Advanced Microwave Sounding Unit Channel Research Articles

A Satellite-Derived Lower-Tropospheric Atmospheric Temperature Dataset Using an Optimized Adjustment for Diurnal Effects

Abstract Temperature sounding microwave radiometers flown on polar-orbiting weather satellites provide a long-term, global-scale record of upper-atmosphere temperatures, beginning in late 1978 and continuing to the present. The focus of this paper is a lower-tropospheric temperature product constructed using measurements made by the Microwave Sounding Unit channel 2 and the Advanced Microwave Sounding Unit channel 5. The temperature weighting functions for these channels peak in the middle to upper troposphere. By using a weighted average of measurements made at different Earth incidence angles, the effective weighting function can be lowered so that it peaks in the lower troposphere. Previous versions of this dataset used general circulation model output to remove the effects of drifting local measurement time on the measured temperatures. This paper presents a method to optimize these adjustments using information from the satellite measurements themselves. The new method finds a global-mean land diurnal cycle that peaks later in the afternoon, leading to improved agreement between measurements made by co-orbiting satellites. The changes result in global-scale warming [global trend (70°S–80°N, 1979–2016) = 0.174°C decade−1], ~30% larger than our previous version of the dataset [global trend (70°S–80°N, 1979–2016) = 0.134°C decade−1]. This change is primarily due to the changes in the adjustment for drifting local measurement time. The new dataset shows more warming than most similar datasets constructed from satellites or radiosonde data. However, comparisons with total column water vapor over the oceans suggest that the new dataset may not show enough warming in the tropics.

Monitoring the Jason-2/AMR Stability Using SNO Observations from AMSU on MetOp-A

The microwave radiometers aboard the Jason satellites for altimetry missions are a key component of the Jason system, providing important measurements for water vapor correction, which is the most variable path delay correction in the altimeter measurement system. Unfortunately, these radiometers have exhibited on-orbit calibration drifts, step jumps, and other types of irregularities that can result in height rate errors comparable to 1 mm/yr, the stability requirement for measuring global mean sea level rise. Therefore, the calibration accuracy and short- and long-term stability of these radiometers are critical for the Jason mission to meet the stringent requirements. This study investigates the stability of the Jason-2 Advanced Microwave Radiometer (AMR) relative to the Advanced Microwave Sounding Unit (AMSU) on the MetOp-A satellite using the Simultaneous Nadir Overpass (SNO) time series method. Preliminary results show that using the AMSU as a stable reference, which has a demonstrated stability of better than 0.5 K per decade in previous studies, the Jason radiometer stability can be reliably monitored at 0.1 K per year level. The method has successfully detected a downward trend in the 23.8 GHz AMR channel (the primary one for detecting atmospheric water vapor) relative to the same AMSU channel for about −0.48 K per year since its launch on June 20, 2008, until February 2010, which is likely caused by AMR calibration problems during the period.

Tropospheric methane in the tropics – first year from IASI hyperspectral infrared observations

Abstract. Simultaneous observations from the Infrared Atmospheric Sounding Interferometer (IASI) and from the Advanced Microwave Sounding Unit (AMSU), launched together onboard the European MetOp platform in October 2006, are used to retrieve a mid-to-upper tropospheric content of methane (CH4) in clear-sky conditions, in the tropics, over sea, for the first 16 months of operation of MetOp (July 2007–October 2008). With its high spectral resolution, IASI provides nine channels in the 7.7 μm band highly sensitive to CH4 with reduced sensitivities to other atmospheric variables. These channels, sensitive to both CH4 and temperature, are used in conjunction with AMSU channels, only sensitive to temperature, to decorrelate both signals through a non-linear inference scheme based on neural networks. A key point of this approach is that no use is made of prior information in terms of methane seasonality, trend, or geographical patterns. The precision of the retrieval is estimated to be about 16 ppbv (~0.9%). Features of the retrieved methane space-time distribution include: (1) a strong seasonal cycle of 30 ppbv in the northern tropics with a maximum in January–March and a minimum in July–September, and a flat seasonal cycle in the southern tropics, in agreement with in-situ measurements; (2) a latitudinal decrease of 30 ppbv from 20° N to 20° S, in boreal spring and summer, lower than what is observed at the surface but in excellent agreement with tropospheric aircraft measurements; (3) geographical patterns in good agreement with simulations from the atmospheric transport and chemistry model MOZART-2, but with a higher variability and a higher concentration in boreal winter; (4) signatures of CH4 emissions transported to the middle troposphere such as a large plume of elevated tropospheric methane south of the Asian continent, which might be due to Asian emissions from rice paddies uplifted by deep convection during the monsoon period and then transported towards Indonesia. In addition to bringing a greatly improved view of methane distribution, these results from IASI should provide a means to observe and understand atmospheric transport pathways of methane from the surface to the upper troposphere.

