Xiaolei Zou

Estimation and Correction of Geolocation Errors in FengYun-3C Microwave Radiation Imager Data

Microwave Radiation Imager (MWRI) onboard the FengYun (FY)-3C satellite provides measurements of the Earths atmosphere and surface at 10.65, 18.7, 23.8, 36.5, and 89.0 GHz with dual polarization. While FY MWRI data have been widely distributed to the user community, their geolocation accuracy has not been documented. In this paper, the coastline inflection method is used to estimate MWRI geolocation errors. Three coastal regions where MWRI brightness temperature exhibits a large contrast are selected for the geolocation analysis. A total of 720 MWRI data points are identified that cross the coastlines. The latitudes and longitudes at these data points are compared with the fine-resolution database of the Global Self-consistent, Hierarchical, High-resolution Shoreline (GSHHS). It is found that the mean geolocation errors in along- and cross-track directions are approximately 5-6 km at 89 GHz. This magnitude of errors is more than 30% of the field-of-view size at 89 GHz. Such a geolocation error must be corrected so that the MWRI data can be more useful for quantitative remote sensing. Thus, the mean geolocation errors are further utilized to adjust the satellite attitude angles (e.g., pitch, roll, and raw). After the attitude angle correction, the MWRI geolocation is very accurate at 89 GHz, and errors in other MWRI channels may be corrected through their co-registration relationships to the 89-GHz channel.

Characterization of Bias of Advanced Himawari Imager Infrared Observations from NWP Background Simulations Using CRTM and RTTOV

AbstractStarting in 2014, the new generation of Japanese geostationary meteorological satellites carries an Advanced Himawari Imager (AHI) to provide the observations of visible, near infrared, and infrared with much improved spatial and temporal resolutions. For applications of the AHI measurements in numerical weather prediction (NWP) data assimilation systems, the biases of the AHI brightness temperatures at channels 7–16 from the model simulations are first characterized and evaluated using both the Community Radiative Transfer Model (CRTM) and the Radiative Transfer for the TIROS Operational Vertical Sounder (RTTOV). It is found that AHI biases under a clear-sky atmosphere are independent of satellite zenith angle except for channel 7. The biases of three water vapor channels increase with scene brightness temperatures and are nearly constant except at high brightness temperatures for the remaining infrared channels. The AHI biases at all the infrared channels are less than 0.6 and 1.2 K over ocean a...

Use of Allan Deviation for Characterizing Satellite Microwave Sounder Noise Equivalent Differential Temperature (NEDT)

Currently, the instrument sensitivity of sensors onboard weather satellites is quantified by computing the standard deviation of the measurements taken from their calibration targets. The standard deviation is valid for describing the spread of a statistical distribution of the measured values around its mean that is stable. However, the actual measurements of a calibration target can exhibit considerable variations in time as shown from the Suomi National Polar-orbiting Partnership Advanced Technology Microwave Sounder (ATMS) blackbody data. In this letter, the Allan deviation is proposed as an alternative to the standard deviation for characterizing the instrument sensitivity. It is found that, in the overlapping Allan deviation formula, the averaging window size has to be set to one in order to accurately assess the noise magnitudes for both stationary and nonstationary time series. Furthermore, from the ATMS on-orbit data, the estimates of the noise magnitudes at several channels show a large discrepancy between the Allan deviation and the standard deviation. Finally applying the Allan deviation, the sensitivity of the NOAA-18 Advanced Microwave Sounding Unit-A is also derived and compared against the traditional algorithm results. From this comparison, significant improvements can be seen in the Allan deviation-based noise-equivalent-differential-temperature estimation.

