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In this study, we use a long-term gridded dataset of daily precipitation and atmospheric fronts delineated on weather maps of Japan, the Northwestern Pacific, to identify rainfalls influenced by fronts within heavy rainfall periods occurring from June to August. We clarify the relationship between daily precipitation and the distance to fronts. The analytical targets are heavy rain events that occur for approximately four days each season. In the areas from Northwestern Kyushu to Western Tohoku, facing the Sea of Japan, the amount of precipitation from heavy rain events occurring within 500 km of fronts accounts for at least 80% of all heavy rain events. This is the same for the number of heavy rain events as well. Specifically, in Northwestern Kyushu, the amount of precipitation and the number of heavy rain events occurring within 200 km of fronts account for approximately 70% of all heavy rain events. [ABSTRACT FROM AUTHOR]

Earlier onset of the Southeast Asian summer monsoon (SAM) was observed over the Chao Phraya River basin in Thailand using Thai Meteorological Department-derived high-resolution merged rainfall data from 1981 to 2016. SAM variability depends on numerous local and global factors, including thermal conditions over the Bay of Bengal (BoB) and Tibetan Plateau (TbT). Despite tremendous past research efforts, the effect of thermal heat contrast on the SAM remains unclear. Using observational and reanalysis datasets, we found that the absolute value of total heat over the BoB was increasing. However, the interannual variability of total heat was greater over the TbT. Changes in surface temperature (± 1.5 °C), air thickness (± 20 m), and geopotential height over the TbT were associated with the timing of SAM onset. The results also suggested that significant changes in air thickness are driven by surface temperature differences over the TbT, while changes in the integrated apparent heat source and integrated apparent moisture sink of ± 100 W m−2 resulted in anomalous convective activities over the BoB and mainland of the Indochina Peninsula in years of early and late SAM onset. At the intraseasonal timescale, Madden–Julian oscillation (MJO) was observed over the Indian Ocean and Western Hemisphere for 4–10 days in years of early SAM onset. The opposite situation was found for years of late SAM onset, with MJO located over the Western Pacific Ocean and Maritime Continent. [ABSTRACT FROM AUTHOR]

This study investigated the relationship between extreme precipitation and near‐surface temperature (precipitation–temperature relation) from two different perspectives, the rate of change of precipitation with temperature and dynamic (i.e., effect of the change in atmospheric motion) and thermodynamic (i.e., effect of the change in atmospheric moisture content) aspects, using a 5‐km dynamical downscaled hundreds‐year data set for past climate condition (PAST; from 1951 to 2010) and future climate condition (FUTURE; 4°C warmer than the preindustrial condition). Initially, using the observation and the PAST and FUTURE data sets, it was found that the 99th and 99.9th percentile hourly precipitation for each temperature bin (P99 and P99.9, respectively) paralleled the slope of the Clausius–Clapeyron (C–C) relation for a certain temperature range over the Tokachi River basin in Hokkaido, the northern island of Japan; however, both P99 and P99.9 decreased in the high‐temperature range. Next, we examined the cause of the P99 and P99.9 differences between PAST and FUTURE for each temperature bin by classifying dynamic and thermodynamic factors. The result showed that the thermodynamic effect dominates the differences in P99 and P99.9 between PAST and FUTURE, which means that the thermodynamic effect is the main component of the precipitation–temperature relation. Similar analyses were applied to the whole river basin, including the mountainous area. The results showed that the differences in P99 and P99.9 between PAST and FUTURE are mainly due to the thermodynamic contribution, regardless of plain or mountain area. Using such large model data sets, we could make a robust assessment of the precipitation–temperature relation and the dynamic and thermodynamic contributions to precipitation changes. Moreover, using the 5‐km resolution hundreds‐year data set enabled us to quantify the spatial distribution of such precipitation characteristics over a thousands of square kilometer catchment. [ABSTRACT FROM AUTHOR]

