Abstract

Tropical cyclones (TCs) are identified and tracked in six recent reanalysis datasets and compared with those from the IBTrACS best-track archive. Results indicate that nearly every cyclone present in IBTrACS over the period 1979–2012 can be found in all six reanalyses using a tracking and matching approach. However, TC intensities are significantly underrepresented in the reanalyses compared to the observations. Applying a typical objective TC identification scheme, it is found that the largest uncertainties in TC identification occur for the weaker storms; this is exacerbated by uncertainties in the observations for weak storms and lack of consistency in operational procedures. For example, certain types of storms, such as tropical depressions, subtropical cyclones, and monsoon depressions, are not included in the best-track data for all reporting agencies. There are definite improvements in how well TCs are represented in more recent, higher-resolution reanalyses; in particular MERRA-2 is comparable with the NCEP-CFSR and JRA-55 reanalyses, which perform significantly better than the older MERRA reanalysis.

Abstract

Land surface models (LSMs) used in climate modeling include detailed above-ground biophysics but usually lack a good representation of runoff. Both processes are closely linked through soil moisture. Soil moisture however has a high spatial variability that is unresolved at climate model grid scales. Physically based vertical and horizontal aggregation methods exist to account for this scaling problem. Effects of scaling and aggregation have been evaluated in this study by performing catchment-scale LSM simulations for the Rhône catchment. It is found that evapotranspiration is not sensitive to soil moisture over the Rhône but it largely controls total runoff as a residual of the terrestrial water balance. Runoff magnitude is better simulated when the vertical soil moisture fluxes are resolved at a finer vertical resolution. The use of subgrid-scale topography significantly improves both the timing of runoff on the daily time scale (response to rainfall events) and the magnitude of summer baseflow (from seasonal groundwater recharge). Explicitly accounting for soil moisture as a subgrid-scale process in LSMs allows one to better resolve the seasonal course of the terrestrial water storage and makes runoff insensitive to the used grid scale. However, scale dependency of runoff to above-ground hydrology cannot be ignored: snowmelt runoff from the Alpine part of the Rhône is sensitive to the spatial resolution of the snow scheme, and autumnal runoff from the Mediterranean part of the Rhône is sensitive to the spatial resolution of precipitation.

Abstract

The coastal region of East Asia (EA) is one of the regions with the most frequent impacts from tropical cyclones (TCs). In this study, rainfall and moisture transports related to TCs are measured over EA, and the contribution of TCs to the regional water budget is compared with other contributors, especially the mean circulation of the EA summer monsoon (EASM). Based on ERA-Interim reanalysis (1979–2012), the trajectories of TCs are identified using an objective feature tracking method. Over 60% of TCs occur from July to October (JASO). During JASO, TC rainfall contributes 10%–30% of the monthly total rainfall over the coastal region of EA; this contribution is highest over the south/southeast coast of China in September. TCs make a larger contribution to daily extreme rainfall (above the 95th percentile): 50%–60% over the EA coast and as high as 70% over Taiwan Island. Compared with the mean EASM, TCs transport less moisture over EA. However, as the peak of the mean seasonal cycle of TCs lags two months behind that of the EASM, the moisture transported by TCs is an important source for the water budget over the EA region when the EASM withdraws. This moisture transport is largely performed by westward-moving TCs. These results improve understanding of the water cycle of EA and provide a useful test bed for evaluating and improving seasonal forecasts and coupled climate models.

Abstract

The authors present an assessment of how tropical cyclone activity might change owing to the influence of increased atmospheric carbon dioxide concentrations, using the U.K. High-Resolution Global Environment Model (HiGEM) with N144 resolution (~90 km in the atmosphere and ~40 km in the ocean). Tropical cyclones are identified using a feature-tracking algorithm applied to model output. Tropical cyclones from idealized 30-yr 2×CO₂ (2CO2) and 4×CO₂ (4CO2) simulations are compared to those identified in a 150-yr present-day simulation that is separated into a five-member ensemble of 30-yr integrations. Tropical cyclones are shown to decrease in frequency globally by 9% in the 2CO2 and 26% in the 4CO2. Tropical cyclones only become more intense in the 4CO2; however, uncoupled time slice experiments reveal an increase in intensity in the 2CO2. An investigation into the large-scale environmental conditions, known to influence tropical cyclone activity in the main development regions, is used to determine the response of tropical cyclone activity to increased atmospheric CO₂. A weaker Walker circulation and a reduction in zonally averaged regions of updrafts lead to a shift in the location of tropical cyclones in the Northern Hemisphere. A decrease in mean ascent at 500 hPa contributes to the reduction of tropical cyclones in the 2CO2 in most basins. The larger reduction of tropical cyclones in the 4CO2 arises from further reduction of the mean ascent at 500 hPa and a large enhancement of vertical wind shear, especially in the Southern Hemisphere, North Atlantic, and northeast Pacific.