ATMS‐ and AMSU‐A‐derived hurricane warm core structures using a modified retrieval algorithm

The Advanced Technology Microwave Sounder (ATMS) is a cross-track microwave radiometer. Its temperature sounding channels 5-15 can provide measurements of thermal radiation emitted from different layers of the atmosphere. In this study, a traditional Advanced Microwave Sounding Unit-A (AMSU-A) temperature retrieval algorithm is modified to remove the scan biases in the temperature retrieval and to include only those ATMS sounding channels that are correlated with the atmospheric temperatures on the pressure level of the retrieval. The warm core structures derived for Hurricane Sandy when it moved from tropics to middle latitudes are examined. It is shown that scan biases that are present in the traditional retrieval are adequately removed using the modified algorithm. In addition, temperature retrievals in the upper troposphere (~250 hPa) obtained by using the modified algorithm have more homogeneous warm core structures and those from the traditional retrieval are affected by small-scale features from the low troposphere such as precipitation. Based on ATMS observations, Hurricane Sandys warm core was confined to the upper troposphere during its intensifying stage and when it was located in the tropics, but extended to the entire troposphere when it moved into subtropics and middle latitudes and stopped its further intensification. The modified algorithm was also applied to AMSU-A observation data to retrieve the warm core structures of Hurricane Michael. The retrieved warm core features are more realistic when compared with those from the operational Microwave Integrated Retrieval System (MIRS).

Cloud and precipitation features of Super Typhoon Neoguri revealed from dual oxygen absorption band sounding instruments on board FengYun‐3C satellite

A new methodology is developed to detect the cloud structures at different vertical levels using the dual oxygen absorption bands located near 60 GHz and 118 GHz, respectively. Observations from Microwave Temperature Sounder (MWTS) and Microwave Humidity Sounder (MWHS) on board the recently launched Chinese FengYun-3C satellite are used to prove the concept. It is shown that a paired oxygen MWTS and MWHS sounding channel with the same peak weighting function altitude allows for detecting the vertically integrated cloud water path above that level. A cloud emission and scattering index (CESI) is defined using dual oxygen band measurements to indicate the amounts of cloud liquid and ice water paths. The CESI distributions from three paired channels reveal unique three-dimensional structures of clouds and precipitation within Super Typhoon Neoguri that occurred in July 2014.

Impacts of assimilating all or GOES-like AHI infrared channels radiances on QPFs over Eastern China

Abstract The launch of the Japanese Advanced Himawari Imager (AHI) on 7 October 2014 represents a new era of geostationary operational environmental satellite (GOES) imagers, providing many more channels than any previously launched GOES imagers for the first time. In this study, we compare the impacts of assimilating all AHI versus GOES-like infrared channels radiances on regional forecasts over Eastern China. The National Centers for Environmental Prediction (NCEP) Gridpoint Statistical Interpolation (GSI) analysis system and Advanced Research Weather Research and Forecast model are employed. Positive impacts are obtained on quantitative precipitation forecasts (QPFs) associated with a typical summer precipitation case over eastern China in both set-ups, i.e. one assimilating all 10 AHI infrared channels (AHIA) and the other assimilating only four GOES-like AHI channels (AHIG). It is found that a southwest to northeast oriented band of the atmosphere with high water vapor content that was formed and moved inland with time under the influence of a subtropical high and an eastward-propagating middle-latitude trough was responsible for the persistent precipitation in the eastern China of the selected case. The AHIA experiment generated the largest improvement on QPFs due to it generating a wetter atmosphere in the middle and low troposphere over the ocean off the southeast coast of China than the AHIG experiment and a control experiment without assimilating any AHI channel.

Potential Applications of Small Satellite Microwave Observations for Monitoring and Predicting Global Fast-Evolving Weathers

Two new constellations comprising 14 small satellites with microwave instruments onboard are proposed in this study. Properly arranged, the first constellation is capable of covering the entire globe at an hourly interval and the second constellation is more favorable for the tropical area. Compared to the current JPSS and MetOp satellite constellation, which has passive microwave sounding instruments ATMS or AMSU, a small satellite constellation is more cost effective, requires a shorter development cycle, and has a smaller launch-failure impact. For a designated microwave small satellite constellation, the brightness temperature distribution in space and time is simulated using the operational forecast fields as inputs to the Community Radiative Transfer Model (CRTM). It is demonstrated that the structural change of fast-evolving weather systems such as a middle-latitude cyclone can be well captured from small satellite brightness temperatures.

