Baike Xi

CERES Edition-2 Cloud Property Retrievals Using TRMM VIRS and Terra and Aqua MODIS Data—Part II: Examples of Average Results and Comparisons With Other Data

Cloud properties were retrieved by applying the Clouds and Earths Radiant Energy System (CERES) project Edition-2 algorithms to 3.5 years of Tropical Rainfall Measuring Mission Visible and Infrared Scanner data and 5.5 and 8 years of MODerate Resolution Imaging Spectroradiometer (MODIS) data from Aqua and Terra, respectively. The cloud products are consistent quantitatively from all three imagers; the greatest discrepancies occur over ice-covered surfaces. The retrieved cloud cover (~59%) is divided equally between liquid and ice clouds. Global mean cloud effective heights, optical depth, effective particle sizes, and water paths are 2.5 km, 9.9, 12.9 μm , and 80 g·m-2, respectively, for liquid clouds and 8.3 km, 12.7, 52.2 μm, and 230 g·m-2 for ice clouds. Cloud droplet effective radius is greater over ocean than land and has a pronounced seasonal cycle over southern oceans. Comparisons with independent measurements from surface sites, the Ice Cloud and Land Elevation Satellite, and the Aqua Advanced Microwave Scanning Radiometer-Earth Observing System are used to evaluate the results. The mean CERES and MODIS Atmosphere Science Team cloud properties have many similarities but exhibit large discrepancies in certain parameters due to differences in the algorithms and the number of unretrieved cloud pixels. Problem areas in the CERES algorithms are identified and discussed.

A Comparison of MERRA and NARR Reanalyses with the DOE ARM SGP Data

AbstractAtmospheric states from the Modern-Era Retrospective analysis for Research and Applications (MERRA) and the North American Regional Reanalysis (NARR) are compared with data from the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site, including the ARM continuous forcing product and Cloud Modeling Best Estimate (CMBE) soundings, during the period 1999–2001 to understand their validity for single-column model (SCM) and cloud-resolving model (CRM) forcing datasets. Cloud fraction, precipitation, and radiation information are also compared to determine what errors exist within these reanalyses. For the atmospheric state, ARM continuous forcing and the reanalyses have good agreement with the CMBE sounding information, with biases generally within 0.5 K for temperature, 0.5 m s−1 for wind, and 5% for relative humidity. Larger disagreements occur in the upper troposphere (p 800 hPa) for meri...

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility. Part II: Cloud Fraction and Surface Radiative Forcing

Abstract Data collected at the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Central Facility (SCF) are analyzed to determine the monthly and hourly variations of cloud fraction and radiative forcing between January 1997 and December 2002. Cloud fractions are estimated for total cloud cover and for single-layered low (0–3 km), middle (3–6 km), and high clouds (>6 km) using ARM SCF ground-based paired lidar–radar measurements. Shortwave (SW) and longwave (LW) fluxes are derived from up- and down-looking standard precision spectral pyranometers and precision infrared radiometer measurements with uncertainties of ∼10 W m−2. The annual averages of total and single-layered low-, middle-, and high-cloud fractions are 0.49, 0.11, 0.03, and 0.17, respectively. Both total- and low-cloud amounts peak during January and February and reach a minimum during July and August; high clouds occur more frequently than other types of clouds with a peak in summer. The average annual ...

A Climatology of Midlatitude Continental Clouds from the ARM SGP Central Facility: Part I: Low-Level Cloud Macrophysical, Microphysical, and Radiative Properties

Abstract A record of single-layer and overcast low cloud (stratus) properties has been generated using approximately 4000 h of data collected from January 1997 to December 2002 at the Atmospheric Radiation Measurement (ARM) Southern Great Plains Central Facility (SCF). The cloud properties include liquid-phase and liquid-dominant mixed-phase low cloud macrophysical, microphysical, and radiative properties including cloud-base and -top heights and temperatures, and cloud physical thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding; cloud liquid water path (LWP) and content (LWC), and cloud-droplet effective radius (re) and number concentration (N) derived from the macrophysical properties and radiometer data; and cloud optical depth (τ), effective solar transmission (γ), and cloud/top-of-atmosphere albedos (Rcldy/RTOA) derived from Eppley precision spectral pyranometer measurements. The cloud properties were analyzed in terms of their seasonal, monthly, and hourly variations...

