Black sea annual and inter-annual water mass variations from space

This study evaluates the performance of two widely used GRACE solutions (CNES/GRGS RL02 and CSR RL04) in deriving annual and inter-annual water mass variations in the Black Sea for the period 2003–2007. It is demonstrated that the GRACE derived water mass variations in the Black Sea are heavily influenced by the leakage of hydrological signals from the surrounding land. After applying the corresponding correction, we found a good agreement with water mass variations derived from steric-corrected satellite altimetry observations. Both GRACE and altimetry show significant annual water mass variations of roughly 7 cm amplitude peaking in May and a semi-annual signal of roughly 3 cm peaking in June and in December. The amplitude of the annual water mass signal varies significantly from year to year and is significantly larger during 2004–2006 than in 2003 and 2007. This is also in agreement with the steric corrected altimetry.     

Self-consistent treatment of tidal variations in the geocenter for precise orbit determination

We show that the current levels of accuracy being achieved for the precise orbit determination (POD) of low-Earth orbiters demonstrate the need for the self-consistent treatment of tidal variations in the geocenter. Our study uses as an example the POD of the OSTM/Jason-2 satellite altimeter mission based upon Global Positioning System (GPS) tracking data. Current GPS-based POD solutions are demonstrating root-mean-square (RMS) radial orbit accuracy and precision of \({<}1\)  cm and 1 mm, respectively. Meanwhile, we show that the RMS of three-dimensional tidal geocenter variations is \({<}6\)  mm, but can be as large as 15 mm, with the largest component along the Earth’s spin axis. Our results demonstrate that GPS-based POD of Earth orbiters is best performed using GPS satellite orbit positions that are defined in a reference frame whose origin is at the center of mass of the entire Earth system, including the ocean tides. Errors in the GPS-based POD solutions for OSTM/Jason-2 of \({<}4\)  mm (3D RMS) and \({<}2\)  mm (radial RMS) are introduced when tidal geocenter variations are not treated consistently. Nevertheless, inconsistent treatment is measurable in the OSTM/Jason-2 POD solutions and manifests through degraded post-fit tracking data residuals, orbit precision, and relative orbit accuracy. For the latter metric, sea surface height crossover variance is higher by \(6~\hbox {mm}^{2}\) when tidal geocenter variations are treated inconsistently.     

Secular changes in Earth’s shape and surface mass loading derived from combinations of reprocessed global GPS networks

The changing distribution of surface mass (oceans, atmospheric pressure, continental water storage, groundwater, lakes, snow and ice) causes detectable changes in the shape of the solid Earth, on time scales ranging from hours to millennia. Transient changes in the Earth’s shape can, regardless of cause, be readily separated from steady secular variation in surface mass loading, but other secular changes due to plate tectonics and glacial isostatic adjustment (GIA) cannot. We estimate secular station velocities from almost 11 years of high quality combined GPS position solutions (GPS weeks 1,000–1,570) submitted as part of the first international global navigation satellite system service reprocessing campaign. Individual station velocities are estimated as a linear fit, paying careful attention to outliers and offsets. We remove a suite of a priori GIA models, each with an associated set of plate tectonic Euler vectors estimated by us; the latter are shown to be insensitive to the a priori GIA model. From the coordinate time series residuals after removing the GIA models and corresponding plate tectonic velocities, we use mass-conserving continental basis functions to estimate surface mass loading including the secular term. The different GIA models lead to significant differences in the estimates of loading in selected regions. Although our loading estimates are broadly comparable with independent estimates from other satellite missions, their range highlights the need for better, more robust GIA models that incorporate 3D Earth structure and accurately represent 3D surface displacements.     

