Nonhydrostatic Icosahedral Atmospheric Model Research Articles

Development of an Aerosol Assimilation System Using a Global Non‐Hydrostatic Model, a 2‐Dimensional Variational Method, and Multiple Satellite‐Based Aerosol Products

AbstractThe computational balance between the model grid resolution and the complexity of the data assimilation technique is essential for accurate aerosol forecasting and obtaining aerosol reanalysis data sets. This study aimed to develop a high‐resolution aerosol assimilation system. A 2‐dimensional variational method (2DVar) was implemented in a non‐hydrostatic icosahedral atmospheric model (NICAM). This new model (NICAM/2DVar), with a global grid size of 56 km, assimilated the observed aerosol optical depth (AOD) that is estimated by combining multiple products of geostationary and polar‐orbital satellites. The model results were evaluated against ground‐based AOD observations on a global scale. They exhibited higher correlations, lower uncertainties, and lower biases than those obtained without the 2DVar. The model also reproduced the observed surface aerosols (PM2.5) mass concentrations, especially in Kyushu, Japan. This occurred because the satellite‐estimated AODs over ocean close to air pollution sources were obtained for many occasions. The correlation coefficient values against the PM2.5 observations increased from 0.44 to 0.65 compared to the results without the 2DVar. The impact of the 2DVar on the forecast results was investigated, and the forecast values for 2–3 days were improved. Because satellite‐retrieved AODs are often lacking over land owing to retrieval difficulties, the use of ground‐based AODs in assimilations is essential for precise processing the of aerosol reanalysis data sets. The computational cost with the use of the 2DVar was only 0.6% more than that without its use. Thus, aerosol assimilation using the NICAM/2DVar can be realistically extended to finer grid sizes.

How Can We Improve the Seamless Representation of Climatological Statistics and Weather Toward Reliable Global K‐Scale Climate Simulations?

AbstractToward the achievement of reliable global kilometer‐scale (k‐scale) climate simulations, we improve the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) by focusing on moist physical processes. A goal of the model improvement is to establish a configuration that can simulate realistic fields seamlessly from the daily‐scale variability to the climatological statistics. Referring to the two representative configurations of the present NICAM, each of which has been used for climate‐scale and sub‐seasonal‐scale experiments, we try to find the appropriate partitioning of fast/local and slow/global‐scale circulations. In a series of sensitivity experiments at 14‐km horizontal resolution, we test (a) the tuning of terminal velocities of rain, snow, and cloud ice, (b) the implementation of turbulent diffusion by the Leonard term, and (c) enhanced vertical resolution. These tests yield reasonable convection triggering and convection‐induced tropospheric moistening, and result in better performance than in previous NICAM climate simulations. In the mean state, double Intertropical Convergence Zone bias disappears, and the zonal contrast of equatorial precipitation, top‐of‐atmosphere radiation balance, vertical temperature profile, and position/strength of subtropical jet are reproduced dramatically better. Variability such as equatorial waves and the Madden–Julian oscillation (MJO) is spontaneously realized with appropriate spectral power balance, and the Asian summer monsoon, boreal‐summer MJO, and tropical cyclone (TC) activities are more realistically simulated especially around the western Pacific. Meanwhile, biases still exist in the representation of low‐cloud fraction, TC intensity, and precipitation diurnal cycle, suggesting that both higher spatial resolutions and further model development are warranted.

