras gathering data in four spectral bands. A single camera points to nadir, while four cameras point in the forward and another four point in the backward direction along the satellite’s track. MISR CTHs are calculated through a purely geometric stereoscopic technique. A caveat to consider is that the motion of the cloud along the track also causes a disparity in addition to the height of the cloud. Neglecting the along-track cloud motion would bias the stereo cloud top height retrievals, therefore, the final CTHs are corrected for along-track winds. Here, MISR Level 2 Version F008-17 CTHs were used. SEVIRI is an optical imaging radiometer aboard the Meteosat-9 geostationary satellite. SEVIRI cloudtop products contain information on cloud-top temperature and cloud-top height for all pixels identified as cloudy in the satellite scene. The product combines measurements and model calculations to obtain cloud parameters. The cloud-top height product (converted from cloud-top pressure) is primarily derived from the IR brightness temperature and CO2-slicing methods, using vertical temperature and humidity profiles from numerical weather forecasts and a radiative transfer model. MODIS is a passive imaging spectroradiometer with 36 spectral bands aboard Aqua and Terra. Level 2 Collection 5 cloud products from both Aqua (MYD06) and Terra (MOD06) were included in our analysis. MODIS provides cloud-top pressures calculated by the window channel IR equivalent blackbody brightness temperature and CO2-slicing methods. While CALIOP, MISR, and Meteosat-9 provided geometric CTHs, the MODIS product contained cloud-top pressures (CTPs). To facilitate comparison, MODIS CTPs were converted to CTHs using ERA-Interim geopotential heights. A well-known limitation of the MODIS window channel IR equivalent blackbody brightness temperature method arises from its top-down approach of analyzing the temperature profile, which can lead to severely overestimated heights in case of low-level temperature inversions. Due to the frequent occurrence of low-level temperature inversions during the first three days of the transition (see Figure 2), a strong discrepancy existed between MODIS and the other sensors. Compared to the reference CALIOP instrument differences of several hundred meters were noted. To correct these artifacts, we tested three methods that were based on interpreting the difference between cloud-top temperature (CTT) and surface temperature (Tsurf = SST-1K) using various lapse rate (Γ) formulations. The best results were obtained from the method of Wang et al. (1999), where CTH depends linearly on the CTT (from MODIS) - Tsurf (from TMI and AMSR-E) difference and Γ (for other methods, see Ludewig, 2010).
(1)
Equation (1) was used in case of low-level temperature inversions (temperature difference between top and bottom of inversion ≥ 3 degrees) as obtained from ERA-Interim temperature profiles, otherwise the operational MODIS cloud top height was used. This hybrid MODIS CTH product was used for further analysis.
Figure 2. a) Mean inversion strength in the south Atlantic region, as identified by ERA-Interim. (b) The black solid line shows the mean CALIOP CTH along the south Atlantic transition trajectory and the grey solid line is the operational MODIS CTH. The red dotted line gives CTHs using equation (1). The red solid line refers to hybrid CTHs, which combine operational MODIS CTHs and equation (1) in case of low-level temperature inversions.
SAMPLING ISSUES Differences in mean CTH could arise because there were considerably fewer CALIOP observations than MODIS, MISR, or Meteosat-9 measurements in a 1°x1° gridbox. In order to estimate the magnitude of such spatial sampling effects we compared MODIS, MISR, and Meteosat-9 gridboxmean CTHs obtained by averaging all available observations with gridbox-mean CTHs obtained by averaging observations along the CALIOP track only. An example is given in Figure 3 for MODIS and MISR (similar results were found for Meteosat-9 as well). As shown, differences between the full and sub-sampled gridbox-mean CTHs were generally small (rmsd of 240 m for MODIS and 65 m for MISR) and fluctuated around zero, with perhaps the exception of the very end of the transition trajectory. Therefore, the spatial sampling effects introduced only small biases in mean CTHs (130 m and 10 m for MODIS and MISR, respectively). We also investigated temporal sampling effects due to the time difference between Aqua, Terra, and Meteosat-9 observations. Results showed that the transition was not significantly affected by the diurnal cycle [Ludewig, 2010] and, consequently, temporal sampling biases were also small.
Figure 3. Spatial sampling effects in the south Atlantic transition region. (a) The black dashed line shows the mean CALIOP CTH, the blue solid line is the operational MODIS CTH, while the red solid line corresponds to the operational MODIS CTH sub-sampled along the CALIOP track. The sampling bias, that is, the difference between the blue and red curves, is shown in green. (b) Same as (a) but for MISR.
