Summary The present report describes one possible way to correct radiometric measurements of the SSM/I (Special Sensor Microwave Imager) at 85.5 GHz f

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1 Compensating for atmospheric eects on passive radiometry at 85.5 GHz using a radiative transfer model and NWP model data Stefan Kern Institute of Environmental Physics University of Bremen, Bremen, Germany Tel.: , Fax: skern@thor.physik.uni-bremen.de

2 Summary The present report describes one possible way to correct radiometric measurements of the SSM/I (Special Sensor Microwave Imager) at 85.5 GHz for the atmospheric eect enhancing its potential for sea ice edge detection. Data used in this study are swath data from the SSM/I and model data from the Danish NWP model HIRLAM for the North Atlantic region. First the low frequencies of the SSM/I, i. e. 19, 22, and 37 GHz, were used to retrieve the elds of the surface wind speed, v, the integrated total water vapor, w, and the cloud liquid water path, c lwp. The retrieved elds were compared to the modeled after gridding them onto a 2525 km 2 grid. The comparison reveals correlations over the open water of approximately 0.9 for w, 0.65 for v and mostly far below 0.5 for c lwp. Therefore only the model elds of w and v were used for the correction. Usage of the radiative transfer model MWMOD provides sensitivities of the measured brightness temperature to w of 2.3 K per kgm ;2 at horizontal and 0.8 K per kgm ;2 at vertical polarization over the North Atlantic. The sensitivity of the brightness temperatures to v is non-linear. As the polarization ratio at 85.5 GHz (85) is most suitable for the detection of the sea ice edge the sensitivities have been expressed in terms of this quantitiy. A comparison of the uncorrected with the corrected 85 maps using the sensitivities derived with MWMOD and the modeled elds provided by HIRLAM shows that most features in the maps of the uncorrected 85 that can be adressed to high valued elds of w and v over the open water have vanished. Remaining features often seem to be caused by the c lwp. But due to the bad correlation between the modeled and the retrieved elds of c lwp its eect remains uncorrectable so far and as the remaining features coincide more with the retrieved c lwp using the latter seems to be more promising in future. 1 This work was performed at the Danish Meteorological Institute (DMI) within the Visiting Scientist Program of the SAF O&SI, METEO FRANCE, in April/May

3 1 Introduction Since 1987 the complete globe is monitored by the passive microwave sensor SSM/I (Special Sensor Microwave Imager) on board the DMSP satellite series measuring the brightness temperatures at the frequencies of 19.35, , 37.0 and 85.5 GHz. The coverage of the polar regions is better than one per day. Most of the currently used ice concentration algorithms are based on the brightness temperatures measured at the frequencies of 19 and 37 GHz, e.g. the NASA-Team [Cavalieri et al., 1991], [Heygster et al., 1996] or the BOOTSTRAP algorithm [Comiso and Sullivan, 1986], although the 85.5 GHz channels would allow for twice the spatial resolution of the lower ones. This is due to the atmospheric eect and has been investigated quantitatively for the Arctic with the radiative transfer model MWMOD (MicroWave MODel), e. g. [Fuhrhop et al., 1997]. Following that study an increase of the brightness temperatures at 85.5 GHz over open water of about8and20kper10kgm ;2 w and of about 5 and 14 K per 100 gm ;2 c lwp could be expected for vertical and horizontal polarizations, respectively. Therefore regions with high values for w and c lwp should exhibit higher brightness temperatures than those with lower values. Following Lomax et al. [1995] and Lubin et al. [1997] the polarization at 85.5 GHz, 85, is suitable for the sea ice edge detection as well as the sea ice concentration retrieval. The polarization is dened by =(T v ; T h )(T v + T h ) ;1 (1) where the indices v and h denote vertical and horizontal polarization, respectively. Therefore the brightness temperatures at both polarizations have to be corrected for the atmospheric eect if the 85 will be used for sea ice detection. As the extinction due to water vapor and hydrometeors has a depolarizing eect and therefore the 85 shows low values over open water in areas with high w and/or c lwp, this correction should result in an increase of the 85. The following two sections will show the work steps required for the correction, the derived sensitivites, and maps of the atmospheric quantities and the raw as well as the corrected Data comparison Data used were SSM/I swath data and data from the Danish NWP model HIRLAM. First the brightness temperatures measured at the low frequencies of the SSM/I, i. e. 19, 22 and 37 GHz, were used to retrieve v, w and c lwp. For v an algorithm from Lo [1983] was used. w was calculated using an algorithm developed by Simmer [1994] whereas for c lwp the algorithm from Karstens et al. [1994] was selected. Those algorithms have been used in many applications and works concerning the retrieval of atmospheric parameters in polar regions, e. g. [Thomas, 1998], [Oelke, 1996], and reveal accuracies of 2ms ;1 for v, 1.4 kgm ;2 for w, and30 gm ;2 for c lwp. Due to the high variability ofthemicrowave emissivities over sea ice compared to the open water those algorithms only work over open water with the mentioned accuracy. For a reasonable sea ice detection a correction of the polarization ratio in the marginal ice zone is of crucial importance. Usage of elds of v, w and c lwp provided from NWP models could help overcome the lack of data in polar regions over the sea ice. The model used in this report is the Danish NWP model HIRLAM which gives the data base for the present Danishweather forecasting. It is a grid point model covering most parts of the northern hemisphere north of 40 degrees latitude with a horizontal resolution of about 0.45 (approx. 50 km), 31 vertical levels, and uses Eulerian dynamics. Boundary conditions are given by ECMWF forecasts, which are 2