In this study, self-organizing maps in combination with K-means clustering are used to objectively classify the anomalous weather patterns (WPs) associated with the summertime [May–June (MJ) and July–August–September (JAS)] heavy rainfall days during 1979–2007 over the Upper Nan River basin, northwestern Thailand. The results show that in MJ, intensive rains are mainly brought by the remarkable enhancement of the westerly summer monsoon. Meanwhile, westward-propagating tropical disturbances including tropical cyclones are the primary factors that reproduce heavy rainfall over the Upper Nan in JAS. These results also suggest that the occurrence time of local heavy rainfall is strongly related to the seasonal transition of the summer monsoon over the Indochina Peninsula. The classification results are then implemented with the perfect prognosis and analog method to predict the occurrence (yes/no) of heavy rainfall days over the studied basin in summer 2008–17 using prognostic WPs from the operational Japan Meteorological Agency Global Spectral Model (GSM). In general, the forecast skill of this approach up to 3-day lead times is significantly improved, in which the method not only outperforms GSM with the same forecast ranges, but also its 3-day forecast is better than the 1–2-day forecasts from GSM. However, the false alarms ratio is still high, particularly in JAS. Nevertheless, it is expected that the new approach will provide warning and useful guidance for decision-making by forecasters or end-users engaging in water management and disaster prevention activities. [ABSTRACT FROM AUTHOR]

ABSTRACT: Extreme winter daily temperature is an important parameter for determining winter precipitation. This study used a principal component analysis and k‐means clustering to characterize the circulation patterns of extreme daily temperatures for 19 winter seasons in Sapporo, Hokkaido, Japan. Climatological anomaly maps were constructed for sea level pressure (SLP) and the 500‐hPa geopotential height for the identified minimum (Tmin10; 239 days) and maximum (Tmax90; 236 days) daily temperature extremes. The Tmax90 SLP anomaly pattern was the opposite (west–east orientation) of the Tmin10 pattern. The circulation patterns that predominantly contributed to winter rainfall were derived from cyclones over the Sea of Japan via instability created by abundant heat and moisture over the ocean and a strong positive 500‐hPa height anomaly over Hokkaido. [ABSTRACT FROM AUTHOR]

In this study, the Self-Organizing Maps in combination with K-means clustering technique are used for classification of synoptic weather patterns inducing heavy rainfall exceeding 100 mm day−1 during the Baiu season (June-July) of 1979-2010 over northern Kyushu, southwestern Japan. It suggests that these local extreme rainfall events are attributed to four clustered patterns, which are primarily related to the Baiu front and the extratropical/tropical cyclone/depression activities and represented by the intrusion of warm and moist air accompanied by the low-level jet or cyclonic circulation. The classification results are then implemented with the analogue method to predict the occurrence (yes/no) of local heavy rainfall days in June-July of 2011-2016 by using the prognostic synoptic fields from the operational Japan Meteorological Agency ( JMA) Global Spectral Model ( GSM). In general, the predictability of our approach evaluated by the Equitable Threat Score up to 7-day lead times is significantly improved than that from the conventional method using only the predicted rainfall intensity from GSM. Although the false alarm ratio is still high, it is expected that the new method will provide a useful guidance, particularly for ranges longer than 2 days, for decision-making and preparation by weather forecasters or end-users engaging in disaster-proofing and water management activities. [ABSTRACT FROM AUTHOR]

• One spatiotemporal rainfall pattern classification method was proposed. • Heavy rainfall events in massive ensemble climate dataset were classified. • Rainfall patterns and those frequencies in target basin were clarified. • The method can detect high-risk rainfall patterns for each location in target basin. • Proposed method with climate datasets will contribute to flood control planning. Peak discharge in rivers mostly varies depending on spatiotemporal characteristics of the rainfall, even with the same total rainfall amount. However, the spatiotemporal patterns of heavy rainfall such as rainfall levels used for river planning are difficult to determine due to the limited number of rainfall observations. We propose a spatiotemporal classification method for massive-ensemble rainfall datasets produced through dynamical downscaling with a regional climate model to clarify the possible rainfall patterns. This classification method was applied to several hundred heavy rainfall events from the massive-ensemble climate dataset, corresponding to identical exceedance probabilities within a given statistical confidence interval (i.e., 95% confidence interval of the 150-year return period in the probability limit test). The new classification method detected spatiotemporal rainfall patterns affecting peak discharges in the main river and tributaries within the target basin. These classified rainfall patterns can be used to investigate damage scenarios in the target basin, which are difficult to determine from the observed rainfall patterns. As a result, the proposed method with the massive-ensemble climate dataset will contribute to flood control planning. [ABSTRACT FROM AUTHOR]

Pakistan and northwestern India have frequently experienced severe heavy rainfall events during the boreal summer over the last 50 years including an event in late July and early August 2010 due to a sequence of monsoon surges. This study identified five dominant atmospheric patterns by applying principal component analysis and k-means clustering to a long-term sea level pressure dataset from 1979 to 2014. Two of these five dominant atmospheric patterns corresponded with a high frequency of the persistent atmospheric blocking index and positive sea level pressure over western Russia as well as an adjacent meridional trough ahead of northern Pakistan. In these two groups, a negative sea surface temperature anomaly was apparent over the equatorial mid- to eastern Pacific Ocean. The heavy precipitation periods with high persistent blocking frequency in western Russia as in the 2010 heat wave tended to have 1.2 times larger precipitation intensity compared to the whole of the heavy precipitation periods during the 36 years. [ABSTRACT FROM AUTHOR]

