Abstract

Efforts to improve the prediction accuracy of high-resolution (1–10 km) surface precipitation distribution and variability are of vital importance to local aspects of air pollution, wet deposition, and regional climate. However, precipitation biases and errors can occur at these spatial scales due to uncertainties in initial meteorological conditions and/or grid-scale cloud microphysics schemes. In particular, it is still unclear to what extent a subgrid-scale convection scheme could be modified to bring in scale awareness for improving high-resolution short-term precipitation forecasts in the WRF Model. To address these issues, the authors introduced scale-aware parameterized cloud dynamics for high-resolution forecasts by making several changes to the Kain–Fritsch (KF) convective parameterization scheme in the WRF Model. These changes include subgrid-scale cloud–radiation interactions, a dynamic adjustment time scale, impacts of cloud updraft mass fluxes on grid-scale vertical velocity, and lifting condensation level–based entrainment methodology that includes scale dependency.

A series of 48-h retrospective forecasts using a combination of three treatments of convection (KF, updated KF, and the use of no cumulus parameterization), two cloud microphysics schemes, and two types of initial condition datasets were performed over the U.S. southern Great Plains on 9- and 3-km grid spacings during the summers of 2002 and 2010. Results indicate that 1) the source of initial conditions plays a key role in high-resolution precipitation forecasting, and 2) the authors’ updated KF scheme greatly alleviates the excessive precipitation at 9-km grid spacing and improves results at 3-km grid spacing as well. Overall, the study found that the updated KF scheme incorporated into a high-resolution model does provide better forecasts for precipitation location and intensity.

Abstract

The observation and representation in general circulation models (GCMs) of cloud vertical overlap are the objects of active research due to their impacts on the earth’s radiative budget. Previous studies have found that vertically contiguous cloudy layers show a maximum overlap between layers up to several kilometers apart but tend toward a random overlap as separations increase. The decorrelation length scale that characterizes the progressive transition from maximum to random overlap changes from one location and season to another and thus may be influenced by large-scale vertical motion, wind shear, or convection. Observations from the U.S. Department of Energy Atmospheric Radiation Measurement program ground-based radars and lidars in midlatitude and tropical locations in combination with reanalysis meteorological fields are used to evaluate how dynamics and atmospheric state influence cloud overlap. For midlatitude winter months, strong synoptic-scale upward motion maintains conditions closer to maximum overlap at large separations. In the tropics, overlap becomes closer to maximum as convective stability decreases. In midlatitude subsidence and tropical convectively stable situations, where a smooth transition from maximum to random overlap is found on average, large wind shears sometimes favor minimum overlap. Precipitation periods are discarded from the analysis but, when included, maximum overlap occurs more often at large separations. The results suggest that a straightforward modification of the existing GCM mixed maximum–random overlap parameterization approach that accounts for environmental conditions can capture much of the important variability and is more realistic than approaches that are only based on an exponential decay transition from maximum to random overlap.

Abstract

Previous studies have shown that variations in extratropical cyclone activity significantly affect the frequency of extreme precipitation events over the Ohio Valley and northwestern United States. In this study, we examine the similarities and differences between the dynamics governing these events in these two regions. In the Ohio Valley, extreme precipitation events are associated with midlatitude synoptic-scale convergence northeast of cyclones and a southwestward oriented ridge near the Atlantic coast that drives strong water vapor transport from the Gulf of Mexico into the Ohio Valley. In the northwestern United States, extreme precipitation events are associated with a cyclonic and anticyclonic circulation pair aligned northwest to southeast, which together drive a long and strong moisture transport corridor from the lower latitude of the central Pacific Ocean toward the northwestern United States. Moisture budget analysis shows that moisture convergence due to dynamical convergence dominates in the Ohio Valley, whereas moisture advection dominates over the Pacific Northwest. Differences between the cases in the same region are examined by an empirical orthogonal function (EOF) analysis conducted on the vertically integrated moisture flux. Different EOFs highlight shifts in spatial location, orientation, and intensity of the moisture flux but demonstrate consistent roles of dynamics in the two regions. Composites based on these EOFs highlight the range of likely synoptic scenarios that can give rise to precipitation extremes over these two regions.

