Advanced Microwave Sounding Unit-A Observations Research Articles

Assimilation of the AMSU-A radiances using the CESM (v2.1.0) and the DART (v9.11.13)–RTTOV (v12.3)

Abstract. To improve the initial condition (“analysis”) for numerical weather prediction, we attempt to assimilate observations from the Advanced Microwave Sounding Unit-A (AMSU-A) on board the low-Earth-orbiting satellites. The data assimilation system, used in this study, consists of the Data Assimilation Research Testbed (DART) and the Community Earth System Model as the global forecast model. Based on the ensemble Kalman filter scheme, DART supports the radiative transfer model that is used to simulate the satellite radiances from the model state. To make the AMSU-A data available to be assimilated in DART, preprocessing modules are developed, which consist of quality control, spatial thinning, and bias correction processes. In the quality control, two sub-processes are included, outlier test and channel selection, depending on the cloud condition and surface type. The bias correction process is divided into scan-bias correction and air-mass-bias correction. Like input data used in DART, the observation errors are also estimated for the AMSU-A channels. In the trial experiments, a positive analysis impact is obtained by assimilating the AMSU-A observations on top of the DART data assimilation system that already makes use of the conventional measurements. In particular, the analysis errors are significantly reduced in the whole troposphere and lower stratosphere over the Northern Hemisphere. Overall, this study demonstrates a positive impact on the analysis when the AMSU-A observations are assimilated in the DART assimilation system.

Estimation of AMSU-A Radiance Observation Impacts in an LETKF-Based Atmospheric Global Data Assimilation System: Comparison with EFSO and Observing System Experiments

Abstract This work assesses the contribution of assimilating AMSU-A satellite-based radiance measurements to a global data assimilation system based on an atmospheric general circulation model and the local ensemble transform Kalman filter (LETKF). The radiance measurements were from three channels that are sensitive to the upper troposphere and lower stratosphere. The contribution of these measurements, or AMSU-A observation impact, was estimated both through ensemble-based forecast sensitivity to observations (EFSO) and observing system experiments (OSEs). Two streams of data-denial experiments for the AMSU-A observations were performed for about one month during winter in each hemisphere. The OSEs quantified the accumulated observation impact by cycling (repeating) data denials: including AMSU-A observations reduced the total observation impact for all observations of each data assimilation cycle. In contrast, EFSO estimated AMSU-A to increase the total observation impact. The opposing effects were attributed to the accumulated observation impact in the OSEs; the accumulation could stabilize the data assimilation cycles. In both experiments, the accumulated observation impact of AMSU-A was strongest in the upper troposphere, particularly in the austral midlatitudes where westerly jets exist and observations of other types are sparse. EFSO also assessed AMSU-A to have the most beneficial observation impact in similar locations. The AMSU-A observation impact tended to accumulate just downstream of where EFSO estimated the beneficial observation impact signals. The accumulated AMSU-A observation impact was tied to dynamic processes in the upper-tropospheric and general stratospheric circulation. Therefore, EFSO helps estimate the beneficial distributions of AMSU-A accumulated observation impact by considering their dynamical propagation. Significance Statement The Advanced Microwave Sounding Unit-A (AMSU-A) satellite radiance assimilation technique was successfully integrated into the Atmospheric General Circulation Model for the Earth Simulator (AFES)–LETKF data assimilation system. We conducted OSEs and used EFSO to assess the AMSU-A observation impact. The two estimation methods identified opposite observation impacts due to the cycling (repeating) OSEs of the AMSU-A observations. We interpreted the causes of the opposite estimations. However, even for the cycling OSEs, EFSO appeared to help estimate distributions of the accumulated observation impact. It is important to consider the dynamical propagation of accumulated observation impact in general circulation.

Assessing Sensitivity of MERRA-2 to AMSU-A in the Upper Stratosphere

AbstractMicrowave temperature sounders provide key observations in data assimilation, both in the current and historical global observing systems, as they provide the largest amount of horizontal and vertical temperature information due to their insensitivity to clouds. In the Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), microwave sounder radiances from the Advanced Microwave Sounding Unit-A (AMSU-A) are assimilated beginning with NOAA-15 and continuing through the current period. The time series of observation minus background statistics for AMSU-A channels sensitive to the upper stratosphere and lower mesosphere show variabilities due to changes in the AMSU-A constellation in the early AMSU-A period. Noted discrepancies are seen at the onset and exit of AMSU-A observations on the NOAA-15, NOAA-16, NOAA-17, and NASA EOS Aqua satellites. This effort characterizes the sensitivity, both in terms of the observations and the MERRA-2 data. Furthermore, it explores the use of reprocessed and intercalibrated datasets to evaluate whether these homogenized observations can reduce the disparity due to change in instrumental biases against the model background. The results indicate that the AMSU-A radiances used in MERRA-2 are the fundamental cause of this interplatform sensitivity, which can be mitigated by using reprocessed data. The results explore the importance of the reprocessing of the AMSU-A radiances as well as their intercalibration.