Impacts of a double-moment bulk cloud microphysics scheme (NDW6-G23) on aerosol fields in NICAM.19 with a global 14 km grid resolution

Abstract. In accordance with progression in current capabilities towards high-resolution approaches, applying a convective-permitting resolution to global aerosol models helps comprehend how complex cloud–precipitation systems interact with aerosols. This study investigates the impacts of a double-moment bulk cloud microphysics scheme, i.e., NICAM Double-moment bulk Water 6 developed in this study (NDW6-G23), on the spatiotemporal distribution of aerosols in the Nonhydrostatic ICosahedral Atmospheric Model as part of the version-19 series (NICAM.19) with 14 km grid spacing. The mass concentrations and optical thickness of the NICAM-simulated aerosols are generally comparable to those obtained from in situ measurements. However, for some aerosol species, especially dust and sulfate, the differences between experiments of NDW6 and of the NICAM single-moment bulk module with six water categories (NSW6) were larger than those between experiments with different horizontal resolutions (14 and 56 km grid spacing), as shown in a previous study. The simulated aerosol burdens using NDW6 are generally lower than those using NSW6; the net instantaneous radiative forcing due to aerosol–radiation interaction (IRFari) is estimated to be −1.36 W m−2 (NDW6) and −1.62 W m−2 (NSW6) in the global annual mean values at the top of the atmosphere (TOA). The net effective radiative forcing due to anthropogenic aerosol–radiation interaction (ERFari) is estimated to be −0.19 W m−2 (NDW6) and −0.23 W m−2 (NSW6) in the global annual mean values at the TOA. This difference among the experiments using different cloud microphysics modules, i.e., 0.26 W m−2 or 16 % difference in IRFari values and 0.04 W m−2 or 16 % difference in ERFari values, is attributed to a different ratio of column precipitation to the sum of the column precipitation and column liquid cloud water, which strongly determines the magnitude of wet deposition in the simulated aerosols. Since the simulated ratios in the NDW6 experiment are larger than those of the NSW6 result, the scavenging effect of the simulated aerosols in the NDW6 experiment is larger than that in the NSW6 experiment. A large difference between the experiments is also found in the aerosol indirect effect (AIE), i.e., the net effective radiative forcing due to aerosol–cloud interaction (ERFaci) from the present to preindustrial days, which is estimated to be −1.28 W m−2 (NDW6) and −0.73 W m−2 (NSW6) in global annual mean values. The magnitude of the ERFaci value in the NDW6 experiment is larger than that in the NSW6 result due to the differences in both the Twomey effect and the susceptibility of the simulated cloud water to the simulated aerosols between NDW6 and NSW6. Therefore, this study shows the importance of the impacts of the cloud microphysics module on aerosol distributions through both aerosol wet deposition and the AIE.

Including the Horizontal Observation Error Correlation in the Ensemble Kalman Filter: Idealized Experiments with NICAM-LETKF

Abstract Densely observed remote sensing data such as radars and satellites generally contain significant spatial error correlations. In data assimilation, the observation error covariance matrix is usually assumed to be diagonal, and the dense data are thinned or spatially averaged to compensate for neglecting the spatial observation error correlation. However, in theory, including the spatial observation error correlation in data assimilation can make better use of the dense data. This study performs perfect model observing system simulation experiments (OSSEs) using the nonhydrostatic icosahedral atmospheric model (NICAM) and the local ensemble transform Kalman filter (LETKF) to assess the impact of assimilating horizontally dense and error-correlated observations. The condition number of the observation error covariance matrix, defined as the ratio of the largest to smallest eigenvalues, is important for the numerical stability of the LETKF computation. A large condition number makes it difficult to compute the ensemble transform matrix correctly. Reducing the condition number by reconditioning is found effective for stable computation. The results show that including the horizontal observation error correlation with reconditioning makes the analysis more accurate but requires 6 times more computations than the case with the diagonal observation error covariance matrix. Significance Statement It is important to effectively utilize observations in data assimilation for more accurate weather prediction. Spatially dense observations are known to have an error correlation that is ignored in the data assimilation. This study explores assimilating dense observations by explicitly including observation error correlations with an idealized experiment. The results shows that the analysis is improved by including the observation error correlations. Also, the condition number of the observation error covariance matrix is essential for stable computations.

