Tomohito J. Yamada

GLACE: The Global Land–Atmosphere Coupling Experiment. Part I: Overview

Abstract The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detai...

The Second Phase of the Global Land–Atmosphere Coupling Experiment: Soil Moisture Contributions to Subseasonal Forecast Skill

AbstractThe second phase of the Global Land–Atmosphere Coupling Experiment (GLACE-2) is a multi-institutional numerical modeling experiment focused on quantifying, for boreal summer, the subseasonal (out to two months) forecast skill for precipitation and air temperature that can be derived from the realistic initialization of land surface states, notably soil moisture. An overview of the experiment and model behavior at the global scale is described here, along with a determination and characterization of multimodel “consensus” skill. The models show modest but significant skill in predicting air temperatures, especially where the rain gauge network is dense. Given that precipitation is the chief driver of soil moisture, and thereby assuming that rain gauge density is a reasonable proxy for the adequacy of the observational network contributing to soil moisture initialization, this result indeed highlights the potential contribution of enhanced observations to prediction. Land-derived precipitation forec...

Migrating tremor off southern Kyushu as evidence for slow slip of a shallow subduction interface

Silent slip events get shallow Clues to help better predict the likelihood of devastating earthquakes and tsunamis may be embedded in a more gentle type of rumbling. Using oceanbottom seismometers, Yamashita et al. report rare observations of migrating tremors in the shallow part of a subduction zone off southern Kyushu, Japan. The tremors appear to be linked to a very low-frequency earthquake and seem to migrate to the region where big earthquakes are generated. The tremors may be tracing how and where stress gets concentrated onto the earthquake-producing portion of the fault. Science, this issue p. 676 Earthquake and tsunami hazard forecasts may benefit from shallow observations of seismic tremor migration in subduction zones. Detection of shallow slow earthquakes offers insight into the near-trench part of the subduction interface, an important region in the development of great earthquake ruptures and tsunami generation. Ocean-bottom monitoring of offshore seismicity off southern Kyushu, Japan, recorded a complete episode of low-frequency tremor, lasting for 1 month, that was associated with very-low-frequency earthquake (VLFE) activity in the shallow plate interface. The shallow tremor episode exhibited two migration modes reminiscent of deep tremor down-dip of the seismogenic zone in some other subduction zones: a large-scale slower propagation mode and a rapid reversal mode. These similarities in migration properties and the association with VLFEs strongly suggest that both the shallow and deep tremor and VLFE may be triggered by the migration of episodic slow slip events.

Influence of “Realistic” Land Surface Wetness on Predictability of Seasonal Precipitation in Boreal Summer

Outputs from two ensembles of atmospheric model simulations for 1951–98 define the influence of “realistic” land surface wetness on seasonal precipitation predictability in boreal summer. The ensembles consist of one forced with observed sea surface temperatures (SSTs) and the other forced with realistic land surface wetness as well as SSTs. Predictability was determined from correlations between the time series of simulated and observed precipitation. The ratio of forced variance to total variance determined potential predictability. Predictability occurred over some land areas adjacent to tropical oceans without land wetness forcing. On the other hand, because of the chaotic nature of the atmosphere, considerable parts of the land areas of the globe did not even show potential predictability with both land wetness and SST forcings. The use of land wetness forcing enhanced predictability over semiarid regions. Such semiarid regions are generally characterized by a negative correlation between fluxes of latent heat and sensible heat from the land surface, and are “water-regulating” areas where soil moisture plays a governing role in land– atmosphere interactions. Actual seasonal prediction may be possible in these regions if slowly varying surface conditions can be estimated in advance. In contrast, some land regions (e.g., south of the Sahel, the Amazon, and Indochina) showed little predictability despite high potential predictability. These regions are mostly characterized by a positive correlation between the surface fluxes, and are “radiation-regulating” areas where the atmosphere plays a leading role. Improvements in predictability for these regions may require further improvements in model physics.

Estimation of Predictability with a Newly Derived Index to Quantify Similarity among Ensemble Members

Abstract This study reveals the mathematical structure of a statistical index, Ω, that quantifies similarity among ensemble members in a weather forecast. Previous approaches for quantifying predictability estimate separately the phase and shape characteristics of a forecast ensemble. The diagnostic Ω, on the other hand, characterizes the similarity (across ensemble members) of both aspects together with a simple expression. The diagnostic Ω is thus more mathematically versatile than previous indices.