Characterization of geolocation accuracy of Suomi NPP Advanced Technology Microwave Sounder measurements

The Advanced Technology Microwave Sounder (ATMS) onboard Suomi National Polar-orbiting Partnership satellite has 22 channels at frequencies ranging from 23 to 183GHz for probing the atmospheric temperature and moisture under all weather conditions. As part of the ATMS calibration and validation activities, the geolocation accuracy of ATMS datamust be well characterized and documented. In this study, the coastline crossing method (CCM) and the land-sea fraction method (LFM) are utilized to characterize and quantify the ATMS geolocation accuracy. The CCM is based on the inflection points of the ATMS window channel measurements across the coastlines, whereas the LFM collocates the ATMS window channel data with high-resolution land-sea mask data sets. Since the ATMS measurements provide five pairs of latitude and longitude data for K, Ka, V, W, and G bands, respectively, the window channels 1, 2, 3, 16, and 17 from each of these five bands are chosen for assessing the overall geolocation accuracy. ATMS geolocation errors estimated from both methods are generally consistent from 40 cases in June 2014. The ATMS along-track (cross-track) errors at nadir are within ±4.2 km (±1.2 km) for K/Ka, ±2.6 km (±2.7 km) for V bands, and ±1.2 km (±0.6 km) at W and G bands, respectively. At the W band, the geolocation errors derived from both algorithms are probably less reliable due to a reduced contrast of brightness temperatures in coastal areas. These estimated ATMS along-track and cross-track geolocation errors are well within the uncertainty requirements for all bands.

An Empirical Model for Television Frequency Interference Correction of AMSR2 Data Over Ocean Near the U.S. and Europe

Television (TV) radio frequency interference (TFI) signals are found in the Advanced Microwave Scanning Radiometer 2 (AMSR2) observations of those channels with their frequencies centered at 18.7- or 10.65-GHz frequencies over coastal regions near the U.S. and Europe, respectively. When TV signals are reflected off the ocean surface and get into AMSR2 field of views, the AMSR2-measured radiance contains not only information of natural emission from Earths surface but also the reflected TV signals. If not detected and corrected, TFI introduces errors into the geophysical retrieval products. The occurrence and intensity of TFI are determined by the angle between the observation beam vector and the reflected TV signal vector (i.e., TFI glint angle) and the background TV signal intensity. In this paper, an empirical model is developed to quantitatively calculate the contribution of TFI signals to AMSR2 observations based on TFI glint angle and TV signal intensity. This empirical model is then applied to AMSR2 K-band channels over North America and X-band channels over Europe. It is shown that the annual mean bias for the TFI-affected observations of the 18.7-GHz channel at horizontal (vertical) polarization reduces from a value of more than 5 K (2 K) to about -0.5 K (0.5) after TFI correction over the coastal ocean near North America. The annual mean bias for the TFI-affected observations of the 10.65-GHz channel at horizontal (vertical) polarization reduces from a value of about 2.5 K to about -0.7 K (0.5 K) after TFI correction over the coastal ocean near Europe. False maxima in AMSR2-retrieved cloud liquid water path and dry anomalies in AMSR2-retrieved total precipitable water near the coastal regions are also eliminated after incorporating the TFI correction.

Impact of 4DVAR assimilation of AIRS total column ozone observations on the simulation of Hurricane Earl

The Atmospheric Infrared Sounder (AIRS) provides twice-daily global observations of brightness temperature, which can be used to retrieve the total column ozone with high spatial and temporal resolution. In order to apply the AIRS ozone data to numerical prediction of tropical cyclones, a four-dimensional variational (4DVAR) assimilation scheme on selected model levels is adopted and implemented in the mesoscale non-hydrostatic model MM5. Based on the correlation between total column ozone and potential vorticity (PV), the observation operator of each level is established and five levels with highest correlation coefficients are selected for the 4DVAR assimilation of the AIRS total column ozone observations. The results from the numerical experiments using the proposed assimilation scheme for Hurricane Earl show that the ozone data assimilation affects the PV distributions with more mesoscale information at high levels first and then influences those at middle and low levels through the so-called asymmetric penetration of PV anomalies. With the AIRS ozone data being assimilated, the warm core of Hurricane Earl is intensified, resulting in the improvement of other fields near the hurricane center. The track prediction is improved mainly due to adjustment of the steering flows in the assimilation experiment.