Evaluation and Intercomparison of Cloud Fraction and Radiative Fluxes in Recent Reanalyses over the Arctic Using BSRN Surface Observations

AbstractWith continual advancements in data assimilation systems, new observing systems, and improvements in model parameterizations, several new atmospheric reanalysis datasets have recently become available. Before using these new reanalyses it is important to assess the strengths and underlying biases contained in each dataset. A study has been performed to evaluate and compare cloud fractions (CFs) and surface radiative fluxes in several of these latest reanalyses over the Arctic using 15 years (1994–2008) of high-quality Baseline Surface Radiation Network (BSRN) observations from Barrow (BAR) and Ny-Alesund (NYA) surface stations. The five reanalyses being evaluated in this study are (i) NASAs Modern-Era Retrospective analysis for Research and Applications (MERRA), (ii) NCEPs Climate Forecast System Reanalysis (CFSR), (iii) NOAAs Twentieth Century Reanalysis Project (20CR), (iv) ECMWFs Interim Reanalysis (ERA-I), and (v) NCEP–Department of Energy (DOE)s Reanalysis II (R2). All of the reanalyses ...

Top‐of‐atmosphere radiation budget of convective core/stratiform rain and anvil clouds from deep convective systems

[1] A new hybrid classification algorithm to objectively identify Deep Convective Systems (DCSs) in radar and satellite observations has been developed. This algorithm can classify the convective cores (CC), stratiform rain (SR) area and nonprecipitating anvil cloud (AC) from the identified DCSs through an integrative analysis of ground-based scanning radar and geostationary satellite data over the Southern Great Plains. In developing the algorithm, AC is delineated into transitional, thick, and thin components. While there are distinct physical/dynamical differences among these subcategories, their top-of-atmosphere (TOA) radiative fluxes are not significantly different. Therefore, these anvil subcategories are grouped as total anvil, and the radiative impact of each DCS component on the TOA radiation budget is quantitatively estimated. We found that more DCSs occurred during late afternoon, producing peak AC fraction right after sunset. AC covers 3 times the area of SR and almost an order of magnitude larger than CC. The average outgoing longwave (LW) irradiances are almost identical for CC and SR, while slightly higher for AC. Compared to the clear-sky average, the reflected shortwave (SW) fluxes for the three DCS components are greater by a factor of 2–3 and create a strong cooling effect at TOA. The calculated SW and LW cloud radiative forcing (CRF) of AC contribute up to 31% of total NET CRF, while CC and SR contribute only 4 and 11%, respectively. The hybrid classification further lays the groundwork for studying the life cycle of DCS and improvements in geostationary satellite IR-based precipitation retrievals.

Life cycle of midlatitude deep convective systems in a Lagrangian framework

Deep Convective Systems (DCSs) consist of intense convective cores (CC), large stratiform rain (SR) regions, and extensive non-precipitating anvil clouds (AC). This study focuses on the evolution of these three components and the factors that affect convective AC production. An automated satellite tracking method is used in conjunction with a recently developed multi-sensor hybrid classification to analyze the evolution of DCS structure in a Lagrangian framework over the central United States. Composite analysis from 4221 tracked DCSs during two warm seasons (May-August, 2010-2011) shows that maximum system size correlates with lifetime, and longer-lived DCSs have more extensive SR and AC. Maximum SR and AC area lag behind peak convective intensity and the lag increases linearly from approximately 1-hour for short-lived systems to more than 3-hours for long-lived ones. The increased lag, which depends on the convective environment, suggests that changes in the overall diabatic heating structure associated with the transition from CC to SR and AC could prolong the system lifetime by sustaining stratiform cloud development. Longer-lasting systems are associated with up to 60% higher mid-tropospheric relative humidity and up to 40% stronger middle to upper tropospheric wind shear. Regression analysis shows that the areal coverage of thick AC is strongly correlated with the size of CC, updraft strength, and SR area. Ambient upper tropospheric wind speed and wind shear also play an important role for convective AC production where for systems with large AC (radius greater than 120-km) they are 24% and 20% higher, respectively, than those with small AC (radius=20 km).