Atmospheric blocking is one of the most impactful weather patterns in midlatitude regions, causing floods, droughts and unusually high or low temperatures. This study investigates the relationship between extremely cold days over Japan and its surroundings and North Pacific blocking in the European Centre for Medium-range Weather Forecasts ( ECMWF) re-analysis ( ERA-40), phase 5 of the Coupled Model Intercomparison Project ( CMIP5) for historical weather and the representative concentration pathway 8.5 ( RCP8.5) experiments based on nine climate model datasets in the boreal winter season. Under the climate change conditions based on the RCP8.5 future scenario, extreme cold days (i.e. the first percentile of cold days) over Japan and its surroundings will become weaker but occur more widely when blocking is generated over the northwestern Sea of Okhotsk and its surroundings, because the blocking frequency over this area will decrease and the intensity will weaken. [ABSTRACT FROM AUTHOR]

Synoptic-scale atmospheric circulations are crucial for extreme snowfall events. On the basis of topmost 100 snowfall intensity days in Sapporo, Hokkaido, Japan over winter seasons from 1992 to 2011, this study uses principal component analysis and K-means clustering to characterize synoptic circulation patterns. Composite maps were constructed for sea-level pressure, 850 hPa moisture and wind field, and 500 hPa geopotential height. The circulation patterns of the topmost seven snowfall events were triggered by the advection of very cold airmass from eastern Siberia, anomalously huge moisture with northerly strong wind, active and stationary Aleutian low, and 500 hPa deep cold-core low over the southern Hokkaido. [ABSTRACT FROM AUTHOR]

A rainfall estimation method was developed based on the statistical relationships between cloud-top temperature and rainfall rates acquired by both the 10.8-μm 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. [ABSTRACT FROM AUTHOR]

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. EditorZ. W. Kundzewicz CitationYamada, 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 results suggest an important role of the horizontal resolution of the model in resolving small-scale, propagating convective systems to improve the diurnal cycle of summer rainfall. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The effects of sea spray on open-ocean rainfall measurements-the drop size distribution (DSD) and rainfall intensities-were studied using a state-of-the-art optical disdrometer. The number of rain droplets less than 1 mm in diameter is affected by several factors, including the type of rainfall and seasonality. Over the ocean, small rain and large sea spray droplets co-exist in the same diameter size class (0.072 to 1000 mm); hence, sea spray creates uncertainty when seeking to characterize the drop size distribution (DSD) of rain droplets over the ocean. We measured droplet sizes at a marine tower using a state-of-the-art optical disdrometer, a tipping-bucket rain gauge, a wind anemometer, and a time-lapse camera, over a period that included typhoon Krosa of 2019. The number of rain droplets of diameter less than 1 mm increased monotonically as the horizontal wind speed became stronger. Thus, the shape parameter μ of the Ulbrich distribution decreased. This decreasing trend can be recognized as an increase in sea spray. During no-rainfall hours (indicated by rain gauges on the ocean tower and nearby land), sea spray DSDs were obtained at various horizontal wind speeds. Furthermore, the proportions of sea spray to rainfall at different rainfall intensities and horizontal wind speeds were determined; at a horizontal wind speed of 16 to 20 m s−1, the average sea spray proportions were 82.7%, 19.1%, and 5.3% during total rainfall periods of 2.1 mm h−1, 8.9 mm h−1, and 32.1 mm h−1, respectively. Representation of sea spray DSDs, as well as rainfall DSDs, is a key element of calculating real rainfall intensities over the open ocean. [ABSTRACT FROM AUTHOR]

Previous studies have shown that the acceleration of global warming will increase the intensity of rainfall induced by tropical cyclones (TCs) (hereinafter referred to as "TC-induced rainfall"). TC-induced rainfall is affected by TC position and topography (slope shape and direction). Thus, TC-induced rainfall is expected to vary by sub-basin due to varying topographies. However, these relationships have not been explained, as historical TCs, which occurred several decades earlier, do not exhaustively encompass all TC positions that could potentially affect each basin. We used large ensemble regional climate model experiments with 5 km grid spacing, which enabled us to prepare a huge TC database for understanding the characteristics of TC-induced rainfall over sub-basins. We quantified the characteristics of TC-induced rainfall (rainfall volume, relationship between TC position and rainfall intensity, and contribution of TC intensity on rainfall) over four sub-basins in the Tokachi River basin, central Hokkaido, northern Japan. The results reveal differences in TC-induced rainfall characteristics between the sub-basins. In addition, the large ensemble data under a future climate scenario were used to evaluate future changes in the characteristics of TC-induced rainfall for each sub-basin. [ABSTRACT FROM AUTHOR]

