Jui-n Li

A Multiscale Modeling System: Developments, Applications, and Critical Issues

A multiscale modeling framework (MMF), which replaces the conventional cloud parameterizations with a cloud-resolving model (CRM) in each grid column of a GCM, constitutes a new and promising approach for climate modeling. The MMF can provide for global coverage and two-way interactions between the CRMs and their parent GCM. The CRM allows for explicit simulation of cloud processes and their interactions with radiation and surface processes, and the GCM allows for global coverage. A new MMF has been developed that is based on the NASA Goddard Space Flight Center (GSFC) finite-volume GCM (fvGCM) and the Goddard Cumulus Ensemble (GCE) model. This Goddard MMF produces many features that are similar to another MMF that was developed at Colorado State University (CSU), such as an improved surface precipitation pattern, better cloudiness, improved diurnal variability over both oceans and continents, and a stronger propagating Madden-Julian oscillation (MJO) compared to their parent GCMs using traditional cloud ...

Tropical and subtropical cloud transitions in weather and climate prediction models: the GCSS/WGNE Pacific cross-section intercomparison (GPCI)

AbstractA model evaluation approach is proposed in which weather and climate prediction models are analyzed along a Pacific Ocean cross section, from the stratocumulus regions off the coast of California, across the shallow convection dominated trade winds, to the deep convection regions of the ITCZ—the Global Energy and Water Cycle Experiment Cloud System Study/Working Group on Numerical Experimentation (GCSS/WGNE) Pacific Cross-Section Intercomparison (GPCI). The main goal of GPCI is to evaluate and help understand and improve the representation of tropical and subtropical cloud processes in weather and climate prediction models. In this paper, a detailed analysis of cloud regime transitions along the cross section from the subtropics to the tropics for the season June–July–August of 1998 is presented. This GPCI study confirms many of the typical weather and climate prediction model problems in the representation of clouds: underestimation of clouds in the stratocumulus regime by most models with the co...

The Maintenance of the Relative Humidity of the Subtropical Free Troposphere

The relative importance of different processes in the water vapor balance of the troposphere is assessed, using high-resolution hindcast data from the ECMWF Integrated Forecast System (IFS) for December‐ February 1998/99 interpolated to isentropic coordinates. The focus is on elucidating the processes that maintain the relative humidity of the subtropical free troposphere. The dominant drying process in the subtropical free troposphere is cross-isentropic subsidence driven by radiative cooling. In some subtropical regions [e.g., over continents in the Southern (summer) Hemisphere and over western portions of ocean basins in the Northern (winter) Hemisphere], drying by radiative subsidence is partially offset or overcompensated by moistening by cross-isentropic dynamic transport of water vapor from the surface upward (e.g., in convection). Any resultant net drying or moistening of the subtropical free troposphere by crossisentropic motions is regionally primarily balanced by isentropic mean and eddy transport of water vapor from moister into drier regions. Isentropic transport redistributes water vapor within the subtropics and moderates relative humidity contrasts; however, it does not consistently lead to a substantial net import or export of water vapor into or out of the subtropics.

Vertical Heating Structures Associated with the MJO as Characterized by TRMM Estimates, ECMWF Reanalyses and Forecasts: A Case Study during 1998-99 Winter

The Madden–Julian oscillation (MJO) is a fundamental mode of the tropical atmosphere variability that exerts significant influence on global climate and weather systems. Current global circulation models, unfortunately, are incapable of robustly representing this form of variability. Meanwhile, a well-accepted and comprehensive theory for the MJO is still elusive. To help address this challenge, recent emphasis has been placed on characterizing the vertical structures of the MJO. In this study, the authors analyze vertical heating structures by utilizing recently updated heating estimates based on the Tropical Rainfall Measuring Mission (TRMM) from two different latent heating estimates and one radiative heating estimate. Heating structures from two different versions of the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalyses/forecasts are also examined. Because of the limited period of available datasets at the time of this study, the authors focus on the winter season from October 1998 to March 1999. The results suggest that diabatic heating associated with the MJO convection in the ECMWF outputs exhibits much stronger amplitude and deeper structures than that in the TRMM estimates over the equatorial eastern Indian Ocean and western Pacific. Further analysis illustrates that this difference might be due to stronger convective and weaker stratiform components in the ECMWF estimates relative to the TRMM estimates, with the latter suggesting a comparable contribution by the stratiform and convective counterparts in contributing to the total rain rate. Based on the TRMM estimates, it is also illustrated that the stratiform fraction of total rain rate varies with the evolution of the MJO. Stratiform rain ratio over the Indian Ocean is found to be 5% above (below) average for the disturbed (suppressed) phase of the MJO. The results are discussed with respect to whether these heating estimates provide enough convergent information to have implications on theories of the MJO and whether they can help validate global weather and climate models.