Construction of the RSS V3.2 Lower-Tropospheric Temperature Dataset from the MSU and AMSU Microwave Sounders

Abstract Measurements made by microwave sounding instruments provide a multidecadal record of atmospheric temperature in several thick atmospheric layers. Satellite measurements began in late 1978 with the launch of the first Microwave Sounding Unit (MSU) and have continued to the present via the use of measurements from the follow-on series of instruments, the Advanced Microwave Sounding Unit (AMSU). The weighting function for MSU channel 2 is centered in the middle troposphere but contains significant weight in the lower stratosphere. To obtain an estimate of tropospheric temperature change that is free from stratospheric effects, a weighted average of MSU channel 2 measurements made at different local zenith angles is used to extrapolate the measurements toward the surface, which results in a measurement of changes in the lower troposphere. In this paper, a description is provided of methods that were used to extend the MSU method to the newer AMSU channel 5 measurements and to intercalibrate the results from the different types of satellites. Then, satellite measurements are compared to results from homogenized radiosonde datasets. The results are found to be in excellent agreement with the radiosonde results in the northern extratropics, where the majority of the radiosonde stations are located.

Relationship between snow parameters and microwave satellite measurements: Theory compared with Advanced Microwave Sounding Unit observations from 23 to 150 GHz

A theoretical model is used to examine the relationship between snow parameters and satellite‐based microwave radiometer measurements between 23 and 150 GHz. The model is based on the two‐stream radiative transfer equation whose optical parameters are obtained from dense media theory. Model simulations are used to show how the grain size, density, snow depth, and an ice crust affect the emissivity and brightness temperatures measured by the Advanced Microwave Sounding Unit (AMSU). The AMSU channels at 23, 31, 89, and 150 GHz are shown to be more sensitive to grain size variations than the other snow parameters. For ice particle diameters less than 1 mm the emissivity and brightness temperatures are found to decrease continuously up to 150 GHz. However, for larger particles, the emissivity and brightness temperature results in a flatter frequency response beyond 89 GHz as the wavelength approaches the particle size. Model results are tested using AMSU measurements for snow events over the central United States during a 2‐week period in the late fall. In agreement with model simulations, the brightness temperature is shown to decrease continuously up to 150 GHz for the small grain size associated with new snow, whereas the brightness temperature no longer decreases beyond 89 GHz as the snow ages and larger grains form owing to snow metamorphosis. Most importantly, the difference between the 89 and 150 GHz AMSU measurements is shown to provide a unique signature for identifying and separating new from aged snow. Consequently, it is now possible to identify four different snow types (wet, new, aged, and stratified snow) from AMSU.

Retrieval of upper tropospheric water vapor and upper tropospheric humidity from AMSU radiances

Abstract. A regression method was developed to retrieve upper tropospheric water vapor (UTWV in kg/m2) and upper tropospheric humidity (UTH in % RH) from radiances measured by the Advanced Microwave Sounding Unit (AMSU). In contrast to other UTH retrieval methods, UTH is defined as the average relative humidity between 500 and 200hPa, not as a Jacobian weighted average, which has the advantage that the UTH altitude does not depend on the atmospheric conditions. The method uses AMSU channels 6-10, 18, and 19, and should achieve an accuracy of 0.48 kg/m2 for UTWV and 6.3% RH for UTH, according to a test against an independent synthetic data set. This performance was confirmed for northern mid-latitudes by a comparison against radiosonde data from station Lindenberg in Germany, which yielded errors of 0.23 kg/m2 for UTWV and 6.1% RH for UTH.

