Abstract

In this study, landslide potential is investigated, using a new constitutive relationship for granular flow in a numerical model. Unique to this study is an original relationship between soil moisture and the inertial number for soil particles. This numerical model can be applied to arbitrary soil slab profile configurations and to the analysis of natural disasters, such as mudslides, glacier creeping, avalanches, landslips, and other pyroclastic flows. Here the focus is on mudslides.

The authors examine the effects of bed slope and soil slab thickness, soil layered profile configuration, soil moisture content, basal sliding, and the growth of vegetation, and show that increased soil moisture enhances instability primarily by decreasing soil strength, together with increasing loading. Moreover, clay soils generally require a smaller relative saturation than sandy soils for sliding to commence. For a stable configuration, such as a small slope and/or dry soil, the basal sliding is absorbed if the perturbation magnitude is small. However, large perturbations can trigger significant-scale mudslides by liquefying the soil slab.

The role of vegetation depends on the wet soil thickness and the spacing between vegetation roots. The thinner the saturated soil layer, the slower the flow, giving the vegetation additional time to extract soil moisture and slow down the flow. By analyzing the effect of the root system on the stress distribution, it is shown that closer tree spacing increases the drag effects on the velocity field, provided that the root system is deeper than the shearing zone.

Finally, the authors investigated a two-layer soil profile, namely, sand above clay. A significant stress jump occurs at the interface of the two media.

Abstract

The real-time prediction of the location, strength, and structure of the summertime heat trough is a major forecasting problem over Western Australia. Maximum temperatures, wind strength and direction along the west coast, low-level coastal cloud, and thunderstorm activity are vulnerable to forecast errors in the heat trough.

This study has three main parts. First, prediction errors of the operational Australian region numerical weather prediction (NWP) model were quantified over the period December 1991 to February 1992. Second, a newly developed regional NWP model, which will be the next operational regional model, was compared with the current operational model. The new model has more efficient numerics than the present operational model, allowing higher-resolution forecasts and a more sophisticated representation of physical processes. The third part was a set of sensitivity experiments to assess the relative importance of the differences.

The dominant errors in the current operational model are a large westward bias in the trough location, a wide spread of errors in the intensity of the low in the northern section of the heat trough, a sizable range of coastal pressure gradient errors, and a northward bias in the latitude of the subtropical ridge axis between longitudes 110° and 120°E. It was demonstrated that these errors are reduced significantly in the new model, especially the subtropical ridge error, which has been virtually eliminated. The sensitivity studies revealed the importance of each of the differences between the models, and that the relative impact varies from case to case.

Abstract

The synoptic pattern over northeastern Australia is dominated in the warmer months by a ridge–trough system. Accurate prediction of the location of the system is a significant forecasting problem for regional and global operational models. The regional model that was operational at the time of this study exhibited two significant weaknesses characteristic of many current operational global models, a westward bias in the location of the east coast ridge and errors in the location and strength of the inland trough. The present investigation had three aims:to compute model location errors of the ridge–trough system from a large (6 month, twice daily) dataset of operational forecasts, to explain these errors by evaluating a new regional model, and to confirm the diagnosis using a series of case studies and sensitivity studies. The operational model had a marked mean westward bias of about 2° longitude in the location of both the trough and the ridge. There was a noticeable latitudinal distribution in trough errors with the greatest errors in the north. Ridge location errors were much larger in the south. Overall, almost 60% of errors were 2° longitude or greater. The new model was far more skillful in forecasting the ridge–trough system with predicted locations of both ridges and troughs being superior at greater than the 99% confidence level. In the new model a mean westward error remained in the location of the ridges and troughs but was less than 1°. The percentage of errors greater than 2° longitude dropped to about 20% for ridges and 35% for troughs. The decreased location errors in the new model are attributed to improved representation of the steep coastal orography and of the simulations of both the heat low and inland trough to the west of the coastal ranges. This was confirmed in three case studies at very high resolution (15 km) using the new model but with operational data and also in two sensitivity studies with the new model using the operational model forecast surface temperatures. The forecasts showed similar trough location problems to the operational model.

Abstract

Advances in observations, theory, and modeling have revealed that inner-core asymmetries are a common feature of tropical cyclones (TCs). In this study, the inner-core asymmetries of a severe Southern Hemisphere tropical cyclone, TC Larry (2006), are investigated using the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model (MM5) and the Kepert–Wang boundary layer model. The MM5-simulated TC exhibited significant asymmetries in the inner-core region, including rainfall distribution, surface convergence, and low-level vertical motion. The near-core environment was characterized by very low environmental vertical shear and consequently the TC vortex had almost no vertical tilt. It was found that, prior to landfall, the rainfall asymmetry was very pronounced with precipitation maxima consistently to the right of the westward direction of motion. Persistent maxima in low-level convergence and vertical motion formed ahead of the translating TC, resulting in deep convection and associated hydrometeor maxima at about 500 hPa. The asymmetry in frictional convergence was mainly due to the storm motion at the eyewall, but was dominated by the proximity to land at larger radii. The displacement of about 30°–120° of azimuth between the surface and midlevel hydrometeor maxima is explained by the rapid cyclonic advection of hydrometeors by the tangential winds in the TC core. These results for TC Larry support earlier studies that show that frictional convergence in the boundary layer can play a significant role in determining the asymmetrical structures, particularly when the environmental vertical shear is weak or absent.