Abstract

The tropical subseasonal variability simulated by the Goddard Institute for Space Studies general circulation model, Model E2, is examined. Several versions of Model E2 were developed with changes to the convective parameterization in order to improve the simulation of the Madden–Julian oscillation (MJO). When the convective scheme is modified to have a greater fractional entrainment rate, Model E2 is able to simulate MJO-like disturbances with proper spatial and temporal scales. Increasing the rate of rain reevaporation has additional positive impacts on the simulated MJO. The improvement in MJO simulation comes at the cost of increased biases in the mean state, consistent in structure and amplitude with those found in other GCMs when tuned to have a stronger MJO. By reinitializing a relatively poor-MJO version with restart files from a relatively better-MJO version, a series of 30-day integrations is constructed to examine the impacts of the parameterization changes on the organization of tropical convection. The poor-MJO version with smaller entrainment rate has a tendency to allow convection to be activated over a broader area and to reduce the contrast between dry and wet regimes so that tropical convection becomes less organized. Besides the MJO, the number of tropical-cyclone-like vortices simulated by the model is also affected by changes in the convection scheme. The model simulates a smaller number of such storms globally with a larger entrainment rate, while the number increases significantly with a greater rain reevaporation rate.

Abstract

This study evaluates the performances of seven single-column models (SCMs) by comparing simulated cloud fraction with observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site from January 1999 to December 2001. Compared with the 3-yr mean observational cloud fraction, the ECMWF SCM underestimates cloud fraction at all levels and the GISS SCM underestimates cloud fraction at levels below 200 hPa. The two GFDL SCMs underestimate lower-to-middle level cloud fraction but overestimate upper-level cloud fraction. The three Community Atmosphere Model (CAM) SCMs overestimate upper-level cloud fraction and produce lower-level cloud fraction similar to the observations but as a result of compensating overproduction of convective cloud fraction and underproduction of stratiform cloud fraction. Besides, the CAM3 and CAM5 SCMs both overestimate midlevel cloud fraction, whereas the CAM4 SCM underestimates. The frequency and partitioning analyses show a large discrepancy among the seven SCMs: Contributions of nonstratiform processes to cloud fraction production are mainly in upper-level cloudy events over the cloud cover range 10%–80% in SCMs with prognostic cloud fraction schemes and in lower-level cloudy events over the cloud cover range 15%–50% in SCMs with diagnostic cloud fraction schemes. Further analysis reveals different relationships between cloud fraction and relative humidity (RH) in the models and observations. The underestimation of lower-level cloud fraction in most SCMs is mainly due to the larger threshold RH used in models. The overestimation of upper-level cloud fraction in the three CAM SCMs and two GFDL SCMs is primarily due to the overestimation of RH and larger mean cloud fraction of cloudy events plus more occurrences of RH around 40%–80%, respectively.

Abstract

In Part I of this study, the NASA GISS Coupled Model Intercomparison Project (CMIP5) and post-CMIP5 (herein called C5 and P5, respectively) simulated cloud properties were assessed utilizing multiple satellite observations, with a particular focus on the southern midlatitudes (SMLs). This study applies the knowledge gained from Part I of this series to evaluate the modeled TOA radiation budgets and cloud radiative effects (CREs) globally using CERES EBAF (CE) satellite observations and the impact of regional cloud properties and water vapor on the TOA radiation budgets. Comparisons revealed that the P5- and C5-simulated global means of clear-sky and all-sky outgoing longwave radiation (OLR) match well with CE observations, while biases are observed regionally. Negative biases are found in both P5- and C5-simulated clear-sky OLR. P5-simulated all-sky albedo slightly increased over the SMLs due to the increase in low-level cloud fraction from the new planetary boundary layer (PBL) scheme. Shortwave, longwave, and net CRE are quantitatively analyzed as well. Regions of strong large-scale atmospheric upwelling/downwelling motion are also defined to compare regional differences across multiple cloud and radiative variables. In general, the P5 and C5 simulations agree with the observations better over the downwelling regime than over the upwelling regime. Comparing the results herein with the cloud property comparisons presented in Part I, the modeled TOA radiation budgets and CREs agree well with the CE observations. These results, combined with results in Part I, have quantitatively estimated how much improvement is found in the P5-simulated cloud and radiative properties, particularly over the SMLs and tropics, due to the implementation of the new PBL and convection schemes.

