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Amar Deep Tiwari, Parthasarathi Mukhopadhyay, and Vimal Mishra

Abstract

The efforts to develop a hydrologic model-based operational streamflow forecast in India are limited. We evaluate the role of bias correction of meteorological forecast and streamflow post-processing on hydrological prediction skill in India. We use the Variable Infiltration Capacity (VIC) model to simulate runoff and root zone soil moisture in the Narmada basin (drainage area: 97,410 km2), which was used as a testbed to examine the forecast skill along with the observed streamflow. We evaluated meteorological and hydrological forecasts during the monsoon (June-September) season for 2000-2018 period. The raw meteorological forecast displayed relatively low skill against the observed precipitation at 1-3 day lead time during the monsoon season. Similarly, the forecast skill was low with mean normalized root mean squared error (NRMSE) more than 0.9 and mean absolute bias larger than 60% for extreme precipitation at the 1-3-day lead time. We used Empirical Quantile Mapping (EQM) to bias correct precipitation forecast. The bias correction of precipitation forecast resulted in significant improvement in the precipitation forecast skill. Runoff and root zone soil moisture forecast was also significantly improved due to bias correction of precipitation forecast where the forecast evaluation is performed against the reference model run. However, bias correction of precipitation forecast did not cause considerable improvement in the streamflow prediction. Bias correction of streamflow forecast performs better than the streamflow forecast simulated using the bias-corrected meteorological forecast. The combination of the bias correction of precipitation forecast and post-processing of streamflow resulted in a significant improvement in the streamflow prediction (reduction in bias from 40% to 5%).

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Leo Middleton, Catherine A. Vreugdenhil, Paul R. Holland, and John R. Taylor

Abstract

The transport of heat and salt through turbulent ice shelf–ocean boundary layers is a large source of uncertainty within ocean models of ice shelf cavities. This study uses small-scale, high-resolution, 3D numerical simulations to model an idealized boundary layer beneath a melting ice shelf to investigate the influence of ambient turbulence on double-diffusive convection (i.e., convection driven by the difference in diffusivities between salinity and temperature). Isotropic turbulence is forced throughout the simulations and the temperature and salinity are initialized with homogeneous values similar to observations. The initial temperature and the strength of forced turbulence are varied as controlling parameters within an oceanographically relevant parameter space. Two contrasting regimes are identified. In one regime double-diffusive convection dominates, and in the other convection is inhibited by the forced turbulence. The convective regime occurs for high temperatures and low turbulence levels, where it is long lived and affects the flow, melt rate, and melt pattern. A criterion for identifying convection in terms of the temperature and salinity profiles, and the turbulent dissipation rate, is proposed. This criterion may be applied to observations and theoretical models to quantify the effect of double-diffusive convection on ice shelf melt rates.

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Duong Hoang Trinh, Hoang Duc Cuong, Duong Van Kham, and Chanh Kieu

Abstract

This study examines the teleconnection between sea surface temperature (SST) in different ocean regions and tropical cyclone (TC) activity affecting Vietnam’s coastal region. Using spatial correlation and principal component analyses, it is found that the variability of TCs affecting Vietnam during 1982-2018 is remotely connected with SST in the Indian Ocean, the southwestern Pacific Ocean, and the northern Philippine Sea. Among the three regions, SST in the northern Philippine Sea displays the most significant inverse relationship with TC activity in the South China Sea (SCS), with lower June-November TC accumulated energy (ACE) for warmer northern Philippine Sea SST. Further analyses of large-scale atmospheric circulations show that this teleconnection between the northern Philippine Sea SST and TC activity in the SCS is linked to the East Asian subtropical jet (EASJ). Principal component analyses of the 200-hPa zonal wind associated with EASJ capture indeed a strong relationship between the second principal component, which characterizes the EASJ intensity, and ACE. Specifically, higher EASJ intensity corresponding to colder northern Philippine Sea SST would enhance large-scale ascending motion and low-level cyclonic anomalies in the SCS, which are favorable for TC formation and result in an overall increased ACE. Examination of correlation between this second principal component and the northern Philippine Sea SST confirms that this correlation is statistically significant at a 95% confidence level. In this regard, these results support the Pacific-Japan teleconnection between the northern Philippine Sea SST and TC activity in the SCS.

