Improving a Spectral Bin Microphysical Scheme Using TRMM Satellite Observations

Comparisons between cloud model simulations and observations are crucial in validating model performance and improving physical processes represented in the mod Tel.hese modeled physical processes are idealized representations and almost always have large rooms for improvements. In this study, we use data from two different sensors onboard TRMM (Tropical Rainfall Measurement Mission) satellite to improve the microphysical scheme in the Goddard Cumulus Ensemble (GCE) model. TRMM observed mature-stage squall lines during late spring, early summer in central US over a 9-year period are compiled and compared with a case simulation by GCE model. A unique aspect of the GCE model is that it has a state-of-the-art spectral bin microphysical scheme, which uses 33 different bins to represent particle size distribution of each of the seven hydrometeor species. A forward radiative transfer model calculates TRMM Precipitation Radar (PR) reflectivity and TRMM Microwave Imager (TMI) 85 GHz brightness temperatures from simulated particle size distributions. Comparisons between model outputs and observations reveal that the model overestimates sizes of snow/aggregates in the stratiform region of the squall line. After adjusting temperature-dependent collection coefficients among ice-phase particles, PR comparisons become good while TMI comparisons worsen. Further investigations show that the partitioning between graupel (a high-density form of aggregate), and snow (a low-density form of aggregate) needs to be adjusted in order to have good comparisons in both PR reflectivity and TMI brightness temperature. This study shows that long-term satellite observations, especially those with multiple sensors, can be very useful in constraining model microphysics. It is also the first study in validating and improving a sophisticated spectral bin microphysical scheme according to long-term satellite observations

Evaluation of Long-Term Cloud-Resolving Model Simulations Using Satellite Radiance Observations and Multi-Frequency Satellite Simulators

This paper proposes a methodology known as the Tropical Rainfall Measuring Mission (TRMM) Triple-Sensor Three-step Evaluation Framework (T3EF) for the systematic evaluation of precipitating cloud types and microphysics in a cloud-resolving model (CRM). T3EF utilizes multi-frequency satellite simulators and novel statistics of multi-frequency radiance and backscattering signals observed from the TRMM satellite. Specifically, T3EF compares CRM and satellite observations in the form of combined probability distributions of precipitation radar (PR) reflectivity, polarization-corrected microwave brightness temperature (Tb), and infrared Tb to evaluate the candidate CRM. T3EF is used to evaluate the Goddard Cumulus Ensemble (GCE) model for cases involving the South China Sea Monsoon Experiment (SCSMEX) and Kwajalein Experiment (KWAJEX). This evaluation reveals that the GCE properly captures the satellite-measured frequencies of different precipitating cloud types in the SCSMEX case but underestimates the frequencies of deep convective and deep stratiform types in the KWAJEX case. Moreover, the GCE tends to simulate excessively large and abundant frozen condensates in deep convective clouds as inferred from the overestimated GCE-simulated radar reflectivities and microwave Tb depressions. Unveiling the detailed errors in the GCE s performance provides the best direction for model improvements

Transient aggregation of convection: observed behavior and underlying processes

Convective self-aggregation is among the most striking features emerging from radiative-convective equilibrium simulations, but its relevance to convective disturbances observed in the real atmosphere remains under debate. This work seeks the observational signals of convective aggregation intrinsic to the life cycle of cloud clusters. To this end, composite time series of the Simple Convective Aggregation Index (SCAI), a metric of aggregation, and other variables from satellite measurements are constructed around the temporal maxima of precipitation. All the parameters analyzed are large-scale means over 10o×10o domains. The composite evolution for heavy precipitation regimes shows that cloud clusters are gathered into fewer members during a period of ±12 h has precipitation picks up. The high-cloud cover per cluster expands as the number of clusters drops, suggesting a transient occurrence of convective aggregation. The sign of the transient aggregation is less evident or entirely absent in light precipitation regimes. An energy budget analysis is performed in search of the physical processes underlying the transient aggregation. The column moist static energy (MSE) accumulates before the precipitation peak and dissipates after, accounted for primarily by the horizontal MSE advection. The domain-averaged column radiative cooling is greater in a more aggregated composite than in a less aggregated one, although the role of radiative-convective feedback behind this remains unclear

Quantifying Uncertainties in Land Surface Microwave Emissivity Retrievals

Uncertainties in the retrievals of microwave land surface emissivities were quantified over two types of land surfaces: desert and tropical rainforest. Retrievals from satellite-based microwave imagers, including SSM/I, TMI and AMSR-E, were studied. Our results show that there are considerable differences between the retrievals from different sensors and from different groups over these two land surface types. In addition, the mean emissivity values show different spectral behavior across the frequencies. With the true emissivity assumed largely constant over both of the two sites throughout the study period, the differences are largely attributed to the systematic and random errors in the retrievals. Generally these retrievals tend to agree better at lower frequencies than at higher ones, with systematic differences ranging 1~4% (3~12 K) over desert and 1~7% (3~20 K) over rainforest. The random errors within each retrieval dataset are in the range of 0.5~2% (2~6 K). In particular, at 85.0/89.0 GHz, there are very large differences between the different retrieval datasets, and within each retrieval dataset itself. Further investigation reveals that these differences are mostly likely caused by rain/cloud contamination, which can lead to random errors up to 10~17 K under the most severe conditions