利用GRACE、GPS和绝对重力数据监测斯堪的纳维亚陆地水储量变化

重力卫星GRACE(gravity recovery and climate experiment)监测斯堪的纳维亚半岛陆地水储量变化会受到冰川均衡调整(GIA)信号的严重影响。首先根据该地区绝对重力和GPS并址观测数据计算了GIA重力和垂直位移的实测线性比值,利用该比值和GPS网观测的垂直位移速度场得到了GIA重力。然后,对GRACE观测的重力变化速率进行GIA重力改正,进而可分离陆地水储量变化趋势,避免了使用GIA模型所带来的巨大不确定性,并根据观测数据完整估计了所得结果的不确定性。最后与水文模型作对比分析。结果表明,实测的GIA重力-垂直位移线性比值为0.148±0.020μGal/mm(1Gal=10-2 m/s2),该结果检验了Wahr的理论近似值且与北美实测的结果非常接近。2003年1月至2011年3月期间,斯堪的纳维亚半岛陆地水储量存在明显的增加趋势,信号的主体位于半岛南端的维纳恩湖附近,总的水量增加速率为4.6±2.1km3/a,数据观测期间的累积增加水量为38±17km3。研究结果与WGHM水文模型的结果有较好的一致性,相关系数达到0.69,而与GLDAS水文模型的相关性略小。     

Slope correction for ocean radar altimetry

We develop a slope correction model to improve the accuracy of mean sea surface topography models as well as marine gravity models. The correction is greatest above ocean trenches and large seamounts where the slope of the geoid exceeds 100  \(\upmu \) rad. In extreme cases, the correction to the mean sea surface height is 40 mm and the correction to the along-track altimeter slope is 1–2  \(\upmu \) rad which maps into a 1–2 mGal gravity error. Both corrections are easily applied using existing grids of sea surface slope from satellite altimetry.     

Voxel-optimized regional water vapor tomography and comparison with radiosonde and numerical weather model

Water vapor tomography has been developed as a powerful tool to model spatial and temporal distribution of atmospheric water vapor. Global navigation satellite systems (GNSS) water vapor tomography refers to the 3D structural construction of tropospheric water vapor using a large number of GNSS signals that penetrate the tomographic modeling area from different positions. The modeling area is usually discretized into a number of voxels. A major issue involved is that some voxels are not crossed by any GNSS signal rays, resulting in an undetermined solution to the tomographic system. To alleviate this problem, the number of voxels crossed by GNSS signal rays should be as large as possible. An important way to achieve this is to optimize the geographic distribution of tomographic voxels. We propose an approach to optimize voxel distribution in both vertical and horizontal domains. In the vertical domain, water vapor profiles derived from radiosonde data are exploited to identify the maximum height of tomography and the optimal vertical resolution. In the horizontal domain, the optimal horizontal distribution of voxels is obtained by searching the maximum number of ray-crossing voxels in both latitude and longitude directions. The water vapor tomography optimization procedures are implemented using GPS water vapor data from the Hong Kong Satellite Positioning Reference Station Network. The tomographic water vapor fields solved from the optimized tomographic voxels are evaluated using radiosonde data and a numerical weather prediction non-hydrostatic model (NHM) obtained for the Hong Kong station. The comparisons of tomographic integrated water vapor (IWV) with the radiosonde and NHM IWV show that RMS errors of their differences are 1.41 and 3.09 mm, respectively. Moreover, the tomographic water vapor density results are compared with those of radiosonde and NHM. The RMS error of the density differences between tomography and radiosonde data is 1.05  \(\mathrm{g/m}^{3}\) . For the comparison between tomography and NHM, an overall RMS error of \(1.43\,\mathrm{g/m^{3}}\) is achieved.     