Record-breaking precipitation events have been frequent in Japan in recent years. To investigate the statistical characteristics of the frequency of record-breaking events, observations can be compared with the values derived from sampling theory with a stationary state. This study counted the number of record-breaking daily and 3-day total precipitation events at 58 rain-gauge stations in Japan between 1901 and 2018. The average number of record-breaking events over the 118-year period was 5.9 for daily total precipitation, which is larger than the theoretical value of 5.4 derived using the assumption that the climate system over the same period was stationary. Sampling theory was used to incorporate the influence of the long-term temperature trend from the Clausius–Clapeyron relation associated with the saturation vapor pressure. In theory, the long-term temperature trend gives a similar number of observed record-breaking events when the long-term temperature trend is approximately 0.5 Kelvin/100 years. [ABSTRACT FROM AUTHOR]

Irrigation can affect climate and weather patterns from regional to global scales through the alteration of surface water and energy balances. Here, we couple a land-surface model (LSM) that includes various human land-water management activities including irrigation with an atmospheric general circulation model (AGCM) to examine the impacts of irrigation-induced land disturbance on the subseasonal predictability of near-surface variables. Results indicate that the simulated global irrigation and groundwater withdrawals (circa 2000) are ~3600 and ~370 km3/year, respectively, which are in good agreement with previous estimates from country statistics and offline–LSMs. Subseasonal predictions for boreal summers during the 1986–1995 period suggest that the spread among ensemble simulations of air temperature can be substantially reduced by using realistic land initializations considering irrigation-induced changes in soil moisture. Additionally, it is found that the subseasonal forecast skill for near-surface temperature and sea level pressure significantly improves when human-induced land disturbance is accounted for in the AGCM. These results underscore the need to incorporate irrigation into weather forecast models, such as the global forecast system. [ABSTRACT FROM AUTHOR]

This study investigates the change in extreme rainfall and river flooding for a large river basin due to climate change during the summer monsoon using a large ensemble dataset (d4PDF) coupled with the Integrated Flood Analysis System (IFAS). Frequent severe flooding causes significant damage in Japan. Therefore, we aim to provide useful information to mitigate flood damage. The study area is the Ishikari River basin (IRB) in Hokkaido, Japan. We used the d4PDF 5-km downscaled rainfall data as input for the IFAS model. The results showed that, for a given increase in extreme rainfall, the discharges from the IRB and its main sub-basins increase to a greater extent. The differences between the time of peak discharge at the reference stations in each tributary and the time of peak water level at the confluence points in the main river are evaluated. Climate change effects are significant in the southern sub-basins, wherein the amount of extreme rainfall increases by 29%- 35%, whereas the river discharge increases drastically (37%-56%). Additionally, the time difference decreases by 1.02-2.14 h. These findings will help policymakers develop future flood control measures in flood-prone areas. [ABSTRACT FROM AUTHOR]

Motivated by the problem of rainfall duration bias typically found in dynamical downscaling, its possible effect on hydrology was evaluated for heavy rainfall events over Kyushu, Japan, during summer. Heavy rainfall in western Kyushu is often related to a persistent Baiu rainband across Kyushu, while in eastern Kyushu it is related to the passage of typhoons near Kyushu. For typical heavy-rainfall periods, we ran a tank model for several target rivers to analyze runoff and water-depth sensitivity to the hyetograph by artificially extending the rainfall duration to 8 hours while maintaining the same total rainfall. This showed that a spike in peak runoff was suppressed by prolonged weak rainfall as typically found in downscaling outputs. The timing of rising runoff and water depth in the tank model was shifted earlier. [ABSTRACT FROM AUTHOR]

