Abstract

The performance of climate models participating in phases 5 and 3 of the Coupled Model Intercomparison Project (CMIP5 and CMIP3, respectively) is evaluated and compared with respect to precipitation over East Asia (20°–50°N, 110°–150°E). The target period covers the 20 years from 1981 through 2000. The CMIP5 and CMIP3 models underestimate precipitation amounts over East Asia in the warmer season (May–September), while they overestimate precipitation amounts in the colder season (October–April). Both sets of models have some difficulty in simulating the seasonal march of the rainy season over China, the Korean Peninsula, and Japan, and they also underestimate the precipitation intensity over East Asia. Nevertheless, the CMIP5 models show a higher reproducibility of precipitation over East Asia than the CMIP3 models with respect to the geographical distribution of precipitation throughout the year, seasonal march of the rainy season, and extreme precipitation events. Models with a higher reproducibility of annual precipitation tend to show a higher reproducibility of precipitation intensity for both the CMIP5 and CMIP3 models. Correlation analysis using all of the CMIP5 and CMIP3 models reveals that models with higher horizontal resolution tend to perform better than those with a lower resolution. The advantage of the CMIP5 models over the CMIP3 models in the simulation of the East Asian climate can be partly attributed to the improved representation of the west Pacific subtropical high in the CMIP5 models, especially during the summer.

Abstract

The present study investigated the onset and withdrawal dates of the rainy season in Panama by using newly developed, gridded, daily precipitation datasets with a high horizontal resolution of 0.05° based on ground precipitation observations. The onset and withdrawal dates showed very complicated geographical features, although the country of Panama is oriented parallel to latitude lines, and the geographical patterns of the onset and withdrawal dates could simply reflect the latitudinal migration of the intertropical convergence zone, as seen in other regions and countries. An absolute threshold value of 3 mm day⁻¹ (pentad mean precipitation) was used to determine the onset and withdrawal dates. The onset and withdrawal dates obtained from the gridded daily precipitation dataset clearly depicted the migration of the rainy season. The rainy season starts suddenly in pentad 21 (11–15 April) in most of eastern Panama and in pentad 22 (16–20 April) in most of western Panama. The termination of the rainy season begins in Los Santos Province during pentad 67 (27 November–1 December) and expands to both the eastern and western surrounding areas. There is no dry season in the western part of the Caribbean coastal zone. Water vapor fluxes and topography suggest dynamical causes, such as a topographically induced upward mass flux accompanied by high humidity, for the complicated geographical features of the onset and withdrawal dates. An assessment was made of uncertainties in the timing of the onset and withdrawal associated with the definition of these terms.

Abstract

The influence of model biases on projected future changes in the frequency of occurrence of tropical cyclones (FOCs) was investigated using a new empirical statistical method. Assessments were made of present-day (1979–2003) simulations and future (2075–99) projections, using atmospheric general circulation models under the Intergovernmental Panel on Climate Change (IPCC) A1B scenario and phase 5 of the Coupled Model Intercomparison Project (CMIP5) models under the representative concentration pathway (RCP) 4.5 and 8.5 scenarios. The models project significant decreases in global-total FOCs by approximately 6%–40%; however, model biases introduce an uncertainty of approximately 10% in the total future changes. The influence of biases depends on the model physics rather than model resolutions and emission scenarios. In general, the biases result in overestimates of projected future changes in basin-total FOCs in the north Indian Ocean (by +18%) and South Atlantic Ocean (+143%) and underestimates in the western North Pacific Ocean (−27%), eastern North Pacific Ocean (−29%), and North Atlantic Ocean (−53%). The calibration of model performance using the smaller bias influence appears crucial to deriving meaningful signals in future FOC projections. To obtain more reliable projections, ensemble averages were calculated using the models less influence by model biases. Results indicate marked decreases in projected FOCs in the basins of the Southern Hemisphere, Bay of Bengal, western North Pacific Ocean, eastern North Pacific, and Caribbean Sea and increases in the Arabian Sea and the subtropical central Pacific Ocean.