Effects of atmospheric sphericity on stratospheric chemistry and dynamics over Antarctica

Atmospheric sphericity is an important factor that must be considered in order to evaluate an accurate ozone loss rate in the polar stratosphere. The built-in plane-parallel radiative transfer scheme of a nudging chemical transport model (CTM) and an atmospheric general circulation model (AGCM) with coupled chemistry is modified by a pseudospherical approximation. The plane-parallel atmosphere radiative transfer version (PPA version) is compared with the pseudospherical atmosphere radiative transfer version (SA version) for both the nudging CTM and AGCM. The nudging CTM can isolate the chemical effects for a given dynamical field, while the interaction among the chemical, radiative, and dynamical processes can be studied with the AGCM. The present analysis focuses on Antarctica during an ozone hole period. In the ozone loss period over Antarctica, ozone starts to decrease earlier and minimum value of total ozone becomes lower in the SA versions of both the nudging CTM and the AGCM than in the corresponding PPA versions. The ozone mixing ratio decreases earlier in the SA version because of an earlier increase of ClO concentration initiated by the upward actinic flux at solar zenith angles greater than 90°. Dynamics plays an important role as well as the chemical processes. During the ozone recovery period, the ozone distribution becomes almost the same in the SA and PPA versions of the nudging CTM, while in the AGCM the ozone amount in the SA version remains at lower values compared to those of the PPA version. In the AGCM, a decrease of ozone over Antarctica enhances the latitudinal gradient of temperature and thus strengthens the polar vortex in the SA version. A resultant delay of the polar vortex breakup causes the delay of the ozone recovery. For the AGCM, ensemble runs are performed. The ensemble experiment exhibits large ozone variances after the middle of December, when the ozone recovery is dynamically controlled. Most ensemble members of the AGCM show a delay of the polar vortex breakup in the SA version, while a few members show opposite results. In the latter members, the polar vortex breakup is strongly affected by the enhanced EP flux from the troposphere around 100 hPa, which causes the variances in the ozone recovery period. Most members, however, do not show large statistical variances; that justifies the conclusions from the ensemble means

Observing convective aggregation

Convective self-aggregation, the spontaneous organization of initially scattered convection into isolated convective clusters despite spatially homogeneous boundary conditions and forcing, was first recognized and studied in idealized numerical simulations. While there is a rich history of observational work on convective clustering and organization, there have been only a few studies that have analyzed observations to look specifically for processes related to self-aggregation in models. Here we review observational work in both of these categories and motivate the need for more of this work. We acknowledge that self-aggregation may appear to be far-removed from observed convective organization in terms of time scales, initial conditions, initiation processes, and mean state extremes, but we argue that these differences vary greatly across the diverse range of model simulations in the literature and that these comparisons are already offering important insights into real tropical phenomena. Some preliminary new findings are presented, including results showing that a self-aggregation simulation with square geometry has too broad a distribution of humidity and is too dry in the driest regions when compared with radiosonde records from Nauru, while an elongated channel simulation has realistic representations of atmospheric humidity and its variability. We discuss recent work increasing our understanding of how organized convection and climate change may interact, and how model discrepancies related to this question are prompting interest in observational comparisons. We also propose possible future directions for observational work related to convective aggregation, including novel satellite approaches and a ground-based observational network

A toy model of tropical convection with a moisture storage closure

Abstract A time‐dependent, zero‐dimensional toy model is constructed to study the large‐scale variability in association with tropical moist convection. Case studies from sounding‐array observations are analyzed as a benchmark to test the model performance. The model predicts the vertical integral of vertical moisture advection decomposed into the deep convective and congestus/stratiform modes. A closure representing the consumption efficiency of water vapor into precipitation is introduced using the moisture storage ratio, or the degree to which the vertical moisture advection associated with each vertical mode accounts for moisture storage. The observations suggest that this moisture consumption is highly inefficient for the convective/stratiform mode while efficient for the deep convective mode. The model solution is interpreted as a delayed response to the diabatic forcing, unless the sum of the moisture storage ratio and gross moist stability is negative, in which case the system is unstable. Baseline experiments with a fixed moisture storage closure overall reproduce the vertical moisture advection and precipitation as observed, but fail to simulate a sharp pickup of precipitation in the well‐known moisture‐rainfall curve. This deficiency is eliminated when the moisture storage ratio is allowed to vary as convection intensifies and dissipates

Radiative Invigoration of Tropical Convection by Preceding Cirrus Clouds

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