Homogeneous reprocessing of GPS,GLONASS and SLR observations

The International GNSS Service (IGS) provides operational products for the GPS and GLONASS constellation. Homogeneously processed time series of parameters from the IGS are only available for GPS. Reprocessed GLONASS series are provided only by individual Analysis Centers (i. e. CODE and ESA), making it difficult to fully include the GLONASS system into a rigorous GNSS analysis. In view of the increasing number of active GLONASS satellites and a steadily growing number of GPS+GLONASS-tracking stations available over the past few years, Technische Universität Dresden, Technische Universität München, Universität Bern and Eidgenössische Technische Hochschule Zürich performed a combined reprocessing of GPS and GLONASS observations. Also, SLR observations to GPS and GLONASS are included in this reprocessing effort. Here, we show only SLR results from a GNSS orbit validation. In total, 18 years of data (1994–2011) have been processed from altogether 340 GNSS and 70 SLR stations. The use of GLONASS observations in addition to GPS has no impact on the estimated linear terrestrial reference frame parameters. However, daily station positions show an RMS reduction of 0.3 mm on average for the height component when additional GLONASS observations can be used for the time series determination. Analyzing satellite orbit overlaps, the rigorous combination of GPS and GLONASS neither improves nor degrades the GPS orbit precision. For GLONASS, however, the quality of the microwave-derived GLONASS orbits improves due to the combination. These findings are confirmed using independent SLR observations for a GNSS orbit validation. In comparison to previous studies, mean SLR biases for satellites GPS-35 and GPS-36 could be reduced in magnitude from \(-35\) and \(-38\)  mm to \(-12\) and \(-13\)  mm, respectively. Our results show that remaining SLR biases depend on the satellite type and the use of coated or uncoated retro-reflectors. For Earth rotation parameters, the increasing number of GLONASS satellites and tracking stations over the past few years leads to differences between GPS-only and GPS+GLONASS combined solutions which are most pronounced in the pole rate estimates with maximum 0.2 mas/day in magnitude. At the same time, the difference between GLONASS-only and combined solutions decreases. Derived GNSS orbits are used to estimate combined GPS+GLONASS satellite clocks, with first results presented in this paper. Phase observation residuals from a precise point positioning are at the level of 2 mm and particularly reveal poorly modeled yaw maneuver periods.     

A complete VLBI delay model for deforming radio telescopes: the Effelsberg case

Deformations of radio telescopes used in geodetic and astrometric very long baseline interferometry (VLBI) observations belong to the class of systematic error sources which require correction in data analysis. In this paper we present a model for all path length variations in the geometrical optics of radio telescopes which are due to gravitational deformation. The Effelsberg 100 m radio telescope of the Max Planck Institute for Radio Astronomy, Bonn, Germany, has been surveyed by various terrestrial methods. Thus, all necessary information that is needed to model the path length variations is available. Additionally, a ray tracing program has been developed which uses as input the parameters of the measured deformations to produce an independent check of the theoretical model. In this program as well as in the theoretical model, the illumination function plays an important role because it serves as the weighting function for the individual path lengths depending on the distance from the optical axis. For the Effelsberg telescope, the biggest contribution to the total path length variations is the bending of the main beam located along the elevation axis which partly carries the weight of the paraboloid at its vertex. The difference in total path length is almost \(-\) 100 mm when comparing observations at 90 \(^\circ \) and at 0 \(^\circ \) elevation angle. The impact of the path length corrections is validated in a global VLBI analysis. The application of the correction model leads to a change in the vertical position of \(+120\)  mm. This is more than the maximum path length, but the effect can be explained by the shape of the correction function.     

Evaluation and validation of mascon recovery using GRACE KBRR data with independent mass flux estimates in the Mississippi Basin