A new procedure for estimating observation errors in AMSU data and its application to retrieval

AbstractAn accurate estimate of observation errors is crucial to the retrieval of atmospheric profiles from satellite data using a variational method. In practice, observation errors, both systematic and random, are often estimated from the difference between satellite observations and simulated satellite observations obtained from a radiative‐transfer operator with a 12 h forecast as its input. Observation errors estimated by this approach may be contaminated by errors in the 12 h forecast. This work describes a practical way to eliminate the 12 h forecast error and improve the estimate of the observation error in the Advanced Microwave Sounding Unit (AMSU) data. Following the philosophy of the National Meteorological Center (NMC) method (that derives the statistics of forecast error from the differences between pairs of forecasts at disparate ranges valid at the same time), in this study the pairs of forecasts at different ranges in the NMC method are first converted to brightness temperatures in the AMSU channels by a radiative‐transfer operator. The 12 h forecast errors are then determined from the representations of these forecasts in radiance space spanned by the AMSU channels. Since most AMSU channels have beam position‐dependent systematic observation errors, the procedure further takes into account this dependence by performing the statistics separately for sub‐groups of data in each AMSU channel with different beam positions. In a case‐study, after eliminating the 12 h forecast error obtained by this procedure from the total estimated observation error, the remaining random error of the satellite observation is shown to be smaller than the background error (provided by 12 h forecasts of a numerical weather‐prediction model) in most of the AMSU temperature sounding channels. Using the error‐corrected AMSU data in these channels, a retrieval experiment using a one‐dimensional variational scheme shows an improvement of 0.2–0.4 K over the background error in the retrieved temperature profiles above 780 hPa. Copyright © 2004 Royal Meteorological Society

Radiance and Jacobian intercomparison of radiative transfer models applied to HIRS and AMSU channels

The goals of this study are the evaluation of current fast radiative transfer models (RTMs) and line‐by‐line (LBL) models. The intercomparison focuses on the modeling of 11 representative sounding channels routinely used at numerical weather prediction centers: 7 HIRS (High‐resolution Infrared Sounder) and 4 AMSU (advanced microwave sounding unit) channels. Interest in this topic was evident by the participation of 24 scientists from 16 institutions. An ensemble of 42 diverse atmospheres was used and results compiled for 19 infrared models and 10 microwave models, including several LBL RTMs. For the first time, not only radiances but also Jacobians (of temperature, water vapor, and ozone) were compared to various LBL models for many channels. In the infrared, LBL models typically agree to within 0.05–0.15 K (standard deviation) in terms of top‐of‐the‐atmosphere brightness temperature (BT). Individual differences up to 0.5 K still exist, systematic in some channels, and linked to the type of atmosphere in others. The best fast models emulate LBL BTs to within 0.25 K, but no model achieves this desirable level of success for all channels. The ozone modeling is particularly challenging. In the microwave, fast models generally do quite well against the LBL model to which they were tuned. However, significant differences were noted among LBL models. Extending the intercomparison to the Jacobians proved very useful in detecting subtle or more obvious modeling errors. In addition, total and single gas optical depths were calculated, which provided additional insight on the nature of differences.

Retrieval of Nonprecipitating Liquid Water Cloud Parameters from Microwave Data: A Simulation Study

A new microwave algorithm, analogous to the IR 'radiance-ratioing' method of Eyre and Menzel (1989) is developed to retrieve the height and 'effective' fraction (defined as the product of the emissivity times the actual physical fractional coverage) of nonprecipitating water clouds using various pairs of the 20 microwave channels planned for the Advanced Microwave Sounding Unit (AMSU), an instrument slated to fly on polar-orbiting satellites beginning in 1994. The results of a simulation study are presented to provide some insights into the potentials of this technique using different AMSU channel combinations. This study suggests that the use of the oxygen channels 3 and 5 and water vapor channels 19 and 20 will produce the most accurate retrievals of liquid water cloud parameters and the highest percentage of good-quality retrievals over a range of meteorological and cloud conditions.