Arctic sea level variability from high-resolution model simulations and implications for the Arctic observing system

Two high-resolution model simulations are used to investigate the spatiotemporal variability of the Arctic Ocean sea level. The model simulations reveal barotropic sea level variability at periods of < 30 d, which is strongly captured by bottom pressure observations. The seasonal sea level variability is driven by volume exchanges with the Pacific and Atlantic oceans and the redistribution of the water by the wind. Halosteric effects due to river runoff and evaporation minus precipitation ice melting/formation also contribute in the marginal seas and seasonal sea ice extent regions. In the central Arctic Ocean, especially the Canadian Basin, the decadal halosteric effect dominates sea level variability. The study confirms that satellite altimetric observations and Gravity Recovery and Climate Experiment (GRACE) could infer the total freshwater content changes in the Canadian Basin at periods longer than 1 year, but they are unable to depict the seasonal and subseasonal freshwater content changes. The increasing number of profiles seems to capture freshwater content changes since 2007, encouraging further data synthesis work with a more complicated interpolation method. Further, in situ hydrographic observations should be enhanced to reveal the freshwater budget and close the gaps between satellite altimetry and GRACE, especially in the marginal seas.

Analysis and Simulations of a Heavy Rainfall Event Associated with the Passage of a Shallow Front over Northern Taiwan on 2 June 2017

From 0200 to 1000 LST 2 June 2017, the shallow, East-West oriented Mei-Yu front (< 1 km) cannot move over the Yang-Ming Mountains (with peaks ∼ 1120 m) when it first arrives. The postfrontal cold air at the surface is deflected by the Yang-Ming Mountains and moves through the Keelung River and Tamsui River valleys into the Taipei Basin. The shallow northerly winds are anchored along the northern side of the Yang-Ming Mountains for 8 hours. In addition, the southwesterly barrier jet with maximum winds in the 900–950-hPa layer brings in abundant moisture and converges with the northwesterly flow in the southwestern flank of the Mei-Yu frontal cyclone. Therefore, torrential rain (> 600 mm) occurs over the northern side of the Yang-Ming Mountains. From 1100 to 1200 LST, with the gradual deepening of the postfrontal cold air, the front finally passes over the Yang-Ming Mountains and arrives at the Taipei Basin, which results in an E-W oriented rainband with the rainfall maxima over the northwestern coast and Taipei Basin. From 1300 to 1400 LST, the frontal rainband continues to move southward with rainfall over the northwestern slopes of the Snow Mountains. In the prefrontal southwesterly flow, the orographic lifting of the moisture-laden low-level winds results in heavy rainfall on the southwestern slopes of the Snow Mountains and the Central Mountain Range. With the terrain of the Yang-Ming Mountains removed in the high-resolution model, the Mei-Yu front moves quickly southward without a rainfall maximum over the northern tip of Taiwan.

Satellite data validation: a parametrization of the natural variability of atmospheric mixing ratios

High-resolution model data are used to estimate typical variabilities of mixing ratios of trace species as a function of spatial and temporal distance. These estimates can be used to explain that part of the differences between observations made with different observing systems that are due to less than perfect collocation of the measurements. The variability values are described by a two-parameter regression function. A reparametrization of the variabilities values as function of latitudinal graidents is proposed, and season-independence of linear approximation of such function is demonstrated.

Formulation and demonstration of an extended-3DVAR multi-scale data assimilation system for the SWOT altimetry era

A state-of-the-art data assimilation system for a high-resolution model has been developed to address the opportunities and challenges posed by the upcoming Surface Water and Ocean Topography (SWOT) satellite mission. A new ‘extended’ three-dimensional variational data assimilation scheme (extended-3DVAR) is formulated to assimilate observations over a time interval, and integrated using a multi-scale approach (hereafter MSDA). The new MSDA scheme specifically enhances the efficacy of the assimilation of satellite along-track altimetry observations, which are limited by large repeat time intervals. This developed system is computationally highly efficient, and thus can be applied to a very high-resolution model. A crucial consideration of the system is first to assimilate routinely available observations, including satellite altimetry, sea surface temperature (SST) and temperature/salinity vertical profiles, to constrain large scales and large mesoscales. High-resolution (dense) observations and future SWOT measurements can then be effectively and seamlessly assimilated to constrain the smaller scales. Using this system, a reanalysis dataset was produced for the SWOT pre-launch field campaign that took place in the California Current System from September through December, 2019. An evaluation of this system with assimilated and withheld data demonstrates its ability to effectively utilize both routine and campaign observations. These results suggest a promising avenue for data assimilation development in the SWOT altimetry era, which will require the capability to efficiently assimilate large-volume datasets resolving small-scale ocean processes.