Abstract

Although many improvements have been made in phase 5 of the Coupled Model Intercomparison Project (CMIP5), clouds remain a significant source of uncertainty in general circulation models (GCMs) because their structural and optical properties are strongly dependent upon interactions between aerosol/cloud microphysics and dynamics that are unresolved in such models. Recent changes to the planetary boundary layer (PBL) turbulence and moist convection parameterizations in the NASA GISS Model E2 atmospheric GCM (post-CMIP5, hereafter P5) have improved cloud simulations significantly compared to its CMIP5 (hereafter C5) predecessor. A study has been performed to evaluate these changes between the P5 and C5 versions of the GCM, both of which used prescribed sea surface temperatures. P5 and C5 simulated cloud fraction (CF), liquid water path (LWP), ice water path (IWP), cloud water path (CWP), precipitable water vapor (PWV), and relative humidity (RH) have been compared to multiple satellite observations including the Clouds and the Earth’s Radiant Energy System–Moderate Resolution Imaging Spectroradiometer (CERES-MODIS, hereafter CM), CloudSat–Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO; hereafter CC), Atmospheric Infrared Sounder (AIRS), and Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E). Although some improvements are observed in the P5 simulation on a global scale, large improvements have been found over the southern midlatitudes (SMLs), where correlations increased and both bias and root-mean-square error (RMSE) significantly decreased, in relation to the previous C5 simulation, when compared to observations. Changes to the PBL scheme have resulted in improved total column CFs, particularly over the SMLs where marine boundary layer (MBL) CFs have increased by nearly 20% relative to the previous C5 simulation. Globally, the P5 simulated CWPs are 25 g m⁻² lower than the previous C5 results. The P5 version of the GCM simulates PWV and RH higher than its C5 counterpart and agrees well with the AMSR-E and AIRS observations. The moister atmospheric conditions simulated by P5 are consistent with the CF comparison and provide a strong support for the increase in MBL clouds over the SMLs. Over the tropics, the P5 version of the GCM simulated total column CFs and CWPs are slightly lower than the previous C5 results, primarily as a result of the shallower tropical boundary layer in P5 relative to C5 in regions outside the marine stratocumulus decks.

Abstract

Two recent activities offer an opportunity to test general circulation model (GCM) convection and its interaction with large-scale dynamics for observed Madden–Julian oscillation (MJO) events. This study evaluates the sensitivity of the Goddard Institute for Space Studies (GISS) GCM to entrainment, rain evaporation, downdrafts, and cold pools. Single Column Model versions that restrict weakly entraining convection produce the most realistic dependence of convection depth on column water vapor (CWV) during the Atmospheric Radiation Measurement MJO Investigation Experiment at Gan Island. Differences among models are primarily at intermediate CWV where the transition from shallow to deeper convection occurs. GCM 20-day hindcasts during the Year of Tropical Convection that best capture the shallow–deep transition also produce strong MJOs, with significant predictability compared to Tropical Rainfall Measuring Mission data. The dry anomaly east of the disturbance on hindcast day 1 is a good predictor of MJO onset and evolution. Initial CWV there is near the shallow–deep transition point, implicating premature onset of deep convection as a predictor of a poor MJO simulation. Convection weakly moistens the dry region in good MJO simulations in the first week; weakening of large-scale subsidence over this time may also affect MJO onset. Longwave radiation anomalies are weakest in the worst model version, consistent with previous analyses of cloud/moisture greenhouse enhancement as the primary MJO energy source. The authors’ results suggest that both cloud-/moisture-radiative interactions and convection–moisture sensitivity are required to produce a successful MJO simulation.

Abstract

An atmospheric-water-budget-related phase space is constructed with the tendency terms related to dynamical convergence (QCON ≡ −Q∇ ⋅ V) and moisture advection (QADV ≡ −V ⋅ ∇Q) in the water budget equation. Over the tropical oceans, QCON accounts for large-scale dynamical conditions related to conditional instability, and QADV accounts for conditions related to lower-tropospheric moisture gradient. Two reanalysis products [MERRA and ERA-Interim (ERAi)] are used to calculate QCON and QADV. Using the phase space as a reference frame, the Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-top pressure (CTP) and cloud optical depth (COD) are used to evaluate simulated clouds in the GISS-E2 general circulation model. In regimes of divergence over the tropical oceans, moist advection yields frequent high- to midlevel medium-thickness to thick clouds associated with moderate stratiform precipitation, while dry advection yields low-level thin clouds associated with shallow convection with lowered cloud tops. In regimes with convergence, moist and dry advection modulate the relative abundance of high-level thick clouds and low-level thin to medium-thickness clouds. GISS-E2 qualitatively reproduces the cloud property dependence on moisture budget tendencies in regimes of convergence but with larger COD compared to MODIS. Low-level thick clouds in GISS-E2 are the most frequent in regimes of near-zero convergence and moist advection instead of those of large-scale divergence. Compared to the Global Precipitation Climatology Project product, MERRA, ERAi, and GISS-E2 have more rain in regimes with deep convection and less rain in regimes with shallow convection.