Scaling of tropical rainfall as observed by TRMM precipitation radar

We used a three-year (1998–2000) dataset of TRMM Precipitation Radar observations to investigate the scaling properties of spatial rainfall fields. This dataset allows consideration of spatial scales ranging from about 4.3 km to 138 km and short temporal scales corresponding to the sensor overpasses. The focus is on the marginal spatial moment scaling, which allows estimation of the scaling parameters from a single scene of data. Here we present a global perspective of the scaling properties of tropical rainfall in terms of its spatial variability, atmospheric forcing, predictability, and applicability. Our results reveal the following: 1) the scaling parameters exhibit strong variability associated with land/ocean contrast and mean precipitation at the synoptic scale; 2) there exists a one-to-one relationship between the scaling parameters and the large-scale spatial average rain rate of a universal functional form; 3) the majority of the scenes are consistent with the hypothesis of scale invariance at the moment orders of 0 and 2; 4) relatively there are more scale-invariant rain scenes over land than over ocean; and 5) for the scenes that are non-scale-invariant, deviation from scale-invariance mainly arises from the increasingly intermittent behavior of rainfall as spatial scale decreases. These results have important implications for the development and calibration of downscaling procedures designed to reproduce rainfall properties at different spatial scales and lead to a better understanding of the nature of tropical rainfall at various spatial resolutions.     

Analysis of rainfall characteristics of the Madden–Julian oscillation using TRMM satellite data

Rainfall characteristics of the Madden–Julian oscillation (MJO) are analyzed primarily using tropical rainfall measuring mission (TRMM) precipitation radar (PR), TRMM microwave imager (TMI) and lighting imaging sensor (LIS) data. Latent heating structure is also examined using latent heating data estimated with the spectral latent heating (SLH) algorithm.The zonal structure, time evolution, and characteristic stages of the MJO precipitation system are described. Stratiform rain fraction increases with the cloud activity, and the amplitude of stratiform rain variation associated with the MJO is larger than that of convective rain by a factor of 1.7. Maximum peaks of both convective rain and stratiform rain precede the minimum peak of the outgoing longwave radiation (OLR) anomaly which is often used as a proxy for the MJO convection. Stratiform rain remains longer than convective rain until 4000 km behind the peak of the mature phase. The stratiform rain contribution results in the top-heavy heating profile of the MJO.Associated with the MJO, there are tri-pole convective rain top heights (RTH) at 10–11, 7 and 3 km, corresponding to the dominance of afternoon showers, organized systems, and shallow convections, respectively. The stratiform rain is basically organized with convective rain, having similar but slightly lower RTH and slightly lags the convective rain maximum. It is notable that relatively moderate (7 km) RTH is dominant in the mature phase of the MJO, while very tall rainfall with RTH over 10 km and lightning frequency increase in the suppressed phase. The rain-yield-per flash (RPF) varies about 20–100% of the mean value of 2–10 × 10⁹ kg fl⁻¹ over the tropical warm ocean and that of 2–5 × 10⁹ kg fl⁻¹ over the equatorial Islands, between the convectively suppressed phase and the active phase of MJO, in the manner that RPF is smaller in the suppressed phase and larger in the active phase.     

Validation of precipitation over Japan during 1985–2004 simulated by three regional climate models and two multi-model ensemble means

We dynamically downscaled Japanese reanalysis data (JRA-25) for 60 regions of Japan using three regional climate models (RCMs): the Non-Hydrostatic Regional Climate Model (NHRCM), modified RAMS version 4.3 (NRAMS), and modified Weather Research and Forecasting model (TWRF). We validated their simulations of the precipitation climatology and interannual variations of summer and winter precipitation. We also validated precipitation for two multi-model ensemble means: the arithmetic ensemble mean (AEM) and an ensemble mean weighted according to model reliability. In the 60 regions NRAMS simulated both the winter and summer climatological precipitation better than JRA-25, and NHRCM simulated the wintertime precipitation better than JRA-25. TWRF, however, overestimated precipitation in the 60 regions in both the winter and summer, and NHRCM overestimated precipitation in the summer. The three RCMs simulated interannual variations, particularly summer precipitation, better than JRA-25. AEM simulated both climatological precipitation and interannual variations during the two seasons more realistically than JRA-25 and the three RCMs overall, but the best RCM was often superior to the AEM result. In contrast, the weighted ensemble mean skills were usually superior to those of the best RCM. Thus, both RCMs and multi-model ensemble means, especially multi-model ensemble means weighted according to model reliability, are powerful tools for simulating seasonal and interannual variability of precipitation in Japan under the current climate.     

