Recent progress in computing and model development has initiated the era of global storm-resolving modeling, and with it the potential to transform weather and climate prediction. Within the general theme of vetting this new class of models, the present study evaluates nine global-storm resolving models in their ability to simulate tropical cyclones (TCs). Results indicate that, broadly speaking, the models produce realistic TCs and remove longstanding issues known from global models such as the deficiency in accurately simulating TC intensity. However, TCs are strongly affected by model formulation, and all models suffer from unique biases regarding the number of TCs, intensity, size, and structure. Some models simulated TCs better than others, but no single model was superior in every way. The overall results indicate that global storm-resolving models can open a new chapter in TC prediction, but they need to be improved to unleash their full potential.

A new method that retrieves attenuation profiles using a Dual-frequency Precipitation Radar (DPR) equipped on the Global Precipitation Mission (GPM) is proposed. The DPR operates at Ka and Ku-bands and provides profiles of a differential frequency ratio, which is the difference of the measured or attenuated reflectivity in decibel scale between Ka and Ku bands. For accurate measurements of precipitation, hydrometeor classification is essential. Attenuation of radio wave due to precipitation is closely related to microphysical properties and available for hydrometeor classification. The proposed method estimates range variations of relative values of differential attenuation between two frequencies and can be used for identifying hydrometeor types along the radar propagation path. Numerical simulations indicate that the proposed method performs well for rain, melted snow, mixed-phase precipitation, and some cases of the melting layer. The method was also evaluated for GPM DPR measurements. Results indicate that the method works well for identifying rain and snow and also provides useful information for melting layer detection and attenuation, even for the melting layer in which no enhancement of reflectivity is observed.

The transport and removal processes of aerosol particles, as well as their potential impacts on clouds and climate, are strongly dependent on the particle sizes. Recent advances in computational capabilities enable us to develop sectional aerosol schemes for general circulation models and chemical transport models. The sectional aerosol modeling framework provides a capacity to explicitly simulate the variations in size distributions due to microphysical processes such as nucleation and coagulation, based on the mechanisms suggested from laboratory studies and field observations. Here, we develop a two-moment sectional aerosol scheme for Spectral Radiation-Transport Model for Aerosol Species (SPRINTARS-bin) for use in Nonhydrostatic ICosahedral Atmospheric Model (NICAM) as an alternative to the original mass-based (single-moment) SPRINTARS-orig aerosol module. NICAM-SPRINTARS is a seamless multiscale model that has been used for regional-to-global simulations of different resolutions based on the same model framework. In this study, we performed global simulations with NICAM-SPRINTARS-bin at typical climate model resolution (Δ x ∼ 230 km) with nudging to a meteorological re-analysis. We compared our results with equivalent simulations for the original model (NICAM-SPRINTARS-orig) and observations including 500nm aerosol optical depth and 440–870nm Angstrom Exponent in AErosol RObotic NETwork (AERONET) measurements, particle number concentrations measured at Global Atmospheric Watch (GAW) sites and size-resolved number concentrations measured at European Supersites for Atmospheric Aerosol Research (EUSAAR) and German Ultrafine Aerosol Network (GUAN) sites. We found that compared to NICAM-SPRINTARS-orig, NICAM-SPRINTARS-bin demonstrates the long-range transport of ultra-fine particles to high latitudes and predicts higher Angstrom Exponent and total number concentrations that better agrees with observations. The latter underscores the importance of resolving the microphysical processes that determine concentrations of ultra-fine aerosol particles and explicitly represent size-dependent deposition in predicting these properties. However, number concentrations of coarse particles are still underestimated by both the original mass-based and the new microphysical schemes. Further efforts are needed to understand the reasons for the differences with the observed size distributions, including testing different emission and secondary organic aerosol production schemes, incorporating inter-species coagulation and black carbon aging, as well as performing simulations with higher spatial resolutions.

This study applied the C-band vertically pointing radar with frequency-modulation continuous-wave technology to obtain the continuous observation data of four shallow and two deep snow events during the winter of 2015–2016 in the midlatitudes of China. Generating cells (GCs) were found near the echo tops in every event. The ice particle number concentration (N), ice water content (IWC), and median mass diameter (D_m) retrieved from radar Doppler spectra were used to analyze the microphysical properties in the snow clouds. The clouds were divided into upper GC and lower stratiform (St) regions according to their vertical structure. The fall streaks (FSs) associated with GCs were embedded in the St regions. In the GC regions, the N values in shallow events were smaller compared with those in deep events, and D_m and IWC were larger. In the St regions, N decreased compared with that in the GC regions, and D_m and IWC increased, implying the existence of aggregation and deposition growth. The growth of particle size and mass mainly occurred in the St regions. The increases of N were usually observed near −5°C accompanied by bimodal Doppler spectra, which might be caused by ice multiplication. The average ratios of the median N, D_m, and IWC inside GCs to those outside GCs were 2, 1.3, and 2.5, respectively, for shallow events, with 1.7, 1.2, and 2.3, respectively, for deep events. These values were basically the same as those for the FSs, implying the importance of GCs to the enhanced ice growth subsequently found in FSs. The larger values of N, D_m, and IWC inside GCs could be related to the upward air motions inside GCs. The first Z_e-IWC relationship suitable for snow clouds in the midlatitudes of China was also established.