The direct recovery of surface mass anomalies using GRACE KBRR data processed in regional solutions provides mass variation estimates with 10-day temporal resolution. The approach undertaken herein uses a tailored orbit estimation strategy based solely on the KBRR data and directly estimates mass anomalies from the GRACE data. We introduce a set of temporal and spatial correlation constraints to enable high resolution mass flux estimates. The Mississippi Basin, with its well understood surface hydrological modelling available from the Global Land Data Assimilation System (GLDAS), which uses advanced land surface modeling and data assimilation techniques, and a wealth of groundwater data, provides an opportunity to quantitatively compare GRACE estimates of the mass flux in the entire hydrological column with those available from independent and reliable sources. Evaluating GRACE’s performance is dependent on the accuracy ascribed to the hydrological information, which in and of itself is a complex challenge (Rodell in Hydrogeol J, doi:, 2007). Nevertheless, the Mississippi Basin is one of the few regions having a large hydrological signal that can support a meaningful GRACE comparison on the spatial scale resolved by GRACE. The isolation of the hydrological signal is dependent on the adequacy of the forward mass flux modeling for tides and atmospheric pressure variations. While these models have non-uniform global performance they are excellent in the Mississippi Basin. Through comparisons with the independent hydrology, we evaluate the effect on the solution of changing correlation times and distances in the constraints, altering the parameter recovery for areas external to the Mississippi Basin, and changing the relative strength of the constraints with respect to the KBRR data. The accuracy and stability of the mascon solutions are thereby assessed, especially with regard to the constraints used to stabilize the solution. We show that the mass anomalies, as represented by surface layer of water within regional cells have accuracy estimates of ±2–3 cm on par with the best hydrological estimates and consistent with our accuracy estimates for GRACE mass anomaly estimates. These solutions are shown to be very stable, especially for the recovery of semi-annual and longer period trends, where for example, the phase agreement for the dominant annual signal agrees at the 10-day level of resolution provided by GRACE. This validation confirms that mascons provide critical environmental data records for a wide range of applications including monitoring ground water mass changes.     

An improved and extended GPS-derived 3D velocity field of the glacial isostatic adjustment (GIA) in Fennoscandia

We present a new GPS-derived 3D velocity field for the Fennoscandia glacial isostatic adjustment (GIA) area. This new solution is based upon ∼3,000 days of continuous GPS observations obtained from the permanent networks in Fennoscandia. The period encompasses a prolongated phase of stable observation conditions after the northern autumn of 1996. Several significant improvements have led to smaller uncertainties and lower systematic errors in the new solutions compared to our previous results. The GPS satellite elevation cut-off angle was lowered to 10°, we fixed ambiguities to integers where possible, and only a few hardware changes occurred over the entire network. The GAMIT/GLOBK software package was used for the GPS analysis and reference frame realization. Our new results confirmed earlier findings of maximum discrepancies between GIA models and observations in northern Finland. The reason may be related to overestimated ice-sheet thickness and glaciation period in the north. In general, the new solutions are more coherent in the velocity field, as some of the perturbations are now avoided. We compared GPS-derived GIA rates with sea-level rates from tide-gauge observations, repeated precise leveling, and with GIA model computations, which showed consistency.     

Improved GRACE science results after adjustment of geometric biases in the Level-1B K-band ranging data

The GRACE (Gravity Recovery and Climate Experiment) satellite mission relies on the inter-satellite K-band microwave ranging (KBR) observations. We investigate systematic errors that are present in the Level-1B KBR data, namely in the geometric correction. This correction converts the original ranging observation (between the two KBR antennas phase centers) into an observation between the two satellites’ centers of mass. It is computed from data on the precise alignment between both satellites, that is, between the lines joining the center of mass and the antenna phase center of either satellite. The Level-1B data used to determine this alignment exhibit constant biases as large as 1–2 mrad in terms of pitch and yaw alignment angles. These biases induce non-constant errors in the Level-1B geometric correction. While the precise origin of the biases remains to be identified, we are able to estimate and reduce them in a re-calibration approach. This significantly improves time-variable gravity field solutions based on the CNES/GRGS processing strategy. Empirical assessments indicate that the systematic KBR data errors have previously induced gravity field errors on the level of 6–11 times the so-called GRACE baseline error level. The zonal coefficients (from degree 14) are particularly affected. The re-calibration reduces their rms errors by about 50%. As examples for geophysical inferences, the improvement enhances agreement between mass variations observed by GRACE and in-situ ocean bottom pressure observations. The improvement also importantly affects estimates of inter-annual mass variations of the Antarctic ice sheet.     