Derivation and Validation of Sensor Brightness Temperatures for Advanced Microwave Sounding Unit-A Instruments

In this article, we first present a generalized methodology for deriving sensor brightness temperature sensor data records (SDR) from antenna temperature data records (TDR) applicable for Advanced Microwave Sounding Unit-A (AMSU-A) instruments. It includes corrections for antenna sidelobe contributions, antenna emission, and radiation perturbation due to the difference of Earth radiance in the main beam and that in the sidelobes that lie outside the main beam but within the Earth disk. For practical purposes, we simplify the methodology by neglecting the components other than the antenna sidelobe contributions to establish a consistent formulation with the legacy AMSU-A antenna pattern correction (APC) formula. The simplified formulation is then applied to the final AMSU-A instrument onboard the Metop-C satellite that was launched in November 2018, in order to compute APC coefficients for deriving SDR from TDR data. Furthermore, the performance of the calculated correction coefficients is validated by calculating the differences between the daily averaged AMSU-A (TDR and SDR) observations against radiative transfer model (O–B) simulations under clear sky conditions, and over open oceans. The validation results show that the derived temperature corrections are channel and scan position dependent, and can add 0.2–1.6 K to the antenna temperatures. In addition, the derived SDR O-B results exhibit a reduced and more symmetric scan angle-dependent bias when compared with corresponding TDR antenna temperatures.

Development and Testing of a Clear-Sky Data Selection Algorithm for FY-3C/D Microwave Temperature Sounder-2

The Fengyun (FY)-3C/D microwave temperature sounder-2 (MWTS-2) is similar to the Advanced Microwave Sounding Unit-A (AMSU-A), except it lacks two window channels located at 23.8 GHz and 31.4 GHz. This makes a clear-sky data determination challenging for the MWTS-2 due to the unavailability of cloud liquid water path (LWP) retrievable from the two window channels. The purpose of this study is to develop a clear-sky data selection algorithm for the FY-3C/D MWTS-2 based on the bias-removed differences between observations and model simulations of the MWTS-2 50.3-GHz channel 1 (or equivalently AMSU-A channel 3). First, a point is defined as a temporal clear-sky (cloudy) point if the bias-removed difference between observed and simulated brightness temperatures is smaller than or equal to (greater than) 2 K. Then, a temporal clear-sky (cloudy) point is defined as a final clear-sky (cloudy) point if all points within its 60-km (100-km) radial distance are temporal clear-sky (cloudy) points. Finally, if the mean value of the bias-removed differences between observations and simulations in the 100-km circle from a temporal cloudy point are smaller than or equal to (greater than) 2 K, all temporal clear-sky points within this circle are (not) taken as the final clear-sky points. Applications of this algorithm to FY-3C MWTS-2 and MetOp-B AMSU-A lead to the following conclusions: (i) more than 70% (95%) of the clear-sky (cloudy) data points are successfully identified from both AMSU-A and MWTS-2 observations; (ii) the algorithm-selected clear-sky data points were located in clear-sky areas in the GOES-15 imager, and (iii) the bias-removed differences between observations and model simulations of MWTS-2 channel 1 well reveals the eye, the eyewall, and the spiral rainband structure of Super Typhoon Halong (2014).

New generation of U.S. satellite microwave sounder achieves high radiometric stability performance for reliable climate change detection.

Observations from the satellite microwave sounders play a vital role in measuring the long-term temperature trends for climate change monitoring. Changes in diurnal sampling over time and calibration drift have been the main sources of uncertainties in the satellite-measured temperature trends. We examine observations from the first of a series of U.S. new generation of microwave sounder, the Advanced Technology Microwave Sounder (ATMS), which has been flying onboard the National Oceanic and Atmospheric Administration (NOAA)/NASA Suomi National Polar-orbiting Partnership (SNPP) environmental satellite since late 2011. The SNPP satellite has a stable afternoon orbit that has close to the same local observation time as NASA's Aqua satellite that has been carrying the heritage microwave sounder, the Advanced Microwave Sounding Unit-A (AMSU-A), from 2002 until the present. The similar overpass timing naturally removes most of their diurnal differences. In addition, direct comparison of temperature anomalies between the two instruments shows little or no relative calibration drift for most channels. Our results suggest that both SNPP/ATMS and Aqua/AMSU-A instruments have achieved absolute stability in the measured atmospheric temperatures within 0.04 K per decade. This uncertainty is small enough to allow reliable detection of the temperature climate trends and help to resolve debate on relevant issues. We also analyze AMSU-A observations onboard the European MetOp-A satellite that has a stable morning orbit 8 hours apart from the SNPP overpass time. Their comparison reveals large asymmetric trends between day and night in the lower- and mid-tropospheric temperatures over land. This information could help to improve climate data records for temperature trend detection with improved accuracy. The SNPP satellite will be followed by four NOAA operational Joint Polar Satellite System (JPSS) satellites, providing accurate and stable measurement for decades to come. The primary mission of JPSS is for weather forecasting. Now, with the added feature of stable orbits, JPSS observations can also be used to monitor changes in climate with much lower uncertainty than the previous generation of NOAA operational satellites.