Comparative study of strongly and weakly coupled data assimilation with a global land–atmosphere coupled model

Abstract. This study explores coupled land–atmosphere data assimilation (DA) for improving weather and hydrological forecasts by assimilating soil moisture (SM) data. This study integrates a land DA component into a global atmospheric DA system of the Nonhydrostatic ICosahedral Atmospheric Model and the local ensemble transform Kalman filter (NICAM-LETKF) and performs both strongly and weakly coupled land–atmosphere DA experiments. We explore various types of coupled DA experiments by assimilating atmospheric observations and SM data simultaneously. The results show that analyzing atmospheric variables by assimilating SM data improves the SM analysis and forecasts and mitigates a warm bias in the lower troposphere where a dry SM bias exists. On the other hand, updating SM by assimilating atmospheric observations has detrimental impacts due to spurious error correlations between the atmospheric observations and land model variables. We also find that assimilating SM by strongly coupled DA is beneficial in the Sahel and equatorial Africa from May to October. These regions are characterized by seasonal variations in the precipitation patterns and benefit from updates in the atmospheric variables through SM DA during periods of increased precipitation. Additionally, these regions coincide with those identified in the previous studies, where a global initialization of SM would enhance the prediction skill of seasonal precipitation.

Ensemble‐Based Data Assimilation of GPM DPR Reflectivity: Cloud Microphysics Parameter Estimation With the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)

AbstractDirect assimilation of Dual‐frequency Precipitation Radar (DPR) data of the Global Precipitation Measurement (GPM) core satellite is challenging mainly due to its long revisiting intervals relative to the time scale of precipitation, and precipitation location errors. This study explores a method for improving precipitation forecasts using GPM DPR through model parameter estimation. We developed a 28 km mesh global atmospheric data assimilation system that integrates the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) and Local Ensemble Transform Kalman Filter (LETKF) coupled with a satellite radar simulator. Using the NICAM‐LETKF and GPM DPR observations, this study estimates a model cloud physics parameter corresponding to snowfall terminal velocity. To overcome the difficulties of long revisiting intervals and precipitation location errors, we propose a parameter estimation method based on a two‐dimensional histogram known as the contoured frequency by temperature diagram (CFTD). Parameter estimation effectively mitigated the gap between simulated and observed CFTD, resulting in improved 6 hr precipitation forecasts.

Improvements of the Double-Moment Bulk Cloud Microphysics Scheme in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM)

Abstract This study revises the collisional growth, heterogeneous ice nucleation, and homogeneous ice nucleation processes in a double-moment bulk cloud microphysics scheme implemented in the Nonhydrostatic Icosahedral Atmospheric Model (NICAM). The revised cloud microphysical processes are tested by 10-day global simulations with a horizontal resolution of 14 km. It is found that both the aggregation of cloud ice with smaller diameters and the graupel production by riming are overestimated in the current schemes. A new method that numerically integrates the collection kernel solves this issue, and consequently, the lifetime of cloud ice is reasonably extended in reference to satellite observations. In addition, the results indicate that a reduction in graupel modulates the convective intensity, particularly in intense rainfall systems. The revision of both heterogeneous and homogeneous ice nucleation significantly increases the production rate of cloud ice number concentration. With these revisions, the new version of the cloud microphysics scheme successfully improves outgoing longwave radiation, particularly over the intertropical convergence zone, in reference to satellite observations. Therefore, the revisions are beneficial for both long-term climate simulations and representing the structure of severe storms. Significance Statement Very high-resolution global atmospheric models have been developed to simultaneously address global climate and regional weather. In general, cloud microphysics schemes used in such global models are introduced from regional weather forecasting models to realistically represent mesoscale cloud systems. However, a cloud microphysics scheme that was originally developed with the aim of weather forecasting can cause unexpected errors in global climate simulations because such a cloud microphysics scheme is not designed for interdisciplinary usage across spatiotemporal scales. This study focuses on systematic model biases in evaluating the terminal velocity of ice cloud particles and proposes a method to accurately calculate the growth rate of ice cloud particles. Improvements in ice cloud modeling successfully reduce model biases in the global energy budget. In addition, the internal structure of intense rainfall systems is modified using the new cloud model. Therefore, improvements in ice cloud modeling could further increase the reliability of weather forecasting, seasonal prediction, and climate projection.