4 received by the model twice aday, whereas every six hours a new surface analysis is used. For each level the water vapor content and { since February 1999 { the liquid water content can be put out every hour and integrated to w and c lwp. The surface wind speed v is given by the model separately for the open water and the land surface. In this report v over open water was used. The model data have a spatial resolution of approximately km 2 whereas the brightness temperatures at 85.5 GHz and therefore the 85 is sampled with km 2 spatial resolution. To use the model elds for the correction of the 85 a careful comparison between the modeled and the retrieved atmospheric elds has to take place.for this purpose the model elds are interpolated onto a km 2 grid, which equals the resolution of the retrieved atmospheric elds. Furthermore an ice-ocean mask was used to exclude all pixels with a non-zero probability of sea ice and make sure that the retrievals are not biased by sea ice. To investigate a representative dataset it was decided to use data from all seasons. The above mentioned quantities have therefore been retrieved for 10-day periods in July and October 1998 and January and April For each swath covering the area of interest, i.e. the North Atlantic including the Kara-Sea and the Ban Bay, a correlation between the modeled and retrieved elds was performed. An example for the data sets used and the correlation are shown in Figure 1 for the SSM/I overight at 8:00 GMT on 14 April The correlations shown in Figure 1 are representative for w and c lwp only. The value for v is close to its minimum correlation. Mean correlations using data from 11 April to 20 April 1999 are about 0.9 for w, 0.65 for v and 0.2 for c lwp, exhibiting the greatest amplitude for c lwp and the lowest one for w. This agrees on the one hand to the natural variability ofthe quantities investigated, which is certainly greatest for the c lwp. On the other hand the coarser spatial resolution of the model as well as the averaging over one time step may smooth extrema and erase small-scale features. This and the fact that the SSM/I sensor rather monitors the immediate impact of the wind on the sea surface than the mean wind speed given by the model may cause the somewhat unexpected low correlations between the wind elds. Furthermore pixels containing land lead to unrealsitic values for the retrieved elds as the emissivity is not constant over the sensor's footprint, causing a higher brightness temperature. This can be seen in the rst row of maps near Iceland and is represented by the outliers in the correlation scatter plots, e. g. probably all values of the retrieved v exceeding 20 ms ;1 and those values of the retrieved w exceeding 15 kgm ;2, which coincide with the modeled w less than 8 kgm ;2. These correlations in conjunction with the availability ofmodeledc lwp only after February 1999 leads to the conclusion that w is best for the correction of the 85, followed by v. The mostly poor correlation between the elds of c lwp indicates that this quantity shall not be used here. However, this must not exclude its usage for a correction. Especially for the operationally sea ice prediction on a daily basis amounts of c lwp up to 1kgm ;2 can occur in regions of cyclonic activity leading to areas of low 85 over the open water which might cause spurious ice concentrations up to 50 %. 3