Cloud-precipitation-radiation-dynamics interaction in global climate models: A snow and radiation interaction sensitivity experiment

Conventional global climate models (GCMs) often consider radiation interactions only with small-particle/suspended cloud mass, ignoring large-particle/falling and convective core cloud mass. We characterize the radiation and atmospheric circulation impacts of frozen precipitating hydrometeors (i.e., snow), using the National Center for Atmospheric Research coupled GCM, by conducting sensitivity experiments that turn off the radiation interaction with snow. The changes associated with the exclusion of precipitating hydrometeors exhibit a number differences consistent with biases in CMIP3 and CMIP5 (Coupled Model Intercomparison Project Phase 3 and Phase 5), including more outgoing longwave flux at the top of atmosphere and downward shortwave flux at the surface in the heavily precipitating regions. Neglecting the radiation interaction of snow increases the net radiative cooling near the cloud top with the resulting increased instability triggering more convection in the heavily precipitating regions of the tropics. In addition, the increased differential vertical heating leads to a weakening of the low-level mean flow and an apparent low-level eastward advection from the warm pool resulting in moisture convergence south of the Intertropical Convergence Zone and north of the South Pacific Convergence Zone (SPCZ). This westerly bias, with effective warm and moist air transport, might be a contributing factor in the models northeastward overextension of the SPCZ and the concomitant changes in sea surface temperatures, upward motion, and precipitation. Broader dynamical impacts include a stronger local meridional overturning circulation over the middle and east Pacific and commensurate changes in low and upper level winds, large-scale ascending motion, with a notable similarity to the systematic bias in this region in CMIP5 upper level zonal winds.

The impacts of cloud snow radiative effects on Pacific Ocean surface heat fluxes, surface wind stress, and ocean temperatures in coupled GCM simulations

An accurate representation of the climatology of the coupled ocean-atmosphere system in global climate models has strong implications for the reliability of projected climate change inferred by these models. Our previous efforts have identified substantial biases of ocean surface wind stress that are fairly common in two generations of the Coupled Model Intercomparison Project (CMIP) models, relative to QuikSCAT climatology. One of the potential causes of the CMIP model biases is the missing representation of large frozen precipitating hydrometeors (i.e., cloud snow) in all CMIP3 and most CMIP5 models, which has not been investigated previously. We examine the impacts of cloud snow on the radiation and atmospheric circulation, air-sea fluxes, and explore the implications to common biases in CMIP models using the National Center for Atmospheric Research coupled Community Earth System Model (CESM) to perform sensitivity experiments with and without cloud snow radiative effects. This study focuses on the impacts of cloud snow in CESM on ocean surface wind stress and air-sea heat fluxes, as well as their relationship with sea surface temperature (SST) and subsurface ocean temperatures in the Pacific sector. It is found that inclusion of the cloud snow parameterization in CESM reduces the surface wind stress and upper ocean temperature (including SST) biases in the tropical and midlatitude Pacific. The differences in the upper ocean temperature with and without the cloud snow parameterization are consistent with the effect of different strength of vertical mixing due to ocean surface wind stress differences but cannot be explained by the differences in net air-sea heat fluxes.

Characterizing Arctic mixed‐phase cloud structure and its relationship with humidity and temperature inversion using ARM NSA observations

In this study, the characteristics of the Arctic mixed-phase cloud (AMC) have been investigated using data collected at the Atmospheric Radiation Measurement North Slope Alaska site from October 2006 to September 2009. AMC has an annual occurrence frequency of 42.3%, which includes 18.7% of single-layered AMCs and 23.6% for multiple layers. Two cloud base heights (CBHs) are defined from ceilometer and micropulse lidar (MPL) measurements. For single-layered AMC, the ceilometer-derived CBH represents the base of the liquid-dominant layer near the cloud top, while MPL-derived CBH represents base of the lower ice-dominant layer. The annual mean CBHs from ceilometer and MPL measurements are 1.0 km and 0.6 km, respectively, with the largest difference (~1.0 km) occurring from December to March and the smallest difference in September. The humidity inversion occurrence decreases with increasing humidity inversion intensity (stronger in summer than in winter). During the winter months, AMC occurrences increase from 15% to 35% when the inversion intensity increases from 0.1 to 0.9 g/kg. On the contrary, despite a higher frequency of strong humidity inversion in summer, AMC occurrences are nearly invariant for different inversion intensities. On average, humidity and temperature inversion frequencies of occurrence above an AMC are 5 and 8 times, respectively, as high as those below an AMC. The strong inversion occurrences for both humidity and temperature above an AMC provide the moisture sources from above for the formation and maintenance of AMCs. This result helps to reconcile the persistency of AMCs even when the Arctic surface is covered by snow and ice.