Climate of High-obliquity Exoterrestrial Planets with a Three-dimensional Cloud System Resolving Climate Model

Planetary climates are strongly affected by planetary orbital parameters such as obliquity, eccentricity, and precession. In exoplanetary systems, exoterrestrial planets should have various obliquities. High-obliquity planets would have extreme seasonal cycles due to the seasonal change of the distribution of the insolation. Here, we introduce the Non-hydrostatic ICosahedral Atmospheric Model (NICAM), a global cloud-resolving model, to investigate the climate of high-obliquity planets. This model can explicitly simulate a three-dimensional cloud distribution and vertical transports of water vapor. We simulated exoterrestrial climates with high resolution using the supercomputer FUGAKU. We assumed aqua-planet configurations with 1 bar of air as a background atmosphere, with four different obliquities (0°, 23.5°, 45°, and 60°). We ran two sets of simulations: (1) low resolution (∼220 km mesh as the standard resolution of a general circulation model for exoplanetary science) with parameterization for cloud formation, and (2) high resolution (∼14 km mesh) with an explicit cloud microphysics scheme. Results suggest that high-resolution simulations with an explicit treatment of cloud microphysics reveal warmer climates due to less low cloud fraction and a large amount of water vapor in the atmosphere. It implies that treatments of cloud-related processes lead to a difference between different resolutions in climatic regimes in cases with high obliquities.

Evaluation of cloud and precipitation processes in regional and global models with ULTIMATE (ULTra-sIte for Measuring Atmosphere of Tokyo metropolitan Environment): a case study using the dual-polarization Doppler weather radars

We describe a collaborative analysis study involving numerical models and observation data for the Tokyo metropolitan area called the ULTra-sIte for Measuring Atmosphere of Tokyo Metropolitan Environment (ULTIMATE) project. It evaluates cloud microphysics schemes of numerical models using extensive observation data for the Tokyo area. We have access to various remote sensing and in situ data for the Tokyo area for operational and research purposes, particularly by enhancing observations for ground validation of the EarthCARE satellite, which is set to launch in 2023. This study focuses on using the dual-polarization Doppler weather radar, operated by the Japan Meteorological Agency. In terms of numerical models, we use and compare multi-models with single-moment (SM) and double-moment (DM) cloud microphysics schemes; the global non-hydrostatic model, Non-hydrostatic ICosahedral Atmospheric Model (NICAM) and the two regional models with A System based on a Unified Concept for Atmosphere (ASUCA) and Scalable Computing for Advanced Library and Environment (SCALE) are used. In particular, because NICAM can be used as both a global and a regional model, we can immediately test the improved scheme on a global scale for its effect on climatology and the evaluation of climate sensitivity. This paper introduces the methodology for evaluating numerical models by the dual-polarization radar using the observation simulator and compares numerical model results with observations. In particular, we evaluate the simulated rain in the lower level near the ground and the large ice particles just above the melting level. The simulation with NICAM-DM reproduces the comparable polarimetric radar characteristics of rain as the observation. However, the simulations with NICAM-SM and ASUCA-SM show larger raindrop sizes in stronger rain areas compared to the observation. For the larger ice particles just above the melting level around 4 km, NICAM-DM and ASUCA-SM overestimate particle sizes of graupel or snow, while NICAM-SM has a similar size of the ice particles. In future studies, we will use the present results to improve the cloud microphysics scheme, which will be tested on a global model.