Stratospheric Temperature Climate Data Record from Merged SSU and AMSU-A Observations

AbstractObservations from the Stratospheric Sounding Unit (SSU) on board historical NOAA polar-orbiting satellites have played a vital role in investigations of long-term trends and variability in the middle- and upper-stratospheric temperatures during 1979–2006. The successor to SSU is the Advanced Microwave Sounding Unit-A (AMSU-A) starting from 1998 until the present. Unfortunately, the two observations came from different sets of atmospheric layers, and the SSU weighting functions varied with time and location, posing a challenge to merge them with sufficient accuracy for development of an extended SSU climate data record. This study proposes a variational approach for the merging problem, matching in both temperatures and weighting functions. The approach yields zero means with a small standard deviation and a negligible drift over time in the temperature differences between SSU and its extension to AMSU-A. These features made the approach appealing for reliable detection of long-term climate trends. The approach also matches weighting functions with high accuracy for SSU channels 1 and 2 and reasonable accuracy for channel 3. The total decreases in global mean temperatures found from the merged dataset were from 1.8 K in the middle stratosphere to 2.4 K in the upper stratosphere during 1979–2015. These temperature drops were associated with two segments of piecewise linear cooling trends, with those during the first period (1979–97) being much larger than those of the second period (1998–2015). These differences in temperature trends corresponded well to changes of the atmospheric ozone amount from depletion to recovery during the respective time periods, showing the influence of human decisions on climate change.

The Influence of Frequency Shifts in Microwave Sounder Channels on NWP Analyses and Forecasts

Abstract The sensitivity of numerical weather prediction (NWP) analysis and forecast accuracies with respect to frequency shifts in microwave passbands is quantified through a series of observing system experiments using the ECMWF Integrated Forecast System. First, a parameterization is developed to describe the form and magnitude of the brightness temperature errors arising from frequency shifts in Advanced Microwave Sounding Unit-A (AMSU-A) channels 4–10 and Microwave Humidity Sounder (MHS) channels 3–5. Observing system experiments are then run in which realistic synthetic brightness temperature errors are added to AMSU-A observations for various assumptions about the magnitude of a frequency shift, using the parameterization derived previously. A large negative impact on forecast quality is found when a 20-MHz frequency shift is introduced in experiments using a static bias-correction scheme. Although the degradation in forecast scores is reduced by using a variational bias-correction scheme, it remains around 7%–14% (relative) in RMS 6-h forecast errors for temperature and geopotential. Frequency shifts of 5 MHz or greater give rise to a measurable degradation of the forecast even when the variational correction scheme is used. Only low-frequency shifts (of ~1.5 MHz) are found to have a neutral impact on forecasts. Hence, the value of 1.5 MHz can be regarded as an upper limit below which frequency shifts do not degrade forecasts for the key tropospheric and lower-stratospheric temperature sounding channels in a microwave sounding mission. Calculations show that frequency shift is less problematic for 183-GHz humidity sounding channels due to the symmetric positioning of passbands relative to the 183-GHz absorption line. For these channels a passband center frequency stability of 10 MHz is adequate.

Validation of AMSU-A measurements from two different calibrations in the lower stratosphere using COSMIC radio occultation data

GPS radio occultation data from the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) mission were used to validate the measurements of the advanced microwave sounding unit-A (AMSU-A) in the lower stratosphere from different satellites. AMSU-A observations from two different calibrations—the pre-launch operational and post-launch simultaneous nadir overpass (SNO) calibrations—were compared to microwave brightness temperatures (Tb) simulated from COSMIC data. Observations from three satellites (NOAA-15, -16, and -18) were used in the comparison. The results showed that AMSU-A Tb measurements from both calibrations and from all three NOAA satellites were underestimated in the lower stratosphere, and that the biases were larger in polar winters, especially over the southern high latitudes. In comparison to operational calibration, the SNO-calibrated AMSU-A data produced much smaller biases relative to the COSMIC data. The improvement due to SNO calibration was quantified by a Ratio index, which measured the bias changes from operational to SNO calibrations relative to the biases between the operational-calibrated AMSU-A data and the COSMIC data. The Ratio values were 70 % for NOAA-15 and >80 % for NOAA-18 and -16, indicating that the SNO calibration method significantly reduced AMSU-A biases and effectively improved AMSU-A data quality.