Abstract

This study estimates future changes in the early summer precipitation characteristics around Japan using changes in the large-scale environment, by combining Global Precipitation Measurement precipitation radar observations and phase 5 of the Coupled Models Intercomparison Project climate model large-scale projections. Analyzing satellite-based data, we first relate precipitation in three types of rain events (small, organized, and midlatitude), which are identified via their characteristics, to the large-scale environment. Two environmental fields are chosen to determine the large-scale conditions of the precipitation: the sea surface temperature and the midlevel large-scale vertical velocity. The former is related to the lower-tropospheric thermal instability, while the latter affects precipitation via moistening/drying of the midtroposphere. Consequently, favorable conditions differ between the three types in terms of these two environmental fields. Using these precipitation–environment relationships, we then reconstruct the precipitation distributions for each type with reference to the two environmental indices in climate models for the present and future climates. Future changes in the reconstructed precipitation are found to vary widely between the three types in association with the large-scale environment. In more than 90% of models, the region affected by organized-type precipitation will expand northward, leading to a substantial increase in this type of precipitation near Japan along the Sea of Japan, and in northern and eastern Japan on the Pacific side, where its present amount is relatively small. This result suggests an elevated risk of heavy rainfall in those regions because the maximum precipitation intensity is more intense in organized-type precipitation than in the other two types.

A daily gridded precipitation dataset covering a period of more than 57 yr was created by collecting and analyzing rain gauge observation data across Asia through the activities of the Asian Precipitation—Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE) project. APHRODITE's daily gridded precipitation is presently the only long-term, continental-scale, high-resolution daily product. The product is based on data collected at 5,000–12,000 stations, which represent 2.3–4.5 times the data made available through the Global Telecommunication System network and is used for most daily gridded precipitation products. Hence, the APHRODITE project has substantially improved the depiction of the areal distribution and variability of precipitation around the Himalayas, Southeast Asia, and mountainous regions of the Middle East. The APHRODITE project now contributes to studies such as the determination of Asian monsoon precipitation change, evaluation of water resources, verification of high-resolution model simulations and satellite precipitation estimates, and improvement of precipitation forecasts. The APHRODITE project carries out outreach activities with Asian countries, and communicates with national institutions and world data centers. We have released open-access APHRO_V1101 datasets for monsoon Asia, the Middle East, and northern Eurasia (at 0.5° × 0.5° and 0.25° × 0.25° resolution) and the APHRO_JP_V1005 dataset for Japan (at 0.05° × 0.05° resolution; see www.chikyu.ac.jp/precip/ and http://aphrodite.suiri.tsukuba.ac.jp/). We welcome cooperation and feedback from users.

Abstract

Intense tropical cyclones (TCs) sometimes cause huge disasters, so it is imperative to explore the impacts of climate change on such TCs. Therefore, the authors conducted numerical simulations of the most destructive historical TC in Japanese history, Typhoon Vera (1959), in the current climate and a global warming climate. The authors used four nonhydrostatic models with a horizontal resolution of 5 km: the cloud-resolving storm simulator, the fifth-generation Pennsylvania State University–National Center for Atmospheric Research Mesoscale Model, the Japan Meteorological Agency (JMA) operational nonhydrostatic mesoscale model, and the Weather Research and Forecasting Model. Initial and boundary conditions for the control simulation were provided by the Japanese 55-year Reanalysis dataset. Changes between the periods of 1979–2003 and 2075–99 were estimated from climate runs of a 20-km-mesh atmospheric general circulation model, and these changes were added to the initial and boundary conditions of the control simulation to produce the future climate conditions.

Although the representation of inner-core structures varies largely between the models, all models project an increase in the maximum intensity of future typhoons. It is found that structural changes only appeared around the storm center with sudden changes in precipitation and near-surface wind speeds as the radius of maximum wind speed (RMW) contracted. In the future climate, the water vapor mixing ratio in the lower troposphere increased by 3–4 g kg⁻¹. The increased water vapor allowed the eyewall updrafts to form continuously inside the RMW and contributed to rapid condensation in the taller and more intense updrafts.

Abstract

An unprecedentedly large ensemble of climate simulations with a 60-km atmospheric general circulation model and dynamical downscaling with a 20-km regional climate model has been performed to obtain probabilistic future projections of low-frequency local-scale events. The climate of the latter half of the twentieth century, the climate 4 K warmer than the preindustrial climate, and the climate of the latter half of the twentieth century without historical trends associated with the anthropogenic effect are each simulated for more than 5,000 years. From large ensemble simulations, probabilistic future changes in extreme events are available directly without using any statistical models. The atmospheric models are highly skillful in representing localized extreme events, such as heavy precipitation and tropical cyclones. Moreover, mean climate changes in the models are consistent with those in phase 5 of the Coupled Model Intercomparison Project (CMIP5) ensembles. Therefore, the results enable the assessment of probabilistic change in localized severe events that have large uncertainty from internal variability. The simulation outputs are open to the public as a database called “Database for Policy Decision Making for Future Climate Change” (d4PDF), which is intended to be utilized for impact assessment studies and adaptation planning for global warming.