Deceleration of Madden–Julian Oscillation Speed in NICAM AMIP‐Type Simulation Associated With Biases in the Walker Circulation Strength

AbstractThe eastward movement speed of Madden–Julian Oscillation (MJO) events simulated in a 30‐year simulation on a global cloud resolving model, nonhydrostatic icosahedral atmospheric model, following the atmospheric model intercomparison project protocol with a slab ocean was analyzed and compared with the observation. The simulation reproduced the observed tendency of the MJO to decelerate when it is embedded within the stronger Walker circulation, intensified by background sea surface temperature states with larger zonal gradients between the warmer western Pacific and the cooler Indian Ocean and eastern Pacific. However, the simulated MJO events occurred disproportionately during El Niño events and displayed a slow bias. These biases were associated with an overestimation of the western Walker circulation cell strength, which was partially counteracted during El Niño events. Our results highlight the importance of accurately reproducing the mean atmospheric circulation for the realistic reproduction of the MJO in long term simulations.

Mesoscale Convective Systems Simulated by a High‐Resolution Global Nonhydrostatic Model Over the United States and China

AbstractMesoscale convective systems (MCSs) contribute a large fraction of warm‐season precipitation and generate hazardous weather with substantial socioeconomic impacts. Uncertainties in convection parameterizations in climate models limit our understanding of MCS characteristics and reliability of future projection. We examine MCSs simulated by the global 14 km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) without cumulus parameterization against satellite observation from Global Precipitation Measurement during 2001–2008. We focus on MCSs over the central United States and eastern China where MCSs are prevalent from March to August. A process‐oriented tracking method incorporating both cloud and precipitation criteria is used to identify and track MCSs. About 140/100 MCSs initiate in the central United States/eastern China per warm season and most of them initiate in the east of high mountains and in coastal regions. The frequency distribution of MCS lifetime is well captured by NICAM. However, the simulated MCSs have stronger precipitation, smaller precipitation area, and larger cold cloud system than that observed in both regions, which may be caused by weak entrainment as it is not well resolved at 14 km resolution. The simulated MCS number is also underestimated in summer. By examining the climatological and MCS large‐scale environments, the significant underestimation of MCS number in summer over the central United States may be attributed to the large climatological dry bias in the atmosphere. For China, mean moisture in summer is well simulated but deficiency in capturing the dynamic condition related to the coastal topography for triggering convection may have contributed to underestimation of MCS even in a sufficiently moist environment.

Uncertainty in Aerosol Rainout Processes through the Case of the Radioactive Materials Emitted by the Fukushima Dai-ichi Nuclear Power Plant in March 2011

The process of an aerosol rainout in wet deposition induces large uncertainties among atmospheric aerosol simulations, especially for particles in the fine mode. In this study, we performed an intercomparison study of four different rainout schemes on the model (the nonhydrostatic icosahedral atmospheric model or NICAM) to simulate particulate Cs-137 in the emission scenario of the March 2011 accident at the Fukushima Dai-ichi Nuclear Power Plant. The schemes include global climate models (GCMs) approach with a simple tuning parameter to determine the scavenging coefficient, and another optimized for cloud resolving models (CRMs) to account for prognostic precipitation and realistic vertical transport. The third approach was the conventional method under the assumption of a pseudo-first-order approximation based on the surface precipitation flux. The fourth approach was involved in offline chemical transport models (CTMs) with a simplified parametric analysis approach to clouds and precipitation flux. In most experiments, statistical metrics of the Cs-137 concentrations using in-situ measurements were calculated to be within ±30 % (bias), 0.6–0.9 (correlation), 67–112 Bq m−3 (uncertainty), and < 40 % (precision within a factor of 10). The CRM-type method yielded the best results but required a lower limit of tuning parameters to compensate for the results. Both the GCM-type and the conventional methods were also useful by setting proper tuning parameters. The CTM-type yielded better correlation and lower uncertainty but larger negative bias. These analyses suggest the overestimation of the conversion rate from cloud droplets into raindrops by the NICAM. However, this cannot be resolved by simply interchanging cloud microphysics schemes. It was found that the sensitivity of the rainout scheme has a stronger influence on the Cs-137 concentration than the different treatments of cloud microphysics. Thus, to replicate the observed Cs-137 distribution, it is essential to have a better meteorological field as well as a proper rainout scheme.