Reliability information of satellite precipitation products is required for various applications. This study describes and evaluates a reliability flag of the Global Satellite Mapping of Precipitation Near-Real-Time precipitation product (GSMaP_NRT). This flag was developed to characterize the reliability of GSMaP_NRT data simply and qualitatively by considering its algorithm characteristics. The reliability at each pixel is represented by any one of ten levels (10 being the best and 1 the worst) by considering three major factors: 1) “surface type reliability”— which takes into account that estimation of rainfall using passive microwave sensors is better over the oceans than over land and coastal areas; 2) “low-temperature reliability”—which takes into account the lower reliability due to surface snow cover in low-temperature conditions; and 3) “Moving Vector with Kalman Filter (MVK) propagation reliability”—which means that the reliability gets worse with the increase in time since the last overpass of the passive microwave sensor.

To evaluate the utility of the reliability flag, statistical indices are calculated for each reliability level using gauge-calibrated ground radar data around Japan. It is found that the reliability flag represents the differences in GSMaP accuracy: the accuracy worsens as the reliability decreases. The GSMaP errors exhibit seasonal changes that are well represented by the ten levels of the reliability flag, indicating that the reliability flag can be used to catch seasonal variations in GSMaP accuracy due to changes in environmental factors.

This study also raises the possibility of improving the reliability flag by using information related to heavy orographic rainfall. It is shown how the error features of heavy orographic rainfall differ from those of the total rainfall, and it is suggested that heavy orographic rainfall information can be utilized to further improve the reliability flag.

The Minimal Advanced Treatments of Surface Interaction and RunOff (MATSIRO), which has been used as a land-surface scheme in the global climate model, the Model for Interdisciplinary Research on Climate (MIROC), calculates Dunne runoff and base runoff using the TOPography-based MODEL (TOPMODEL). In past experiments that used MATSIRO, the runoff and its response to precipitation were too low compared to observation. We conjectured that those biases could be attributed to the water table's excessive depth. Its depth was diagnosed based on grid-mean soil moisture using a saturation threshold that was originally set to almost equal the porosity. In this study, sensitivity experiments, in which the threshold was decreased to 75, 50, 25, and less than 13 % of the porosity, were conducted, and the subsequent effects on river flow were investigated in the Chao Phraya River basin, Thailand, as a case study. As a result, both Dunne and base runoff increased along with the response of river flow to precipitation. The simulated river flow matched observations most closely with a threshold of 50 % saturation. In addition, soil moisture and the Bowen ratio changed significantly with the runoff changes induced by the threshold changes. These results suggested the importance of the relationship between grid-mean soil moisture and groundwater level for the TOPMODEL. Preliminary global experiments indicate that runoff sensitivity might be dependent on climate zone.

The Tropical Rainfall Measuring Mission (TRMM) satellite was launched in 1997, and the observations continued for more than 17 years. The features of TRMM observation were as follows: (a) it followed a non-sun synchronized orbit that enabled the diurnal variation of precipitation to be investigated; (b) it carried a precipitation radar and microwave and infrared radiometers, along with two instruments of opportunity in the form of a lighting sensor and a radiation budget sensor; and (c) it worked as a standard reference for precipitation measurements for other spaceborne microwave radiometers, which enabled global rain maps to be developed. For science, TRMM provided precise and accurate rain distributions over tropical and subtropical regions. The rainfall results are primarily essential for the study of precipitation climatologies, whereas the three-dimensional images of precipitation systems enabled the study of the global characteristics of precipitation systems. Technologically, the spaceborne rain radar onboard TRMM demonstrated the effectiveness of radars in space, whereas the combination with other rain observation instruments showed its effectiveness as a calibration source. Multi-satellite rain maps in which TRMM was the reference standard have been developed, and they became prototypes of the multi-satellite Earth observation systems. On the basis of the great success of TRMM, the Global Precipitation Measurement (GPM) was designed to expand TRMM's coverage to higher latitudes. The core satellite of GPM is equipped with a dual-frequency precipitation radar (DPR) and a microwave radiometer. DPR comprises a Ku-band radar (KuPR) and a Ka-band radar (KaPR) and can discriminate solid from liquid precipitation. The period of the precipitation measurement with spaceborne radars extended to more than 23 years, which may make it possible to detect the change of precipitation climatology related to change in the global environment. Although TRMM's and GPM's accomplishments are very broad, this paper attempts to highlight Japan's contributions to the science of these missions.