EVOLUTION OF THE 2011 TOHOKU EARTHQUAKE TSUNAMI ON THE PACIFIC COAST OF HOKKAIDO

A numerical computation of the 2011 Tohoku earthquake tsunami was performed to identify fundamental features of the tsunami evolution along the coast of Hokkaido, Japan. Edge waves formed at multiple locations where the refracted tsunami focused, governing local surface oscillations and regional variations in tsunami height along the Pacific coast of Hokkaido. The computation reasonably reproduced the distribution of surveyed tsunami height as well as the time records of surface elevation recorded at ports in Hokkaido. The major features of the frequency spectrum for the 2011 Tohoku tsunami were identical to those for the 2003 Tokachi-oki earthquake tsunami; inherent local properties of surface oscillation caused by the passage of edge waves existed, determined by the local bathymetry.

Diurnal Characteristics of Rainfall over the Contiguous United States and Northern Mexico in the Dynamically Downscaled Reanalysis Dataset (US10)

The diurnal characteristics of summer rainfall in the contiguous United States and northern Mexico were examined with the United States reanalysis for 5 years in 10-km horizontal resolution (US10), which is dynamically downscaled from the National Centers for Environmental Prediction‐National Center for Atmospheric Research (NCEP‐NCAR) Global Reanalysis 1 using the Regional Spectral Model (RSM). The hourly precipitation outputs demonstrate a realistic structure in the temporal evolution of the observed rainfall episodes and their magnitudes across the United States without any prescriptions of the observed rainfall to the global reanalysis and the downscaled regional reanalysis. Nighttime rainfall over the Great Plains associated with eastward-propagating, mesoscale convective systems originating from the Rocky Mountains is also represented realistically in US10, while the original reanalysis and most general circulation models (GCMs) have difficulties in capturing the series of nocturnal precipitation events in summer over the Plains.The resultssuggestan importantroleof the horizontalresolutionofthe model in resolvingsmall-scale, propagating convective systems to improve the diurnal cycle of summer rainfall.

Seasonal variation of land–atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model

Abstract The seasonal variation of land–atmosphere coupling strength has been examined using an extended series of atmospheric general circulation model (AGCM) simulations. In the Western Sahel of Africa, strong coupling strength for precipitation is found in April and May, just prior to and at the beginning of the monsoon season. At this time, heat and water fluxes from the surface are strongly controlled by land conditions, and the unstable conditions in the lower level of the troposphere, as induced by local land state, allow the surface fluxes to influence the variability of convective precipitation—and thus the timing of monsoon onset. Editor Z. W. Kundzewicz Citation Yamada, T.J., Kanae, S., Oki, T., and Koster, R.D., 2013. Seasonal variation of land–atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model. Hydrological Sciences Journal, 58 (6), 1276–1286.

Two-dimensional, threshold-based cloud type classification using MTSAT data

A new two-dimensional threshold diagram (2D-THR) has been developed based on maximum likelihood cloud classification results, which can readily be applied for Multi-functional Transport Satellite (MTSAT) split window datasets. Because 2D-THR was trained using northern summer 2010 data for Japan and its surrounding area, it is typically suitable only for summer. Comparison of snapshot cloud type distributions showed that 2D-THR images and the corresponding night-time microphysical colour composite images as well as 2D-THR images and Japan Meteorological Agency (JMA) cloud type images are in good agreement. A time series inter-comparison of the hourly 2D-THR cloud classification results with the JMA cloud type classification data product was performed by calculating spatial correlation of cloud percentage for 1° × 1° grid cells. For cumulonimbus, high-level, middle-level and low-level clouds over tropical and subtropical areas in the northwestern Pacific Ocean region, the spatial correlation between 2D-THR and JMA is moderate. Thus, 2D-THR cloud classification algorithm can be applied in both regions.

The Role of GPS Precipitable Water Vapor and Atmosphere Stability Index in the Statistically Based Rainfall Estimation Using MTSAT Data

A rainfall estimation method was developed based on the statistical relationships between cloud-top temperature and rainfall rates acquired by both the 10.8-mm channel of the Multi-Functional Transport Satellite (MTSAT) series and the Automated Meteorological Data Acquisition System (AMeDAS) C-band radar, respectively. The method focused on cumulonimbus (Cb) clouds and was developed in the period of June‐September 2010 and 2011 over the landmass of Japan and its surrounding area. Total precipitable water vapor (PWV) and atmospheric vertical instability were considered to represent the atmospheric environmental conditions during the development of statistical models. Validations were performed by comparing the estimated values with the observed rainfall derived from the AMeDAS rain gauge network and the Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall estimation product. The results demonstrated that the models that considered the combination of total PWV and atmospheric vertical instability were relatively more sensitive to heavy rainfall than were the models that considered no atmospheric environmental conditions. The use of such combined information indicated a reasonable improvement, especially in terms of the correlation between estimated and observed rainfall. Intercomparison results with the TRMM 3B42 confirmed that MTSAT-based rainfall estimations made by considering atmospheric environmental conditions were more accurate for estimating rainfall generated by Cb cloud.