Response of convective systems to the orbital forcing of the last interglacial in a global nonhydrostatic atmospheric model with and without a convective parameterization

Nonhydrostatic Icosahedral Atmospheric Model (NICAM) coupled with a slab ocean model was applied to a paleoclimate research for the first time. The model was run at a horizontal resolution of 56 km with and without a convective parameterization, given the orbital parameters of the last interglacial (127,000 years before present). The simulated climatological mean-states are qualitatively similar to those in previous studies reinforcing their robustness, however, the resolution of this model enables to represent the narrow precipitation band along the southern edge of the Tibetan Plateau. A particular focus was given to convectively coupled disturbances in our analysis. The simulated results show a greater signal of the Madden–Julian Oscillation and weakening of the moist Kelvin waves. Although the model's representation of the boreal summer intraseasonal oscillation in the present-day simulations is not satisfactory, a significant enhancement of its signal is found in the counterpart of the last interglacial. The density of the tropical cyclones decreases over the western north Pacific, north Atlantic and increases over the south Indian Ocean and south Atlantic. The model's performance is generally better when the convective parameterization is used, but the tropical cyclones are better represented without the convective parameterization. Additional simulations using the low-resolution topography reveals that the better representation of the Tibetan Plateau enhances the boreal summer Asian monsoon and its impact is similar and comparable to that of the orbital parameters over the south Asia and the Indian Ocean.

Enhanced Simulation of an Asian Dust Storm by Assimilating GCOM-C Observations

Dust aerosols have great effects on global and regional climate systems. The Global Change Observation Mission-Climate (GCOM-C), also known as SHIKISAI, which was launched on 23 December 2017 by the Japan Aerospace Exploration Agency (JAXA), is a next-generation Earth observation satellite that is used for climate studies. The Second-Generation Global Imager (SGLI) aboard GCOM-C enables the retrieval of more precious global aerosols. Here, the first assimilation study of the aerosol optical thicknesses (AOTs) at 500 nm observed by this new satellite is performed to investigate a severe dust storm in spring over East Asia during 28–31 March 2018. The aerosol observation assimilation system is an integration of the four-dimensional local ensemble transform Kalman filter (4D-LETKF) and the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) coupled with the Non-Hydrostatic Icosahedral Atmospheric Model (NICAM). Through verification with the independent observations from the Aerosol Robotic Network (AERONET) and the Asian Dust and Aerosol Lidar Observation Network (AD-Net), the results demonstrate that the assimilation of the GCOM-C aerosol observations can significantly enhance Asian dust storm simulations. The dust characteristics over the regions without GCOM-C observations are better revealed from assimilating the adjacent observations within the localization length, suggesting the importance of the technical advances in observation and assimilation, which are helpful in clarifying the temporal–spatial structure of Asian dust and which could also improve the forecasting of dust storms, climate prediction models, and aerosol reanalysis.

The Nonhydrostatic ICosahedral Atmospheric Model for CMIP6 HighResMIP simulations (NICAM16-S): experimental design, model description, and impacts of model updates

Abstract. The Nonhydrostatic ICosahedral Atmospheric Model (NICAM), a global model with an icosahedral grid system, has been under development for nearly two decades. This paper describes NICAM16-S, the latest stable version of NICAM (NICAM.16), modified for the Coupled Model Intercomparison Project Phase 6, High Resolution Model Intercomparison Project (HighResMIP). Major updates of NICAM.12, a previous version used for climate simulations, included updates of the cloud microphysics scheme and land surface model, introduction of natural and anthropogenic aerosols and a subgrid-scale orographic gravity wave drag scheme, and improvement of the coupling between the cloud microphysics and the radiation schemes. External forcings were updated to follow the protocol of the HighResMIP. A series of short-term sensitivity experiments were performed to determine and understand the impacts of these various model updates on the simulated mean states. The NICAM16-S simulations demonstrated improvements in the ice water content, high cloud amount, surface air temperature over the Arctic region, location and strength of zonal mean subtropical jet, and shortwave radiation over Africa and South Asia. Some long-standing biases, such as the double intertropical convergence zone and smaller low cloud amount, still exist or are even worse in some cases, suggesting further necessity for understanding their mechanisms, upgrading schemes and parameter settings, and enhancing horizontal and vertical resolutions.