Month-long simulations of gravity waves over North America and North Atlantic in comparison with satellite observations

Mesoscale simulations of gravity waves in the upper troposphere and lower stratosphere over North America and North Atlantic Ocean in January 2003 are compared with satellite radiance measurements from the Advanced Microwave Sounding Unit-A (AMSU-A). Four regions of strong gravity wave (GW) activities are found in the model simulations and the AMSU-A observations: the northwestern Atlantic, the U.S. Rockies, the Appalachians, and Greenland. GWs over the northwestern Atlantic Ocean are associated with the midlatitude baroclinic jet-front system, while the other three regions are apparently related to high topography. Model simulations are further used to analyze momentum fluxes in the zonal and meridional directions. It is found that strong westward momentum fluxes are prevalent over these regions over the whole period. Despite qualitative agreement between model simulations and satellite measurements, sensitivity experiments demonstrate that the simulated GWs are sensitive to the model spin-up time.

Intersatellite calibration of AMSU-A observations for weather and climate applications

[1] Long-term observations from the Advanced Microwave Sounding Unit-A (AMSU-A) onboard polar-orbiting satellites NOAA 15, 16, 17, and 18 and European Meteorological Operational satellite program-A (MetOp-A) were intercalibrated using their overlap observations. Simultaneous nadir overpasses (SNOs) and global ocean mean differences between these satellites were used to characterize calibration errors and to obtain calibration coefficients. Calibration errors were found manifesting themselves as certain scatter or temporal patterns of intersatellite biases, such as well-defined seasonal cycles in the Arctic and Antarctic SNO difference time series or a unique pattern closely correlated to the instrument temperature variability induced by Solar Beta Angle (SBA) variations in global ocean mean difference time series. Analyses of these patterns revealed five different types of biases that need to be removed from existing prelaunch-calibrated AMSU-A observations, which include relatively stable intersatellite biases between most satellite pairs, bias drifts on NOAA 16 and channel 7 of MetOp-A, sun-heating-induced instrument temperature variability in radiances, scene temperature dependency in biases due to inaccurate calibration nonlinearity, and biases due to channel frequency shift from its prelaunch measurement in certain satellite channels. Level-1c time-dependent calibration offsets and nonlinear coefficients were introduced and determined from SNO and global ocean mean temperature regressions to remove or minimize the first four types of biases. Channel frequency shift in NOAA 15 channel 6 was obtained from the radiative transfer model simulation experiments. The new calibration coefficients and channel frequency values have significantly reduced the five different types of biases and resulted in more consistent multisatellite radiance observations for intercalibrated satellite channels. The intercalibrated AMSU-A observations have been merged with its precursor, the intercalibrated microwave sounding unit (MSU), to generate the NOAA/Center for Satellite Applications and Research (STAR) version 2.0 upper-air temperature climate data record (CDR) for climate trend and variability monitoring from 1979 to the present. The intercalibrated AMSU-A radiance data are expected to further improve accuracies of numerical weather prediction and consistencies in climate reanalysis and CDR developments.

Mediterranean hurricanes: large-scale environment and convective and precipitating areas from satellite microwave observations

Abstract. Subsynoptic scale vortices that have been likened to tropical cyclones or polar lows (medicanes) are occasionally observed over the Mediterranean Sea. Generated over the sea, they are usually associated with strong winds and heavy precipitation and thus can be highly destructive in islands and costal areas. Only an accurate forecasting of such systems could mitigate these effects. However, at the moment, the predictability of these systems remains limited. Due to the scarcity of conventional observations, use is made of NOAA/MetOp satellite observations, for which advantage can be taken of the time coverage differences between the platforms that carry it, to give a very complete temporal description of the disturbances. A combination of AMSU-B (Advanced Microwave Sounding Unit-B)/MHS (Microwave Humidity Sounder) observations permit to investigate precipitation associated with these systems while coincident AMSU-A (Advanced Microwave Sounding Unit-A) observations give insights into the larger synoptic-scale environment in which they occur. Three different cases (in terms of intensity, location, trajectory, duration, and periods of the year – May, September and December, respectively) were investigated. Throughout these time periods, AMSU-A observations show that the persisting deep outflow of cold air over the sea together with an upper-level trough upstream constituted a favourable environment for the development of medicanes. AMSU-B/MHS based diagnostics show that convection and precipitation areas are large in the early stage of the low, but significantly reduced afterwards. Convection is maximum just after the upper-level trough, located upstream of cold mid-tropospheric air, reached its maximum intensity and acquired a cyclonic orientation.