Canadian gravimetric geoid model 2010

A new gravimetric geoid model, Canadian Gravimetric Geoid 2010 (CGG2010), has been developed to upgrade the previous geoid model CGG2005. CGG2010 represents the separation between the reference ellipsoid of GRS80 and the Earth’s equipotential surface of $W_0=62{,}636{,}855.69~\mathrm{m}^2\mathrm{s}^{-2}$ W 0 = 62 , 636 , 855.69 m 2 s ? 2 . The Stokes–Helmert method has been re-formulated for the determination of CGG2010 by a new Stokes kernel modification. It reduces the effect of the systematic error in the Canadian terrestrial gravity data on the geoid to the level below 2 cm from about 20 cm using other existing modification techniques, and renders a smooth spectral combination of the satellite and terrestrial gravity data. The long wavelength components of CGG2010 include the GOCE contribution contained in a combined GRACE and GOCE geopotential model: GOCO01S, which ranges from $-20.1$ ? 20.1 to 16.7 cm with an RMS of 2.9 cm. Improvement has been also achieved through the refinement of geoid modelling procedure and the use of new data. (1) The downward continuation effect has been accounted accurately ranging from $-22.1$ ? 22.1 to 16.5 cm with an RMS of 0.9 cm. (2) The geoid residual from the Stokes integral is reduced to 4 cm in RMS by the use of an ultra-high degree spherical harmonic representation of global elevation model for deriving the reference Helmert field in conjunction with a derived global geopotential model. (3) The Canadian gravimetric geoid model is published for the first time with associated error estimates. In addition, CGG2010 includes the new marine gravity data, ArcGP gravity grids, and the new Canadian Digital Elevation Data (CDED) 1:50K. CGG2010 is compared to GPS-levelling data in Canada. The standard deviations are estimated to vary from 2 to 10 cm with the largest error in the mountainous areas of western Canada. We demonstrate its improvement over the previous models CGG2005 and EGM2008.     

Deformation analysis of the Lake Urmia causeway (LUC) embankments in northwest Iran: insights from multi-sensor interferometry synthetic aperture radar (InSAR) data and finite element modeling (FEM)

This paper presents deformation analysis of Lake Urmia causeway (LUC) embankments in northwest Iran using observations from interferometry synthetic aperture radar (InSAR) and finite element model (FEM) simulation. 58 SAR images including 10 ALOS, 30 Envisat and 18 TerraSAR-X are used to assess settlement of the embankments during 2003–2013. The interferometric dataset includes 140 differential interferograms which are processed using InSAR time series technique of small baseline subset approach. The results show a clear indication of large deformation on the embankments with peak amplitude of \(>\) 50 mm/year in 2003–2010, increasing to \(>\!\!80\)  mm/year in 2012–2013 in the line of sight (LOS) direction from ground to the satellite. 2D decomposition of InSAR observations from Envisat and ALOS satellites that overlap in the years 2007–2010 shows that the rate of the vertical settlement and horizontal motion is not uniform along the embankments; Both eastern and western embankments show significant vertical motion, while horizontal motion plays a more significant role in eastern embankment than western embankment. The InSAR results are then used to simulate deformation using FEM at two cross-sections at the distance of 4 and 9 km from the most western edge of the LUC for which detailed stratigraphy data are available. Results suggest that consolidation due to dissipation of excess pore pressure in embankments can satisfactory predict settlement of the LUC embankments. Our numerical modeling indicates that nearly half of the consolidation since the construction time of the causeway 30 years ago has been done.     