5 Figure 1: 14 April 1999, 8:00 GMT: Each column, from the top to the bottom: color bar for the rst two maps, color bar for the third map, correlation between and scatter plot of the modeled and the retrieved elds, map of the retrieved eld, map of the modeled eld, map of the dierence (retrieved ; modeled) from the left to the right: v in ms ;1, w in kgm ;2, and c lwp in kgm ;2. Land areas appear black, regions outside the swath white. Parts of the ice-ocean mask used can be seen for instance o the East coast of Greenland, centered in the middle of each map. 4

6 3 Correction of the atmospheric eects For the correction of the 85 two sensitivities were calculated using the radiative transfer model MWMOD. For the sensitivity of the surface wind speed MWMOD runs were performed for wind speeds ranging from 0 to 40 ms ;1, using steps of 1ms ;1, a constant sea surface temperature (SST) and an atmosphere with w and c lwp set to 0kgm ;2. To account for the dierent SSTs within the area of interest 272 K and 287 K were used. The resulting brightness temperatures were then converted to the 85 using (1) and a polynomial t was introduced. The best t between the 85 and v was achieved using 85 = v= Bv + Cv 2 + Dv 3 (2) with the coecients B...D shown in Table 1 for 272 K and 287 K. The corrected value for 85 will be obtained by solving (2) for 85 v=0, which corresponds to the 85 with v equaling zero, and by putting in the modeled v and the values for 85, which are measured or might be corrected to an other atmospheric eect. Due to the correlation between the measured brightness temperatures and the SST the value for 85 v=0 at 287 K is about 13 % higher than the one at 272 K. This dierence remains as high as 10 % up to wind speeds of 20 ms ;1 before it decreases. Therefore correcting the 85 using (2) and the coecients for a SST of 272 K (Table 1) will probably result in an undercorrection, i. e. underestimation of the 85 far o the ice edge but will reveal best results close to it. Table 1: Coecients for the correction of the 85 to v. SST v=0 85 B C D 272 K e ; e ; e ;7 287 K e ; e ; e ;7 Though MWMOD oers the possibility towork with articial proles of w it was decided to use w given by HIRLAM for the calculation of the sensitivities of 85 to w. Two areas, each consisting of approximately 1000 pixels, within one SSM/I swath covering dierent SST-regimes were selected to account for an eventual correlation between the SST and the w. For each pixel the atmospheric proles of temperature, pressure, and humidity aswell as the SST are fed into MWMOD. The surface wind was set to 0ms ;1 to exclude its inuence. Sensitivities were achieved which were comparable to those published by Fuhrhop et al. [1997]: an increase of the brightness temperature of 8 K and 24 K per 10 kgm ;2 total water vapor for vertical and horizontal polarization, respectively. The sensitivity becomes non-linear when expressed in terms of 85, where again a polynomial t has to be introduced with the coecients shown in Table 2 and the equation Table 2: Coecients for the correction of the 85 for w. w=0 85 B C D E e ; e ; e ; e ;9 85 = w= Bw + Cw 2 + Dw 3 + Ew 4 (3) which can be solved for w=0 85 giving the 85 corrected for the inuence of w. 5

7 Figure 2: 14 April 1999, 8:00 GMT: Starting counterclockwise at upper left panel: raw 85, and, di erence between 85 corrected for, 85 corrected for, 85 corrected for -corrected and raw 85, and di erence between -corrected and raw 85. The color bar ranges from 0 to 0.24 for panels showing the 85 's and from 0 to 0.12 otherwise. w w v w v 6 v

8 Table 2 shows that in this case, i. e using measured data, 85 w=0 lies between the two values of 85 v=0 shown in Table 1. This seems to be realiable as the two selected areas exhibit SSTs between 275 and 285 K. Then the 85 was calculated and corrected for the inuence of v, w, and v and w for each swath covering the area of interest for the April period. Figure 2 shows an example for the SSM/I overight at 8:00 GMT on 14 April Following the color bar low values for the raw 85 (upper left panel) can be seen over areas usually covered with sea ice and over land. Low values can also be seen in the southwestern corner of the swath and around Iceland and can certainly be adressed to atmospheric eects. This is conrmed by Figure 3, which shows the OLS-images of the same overight. The sea ice extending along the East coast of Greenland and in the Svalbard region can be seen as well as the dense cloud cover, extending from Cap Farvel to the East, and the patchy-like cloud structures south of Iceland.