We investigated extremely heavy precipitation that occurred around the Kinugawa River, Japan, in September 2015, and the probability of extreme precipitation occurrence, using data from a large ensemble forecast of more than 1,000 members that were dynamically downscaled to 1.6 km horizontal grid spacing. The observed event was statistically rare among simulated cases and the 3-day accumulated precipitation around the target area was equivalent to the 95th percentile among all simulated ensemble members. Our results show that this extreme precipitation event occurred under specific conditions: two coexisting typhoons at close proximity that produced a high atmospheric instability, and water vapor transported from the Pacific Ocean. We also assessed the probability of extreme precipitation in mountainous areas other than the Kinugawa River case. Heavy precipitation also occurred southwest of the Kinugawa River region due to two typhoons, similar to the Kinugawa River case. The tracks of these typhoons shifted marginally; however, there was a difference in the water vapor supplied to the area, causing heavy precipitation. The large-ensemble downscaled data used in this study hence enabled us to evaluate the occurrence probability of a torrential rainfall event that was rarely observed, which may contribute to updating a disaster-mitigating plan for possible similar disasters in future. [ABSTRACT FROM AUTHOR]

The estimation of extreme wind speeds, their directional variation, and potential future changes is essential for windresistant design and is possible using climate models. Accurate evaluations of local topographic winds such as downslope windstorms and gap winds require highresolution calculation and many ensemble years. However, few climate databases satisfy both requirements and none have been validated for extreme wind speeds. We assessed directional extreme wind speeds using a massive high-resolution ensemble climate dataset (d4PDF-5km-DS) for Hokkaido Island, Japan. Despite some issues due to limited reproducibility of spring extratropical cyclones, downslope windstorms caused by large mountains are reproduced well, indicating decreasing wind speed under predicted future climate. The findings suggest future climatic conditions may influence extreme topographic wind speeds. [ABSTRACT FROM AUTHOR]

The experiments with three general circulation models ( GCMs) by three regional atmospheric models ( RAMs) for the dynamical downscaling ( DDS) have been performed to evaluate the uncertainty in the global warming response during summertime in Hokkaido, Japan. The results of a 10-year RAM integration nested into GCM under present or future climate conditions were synthesized after applying bias correction. For the target decades during which the global-mean temperature increases by 2 K in each GCM, the DDS results indicate that surface air temperature and precipitation mostly depend on the GCM imposed as the lateral boundary condition. [ABSTRACT FROM AUTHOR]

Air pollution is a serious challenge in South Korea and worldwide, and negatively impacts human health and mortality rates. To assess air quality and the spatiotemporal characteristics of atmospheric particulate matter (PM), PM concentrations were compared with meteorological conditions and the concentrations of other airborne pollutants over South Korea from 2015 to 2020, using different linear and non-linear models such as linear regression, generalized additive, and multivariable linear regression models. The results showed that meteorological conditions played a significant role in the formation, transportation, and deposition of air pollutants. PM2.5 levels peaked in January, while PM10 levels peaked in April. Both were at their lowest levels in July. Further, PM2.5 was the highest during winter, followed by spring, autumn, and summer, whereas PM10 was the highest in spring followed by winter, autumn, and summer. PM concentrations were negatively correlated with temperature, relative humidity, and precipitation. Wind speed had an inverse relationship with air quality; zonal and vertical wind components were positively and negatively correlated with PM, respectively. Furthermore, CO, black carbon, SO2, and SO4 had a positive relationship with PM. The impact of transboundary air pollution on PM concentration in South Korea was also elucidated using air mass trajectories. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Dynamical downscaling (DDS) was conducted over Japan by using a regional atmospheric model with reanalysis data to investigate the rainfall duration bias over Kyushu, Japan, in July and August from 2006 to 2015. The model results showed that DDS had a positive rainfall duration bias over Kyushu and a dry bias over almost all of Kyushu, which were emphasized for extreme rainfall events. Investigated was the rainfall duration bias for heavy rainfall days, accompanied by synoptic-scale forcing, in which daily precipitation exceeded 30mm day-1 and covered over 20% of the Kyushu area. Heavy rainfall days were sampled from observed rainfall data that were based on rain gauge and radar observations. A set of daily climatic variables of horizontal wind and equivalent potential temperature at 850 hPa and sea level pressure, around southwestern Japan, corresponding to the sampled dates, was selected to conduct a self-organizing map (SOM) and K-means method. The SOM and K-means method objectively classified three synoptic patterns related to heavy rainfall over Kyushu: strong monsoon, weak monsoon, and typhoon patterns. Rainfall duration had a positive bias in western Kyushu for the strong monsoon pattern and a positive bias in southern and east-coast Kyushu for the typhoon pattern, whereas there was little rainfall duration bias in the weak monsoon pattern. The bias for the typhoon pattern was related to rainfall events with a strong rainfall peak. The results suggest that bias correction for rainfall duration would be required for accurately estimating direct runoff in a catchment area in addition to the precipitation amount. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]