Global empirical model for mapping zenith wet delays onto precipitable water

We can map zenith wet delays onto precipitable water with a conversion factor, but in order to calculate the exact conversion factor, we must precisely calculate its key variable $T_\mathrm{m}$ . Yao et al. (J Geod 86:1125–1135, 2012. doi:10.1007/s00190-012-0568-1) established the first generation of global $T_\mathrm{m}$ model (GTm-I) with ground-based radiosonde data, but due to the lack of radiosonde data at sea, the model appears to be abnormal in some areas. Given that sea surface temperature varies less than that on land, and the GPT model and the Bevis $T_\mathrm{m}$ – $T_\mathrm{s}$ relationship are accurate enough to describe the surface temperature and $T_\mathrm{m}$ , this paper capitalizes on the GPT model and the Bevis $T_\mathrm{m}$ – $T_\mathrm{s}$ relationship to provide simulated $T_\mathrm{m}$ at sea, as a compensation for the lack of data. Combined with the $T_\mathrm{m}$ from radiosonde data, we recalculated the GTm model coefficients. The results show that this method not only improves the accuracy of the GTm model significantly at sea but also improves that on land, making the GTm model more stable and practically applicable.     

Continental hydrology loading observed by VLBI measurements

Variations in continental water storage lead to loading deformation of the crust with typical peak-to-peak variations at very long baseline interferometry (VLBI) sites of 3–15 mm in the vertical component and 1–2 mm in the horizontal component. The hydrology signal at VLBI sites has annual and semi-annual components and clear interannual variations. We have calculated the hydrology loading series using mass loading distributions derived from the global land data assimilation system (GLDAS) hydrology model and alternatively from a global grid of equal-area gravity recovery and climate experiment (GRACE) mascons. In the analysis of the two weekly VLBI 24-h R1 and R4 network sessions from 2003 to 2010 the baseline length repeatabilities are reduced in 79 % (80 %) of baselines when GLDAS (GRACE) loading corrections are applied. Site vertical coordinate repeatabilities are reduced in about 80 % of the sites when either GLDAS or GRACE loading is used. In the horizontal components, reduction occurs in 70–80 % of the sites. Estimates of the annual site vertical amplitudes were reduced for 16 out of 18 sites if either loading series was applied. We estimated loading admittance factors for each site and found that the average admittances were 1.01 \(\pm \) 0.05 for GRACE and 1.39 \(\pm \) 0.07 for GLDAS. The standard deviations of the GRACE admittances and GLDAS admittances were 0.31 and 0.68, respectively. For sites that have been observed in a set of sufficiently temporally dense daily sessions, the average correlation between VLBI vertical monthly averaged series and GLDAS or GRACE loading series was 0.47 and 0.43, respectively.     

Evaluation of the third- and fourth-generation GOCE Earth gravity field models with Australian terrestrial gravity data in spherical harmonics

In March 2013, the fourth generation of European Space Agency’s (ESA) global gravity field models, DIR4 (Bruinsma et al. in Proceedings of the ESA living planet symposium, 28 June–2 July, Bergen, ESA, Publication SP-686, 2010b) and TIM4 (Migliaccio et al. in Proceedings of the ESA living planet symposium, 28 June–2 July, Bergen, ESA, Publication SP-686, 2010), generated from the Gravity field and steady-state Ocean Circulation Explorer (GOCE) gravity observation satellite was released. We evaluate the models using an independent ground truth data set of gravity anomalies over Australia. Combined with Gravity Recovery and Climate Experiment (GRACE) satellite gravity, a new gravity model is obtained that is used to perform comparisons with GOCE models in spherical harmonics. Over Australia, the new gravity model proves to have significantly higher accuracy in the degrees below 120 as compared to EGM2008 and seems to be at least comparable to the accuracy of this model between degree 150 and degree 260. Comparisons in terms of residual quasi-geoid heights, gravity disturbances, and radial gravity gradients evaluated on the ellipsoid and at approximate GOCE mean satellite altitude ( $h=250$  km) show both fourth generation models to improve significantly w.r.t. their predecessors. Relatively, we find a root-mean-square improvement of 39 % for the DIR4 and 23 % for TIM4 over the respective third release models at a spatial scale of 100 km (degree 200). In terms of absolute errors, TIM4 is found to perform slightly better in the bands from degree 120 up to degree 160 and DIR4 is found to perform slightly better than TIM4 from degree 170 up to degree 250. Our analyses cannot confirm the DIR4 formal error of 1 cm geoid height (0.35 mGal in terms of gravity) at degree 200. The formal errors of TIM4, with 3.2 cm geoid height (0.9 mGal in terms of gravity) at degree 200, seem to be realistic. Due to combination with GRACE and SLR data, the DIR models, at satellite altitude, clearly show lower RMS values compared to TIM models in the long wavelength part of the spectrum (below degree and order 120). Our study shows different spectral sensitivity of different functionals at ground level and at GOCE satellite altitude and establishes the link among these findings and the Meissl scheme (Rummel and van Gelderen in Manusrcipta Geodaetica 20:379–385, 1995).     