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Eli J. Dennis and Ernesto Hugo Berbery

Abstract

Soil hydraulic properties are critical in estimating surface and subsurface processes, including surface fluxes, the distribution of soil moisture, and the extraction of water by root systems. In most numerical weather and climate models, those properties are assigned using maps of soil texture complemented by look-up tables. Comparison of two widely used soil texture databases, the USDA State Soil Geographic database (STATSGO) and Beijing Normal University’s soil texture database (GSDE), reveals that differences are widespread and can be spatially coherent over large areas that can eventually lead to regional climate differences. For instance, over the U.S. Great Plains, GSDE stipulates finer soil grains than STATSGO, while the opposite is true over central Mexico. In this study, we employ the WRF/CLM4 modeling suite to investigate the sensitivity of the simulated regional climate to changes in the prescribed soil maps. Wherever GSDE has finer grains than STATSGO (e.g., over the U.S. Great Plains), the soil retains water more strongly, as evidenced by smaller latent heat flux (−20 W m−2), larger sensible heat flux (+20 W m−2), and correspondingly, a decrease in the 2-m humidity (−1 g kg−1) and an increase in 2-m temperature (+1.5 K). The opposite behavior is found over areas of coarser grains in GSDE (e.g., over central Mexico). Further, the changes in surface fluxes via soil texture lead to differences in the thermodynamic structure of the PBL. Results suggest that neither soil hydraulic properties nor soil moisture solely dictate the strength of surface fluxes, but in combination they alter the land–atmosphere coupling in nontrivial ways.

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Qian Liu, Guixing Chen, Lin Wang, Yuki Kanno, and Toshiki Iwasaki

Abstract

The winter monsoon has strong impacts on East Asia via latitude-crossing southward cold airmass fluxes called cold air outbreaks (CAOs). CAOs have a high diversity in terms of meridional extent and induced weather. Using the daily cold airmass flux normalized at 50°N and 30°N during 1958–2016, we categorize the CAOs into three groups: high–middle (H–M), high–low (H–L) and middle–low (M–L) latitude events. The H–L type is found to have the longest duration, and the M–L type is prone to the strong CAOs regarding normalized intensity. The H–L and H–M events feature a large-scale dipole pattern of cold airmass flux over high-latitude Eurasia, and the former (latter) events feature relatively strong anticyclonic circulation over Siberia (cyclonic circulation over northeastern Asia). In contrast, the M–L events are characterized by a cyclonic anomaly over northeastern Asia but no obvious high-latitude precursor. The H–L events have the greatest coldness anomaly in airmasses near the surface, and the M–L events mainly feature a strong northerly wind. As a result, the H–L events induce widespread long-lasting low temperatures over East Asia, while the M–L events induce a sharp temperature drop at mainly low latitudes. Both H–L and M–L events coupling with the MJO enhance rainfall over the South China Sea, while H–M events increase rainfall over southern China. Moreover, the occurrences of H–L and M–L events experience a long-term decrease since the 1980s, which induce a stronger warming trend in the cold extremes than in the winter mean temperature at mid-low latitudes over East Asia.

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Clément Vic, Bruno Ferron, Virginie Thierry, Herlé Mercier, and Pascale Lherminier

Abstract

Internal waves in the semidiurnal and near-inertial bands are investigated using an array of seven moorings located over the Reykjanes Ridge in a cross-ridge direction (57.6°–59.1°N, 28.5°–33.3°W). Continuous measurements of horizontal velocity and temperature for more than 2 years allow us to estimate the kinetic energy density and the energy fluxes of the waves. We found that there is a remarkable phase locking and linear relationship between the semidiurnal energy density and the tidal energy conversion at the spring–neap cycle. The energy-to-conversion ratio gives replenishment time scales of 4–5 days on the ridge top versus 7–9 days on the flanks. Altogether, these results demonstrate that the bulk of the tidal energy on the ridge comes from near-local sources, with a redistribution of energy from the top to the flanks, which is endorsed by the energy fluxes oriented in the cross-ridge direction. Implications for tidally driven energy dissipation are discussed. The time-averaged near-inertial kinetic energy is smaller than the semidiurnal kinetic energy by a factor of 2–3 but is much more variable in time. It features a strong seasonal cycle with a winter intensification and subseasonal peaks associated with local wind bursts. The ratio of energy to wind work gives replenishment time scales of 13–15 days, which is consistent with the short time scales of observed variability of near-inertial energy. In the upper ocean (1 km), the highest levels of near-inertial energy are preferentially found in anticyclonic structures, with a twofold increase relative to cyclonic structures, illustrating the funneling effect of anticyclones.

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Xiaolong Yu, Alberto C. Naveira Garabato, Adrian P. Martin, and David P. Marshall

Abstract

The evolution of upper-ocean potential vorticity (PV) over a full year in a typical midocean area of the northeast Atlantic is examined using submesoscale- and mesoscale-resolving hydrographic and velocity measurements from a mooring array. A PV budget framework is applied to quantitatively document the competing physical processes responsible for deepening and shoaling the mixed layer. The observations reveal a distinct seasonal cycle in upper-ocean PV, characterized by frequent occurrences of negative PV within deep (up to about 350 m) mixed layers from winter to mid-spring, and positive PV beneath shallow (mostly less than 50 m) mixed layers during the remainder of the year. The cumulative positive and negative subinertial changes in the mixed layer depth, which are largely unaccounted for by advective contributions, exceed the deepest mixed layer by one order of magnitude, suggesting that mixed layer depth is shaped by the competing effects of destratifying and restratifying processes. Deep mixed layers are attributed to persistent atmospheric cooling from winter to mid-spring, which triggers gravitational instability leading to mixed layer deepening. However, on shorter time scales of days, conditions favorable to symmetric instability often occur as winds intermittently align with transient frontal flows. The ensuing submesoscale frontal instabilities are found to fundamentally alter upper-ocean turbulent convection, and limit the deepening of the mixed layer in the winter-to-mid-spring period. These results emphasize the key role of submesoscale frontal instabilities in determining the seasonal evolution of the mixed layer in the open ocean.