Characterizing tropical Pacific water vapor and radiative biases in CMIP5 GCMs: Observation‐based analyses and a snow and radiation interaction sensitivity experiment

Significant systematic biases in the moisture fields within the tropical Pacific trade wind regions are found in the Coupled Model Intercomparison Project (CMIP3/CMIP5) against profile and total column water vapor (TotWV) estimates from the Atmospheric Infrared Sounder and TotWV from the Special Sensor Microwave/Imager. Positive moisture biases occur in conjunction with significant biases of eastward low-level moisture convergence north of the South Pacific Convergence Zone and south of the Intertropical Convergence Zone—the V-shaped regions. The excessive moisture there is associated with overestimates of reflected upward shortwave (RSUT), underestimates of outgoing longwave radiation (RLUT) at the top of atmosphere (TOA), and underestimates of downward shortwave flux at the surface (RSDS) compared to Clouds and the Earths Energy System, Energy Balance and Filled data. We characterize the impacts of falling snow and its radiation interaction, which are not included in most CMIP5 models, on the moisture fields using the National Center for Atmospheric Research-coupled global climate model (GCM). A number of differences in the model simulation without snow-radiation interactions are consistent with biases in the CMIP5 simulations. These include effective low-level eastward/southeastward wind and surface wind stress anomalies, and an increase in TotWV, vertical profile of moisture, and cloud amounts in the V-shaped region. The anomalous water vapor and cloud amount might be associated with the model increase of RSUT and decrease of RLUT at TOA and decreased RSDS in clear and all sky in these regions. These findings hint at the importance of water vapor-radiation interactions in the CMIPS/CMIP5 model simulations that exclude the radiative effect of snow.

Performance of the Goddard Multiscale Modeling Framework with Goddard Ice Microphysical Schemes

The multiscale modeling framework (MMF), which replaces traditional cloud parameterizations with cloud-resolving models (CRMs) within a host atmospheric general circulation model (GCM), has become a new approach for climate modeling. The embedded CRMs make it possible to apply CRM-based cloud microphysics directly within a GCM. However, most such schemes have never been tested in a global environment for long-term climate simulation. The benefits of using an MMF to evaluate rigorously and improve microphysics schemes are here demonstrated. Four one-moment microphysical schemes are implemented into the Goddard MMF and their results validated against three CloudSat/CALIPSO cloud ice products and other satellite data. The new four-class (cloud ice, snow, graupel, and frozen drops/hail) ice scheme produces a better overall spatial distribution of cloud ice amount, total cloud fractions, net radiation, and total cloud radiative forcing than earlier three-class ice schemes, with biases within the observational uncertainties. Sensitivity experiments are conducted to examine the impact of recently upgraded microphysical processes on global hydrometeor distributions. Five processes dominate the global distributions of cloud ice and snow amount in long-term simulations: (1) allowing for ice supersaturation in the saturation adjustment, (2) three additional correction terms in the depositional growth of cloud ice to snow, (3) accounting for cloud ice fall speeds, (4) limiting cloud ice particle size, and (5) new size-mapping schemes for snow and graupel. Despite the cloud microphysics improvements, systematic errors associated with subgrid processes, cyclic lateral boundaries in the embedded CRMs, and momentum transport remain and will require future improvement.

The Impacts of Precipitating Hydrometeors Radiative Effects on Land Surface Temperature in Contemporary GCMs using Satellite Observations

An accurate representation of the land surface temperature (LST) climatology of the coupled land-atmosphere system has strong implications for the reliability of projected land surface processes and their variability inferred by the global climate models (GCMs) contributed to the Intergovernmental Panel on Climate Change CMIP5. We have identified a substantial underestimation of the total ice water path and biases of surface radiation budget commonly seen in the CMIP models which are highly correlated to the biases of LST over land. One of the potential causes of the CMIP model biases is the missing representation of large frozen precipitating hydrometeors and their radiative effects (i.e., snow) in all CMIP3 and most CMIP5 models. We examine the impacts of snow on the radiation, all-sky and clear-sky LST, and air-land heat fluxes to explore the implications to the common biases in CMIP models by performing sensitivity experiments with and without snow radiation effects using the National Center for Atmospheric Research Community Earth System Model version 1. It is found that an exclusion of the snow radiative effects the CESM1 generates the LST biases (up to 2–3 K) in the midlatitude and high latitude, in particular, in December, January, and February (DJF). All-sky and clear-sky LST in model simulations are found to be too cold and are mainly due to underestimated downward surface (longwave) LW radiation in DJF, which is consistent with those in CMIP models. The correlation between the changes of the LST and downward surface LW radiation is very high both in summer and winter seasons.