Seasonal and inter-annual variability of atmosphere CO<Subscript>2</Subscript> based on NOAA Carbon Tracker analysis and satellite observations

A study on seasonal and inter-annual variability of the atmospheric CO₂ is carried out based on National Oceanic and Atmospheric Administration Carbon Tracker (NOAACT) re-analysis and satellite measurements of mid-troposphere CO₂ by Atmosphere Infrared Sounder on board NASA’s Aqua and lower troposphere CO₂ by Greenhouse-gas Observing Satellite. Seasonal and non-seasonal components of each time series were extracted by means of least square based harmonic analysis procedure. The data of surface CO₂ fluxes used in the NOAACT are also analyzed to examine its relationship with the atmosphere CO₂ variability at different time scales. There exists good consistency between NOAACT analysis and satellite observations in their respective seasonal harmonics and climatology. Surface layer CO₂ exhibits large climatological mean over the regions of major anthropogenic sources together with strong seasonal cycle over the humid and cold climatic terrestrial regions especially over the northern hemisphere. Existence of high coherency with the different components of the surface fluxes shows that surface layer atmosphere CO₂ seasonality is primarily contributed from the terrestrial ecosystem exchanges and secondarily by anthropogenic and oceanic exchanges. The mid-troposphere CO₂ exhibits large values associated with climatology and amplitudes of semi-annual and annual cycles over the northern extra tropics and Polar Regions along with a gradual decreasing trend from northern to southern hemisphere. Inter-annual variability of atmospheric CO₂ in the NOAACT in some extent is consistent with the satellite observations. Large scale circulation patterns, its fluctuations associated with ENSO events and large scale ecosystem disturbances have significant influence on the inter-annual variability.     

Effect of the processing methodology on satellite altimetry-based global mean sea level rise over the Jason-1 operating period

Determining how the global mean sea level (GMSL) evolves with time is of primary importance to understand one of the main consequences of global warming and its potential impact on populations living near coasts or in low-lying islands. Five groups are routinely providing satellite altimetry-based estimates of the GMSL over the altimetry era (since late 1992). Because each group developed its own approach to compute the GMSL time series, this leads to some differences in the GMSL interannual variability and linear trend. While over the whole high-precision altimetry time span (1993–2012), good agreement is noticed for the computed GMSL linear trend (of $3.1\pm 0.4$  mm/year), on shorter time spans (e.g., ${<}10~\hbox {years}$ ), trend differences are significantly larger than the 0.4 mm/year uncertainty. Here we investigate the sources of the trend differences, focusing on the averaging methods used to generate the GMSL. For that purpose, we consider outputs from two different groups: the Colorado University (CU) and Archiving, Validation and Interpretation of Satellite Oceanographic Data (AVISO) because associated processing of each group is largely representative of all other groups. For this investigation, we use the high-resolution MERCATOR ocean circulation model with data assimilation (version Glorys2-v1) and compute synthetic sea surface height (SSH) data by interpolating the model grids at the time and location of “true” along-track satellite altimetry measurements, focusing on the Jason-1 operating period (i.e., 2002–2009). These synthetic SSH data are then treated as “real” altimetry measurements, allowing us to test the different averaging methods used by the two processing groups for computing the GMSL: (1) averaging along-track altimetry data (as done by CU) or (2) gridding the along-track data into $2^{\circ }\times 2^{\circ }$ meshes and then geographical averaging of the gridded data (as done by AVISO). We also investigate the effect of considering or not SSH data at shallow depths $({<}120~\hbox {m})$ as well as the editing procedure. We find that the main difference comes from the averaging method with significant differences depending on latitude. In the tropics, the $2^{\circ }\times 2^{\circ }$ gridding method used by AVISO overestimates by 11 % the GMSL trend. At high latitudes (above $60^{\circ }\hbox {N}/\hbox {S}$ ), both methods underestimate the GMSL trend. Our calculation shows that the CU method (along-track averaging) and AVISO gridding process underestimate the trend in high latitudes of the northern hemisphere by 0.9 and 1.2 mm/year, respectively. While we were able to attribute the AVISO trend overestimation in the tropics to grid cells with too few data, the cause of underestimation at high latitudes remains unclear and needs further investigation.     