Abstract

Since 1970, tropical cyclone (TC) track forecasts have improved steadily in the Atlantic basin. This improvement has been linked primarily to advances in numerical weather prediction (NWP) models. Concurrently, with few exceptions, the development and operational use of statistical track prediction schemes have experienced a relative decline. Statistical schemes provided the most accurate TC track forecasts until approximately the late 1980s. In this note, it is shown that increased reliance on the global NWP models does not always guarantee the best forecast. Here, Hurricane Ivan is used from the 2004 Atlantic TC season as a classical example, and reminder, of how strong climatological signals still can add substantial value to TC track forecasts, in the form of improved accuracy and increased timeliness at minimal computational cost.

In an 8-day period in early September 2004, Hurricane Ivan was repeatedly, and incorrectly, forecast by 12 operational NWP models to move with a significant northward (poleward) component. It was found that the mean 24-h trajectory forecasts of a consensus of five commonly used NWP track prediction aids had a statistically significant right-of-track bias. Furthermore, the official track forecasts, which relied heavily on erroneous numerical guidance over this period, were also found to have significant poleward trajectory errors. At the same time, a climatology-based prediction technique, drawn entirely from the historical record of motion characteristics of TCs in geographical locations similar to Ivan, correctly and consistently indicated a more westward motion component, had a small directional spread, and was supported by a large number of archived cases. This climatological signal was in conflict with the deterministic NWP model output, and it is suggested that the large errors in the official track forecast for TC Ivan could have been reduced considerably by taking into greater account such a strong climatological signal. The potential impact of such an error reduction is a saving of lives and billions of dollars in both actual damage and unnecessary evacuations costs, for just this one hurricane. We also suggest that this simple strategy of examining the strength of the climatological signal be considered for all TCs to identify cases where the NWP and official forecasts differ significantly from strong, persistent climatological signals.

Abstract

Winter storms in the southern United States can significantly impact infrastructure and the economy. In this study, National Centers for Environmental Information Storm Event Database and local climate summaries, are used to develop a spatial climatology of freezing precipitation (freezing rain and ice pellets) and snow over the southern Great Plains, 1993–2011. Principal component analysis is performed on the 500-hPa height field, at the approximate onset time of precipitation, for 33 freezing precipitation and 42 snow case studies, to differentiate common synoptic flow fields associated with precipitation type. The five leading patterns for each precipitation type are retained. Composites of temperature, moisture, pressure, and wind fields are constructed and extended 24 h before and after precipitation initiation to track the storm system evolution. Many 500-hPa flow fields are similar for both precipitation types. However, snow-dominant events have stronger and/or more frequent surface cyclone development. Freezing precipitation is associated with the southward propagation of an Arctic anticyclone well ahead of precipitation, weak or absent surface cyclone formation, and a more western trough axis. High-impact ice storms in the region often have slow-moving upper-level flow, persistent isentropic ascent over a surface quasi-stationary front with strongly positive moisture anomalies, and warm layer airmass trajectories originating over the Gulf of Mexico. The results here are based on a relatively small sample size. However, this work is intended to be useful for forecasters, in particular as a pattern recognition aid in predicting the evolution of precipitation within southern Great Plains winter storms.

Abstract

Changes in storm-triggered landslide activity for Southern California in a future warming climate are estimated using an advanced, fully three-dimensional, process-based landslide model, the Scalable and Extensible Geofluid Modeling System for landslides (SEGMENT-Landslide). SEGMENT-Landslide is driven by extreme rainfall projections from the Geophysical Fluid Dynamics Laboratory High Resolution Atmospheric Model (GFDL-HIRAM). Landslide changes are derived from GFDL-HIRAM forcing for two periods: 1) the twentieth century (CNTRL) and 2) the twenty-first century under the moderate Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios A1B enhanced greenhouse gas emissions scenario (EGHG). Here, differences are calculated in landslide frequency and magnitude between the CNTRL and EGHG projections; kernel density estimation (KDE) is used to determine differences in projected landslide locations. This study also reveals that extreme precipitation events in Southern California are strongly correlated with several climate drivers and that GFDL-HIRAM simulates well the southern (relative to Aleutian synoptic systems) storm tracks in El Niño years and the rare (~27-yr recurrence period) hurricane-landfalling events. GFDL-HIRAM therefore can provide satisfactory projections of the geographical distribution, seasonal cycle, and interannual variability of future extreme precipitation events (>50 mm) that have possible landslide consequences for Southern California. Although relatively infrequent, extreme precipitation events contribute most of the annual total precipitation in Southern California. Two findings of this study have major implications for Southern California. First is a possible increase in landslide frequency and areal distribution during the twenty-first century. Second, the KDE reveals three clusters in both the CNTRL and EGHG model mean scarp positions, with a future eastward (inland) shift of ~0.5° and a northward shift of ~1°. These findings suggest that previously stable areas might become susceptible to storm-triggered landslides in the twenty-first century.

