Impact of Blackbody Warm-Up Cool-Down Cycle on the Calibration of Aqua MODIS and S-NPP VIIRS Thermal Emissive Bands
This paper evaluates the calibration quality during the blackbody (BB) warm-up cool-down cycle for thermal emissive bands onboard Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) and Suomi National Polar-orbiting Partnership (S-NPP) Visible Infrared Imaging Radiometer Suite (VIIRS). This evaluation utilizes data from Aqua MODIS Collection 6 Level-1B products and VIIRS Sensor Data Records in 6-min granule format provided by the NASA Land Science Investigator-led Processing System. Nearly simultaneous hyperspectral measurements from the Aqua Atmospheric Infrared Sounder (AIRS) and the S-NPP Cross-track Infrared Sounder (CrIS) are used as references for MODIS and VIIRS, respectively. Each AIRS footprint of 13.5 km is co-located with multiple MODIS pixels while each CrIS field of view of 14 km is co-located with multiple VIIRS pixels. The corresponding AIRS-simulated MODIS and CrIS-simulated VIIRS radiances are derived by convolutions based on sensor-dependent relative spectral response functions. In this paper, the analysis mainly focuses on the bands that are used in sea surface temperature products. The results show that there is virtually no impact for MODIS bands 22 and 23 and bands 31 and 32 for a BB temperature below 290 K; however, when the BB temperature increases above 290 K, the impact is up to 0.3 K for bands 22 and 23 and 0.05 K for bands 31 and 32, respectively. For VIIRS, BB temperature-dependent drifts are observed in M15 and M16, which can reach 0.15 and 0.1 K, respectively, over the operational BB temperature range and the VIIRS brightness temperature range.
Long term temporal trends and spatial distribution of total ozone over Pakistan
Considering the potential importance of the concentration of ozone in the atmosphere and threat to its depletion in Pakistan’s environment, AQUA-AIRS Level-3 Daily Global satellite data is used to monitor the Total Column Ozone (TCO) over the entire region of the country. During 2003–2011 with spatial res- olution of 1ox 1o lat/long grid, inter-annual analysis of TCO over the area (62°-76°E and 23-37N) showed that overall average distribution of TCO alterations are dependent on latitude and varied from 275 to 278 DU in the regions of Sindh and Baluchistan province with 297–300 DU in the northern and KPK province regions. Seasonal variations have shown that in the region 23°-29N, highest concentration of ozone is recorded in summer season (JJA) and lowest in winter season (DJF) with mixed trend in both spring (MAM) and autumn (SON) seasons whereas in the region between 30°-37°N, maximum is recorded in winter (DJF) and spring (MAM) seasons with minimum in summer (JJA) and autumn (SON) seasons respectively. Statistical analysis revealed that linear relationship exists between year to year TCO and solar activity.
MJO-related intraseasonal variation in the stratosphere: Gravity waves and zonal winds
Previous work has shown eastward migrating regions of enhanced temper- ature variance due to long-vertical wavelength stratospheric gravity waves that are in sync with intraseasonal precipitation and tropopause wind anoma- lies associated with the Madden-Julian Oscillation (MJO). Here the origin
of these intraseasonal gravity wave variations is investigated with a set of idealized gravity wave-resolving model experiments. The experiments specif- ically test whether tropopause winds act to control gravity wave propaga-
tion into the stratosphere by a critical level filtering mechanism or play a role in gravity wave generation through an obstacle source effect. All experiments use identical convective latent heating variability but the large-scale hori- zontal wind profile is varied to investigate relationships between stratospheric gravity waves and zonal winds at different levels. Results show that the ob- served long vertical wavelength gravity waves are primarily sensitive to strato- spheric zonal wind variations, while tropopause wind variations have only
a very small effect. Thus neither the critical level filter mechanism nor the obstacle source play much of a role in the observed intraseasonal gravity wave variations. Instead the results suggest that the stratospheric waves follow the MJO precipitation sources, and tropopause wind anomalies follow the same sources. We further find evidence of intraseasonal wave drag effects on the stratospheric circulation in reanalyzed winds. The results suggest that waves drive intraseasonal stratospheric zonal wind anomalies that descend in al- titude with increasing MJO phases 3 through 7. Eastward anomalies descend further than westward, suggesting that MJO-related stratospheric waves cause larger eastward drag forces.
Cloudy-sky land surface longwave downward radiation (LWDR) estimation by integrating MODIS and AIRS/AMSU measurements
Longwave downward radiation (LWDR) is another major energy source received by the earth's surface apart from solar radiation. Its importance in regulating air temperature and balancing surface energy is enlarged especially under cloudy-sky conditions. Unfortunately, to date, a large number of efforts have been made to derive LWDR from space under only clear-sky conditions leading to difficulty in utilizing space-based LWDR in most models due to its spatio-temporal discontinuity. Currently, only a few studies are focused on LWDR estimation under cloudy skies, while their global application is still questionable. In this paper, an alternative strategy is proposed aiming to derive high-resolution (1 km) cloudy-sky LWDR by fusing collocated satellite multi-sensor measurements. The results show that the newly developed method works well and can derive LWDR at a better accuracy with RMSE < 27 W/m2 and bias < 10 W/m2 even under cloudy skies and at 1 km scales. By comparing the CCCM and SSF products of CERES, MERRA, ERA-interim and NCEP-CSFR over the Tibetan Plateau region, the new approach demonstrates its superiority in terms of accuracy, temporal variation and spatial distribution patterns of LWDR. Comprehensive comparison analysis also reveals that, except for the proposed product, the other four products (CERES, MERRA, ERA-interim and NCEP-CSFR) show a big difference from each other in the LWDR spatio-temporal distribution pattern and magnitude. The difference between these products can still be up to 60 W/m2 even at the monthly scale, implying that large uncertainties exist in current LWDR estimations. More importantly, besides the higher accuracy of the proposed method, it provides unprecedented possibilities for jointly generating high-resolution global LWDR datasets by connecting the NASA's Earth Observing System-(EOS) mission (MODIS-AIRS/AMSU) and the Suomi National Polar-orbiting Partnership-(NPP) mission (VIIRS-CrIS/ATMS). Meanwhile, the scheme proposed in this study also gives some clues towards multiple data fusing in the remote sensing community.