This paper presents an efficient, practical post-processing algorithm for the quality control of dual-pulse repetition frequency (dual-PRF) Doppler velocity data observed in Plan Position Indicator (PPI) mode. Quality control refers to the enhancement of the quality of the Doppler velocities through the reassignment of an appropriate Nyquist interval number to an erroneous velocity datum and the elimination of unreliable data. The proposed algorithm relies on the local continuity of velocity data, as do most of the preexisting algorithms. Its uniqueness, however, lies both in the preparation of more reliable reference velocity data and its applicability to PPI data at higher elevation angles. The performance of the proposed algorithm is highlighted by its application to observed data from C- and X-band Doppler radars. This algorithm is practical, efficient, and not time-consuming. It may be of great help in the derivation of accurate wind information from dual-PRF Doppler velocities.

Accurate rainfall estimation during the Indian summer monsoon (ISM) is one of the most crucial activities in and around the Indian Sub-continent. Japan Aerospace Exploration Agency (JAXA) provides a couple of Global Satellite Mapping of Precipitation (GSMaP) rainfall products, namely, the GSMaP_MVK, which is a satellite-based product calculated with ancillary data including global objective analysis data, and the GSMaP_Gauge, which is adjusted by global rain gauges. In this study, the daily rainfall amount from the GSMaP rainfall product (version 7) is validated against a dense rain gauge network over Karnataka, one of the southwestern states of India, during ISM 2016–2018. Furthermore, as the primary objective of this study, these dense rain gauge observations are assimilated in the GSMaP rainfall product using a hybrid assimilation method to improve the final rainfall estimate. The hybrid assimilation method is a combination of the two-dimensional variational (2D-Var) method and the Kalman filter, in which the 2D-Var method is utilized to merge rain gauge observations and the Kalman filter is applied to update background error in the 2D-Var method. Preliminary verification results suggest that GSMaP_Gauge rainfall has sufficient skill over north interior Karnataka and south interior Karnataka regions, with large errors over the orographic heavy rainfall region of the Western Ghats. These errors are larger in the GSMaP_MVK rainfall product over orographic heavy rainfall regions. Hybrid assimilation results of randomly selected rain gauge observations improve the skill of GSMaP_Gauge and GSMaP_MVK rainfall products when compared with independent rain gauge observations. These improvements in daily rainfall are more prominent over orographic heavy rainfall regions. GSMaP_MVK rainfall product shows larger improvement due to the absence of the gauge adjustment in the JAXA operational processing. The superiority of the hybrid assimilation method against Cressman and optimal interpolation methods for impacts of utilized rain gauge numbers are also presented in the present study.

A phased array weather radar (PAWR) can complete one volume scan in 30 s, thus enabling us to obtain high spatiotemporal resolution echo intensities and wind fields of storms. Using its rapid scanning capability, we investigated the evolution of a convective storm in detail. To describe the evolution of convective storms, we used the following definitions. The precipitation cell is defined as a three-dimensionally contiguous region of 40 dBZ or greater. The precipitation core is defined by a threshold of positive deviation greater than 7 dBZ, which is a difference from the average reflectivity during the mature stage of the cell. An updraft core is defined as an updraft region of 1 m s⁻¹ or stronger at a height of 2 km.

An isolated convective storm was observed by two PAWRs on 7 August 2015 in the Kinki District, western Japan. The storm was judged as a single cell, according to the above definition. We identified nine precipitation cores and five updraft cores within 49 min in the mature stage of the cell. A long-lasting updraft core and its branches moved southwestward or southeastward. Around these updraft cores, the precipitation cores were generated successively. The updraft core with the longest duration lasted 73.5 min; in contrast, the lifetimes of the precipitation cores were from 4.5 min to 14.5 min. The precipitation cell was maintained by the successive generations of updraft cores which lifted humid air associated with a low-level southwesterly inflow. The total amounts of water vapor inflow supplied by all the identified updraft cores were proportional to the volumes of the precipitation cell, with a correlation coefficient of 0.75. Thus, the extremely high spatiotemporal resolution of the PAWR observations provides us with new evidence that an isolated convective storm can be formed by multiple precipitation cores and updraft cores.