EVALUATION OF CTHS ALONG TRANSITION TRAJECTORIES Our final multi-sensor analysis consisted of four data sets: CTHs from CALIOP, modified MODIS, operational MISR, and SEVIRI. Figure 4 depicts these CTHs along the median Sc to Cu transition trajectories of the two investigation areas in the north and south Atlantic. Basic comparison statistics are also summarized in Table 1. In both regions the SCTTs showed an increase in CTH, especially in SA over the first three days. The slope of the rise in CALIOP CTH was ~5 m/hour, in operational MISR ~6 m/hour, in MODIS Aqua and Terra ~4 m/hour and ~9 m/hour, respectively, and in SEVIRI ~10 m/hour. In the NA area only CALIOP and SEVIRI indicated a positive CTH trend, while MODIS and MISR did not identify a clear transition in CTHs. In the SA area overall correlations between CALIOP and MODIS CTHs were 0.70 for Aqua and 0.76 for Terra, respectively. While the correlation between CALIOP and the operational MISR CTHs was relatively small (0.46) over the whole transition trajectory, over the first three days we found a high correlation of 0.79 and a small bias of -45 m. The correlation between CALIOP and MODIS in the first three days was even higher (0.87) with biases similar to MISR. SEVIRI CTHs showed a high correlation with CALIOP: 0.72 over the whole transition and 0.87 over the first three days, but they showed a large negative bias of about 300 m, especially at the beginning of the trajectory. This strong bias, which can also be seen in the NA region, may be due to the SEVIRI CTH algorithm. Biased CTH can be retrieved if the cloud type is wrongly classified or the used NWP profiles are of poor quality. Mean CTHs could also be affected by sampling issues because SEVIRI does not provide CTHs if a cloud is classified as fractional [CMS SAF, chapter 4.3]. In the NA region the results were much less conclusive. Here, CALIOP’s signal was very noisy; nevertheless, it showed an increase in CTH over the first three days with a slope of ~4 m/hour. Afterwards, CTHs were more or less constant at around 1500 m but with fluctuations of 200-400 m. Up to day four MISR and MODIS showed a slight increase and nearly constant CTHs, respectively, but then MISR CTHs rapidly dropped while MODIS Terra CTHs increased. MODIS Aqua, on the other hand, tended to slowly decrease along the entire trajectory. SEVIRI showed a steady increase of ~900 m over the whole transition. Although MISR CTHs were relatively close to CALIOP ones, after day four all sensors had a generally worse agreement with CALIOP. Within the first 72 hours we observed better correlations with CALIOP: 0.42 for MISR, 0.59 for MODIS Terra, and 0.62 for SEVIRI. Interestingly, MODIS Aqua did not show better agreement with CALIOP than MODIS Terra, despite its close retrieval time to CALIOP. We note that the MODIS data displayed here corresponded to the hybrid dataset employing the Wang et al. (1999) modification in case of low-level inversions. The correspondence between the operational
Collection 5 MODIS retrievals and CALIOP measurements was significantly worse. Considering only operational data, MISR CTHs were almost always better correlated with CALIOP ones and gave a nearly constant bias. Therefore, we concluded that overall MISR retrievals were in the best agreement with the reference lidar heights.
Figure 4. Mean CTH transition trajectories of CALIOP (black), operational MISR (red), MODIS Aqua/Terra (dark blue/cyan), and SEVIRI (green) for the NA and SA regions over the summer months in 2006-2007.
Table 1. Basic CTH comparison statistics for the NA and SA regions over the summer months in 2006-2007. CALIOP to Statistics for area NA, JJA 2006-2007 Statistics for area SA, JJA 2006-2007
MODIS aqua MODIS terra MISR SEVIRI MODIS aqua MODIS terra MISR SEVIRI
CORRELATION (144h/72h) -0.04 0.13 0.34 0.59 -0.02 0.42 0.25 0.62 0.70 0.87 0.76 0.87 0.46 0.79 0.72 0.87
BIAS [m] (144h/72h) 299.69 266.54 192.23 278.45 -5.26 -188.59 -164.19 87.91 82.47 10.54 -46.53 -2224 -45.29 -192.26 230.54 313.10
RMSD [m] (144h/72h) 350.65 312.78 266.00 308.92 283.83 241.74 360.49 171.76 210.36 62.79 198.36 112.73 210.81 209.22 312.18 333.31
CORRECTION OF MISR CTHS WITH METEOSAT-9 WINDS The operational MISR CTHs are derived by correcting raw stereo CTHs with along-track winds also derived from MISR observations. Alternatively, it was possible to use the corresponding collocated Meteosat-9 winds for such cloud-motion correction. These modified wind-corrected MISR CTHs were calculated by the following equation: with a height correction factor hcf of 92.5 m per one m/s along-track wind. These modified MISR CTHs using Meteosat-9 winds are shown in Figure 5.