Note on the effect of horizontal gradients for nadir-viewing microwave and infrared sounders

Passive microwave and infrared nadir sounders such as the Advanced Microwave Sounding Unit A (AMSU-A) and the Atmospheric InfraRed Sounder (AIRS), both flying on NASA s EOS Aqua satellite, provide information about vertical temperature and humidity structure that is used in data assimilation systems for numerical weather prediction and climate applications. These instruments scan cross track so that at the satellite swath edges, the satellite zenith angles can reach approx. 60 deg. The emission path through the atmosphere as observed by the satellite is therefore slanted with respect to the satellite footprint s zenith. Although radiative transfer codes currently in use at operational centers use the appropriate satellite zenith angle to compute brightness temperature, the input atmospheric fields are those from the vertical profile above the center of the satellite footprint. If horizontal gradients are present in the atmospheric fields, the use of a vertical atmospheric profile may produce an error. This note attempts to quantify the effects of horizontal gradients on AIRS and AMSU-A channels by computing brightness temperatures with accurate slanted atmospheric profiles. We use slanted temperature, water vapor, and ozone fields from data assimilation systems. We compare the calculated slanted and vertical brightness temperatures with AIRS and AMSU-A observations. We show that the effects of horizontal gradients on these sounders are generally small and below instrument noise. However, there are cases where the effects are greater than the instrument noise and may produce erroneous increments in an assimilation system. The majority of the affected channels have weighting functions that peak in the upper troposphere (water vapor sensitive channels) and above (temperature sensitive channels) and are unlikely t o significantly impact tropospheric numerical weather prediction. However, the errors could be significant for other applications such as stratospheric analysis. Gradients in ozone and tropospheric temperature appear to be well captured by the analyses. In contrast, gradients in upper stratospheric and mesospheric temperature as well as upper tropospheric humidity are less well captured. This is likely due in part to a lack of data to specify these fields accurately in the analyses. Advanced new sounders, like AIRS, may help to better specify these fields in the future.

The Limb Adjustment of AMSU-A Observations: Methodology and Validation

Abstract The Advanced Microwave Sounding Unit-A (AMSU-A) is the first of a new generation of polar-orbiting cross-track microwave sounders operated by the National Oceanic and Atmospheric Administration. A feature of a cross-track sounder is that the measurements vary with scan angle because of the change in the optical pathlength between the earth and the satellite. This feature is called the limb effect and can be as much as 30 K. One approach to this problem is to limb adjust the measurements to a fixed view angle. This approach was used for the older series of Microwave Sounding Units. Limb adjusting is important for climate applications and regression retrieval algorithms. This paper describes and evaluates several limb adjustment procedures. The recommended procedure uses a combined physical and statistical technique. The limb adjusted measurements were compared with computed radiances from radiosondes and National Centers for Environmental Prediction models. The model error was found to be less tha...

Global Soundings of the Atmosphere from ATOVS Measurements: The Algorithm and Validation

The International Advanced Television and Infrared Observation Satellite Operational Vertical Sounder (ATOVS) Processing Package (IAPP) has been developed to retrieve the atmospheric temperature profile, moisture profile, atmospheric total ozone, and other parameters in both clear and cloudy atmospheres from the ATOVS measurements. The algorithm that retrieves these parameters contains four steps: 1) cloud detection and removal, 2) bias adjustment for ATOVS measurements, 3) regression retrieval processes, and 4) a nonlinear iterative physical retrieval. Nine (3 × 3) adjacent High-Resolution Infrared Sounder (HIRS)/3 spot observations, together with Advanced Microwave Sounding Unit-A observations remapped to the HIRS/3 resolution, are used to retrieve the temperature profile, moisture profile, surface skin temperature, total atmospheric ozone and microwave surface emissivity, and so on. ATOVS profile retrieval results are evaluated by root-mean-square differences with respect to radiosonde observation profiles. The accuracy of the retrieval is about 2.0 K for the temperature at 1-km vertical resolution and 3.0–6.0 K for the dewpoint temperature at 2-km vertical resolution in this study. The IAPP is now available to users worldwide for processing the real-time ATOVS data.