Abstract

The temperate glaciers in the greater Himalayas (GH) and the neighboring region contribute to the freshwater supply for almost one-half of the people on earth. Under global warming conditions, the GH glaciers may melt more rapidly than high-latitude glaciers, owing to the coincidence of the accumulation and ablation seasons in summer. Based on a first-order energy balance approach for glacier thermodynamics, the possible imposed additional melting rate was estimated from three climate simulations using the Geophysical Fluid Dynamics Laboratory Global Coupled Climate Model version 2.1 (GFDL-CM2.1), the Model for Interdisciplinary Research on Climate 3.2, high-resolution version (MIROC3.2-hires), and the Met Office’s Third Hadley Centre Coupled Ocean–Atmosphere General Circulation Model (HadCM3). The simulations were carried out under the Special Report on Emissions Scenarios (SRES) A1B scenario. For the 30-yr period of 2001–30, all three CGCMs indicate that the glacial regions most sensitive to regional warming are the Tianshan–Altai Mountains to the north and Hengduan Mountains to the south. A map of potential melting was produced and was used to calculate the glacier-melting speed, yielding an additional spatially averaged glacier depth reduction of approximately 2 m for the 2001–30 period for those areas located below 4000 m. Averaged over the entire GH region, the melting rate is accelerating at about 5 mm yr⁻². The general circulation over the GH region was found to have clear multidecadal variability, with the 30-yr period of 2001–30 likely to be wetter than the previous 30-yr period of 1971–2000. Considering the possible trend in precipitation from snow to rain, the actual melting rates of the GH glaciers may even be larger than those obtained in this research.

Abstract

A high-resolution nonhydrostatic numerical model, the Advanced Regional Prediction System (ARPS), was used to simulate Typhoon Morakot (2009) as it made landfall over Taiwan, producing record rainfall totals. In particular, the mesoscale structure of the typhoon was investigated, emphasizing its associated deep convection, the development of inner rainbands near the center, and the resultant intense rainfall over western Taiwan.

Simulations at 15- and 3-km grid spacing revealed that, following the decay of the initial inner eyewall, a new, much larger eyewall developed as the typhoon made landfall over Taiwan. Relatively large-amplitude wave structures developed in the outer eyewall and are identified as vortex Rossby waves (VRWs), based on the wave characteristics and their similarity to VRWs identified in previous studies.

Moderate to strong vertical shear over the typhoon system produced a persistent wavenumber-1 (WN1) asymmetric structure during the landfall period, with upward motion and deep convection in the downshear and downshear-left sides, consistent with earlier studies. This strong asymmetry masks the effects of WN1 VRWs. WN2 and WN3 VRWs apparently are associated with the development of deep convective bands in Morakot’s southwestern quadrant. This occurs as the waves move cyclonically into the downshear side of the cyclone. Although the typhoon track and topographic enhancement contribute most to the record-breaking rainfall totals, the location of the convective bands, and their interaction with the mountainous terrain of Taiwan, also affect the rainfall distribution. Quantitatively, the 3-km ARPS rainfall forecasts are superior to those obtained from coarser-resolution models.

Abstract

Horn of Africa rainfall varies on multiple time scales, but the underlying climate system controls on this variability have not been examined comprehensively. This study therefore investigates the linkages between June–September Horn of Africa (especially Ethiopian) rainfall and regional atmospheric circulation and global sea surface temperature (SST) variations on several key time scales. Wavelet analysis of 5-day average or monthly total rainfall for 1970–99 identifies the dominant coherent modes of rainfall variability. Several regional atmospheric variables and global SST are then identically wavelet filtered, based on the rainfall frequency bands. Regression, correlation, and composite analyses are subsequently used to identify the most important rainfall–climate system time-scale relationships.

The results show that Ethiopian monsoon rainfall variation is largely linked with annual time-scale atmospheric circulation patterns involving variability in the major components of the monsoon system. Although variability on the seasonal (75–210 days), quasi-biennial (QB; 1.42–3.04 yr), and El Niño–Southern Oscillation (ENSO; 3.04–4.60 yr) time scales accounts for much less variance than the annual mode (210 days–1.42 yr), they significantly affect Ethiopian rainfall by preferentially modulating the major regional monsoon components and remote teleconnection linkages. The seasonal time scale largely acts in phase with the annual mode, by enhancing or reducing the lower-tropospheric southwesterlies from the equatorial Atlantic during wet or dry periods. The wet QB phase strengthens the Azores and Saharan high and the tropical easterly jet (TEJ) over the Arabian Sea, while the wet ENSO phase enhances the Mascarene high, the TEJ, and the monsoon trough more locally. The effects of tropical SST on Ethiopian rainfall also are prominent on the QB and ENSO time scales. While rainfall–SST correlations for both the QB and ENSO modes are strongly positive (negative) over the equatorial western (eastern) Pacific, only ENSO exhibits widespread strong negative correlations over the Indian Ocean. Opposite QB and ENSO associations tend to characterize dry Ethiopian conditions. The relationships identified on individual time scales now are being used to develop and validate statistical prediction models for Ethiopia.