Effect of horizontal resolution on the simulation of tropical cyclones in the Chinese Academy of Sciences FGOALS-f3 climate system model

The effects of horizontal resolution on the simulation of tropical cyclones were studied using the Chinese Academy of Sciences Flexible Global Ocean–Atmosphere–Land System Finite-Volume version 3 (FGOALS-f3) climate system model from the High-Resolution Model Intercomparison Project (HighResMIP) for the Coupled Model Intercomparison Project phase 6 (CMIP6). Both the low-resolution (about 100 km resolution) FGOALS-f3 model (FGOALS-f3-L) and the high-resolution (about 25 km resolution) FGOALS-f3 (FGOALS-f3-H) models were used to achieve the standard Tier 1 experiment required by HighResMIP. FGOALS-f3-L and FGOALS-f3-H have the same model parameterizations with the exactly the same parameters. The only differences between the two models are the horizontal resolution and the time step. The performance of FGOALS-f3-H and FGOALS-f3-L in simulating tropical cyclones was evaluated using observations. FGOALS-f3-H (25 km resolution) simulated more realistic distributions of the formation, movement and intensity of the climatology of tropical cyclones than FGOALS-f3-L at 100 km resolution. Although the number of tropical cyclones increased by about 50 % at the higher resolution and better matched the observed values in the peak month, both FGOALS-f3-L and FGOALS-f3-H appear to replicate the timing of the seasonal cycle of tropical cyclones. The simulated average and interannual variabilities of the number of tropical cyclones and the accumulated cyclone energy were both significantly improved from FGOALS-f3-L to FGOALS-f3-H over most of the ocean basins. The characteristics of tropical cyclones (e.g., the average lifetime, the wind–pressure relationship and the horizontal structure) were more realistic in the simulation using the high-resolution model. The possible physical linkage between the performance of the tropical cyclone simulation and the horizontal resolution were revealed by further analyses. The improvement in the response between the El Niño–Southern Oscillation and the number of tropical cyclones and the accumulated cyclone energy in FGOALS-f3 contributed to the realistic simulation of tropical cyclones. The genesis potential index and the vorticity, relative humidity, maximum potential intensity and the wind shear terms were used to diagnose the effects of resolution. We discuss the current insufficiencies and future directions of improvement for the simulation of tropical cyclones and the potential applications of the FGOALS-f3-H model in the subseasonal to seasonal prediction of tropical cyclones.

Decay Detection in an Ancient Column with Combined Close-Range Photogrammetry (CRP) and Ultrasonic Tomography

This study presents the integrated application of a few non-destructive techniques, i.e., Close Range Photogrammetry (CRP), and low frequency (24 kHz) ultrasonic tomography complemented by petrographical analysis. The aim here is to assess the conservation state of a Carrara marble column in the Basilica of San Saturnino, which is part of a V-VI century Palaeo Christian complex in the city of Cagliari (Italy). The high resolution 3D modelling of the studied artifact was computed starting from the integration of proximal sensing techniques, such as CRP based on the Structure from Motion (SfM) technique, which provided information on the geometrical anomalies and reflectivity of the investigated marble column surface. The inner parts of the studied body were inspected successfully in a non-invasive way by computing the velocity pattern of the ultrasonic signal through the investigated materials, using 3D ultrasonic tomography. The latter was optimally designed based on the 3D CRP analysis and the locations of the source and receiver points were detected as accurately as possible. The integrated application of in situ CRP and ultrasonic techniques provided a full 3D high resolution model of the investigated artifact, which made it possible to evaluate the material characteristics and its degradation state, affecting mainly the shallower parts of the column. The 3D visualisation improves the efficiency, accuracy, and completeness of the interpretative process of data of a different nature in quite easily understood displays, as well as the communication between different technicians.

Water mass transformation and overturning circulation in the Arabian Gulf

We diagnose the ocean’s residual overturning circulation of the Arabian Gulf in a high-resolution model and interpret it in terms ofwater-mass transformation processes mediated by air-sea buoyancy fluxes and interior mixing. We attempt to rationalise the complex three-dimensional flow in terms of the superposition of a zonal (roughly along-axis) and meridional (transverse) overturning pattern. Rates of overturning and the seasonal cycle of air-sea fluxes sustaining them are quantified and ranked in order of importance. Air-sea fluxes dominate the budget so that, at zero order, the magnitude and sense of the overturning circulation can be inferred from air-sea fluxes, with interior mixing playing a lesser role. We find that wintertime latent heat fluxes dominate the water-mass transformation rate in the interior waters of the Gulf leading to a diapycnal volume flux directed toward higher densities. In the zonal overturning cell, fluid is drawn in from the Sea of Oman through the Strait of Hormuz, transformed and exits the Strait near the southern and bottom boundaries. Along the southern margin of the Gulf, evaporation plays an important role in the meridional overturning pattern inducing sinking there.

Reanalyses and a high-resolution model fail to capture the ‘high tail’ of CAPE distributions

Convective available potential energy (CAPE) is of strong interest in climate modeling because of its role in both severe weather and in model construction. Extreme levels of CAPE (> 2000 J/kg) are associated with high-impact weather events, and CAPE is widely used in convective parametrizations to help determine the strength and timing of convection. However, to date few studies have systematically evaluated CAPE biases in models in a climatological context, and none have addressed bias in the high tail of CAPE distributions. This work compares CAPE distributions in ~200,000 summertime proximity soundings from four sources: the observational radiosonde network (IGRA), 0.125 degree reanalyses (ERA-Interim and ERA5), and a 4-km convection-permitting regional WRF simulation driven by ERA-Interim. Both reanalyses and the WRF model consistently show too-narrow distributions of CAPE, with the high tail (> 90th percentile) systematically biased low by up to 10% in surface-based CAPE and even more in alternate CAPE definitions. This “missing tail” corresponds to the most impacts-relevant conditions. CAPE bias in all datasets is driven by surface temperature and humidity: reanalyses and the WRF model underpredict observed cases of extreme heat and moisture. These results suggest that reducing inaccuracies in land surface and boundary layer models is critical for accurately reproducing CAPE.