Coupling mechanisms between equatorial waves and cumulus convection in an AGCM

In this study, we focused on the difference in appearances of the convectively coupled equatorial waves (CCEWs) in a simulation with the CCSR/NIES/FRCGC AGCM, between two experiments, one with and the other without implementation of the convective suppression scheme (CSS) in the prognostic Arakawa–Schubert cumulus parameterization. Realistic CCEW modes, i.e., Kelvin, Rossby, mixed Rossby-gravity (MRG), and n = 0 eastward inertio-gravity (EIG) wave modes, were reproduced in the with-CSS experiment, while only Rossby-wave-like signals appeared in the without-CSS experiment.By comparing the structures of the Kelvin wave mode and the Rossby wave mode in two runs, it was suggested that the structural difference between these two modes in conjunction with the difference in the controlling factor of cumulus convection determines the CCEW features. The CSS implemented here is such that cumulus convection is suppressed until the cloud-layer-averaged relative humidity exceeds the threshold of 80%. In the without-CSS model, only Rossby wave modes are coupled with the convection. This is because CAPE controls cumulus convection in this model, and the larger frictional convergence of Rossby wave mode prepares CAPE to generate favorable condition for cumulus convection. In the case of the with-CSS model, on the other hand, cumulus convection is largely controlled by the humidity in the free atmosphere. The convergence associated with the equatorial waves can produce the moisture anomaly to overcome the relative humidity threshold, and maintains the favorable condition for cumulus convection once it starts. In this case, not only Rossby waves but also Kelvin, MRG, and n = 0 EIG waves are reproduced more realistically. It is suggested that inclusion of some kind of mechanism connecting the free tropospheric moisture with the convection under the condition of abundant convective available potential energy could be a key factor for realistic coupling between large-scale atmospheric waves and convection.     

Reproducibility of precipitation distribution over the tropical oceans in CMIP5 multi-climate models compared to CMIP3

Reproducibility of precipitation distribution over the tropical oceans for the recent dataset of the Coupled Model Intercomparison Project phase 5 (CMIP5) is investigated and compared to CMIP3. The Taylor skill score for the reproducibility of the CMIP5 multi-model ensemble mean (0.64) is slightly higher than that of CMIP3 (0.60), but the difference is not statistically significant. Still, there is some evidences that the double intertropical convergence zone (ITCZ) bias is mitigated from CMIP3 to CMIP5, whereas the cold tongue bias remains similar. An inter-model empirical orthogonal function analysis shows that these two biases are closely related to the dominant inter-model discrepancies of precipitation patterns. The two biases are attributed to two factors, respectively. In the CMIP5 models with the prominent double ITCZ, the deep convection is not sensitive enough to environmental air humidity at the lower-mid troposphere, as is in CMIP3. Thus, the deep convection is not suppressed even over the dry subsidence region of the southeastern Pacific, forming the double ITCZ bias. Conversely, models with the severe cold tongue bias have lower ocean model resolution with too strong equatorial trades. Therefore, proper representation of the sensitivity of deep convection to humidity and higher resolution of the ocean models with better equatorial trades are important for reducing the double ITCZ and the cold tongue biases.     

Tropical cyclone genesis frequency over the western North Pacific simulated in medium-resolution coupled general circulation models

This study examines the tropical cyclone (TC) genesis frequency over the western North Pacific simulated in atmosphere–ocean coupled general circulation models from the World Climate Research Programme’s Coupled Model Intercomparison Project phase 3. We first evaluate performances of eight models with atmospheric horizontal resolution of T63 or T106 by analyzing their daily-mean atmospheric outputs of twentieth-century climate simulations available from the Program for Climate Model Diagnosis and Intercomparison database. The genesis frequency is validated against the best-track data issued by the Japan Meteorological Agency. Five of the eight models reproduce realistic horizontal distribution of the TC genesis with a large fraction over the 10°–20°N, 120°–150°E area. These five high-performance models also realistically simulate the summer–winter contrast of the frequency. However, detailed seasonal march is slightly unrealistic; four of the models overestimate the frequency in the early season (May–June) while all of them underestimate the frequency in the mature season (July–September). Reasons for these biases in the seasonal march for the five high-performance models are discussed using the TC genesis potential (GP) index proposed by Emanuel and Nolan (in Am Meteor Soc, pp 240–241, 2004). The simulated GP has seasonal biases consistent with those of the TC genesis frequency. For all five models, the seasonal biases in GP are consistent with those in environmental lower-tropospheric vorticity, vertical wind shear, and relative humidity, which can be attributed to the simulated behavior of monsoon trough. The observed trough migrates northward from the equatorial region to reach the 10°–20°N latitudinal band during the mature season and contributes to the TC frequency maximum, whereas the simulated trough migrates northward too rapidly and reaches this latitude band in the early season, leading to the overestimation of the TC genesis frequency. In the mature season, the simulated trough reaches as far as 15°–25°N, accompanied by a strong vertical shear south of the trough, providing an unfavorable condition for TC genesis. It is concluded that an adequate simulation of the monsoon trough behavior is essential for a better reproduction of the TC frequency seasonal march.     

Simulation of state-dependent high-frequency atmospheric variability associated with ENSO

High-frequency atmospheric variability depends on the phase of El Nino/Southern Oscillation (ENSO). Recently, there is increasing evidence that state-dependent high-frequency atmospheric variability significantly modulates ENSO characteristics. Hence, in this study, we examine the model simulations of high-frequency atmospheric variability and, further, its dependency on the El Nino phase, using atmospheric and coupled GCMs (AGCM and CGCM). We use two versions of physical packages here—with and without convective momentum transport (CMT)—in both models. We found that the CMT simulation gives rise to a large climatological zonal wind difference over the Pacific. Also, both the climate models show a significantly improved performance in simulating the state-dependent noise when the CMT parameterization is implemented. We demonstrate that the better simulation of the state-dependent noise results from a better representation of anomalous, as well as climatological, zonal wind. Our further comparisons between the simulations, demonstrates that low-frequency wind is a crucial factor in determining the state-dependency of high-frequency wind variability. Therefore, it is suggested that the so-called state-dependent noise is directly induced by the low-frequency wind anomaly, which is caused by SST associated with ENSO.