Hydrological excitation of polar motion by different variables from the GLDAS models

Continental hydrological loading by land water, snow and ice is a process that is important for the full understanding of the excitation of polar motion. In this study, we compute different estimations of hydrological excitation functions of polar motion (as hydrological angular momentum, HAM) using various variables from the Global Land Data Assimilation System (GLDAS) models of the land-based hydrosphere. The main aim of this study is to show the influence of variables from different hydrological processes including evapotranspiration, runoff, snowmelt and soil moisture, on polar motion excitations at annual and short-term timescales. Hydrological excitation functions of polar motion are determined using selected variables of these GLDAS realizations. Furthermore, we use time-variable gravity field solutions from the Gravity Recovery and Climate Experiment (GRACE) to determine the hydrological mass effects on polar motion excitation. We first conduct an intercomparison of the maps of variations of regional hydrological excitation functions, timing and phase diagrams of different regional and global HAMs. Next, we estimate the hydrological signal in geodetically observed polar motion excitation as a residual by subtracting the contributions of atmospheric angular momentum and oceanic angular momentum. Finally, the hydrological excitations are compared with those hydrological signals determined from residuals of the observed polar motion excitation series. The results will help us understand the relative importance of polar motion excitation within the individual hydrological processes, based on hydrological modeling. This method will allow us to estimate how well the polar motion excitation budget in the seasonal and inter-annual spectral ranges can be closed.     

Error analysis of the NGS’ surface gravity database

Are the National Geodetic Survey’s surface gravity data sufficient for supporting the computation of a 1 cm-accurate geoid? This paper attempts to answer this question by deriving a few measures of accuracy for this data and estimating their effects on the US geoid. We use a data set which comprises ${\sim }1.4$ million gravity observations collected in 1,489 surveys. Comparisons to GRACE-derived gravity and geoid are made to estimate the long-wavelength errors. Crossover analysis and $K$ -nearest neighbor predictions are used for estimating local gravity biases and high-frequency gravity errors, and the corresponding geoid biases and high-frequency geoid errors are evaluated. Results indicate that 244 of all 1,489 surface gravity surveys have significant biases ${>}2$  mGal, with geoid implications that reach 20 cm. Some of the biased surveys are large enough in horizontal extent to be reliably corrected by satellite-derived gravity models, but many others are not. In addition, the results suggest that the data are contaminated by high-frequency errors with an RMS of ${\sim }2.2$  mGal. This causes high-frequency geoid errors of a few centimeters in and to the west of the Rocky Mountains and in the Appalachians and a few millimeters or less everywhere else. Finally, long-wavelength ( ${>}3^{\circ }$ ) surface gravity errors on the sub-mGal level but with large horizontal extent are found. All of the south and southeast of the USA is biased by +0.3 to +0.8 mGal and the Rocky Mountains by $-0.1$ to $-0.3$  mGal. These small but extensive gravity errors lead to long-wavelength geoid errors that reach 60 cm in the interior of the USA.