Effects of atmospheric dynamics and ocean resolution on bi-stability of the thermohaline circulation examined using the Grid ENabled Integrated Earth system modelling (GENIE) framework AbstractWe have used the Grid ENabled Integrated Earth system modelling (GENIE) framework to undertake a systematic search for bi-stability of the ocean thermohaline circulation (THC) for different surface grids and resolutions of 3-D ocean (GOLDSTEIN) under a 3-D dynamical atmosphere model (IGCM). A total of 407,000 years were simulated over a three month period using Grid computing. We find bi-stability of the THC despite significant, quasi-periodic variability in its strength driven by variability in the dynamical atmosphere. The position and width of the hysteresis loop depends on the choice of surface grid (longitude-latitude or equal area), but is less sensitive to changes in ocean resolution. For the same ocean resolution, the region of bi-stability is broader with the IGCM than with a simple energy-moisture balance atmosphere model (EMBM).
A single-valued wavelet-coefficient score is proposed for assessing the similarity of two-dimensional climatedata fields (matrices). It is based on the comparison of wavelet-decomposition coefficients by means of a mean-squared-error skill score. Two applications of the score are illustrated: comparison of real and model maps; and comparison of two model maps. The issue of missing data is addressed, and the evaluation is performed both when data are available over continents or oceans only, and when they are available globally, over the whole domain.The score is tested against the conventional two-dimensional correlation coefficient, which is widely used in evaluating forecast performance. We show that the score eliminates random correlations, which the correlation coefficient incorrectly detects as similarity of fields that are actually dissimilar. The technique is first applied to the case of non-square matrices (spatial fields) of the same dimensions (spatial grids), and then to the most general case of matrices of different dimensions, by applying some necessary interpolations. The technique is tested on data from several runs of different GENIE models. It is then applied to the comparison of climate data (global fields of temperature and specific humidity) from the NCEP and ECMWF reanalyses and from the HadCM3 and GENIE models. To study the time evolution of a given 2D field, we analyse a plot of the score values for consecutive time slices, thus visualizing the temporal dynamics. The technique is particularly useful for automated comparison of large sets of 2D data, where direct visualization is best avoided. The score may be generalized for comparison of data of higher dimensions, in particular 3D ocean fields.
We investigate the post-fit range-rate residuals after the gravity field parameter estimation from the inter-satellite ranging data of the gravity recovery and climate experiment (grace) satellite mission. Of particular interest is the high-frequency spectrum (f >20 mhz) which is dominated by the microwave ranging system noise. Such analysis is carried out to understand the yet unsolved discrepancy between the predicted baseline errors and the observed ones. The analysis consists of two parts. First, we present the effects in the signal-to-noise ratio (snrs) of the k-band ranging system. The snrs are also affected by the moon intrusions into the star cameras' field of view and magnetic torquer rod currents in addition to the effects presented by Harvey et al. [2016]. Second, we analyze the range-rate residuals to study the effects of the kbr system noise. The range-rate residuals are dominated by the non-stationary errors in the high-frequency observations. These high-frequency errors in the range-rate residuals are found to be dependent on the temperature and effects of sun intrusion into the star cameras' field of view reflected in the snrs of the k-band phase observations. an important step in the global gravity field determination. Recent investigations of the star camera [Bandikova & Flury, 2014, Ko et al., 2015 and accelerometer data [Klinger & Mayer-Gürr, 2016], helped to improve the data pre-processing resulted in a significant improvement in the quality of the estimated gravity field.Pre-launch studies of the grace mission done by Kim [2000] show that the sensor noise level in the range-rate observations predominantly consists of the accelerometer noise, star camera noise and kbr (k-band ranging) system noise. The behavior of accelerometer and kbr system noise was predicted in terms of their error models as shown in Fig. 1. When the gravity field models are computed from grace range-rate observations, we observe the deviation between the current error level and the predicted error level of kbr system noise. Earlier studies by Thomas [1999] and Ko [2008] demonstrated that the kbr system noise is dominating in the high frequencies of the range-rate observations, i.e. above mhz. Therefore, we analyze the high-frequency range-rate observations to study the contribution of the kbr system noise (highlighted in Fig. 1).Earlier, the kbr system was comprehensively studied by Thomas [1999] prior to the launch of the grace. The performance of the jpl designed k-band ranging instrument had been thoroughly studied in the context of the satellite-to-satellite tracking principle. Ko [2008] investigated the time-series of the high-frequency post-fit range-rate residuals and provided initial strategies for analyzing sensor noise. This was followed by an analysis of the signal-to-noise ratio (snr) of the ranging system , which correlated the poor snr values of the ranging system with the high-frequency range-rate residuals. However, the study did not establish the source of the poor snr values. We investigated the sour...
Gravity Recovery and Climate Experiment Follow-On (GRACE-FO) was launched on May 22, 2018. It carries the Laser Ranging Interferometer (LRI) as a technology demonstrator that measures the inter-satellite range with nanometer precision using a laser-link between satellites. To maintain the laser-link between satellites, the LRI uses the beam steering method: a Fast Steering Mirror (FSM) is actuated to correct for misalignment between the incoming and outgoing laser beams. From the FSM commands, we can compute the inter-satellite pitch and yaw angles. These angles provide information about the spacecraft's relative orientation with respect to line-of-sight (LOS). We analyze LRI derived intersatellite pointing angles for 2019 and 2020. Further, we present its comparison with the pointing angles derived from GRACE-FO SCA1B data, which represents the spacecraft attitude computed from star cameras and Inertial Measurement Unit (IMU) data using a Kalman filter. We discuss the correlations seen between the laser based attitude data and the spacecraft temperature variations. This analysis serves as the basis to explore the potential of this new attitude product obtained from the Differential Wavefront Sensing (DWS) control of a FSM.
Abstract. For further improvements of gravity field models based on Gravity Recovery and Climate Experiment (GRACE) observations, it is necessary to identify the error sources within the recovery process. Observation residuals obtained during the gravity field recovery contain most of the measurement and modeling errors and thus can be considered a realization of actual errors. In this work, we investigate the ability of wavelets to help in identifying specific error sources in GRACE range-rate residuals. The multiresolution analysis (MRA) using discrete wavelet transform (DWT) is applied to decompose the residual signal into different scales with corresponding frequency bands. Temporal, spatial, and orbit-related features of each scale are then extracted for further investigations. The wavelet analysis has proven to be a practical tool to find the main error contributors. Besides the previously known sources such as K-band ranging (KBR) system noise and systematic attitude variations, this method clearly shows effects which the classic spectral analysis is hardly able or unable to represent. These effects include long-term signatures due to satellite eclipse crossings and dominant ocean tide errors.
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