Abstract

This study assesses the influence of the El Niño–Southern Oscillation (ENSO) on global tropical cyclone activity using a 150-yr-long integration with a high-resolution coupled atmosphere–ocean general circulation model [High-Resolution Global Environmental Model (HiGEM); with N144 resolution: ~90 km in the atmosphere and ~40 km in the ocean]. Tropical cyclone activity is compared to an atmosphere-only simulation using the atmospheric component of HiGEM (HiGAM). Observations of tropical cyclones in the International Best Track Archive for Climate Stewardship (IBTrACS) and tropical cyclones identified in the Interim ECMWF Re-Analysis (ERA-Interim) are used to validate the models. Composite anomalies of tropical cyclone activity in El Niño and La Niña years are used. HiGEM is able to capture the shift in tropical cyclone locations to ENSO in the Pacific and Indian Oceans. However, HiGEM does not capture the expected ENSO–tropical cyclone teleconnection in the North Atlantic. HiGAM shows more skill in simulating the global ENSO–tropical cyclone teleconnection; however, variability in the Pacific is overpronounced. HiGAM is able to capture the ENSO–tropical cyclone teleconnection in the North Atlantic more accurately than HiGEM. An investigation into the large-scale environmental conditions, known to influence tropical cyclone activity, is used to further understand the response of tropical cyclone activity to ENSO in the North Atlantic and western North Pacific. The vertical wind shear response over the Caribbean is not captured in HiGEM compared to HiGAM and ERA-Interim. Biases in the mean ascent at 500 hPa in HiGEM remain in HiGAM over the western North Pacific; however, a more realistic low-level vorticity in HiGAM results in a more accurate ENSO–tropical cyclone teleconnection.

The prediction of climate variability and change requires the use of a range of simulation models. Multiple climate model simulations are needed to sample the inherent uncertainties in seasonal to centennial prediction. Because climate models are computationally expensive, there is a tradeoff between complexity, spatial resolution, simulation length, and ensemble size. The methods used to assess climate impacts are examined in the context of this trade-off. An emphasis on complexity allows simulation of coupled mechanisms, such as the carbon cycle and feedbacks between agricultural land management and climate. In addition to improving skill, greater spatial resolution increases relevance to regional planning. Greater ensemble size improves the sampling of probabilities. Research from major international projects is used to show the importance of synergistic research efforts.

The primary climate impact examined is crop yield, although many of the issues discussed are relevant to hydrology and health modeling. Methods used to bridge the scale gap between climate and crop models are reviewed. Recent advances include large-area crop modeling, quantification of uncertainty in crop yield, and fully integrated crop-climate modeling. The implications of trends in computer power, including supercomputers, are also discussed.

Abstract

Previous studies showed that high-resolution GCMs overestimate land precipitation when compared against observation-based data. Particularly, high-resolution HadGEM3-GC3.1 shows a significant precipitation increase in mountainous regions, where the scarcity of gauge stations increases the uncertainty of gridded observations and reanalyses. This work evaluates such precipitation uncertainties indirectly through the assessment of river discharge, considering that an increase of ~10% in land precipitation produces ~28% more runoff when the resolution is enhanced from 1° to 0.25°, and ~50% of the global runoff is produced in 27% of global land dominated by mountains. We diagnosed the river flow by routing the runoff generated by HadGEM3-GC3.1 low- and high-resolution simulations. The river flow is evaluated using a set of 344 monitored catchments distributed around the world. We also infer the global discharge by constraining the simulations with observations following a novel approach that implies bias correction in monitored rivers with two methods, and extension of the correction to the river mouth, and along the coast. Our global discharge estimate is 47.4 ± 1.6 × 10³ km³ yr⁻¹, which is closer to the original high-resolution estimate (50.5 × 10³ km³ yr⁻¹) than to the low-resolution (39.6 × 10³ km³ yr⁻¹). The assessment suggests that high-resolution simulations perform better in mountainous regions, either because the better-defined orography favors the placement of precipitation in the correct catchment, leading to a more accurate distribution of runoff, or the orographic precipitation increases, reducing the dry runoff bias of coarse-resolution simulations. However, high-resolution slightly increases wet biases in catchments dominated by flat terrain. The improvement of model parameterizations and tuning may reduce the remaining errors in high-resolution simulations.