Precipitation Characteristics and Future Changes Over the Southern Slope of Tibetan Plateau Simulated by a High‐Resolution Global Nonhydrostatic Model

AbstractCurrent climate model resolution cannot accurately describe the complex topography over the Tibetan Plateau, which limits our understanding of past and future precipitation over this region. This study investigates the daily precipitation characteristics and its future changes over the Tibetan Plateau, especially for the southern slope of Tibetan Plateau (SSTP), by 14‐km Nonhydrostatic ICosahedral Atmospheric Model (NICAM) with explicitly calculated convection for historical and future 30‐years period. By comparing with the satellite Global Precipitation Measurement (GPM), NICAM well reproduces the historical precipitation spatial pattern, seasonal cycle, and the extreme precipitation belt over SSTP, but overestimates precipitation amount by ∼35%. It is found that heavy precipitation probability decreases as elevation becomes higher while the light precipitation generally shows the opposite. For the precipitation changes during June to September from 1979–2008 to 2075–2104, NICAM predicts that mean precipitation will decrease over low‐level SSTP but increase over high‐level SSTP. Nonprecipitation and heavy precipitation probability will increase while light precipitation probability will decrease in the future over SSTP. The extreme precipitation probability and intensity will increase ∼50%/°C and ∼8%/°C over SSTP, and this increase is more obvious as elevation becomes higher. The robust increase of extreme precipitation along the SSTP topography is unique and has not been identified by the climate model simulations before. The strong meridional gradient of specific humidity over SSTP is found to be further enhanced under global warming, and this gradient enhancement is suggested to be responsible for the increase in the extreme precipitation over SSTP.

Cloud Assumption of Precipitation Retrieval Algorithms for the Dual-Frequency Precipitation Radar

AbstractAn assumption related to clouds is one of uncertain factors in precipitation retrievals by the Dual-Frequency Precipitation Radar (DPR) on board the Global Precipitation Measurement (GPM) Core Observatory. While an attenuation due to cloud ice is negligibly small for Ku and Ka bands, attenuation by cloud liquid water is larger in the Ka band and estimating precipitation intensity with high accuracy from Ka-band observations can require developing a method to estimate the attenuation due to cloud liquid water content (CLWC). This paper describes a CLWC database used in the DPR level-2 algorithm for the GPM V06A product. In the algorithm, the CLWC value is assumed using the database with inputs of precipitation-related variables, temperature, and geolocation information. A calculation of the database was made using the 3.5-km-mesh global atmospheric simulation derived from the Nonhydrostatic Icosahedral Atmospheric Model (NICAM) global cloud-system-resolving model. Impacts of current CLWC assumptions for surface precipitation estimates were evaluated by comparisons of precipitation retrieval results between default values and 0 mg m−3 of the CLWC. The impacts were quantified by the normalized mean absolute difference (NMAD) and the NMAD values showed 2.3% for the Ku, 9.9% for the Ka, and 6.5% for the dual-frequency algorithms in global averages, while they were larger in the tropics than in high latitudes. Effects of the precipitation estimates from the CLWC assumption were examined further in terms of retrieval processes affected by the CLWC assumption. This study emphasizes the CLWC assumption provided more effects on the precipitation estimates through estimating path-integrated attenuation due to rain.