Figure 5. Transition trajectories for MISR CTH products compared to CALIOP (black solid) in the SA region for SON 2006-2009: raw uncorrected MISR CTH (violet dotted), operational MISR-wind-corrected MISR CTH (red solid), and Meteosat-9-wind-corrected MISR CTH (blue solid).
Comparison between CALIOP and the operational and modified MISR CTHs revealed an improvement due to using Meteosat-9 winds instead of MISR winds, at least in the SA region. Here, the correlation between CALIOP and operational MISR CTHs over the transition trajectory was 0.46, while for corrected MISR CTHs using Meteosat-9 winds the correlation increased to 0.73. The bias was also reduced from 45 m to 18 m and the rmsd from 211 m to 158 m. The CALIOP-MISR comparison improved not only along the transition trajectory but also over the whole SA region, with an increase in correlation by 13%. In particular, the area around the starting point of the transition trajectory showed Meteosat-9-corrected MISR CTHs nearly identical to CALIOP CTHs. The use of Meteosat-9 winds for the MISR CTH correction had an additional positive side effect. One MISR path consists of 180 blocks, with each block containing two rows divided into eight cross-swath domains of 70.4x70.4 km2. A previous investigation by Lonitz and Horváth (2011) found a systematic bias in cloud-motion wind, and hence, cloud-top heights, across the MISR swath from west (domain 2) to east (domain 7). Along the transition trajectory, this results in variations of ~800 m in mean MISR CTH when only one cross-swath domain is used for averaging (see Figure 6). In case of Meteosat-9 wind-corrected MISR CTHs this cross-swath dependence was largely eliminated, because Meteosat-9 winds were very consistent across the MISR swath. The MISR cross-swath effect could also be seen over the whole SA region (see Figure 7). Compared to CALIOP, operational MISR CTHs had larger biases, especially at the eastern edge of the swath, than Meteosat-9-corrected MISR CTHs, which did not show a cross-swath dependence. We note that in the NA region Meteosat-9 winds did not improve the CALIOP-MISR CTH comparison, because MISR wind biases were not the major error source.
Figure 6. Dependence of mean MISR CTH on cross-swath location. In the SA region, operational MISR CTHs (a) showed a systematic bias across the swath from west (domain 2) to east (domain 7). Using Meteosat-9 winds for CTH correction significantly reduced this bias (b).
Figure 7. Mean difference map between CALIOP CTHs and (a) operational MISR and (b) Meteosat-9-corrected MISR CTHs in the SA region.
SUMMARY Cloud-top height retrievals from MODIS, MISR, and SEVIRI were compared to highly accurate CALIOP lidar heights in warm (liquid) marine boundary layer clouds. In case of low-level temperature inversions, MODIS Collection 5 brightness-temperature based CTHs showed very large overestimations. This issue could be mitigated by deriving CTHs from differences between MODIS cloud-top temperatures and sea surface temperatures assuming various lapse-rate formulations, such as Wang et al. (1999). The best overall agreement with CALIOP was found for a hybrid MODIS dataset, which combined operational CTHs and lapse-rate-based ones over inversions. MISR stereo CTHs, on the other hand, were sensitive to errors in the along-track wind. When MISR wind retrievals were known to be biased, use of Meteosat-9 winds lead to significant improvements in MISR CTHs, with an increase in correlation of 13% over the entire SA region and of 30% along the Sc to Cu transition trajectory, as compared to the operational MISR product. In addition, the Meteosat-9 wind correction reduced the known cross-swath bias in operational MISR CTHs. After the MODIS CTH modifications, all sensors showed an increasing CTH along the transition trajectory in the south Atlantic region. Results in the north Atlantic transition area were inconclusive,
with no clear tendency in most CTH retrievals. Considering only operational retrievals, MISR CTHs indicated the best overall agreement with the reference CALIOP values. Although SEVIRI CTHs showed the sharpest increase along the transition trajectory in both regions, they tended to be considerably biased relative to CALIOP, MISR, and MODIS values.
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