Abstract

The ability to run general circulation models (GCMs) at ever-higher horizontal resolutions has meant that tropical cyclone simulations are increasingly credible. A hierarchy of atmosphere-only GCMs, based on the Hadley Centre Global Environmental Model version 1 (HadGEM1) with horizontal resolution increasing from approximately 270 to 60 km at 50°N, is used to systematically investigate the impact of spatial resolution on the simulation of global tropical cyclone activity, independent of model formulation. Tropical cyclones are extracted from ensemble simulations and reanalyses of comparable resolutions using a feature-tracking algorithm. Resolution is critical for simulating storm intensity and convergence to observed storm intensities is not achieved with the model hierarchy. Resolution is less critical for simulating the annual number of tropical cyclones and their geographical distribution, which are well captured at resolutions of 135 km or higher, particularly for Northern Hemisphere basins. Simulating the interannual variability of storm occurrence requires resolutions of 100 km or higher; however, the level of skill is basin dependent. Higher resolution GCMs are increasingly able to capture the interannual variability of the large-scale environmental conditions that contribute to tropical cyclogenesis. Different environmental factors contribute to the interannual variability of tropical cyclones in the different basins: in the North Atlantic basin the vertical wind shear, potential intensity, and low-level absolute vorticity are dominant, whereas in the North Pacific basins midlevel relative humidity and low-level absolute vorticity are dominant. Model resolution is crucial for a realistic simulation of tropical cyclone behavior, and high-resolution GCMs are found to be valuable tools for investigating the global location and frequency of tropical cyclones.

Abstract

The main energy source for the intensification of a tropical cyclone (TC) is widely accepted to be the transfer of energy from the ocean to the atmosphere via surface fluxes. The pathway through which these surface fluxes lead to an increase in the kinetic energy of the cyclone has typically been interpreted either in terms of total potential energy or dry available potential energy (APE), or through the entropy-based heat engine viewpoint. Here, we use the local theory of APE to construct a budget of moist APE for an idealized axisymmetric simulation of a tropical cyclone. This is the first full budget of local moist APE budget for an atmospheric model. In the local moist APE framework, latent surface heat fluxes are the dominant generator of moist APE, which is then converted into kinetic energy via buoyancy fluxes. In the core region of the TC, the inward transport of APE by the secondary circulation is more important than its local production. The APE viewpoint describes spatially and temporally varying efficiencies; these may be useful in understanding how changes in efficiency influence TC development, and have a maximum that can be linked to the Carnot efficiency featuring in potential intensity theory.

Abstract

Precipitation often happens along organized filaments or bands of moisture such as convergence zones. Recent regional studies have shown that these moisture filaments arise from synoptic-scale mixing features known as attracting Lagrangian coherent structures (LCSs). In this study, we present a climatology of synoptic-scale mixing and investigate its covariability with precipitation on temporal scales ranging from weekly to interannual. We characterize mixing with the finite-time Lyapunov exponent (FTLE), a measure of parcel deformation, in ERA5 data between 1980 and 2009. Attracting LCSs are identified as ridges of the FTLE. At the interannual time scale, we compare El Niño and La Niña events and find that composites of precipitation and mixing anomalies share similar spatial patterns. We also compare summer and winter seasons and find that composites of seasonal-mean precipitation and mixing anomalies present similar characteristics, with precipitation being particularly intense (weak) where mixing is strong (weak). In particular, these patterns closely match the typical signatures of the intertropical convergence zone (ITCZ) and monsoon systems and the migrations of extratropical cyclone tracks. At the subseasonal scale, we employ daily composites to investigate the influence of the Madden–Julian oscillation and the North Atlantic Oscillation on the mixing regimes of the Atlantic and east Pacific; our results indicate that these oscillations control the synoptic-scale horizontal mixing and the occurrence of LCSs as to suppress or enhance precipitating systems like the ITCZ and the South Atlantic convergence zone. The results presented in this first climatology of synoptic-scale mixing and LCSs indicate that these are powerful diagnostics to identify circulation mechanisms underlying precipitation variability.