Improvements in Supercooled Liquid Water Simulations of Low-Level Mixed-Phase Clouds over the Southern Ocean Using a Single-Column Model

AbstractA high-resolution global atmospheric model, the nonhydrostatic icosahedral atmospheric model (NICAM), exhibited underestimation biases in low-level mixed-phase clouds in the midlatitudes and polar regions. The ice-cloud microphysics used in a single-moment bulk cloud microphysics scheme (NSW6) was evaluated and improved using a single-column model by reference to a double-moment bulk cloud microphysics scheme (NDW6). Budget analysis indicated that excessive action of the Bergeron–Findeisen and riming processes crucially reduced supercooled liquid water. In addition, the rapid production of rain directly reduced cloud water and indirectly reduced cloud water through the production of snow and graupel by riming. These biases in growth rates were found to originate from the number concentration diagnosis used in NSW6. The diagnosis based on the midlatitude cloud systems assumption was completely different from the one for low-level mixed-phase clouds. To alleviate underestimation biases, rain production, heterogeneous ice nucleation, vapor deposition by snow and graupel, and riming processes were revised. The sequential revisions of cloud microphysics alleviated the underestimation biases step by step without parameter tuning. The lifetime of cloud layers simulated by NSW6 was reasonably prolonged.

Comparison and evaluation of the simulated annual aerosol characteristics over China with two global aerosol models

In this study, simulations of the annual mean aerosol budget, aerosol optical properties, and surface mass concentration in 2006 in China are performed with two aerosol interactive global atmosphere models, namely, the Nonhydrostatic ICosahedral Atmospheric Model (NICAM) coupled with the Spectral Radiation Transport Model for Aerosol Species (SPRINTARS) and the Beijing Climate Center Atmospheric General Circulation Model (BCC_AGCM) coupled with the Canadian Aerosol Module (CAM) online. The observed and simulated aerosol optical depths (AODs) exhibit similar horizontal distributions with large values over eastern and central China, and sulfate aerosols contribute the main differences between the AODs simulated by NICAM and BCC_AGCM. The simulated sulfate and dust surface concentrations are more consistent with observations compared with the simulated carbonaceous surface concentrations, and both models can reproduce the decreasing tendency of the sulfate surface concentration from urban sites to rural sites. However, the dust emission and deposition levels in China simulated by BCC_AGCM are three times as high as those simulated by NICAM, and the major sink processes of the anthropogenic sulfate, black carbon (BC), and organic carbon (OC) aerosols over China are very different between the two models. The emission and deposition results, which are closely related to the model-assumed aerosol particle size distribution, indicate that the current aerosol size distribution used in the two models should be further improved. The differences in dust emission parameterizations also lead significant discrepancies in aerosol cycles and the dust emission scheme is an important factor determining the magnitudes of global and regional dust emission fluxes.

Response of the Asian Summer Monsoon Precipitation to Global Warming in a High-Resolution Global Nonhydrostatic Model

AbstractThis study examined the responses of Asian monsoon precipitation to global warming on the regional scale, focusing on monsoon westerlies and monsoon trough. This is because the Asian monsoon precipitation is closely associated with tropical disturbances. To reproduce convective precipitation and tropical disturbances, this study used outputs of a high-resolution climate simulation. Two sets of approximately 30-yr simulations under present-day (control) and warmer climate conditions (global warming) were conducted by the 14-km Nonhydrostatic Icosahedral Atmospheric Model (NICAM) with explicitly calculated convection. For understanding the spatial pattern of future precipitation changes, a further set of a 5-yr simulation [sea surface temperature (SST) + 4 K] was also conducted. Overall, the Asian summer monsoon was well simulated by the model. Precipitation increased as a result of global warming along the monsoon trough, which was zonally elongated across northern India, the Indochina Peninsula, and the western North Pacific Ocean. This increased precipitation was likely due to an increase in precipitable water. The spatial pattern of the increased precipitation was associated with enhanced cyclonic circulations over a large area along the monsoon trough, although it was difficult to determine whether the large-scale monsoon westerly was enhanced. This enhancement can be explained by future changes in tropical disturbance activity, including weak tropical cyclones. However, over part of South Asia, circulation changes may not contribute to the increased precipitation, suggesting regional characteristics. The regional increase in precipitation along the monsoon trough was mostly explained by the uniform increase in SST, whereas SST spatial patterns are important over some regions.