Evaluation of the NASA GISS Single-Column Model simulated clouds using combined surface and satellite observations.

Three years of surface and Geostationary Operational Environmental Satellite (GOES) data from the Department of Energy Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site are used to evaluate the NASA GISS Single Column Model (SCM) simulated clouds from January 1999 to December 2001. The GOES-derived total cloud fractions for both 0.58 and 2.58 grid boxes are in excellent agreement with surface observations, suggesting that ARM point observations can represent large areal observations. Low (,2 km), middle (2‐6 km), and high (.6 km) levels of cloud fractions, however, have negative biases as compared to the ARM results due to multilayer cloud scenes that can either mask lower cloud layers or cause misidentifications of cloud tops. Compared to the ARM observations, the SCM simulated most midlevel clouds, overestimated low clouds (4%), and underestimated total and high clouds by 7% and 15%, respectively. To examine the dependence of the modeled high and low clouds on the large-scale synopticpatterns,variablessuch as relative humidity(RH) andverticalpressurevelocity(omega)fromNorth American Regional Reanalysis (NARR) data are included. The successfully modeled and missed high clouds are primarily associated with a trough and ridge upstream of the ARM SGP, respectively. The PDFs of observed high and low occurrence as a function of RH reveal that high clouds have a Gaussian-like distribution with mode RH values of ;40%‐50%, whereas low clouds have a gammalike distribution with the highest cloud probability occurring at RH ;75%‐85%. The PDFs of modeled low clouds are similar to those observed;however, forhighcloudsthePDFsareshiftedtowardhighervaluesofRH.Thisresultsin anegative bias for the modeled high clouds because many of the observed clouds occur at RH values below the SCMspecified stratiformparameterization thresholdRH of 60%.Despite manysimilaritiesbetweenPDFs derived from the NARR and ARM forcing datasets for RH and omega, differences do exist. This warrants further investigation of the forcing and reanalysis datasets.

Assessment of NASA GISS CMIP5 and Post-CMIP5 Simulated Clouds and TOA Radiation Budgets Using Satellite Observations. Part I: Cloud Fraction and Properties

AbstractAlthough 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 ...

Aerosol properties and their influences on marine boundary layer cloud condensation nuclei at the ARM mobile facility over the Azores

A multiplatform data set from the Clouds, Aerosol, and Precipitation in the Marine Boundary Layer (MBL) Graciosa, Azores, 2009–2010 field campaign was used to investigate how continental aerosols can influence MBL cloud condensation nuclei (CCN) number concentration (NCCN). The seasonal variations of aerosol properties have shown that the winter and early spring months had the highest mean surface wind speed (> 5 m s−1) and greatest contribution of sea salt to aerosol optical depth (AOD), while continental fine mode aerosols were the main contributors to AOD during the warm season months (May–September). Five aerosol events consisting of mineral dust, pollution, biomass smoke, and volcanic ash particles were selected as case studies using Atmospheric Radiation Measurement (ARM) mobile facility measurements. The aerosols in Case I were found to primarily consist of coarse mode, Saharan mineral dust. For Case II, the aerosols were also coarse mode but consisted of volcanic ash. Case III had fine mode biomass smoke and pollution aerosol influences while Cases IV and V consisted of mixtures of North American pollution and Saharan dust that was advected by an extratropical cyclone to the Azores. Cases I, IV, and V exhibited weak correlations between aerosol loading and NCCN due to mineral dust influences, while Cases II and III had a strong relationship with NCCN likely due to the sulfate content in the volcanic ash and pollution particles. The permanent Eastern North Atlantic ARM facility over the Azores will aid in a future long-term study of aerosol effects on NCCN.