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Sally Potter, Sara Harrison, and Peter Kreft

Abstract

Warnings about impending hazards help to minimise the impacts and reduce the risk through encouraging an appropriate and timely behavioural response. Many hydrometeorological agencies are moving towards impact-based forecast and warning (IBFW) systems, as encouraged by the World Meteorological Organization (WMO). Yet little research has been conducted on such systems from the perspectives of agencies who are or would be involved in their implementation. We investigated the challenges and benefits of IBFW systems as perceived by participants from agencies internationally and within New Zealand. Interviews and workshops were held with meteorologists and weather forecasters, flood forecasters and hydrologists, and emergency managers.

We found that the benefits of implementing IBFW systems included a perceived increase in the understanding of the potential impacts by the public, added awareness of antecedent conditions by forecasters, a possible reduction in ‘false alarms’, and increased interagency communication. Challenges identified by the participants included whether the system should be designed for individuals or society, a lack of impact data, verification of warnings based on impacts, a conflict with roles and responsibilities, the potential for conflicting messages, and the increased burden on agencies providing information to forecasters with a perception of little benefit in return.

We argue that IBFWs could be designed for individual members of the public, with an increased focus on understanding vulnerability and capacities; and that more impact data needs to be collected and stored to inform future warnings. Increased interagency coordination would assist with rapid decision-making and the success of IBFWs.

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Robin Waldman, Joël Hirschi, Aurore Voldoire, Christophe Cassou, and Rym Msadek

Abstract

This work aims to clarify the relation between the Atlantic meridional overturning circulation (AMOC) and the thermal wind. We derive a new and generic dynamical AMOC decomposition that expresses the thermal wind transport as a simple vertical integral function of eastern minus western boundary densities. This allows us to express density anomalies at any depth as a geostrophic transport in Sverdrups (1 Sv ≡ 106 m3 s−1) per meter and to predict that density anomalies around the depth of maximum overturning induce most AMOC transport. We then apply this formalism to identify the dynamical drivers of the centennial AMOC variability in the CNRM-CM6 climate model. The dynamical reconstruction and specifically the thermal wind component explain over 80% of the low-frequency AMOC variance at all latitudes, which is therefore almost exclusively driven by density anomalies at both zonal boundaries. This transport variability is dominated by density anomalies between depths of 500 and 1500 m, in agreement with theoretical predictions. At those depths, southward-propagating western boundary temperature anomalies induce the centennial geostrophic AMOC transport variability in the North Atlantic. They are originated along the western boundary of the subpolar gyre through the Labrador Sea deep convection and the Davis Strait overflow.

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Adam Vaccaro, Julien Emile-Geay, Dominque Guillot, Resherle Verna, Colin Morice, John Kennedy, and Bala Rajaratnam

Abstract

Surface temperature is a vital metric of Earth’s climate state, but is incompletely observed in both space and time: over half of monthly values are missing from the widely used HadCRUT4.6 global surface temperature dataset. Here we apply GraphEM, a recently developed imputation method, to construct a spatially complete estimate of HadCRUT4.6 temperatures. GraphEM leverages Gaussian Markov random fields (aka Gaussian graphical models) to better estimate covariance relationships within a climate field, detecting anisotropic features such as land/ocean contrasts, orography, ocean currents and wave-propagation pathways. This detection leads to improved estimates of missing values compared to methods (such as kriging) that assume isotropic covariance relationships, as we show with real and synthetic data.

This interpolated analysis of HadCRUT4.6 data is available as a 100-member ensemble, propagating information about sampling variability available from the original HadCRUT4.6 dataset. A comparison of NINO3.4 and global mean monthly temperature series with published datasets reveals similarities and differences due in part to the spatial interpolation method. Notably, the GraphEM-completed HadCRUT4.6 global temperature displays a stronger early twenty-first century warming trend than its uninterpolated counterpart, consistent with recent analyses using other datasets. Known events like the 1877/1878 El Niño are recovered with greater fidelity than with kriging, and result in different assessments of changes in ENSO variability through time. Gaussian Markov random fields provide a more geophysically-motivated way to impute missing values in climate fields, and the associated graph provides a powerful tool to analyze the structure of teleconnection patterns. We close with a discussion of wider applications of Markov random fields in climate science.

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