Aaron Kennedy

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...

Diagnosing the Nature of Land–Atmosphere Coupling: A Case Study of Dry/Wet Extremes in the U.S. Southern Great Plains

AbstractLand–atmosphere (L–A) interactions play a critical role in determining the diurnal evolution of land surface and planetary boundary layer (PBL) temperature and moisture states and fluxes. In turn, these interactions regulate the strength of the connection between surface moisture and precipitation in a coupled system. To address model deficiencies, recent studies have focused on development of diagnostics to quantify the strength and accuracy of the land–PBL coupling at the process level. In this paper, a diagnosis of the nature and impacts of local land–atmosphere coupling (LoCo) during dry and wet extreme conditions is presented using a combination of models and observations during the summers of 2006 and 2007 in the U.S. southern Great Plains. A range of diagnostics exploring the links and feedbacks between soil moisture and precipitation is applied to the dry/wet regimes exhibited in this region, and in the process, a thorough evaluation of nine different land–PBL scheme couplings is conducted...

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 ...

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).

A 19-Month Record of Marine Aerosol–Cloud–Radiation Properties Derived from DOE ARM Mobile Facility Deployment at the Azores. Part I: Cloud Fraction and Single-Layered MBL Cloud Properties

A 19-month record of total and single-layered low (,3km), middle (3‐6km), and high (.6km) cloud fractions (CFs) and the single-layered marine boundary layer (MBL) cloud macrophysical and microphysical properties was generated from ground-based measurements at the Atmospheric Radiation Measurement Program (ARM) Azores site between June 2009 and December 2010. This is the most comprehensive dataset of marine cloud fraction and MBL cloud properties. The annual means of total CF and single-layered low, middle, and high CFs derived from ARM radar and lidar observations are 0.702, 0.271, 0.01, and 0.106, respectively. Greater total and single-layered high (.6km) CFs occurred during the winter, whereas singlelayered low (,3km) CFs were more prominent during summer. Diurnal cycles for both total and low CFs were stronger during summer than during winter. The CFs are bimodally distributed in the vertical with a lower peak at ;1km and a higher peak between 8 and 11km during all seasons, except summer when only the low peak occurs. Persistent high pressure and dry conditions produce more single-layered MBL clouds and fewer total clouds during summer, whereas the low pressure and moist air masses during winter generate more total and multilayered clouds, and deep frontal clouds associated with midlatitude cyclones. The seasonal variations of cloud heights and thickness are also associated with the seasonal synoptic patterns. The MBL cloud layer is low, warm, and thin with large liquid water path (LWP) and liquid water content (LWC) during summer, whereas during winter it is higher, colder, and thicker with reduced LWP and LWC. The cloud LWP and LWC values are greater at night than during daytime. The monthly mean daytime cloud droplet effective radius re values are nearly constant, while the daytime droplet number concentration Nd basically follows the LWC variation. There is a strong correlation between cloud condensation nuclei (CCN) concentration NCCN and Nd during January‐May, probably due to the frequent low pressure systems because upward motion brings more surface CCN to cloud base (well-mixed boundary layer). During summer and autumn, the correlation between Nd and NCCN is not as strong as that during January‐May because downward motion from high pressure systems is predominant. Compared to the compiled aircraft in situ measurements during the Atlantic Stratocumulus Transition Experiment (ASTEX), the cloud microphysical retrievals in this study agree well with historical aircraft data. Different air mass sources over the ARM Azores site have significant impacts on the cloud microphysical properties and surface CCN as demonstrated by great variability in NCCN and cloud microphysical properties during some months.

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 ...

Evaluation of Reanalyzed Precipitation Variability and Trends Using the Gridded Gauge-Based Analysis over the CONUS

AbstractAtmospheric reanalyses have been used in many studies to investigate the variabilities and trends of precipitation because of their global coverage and long record; however, their results must be properly analyzed and their uncertainties must be understood. In this study, precipitation estimates from five global reanalyses [ERA-Interim; MERRA, version 2 (MERRA2); JRA-55; CFSR; and 20CR, version 2c (20CRv2c)] and one regional reanalysis (NARR) are compared against the CPC Unified Gauge-Based Analysis (CPCUGA) and GPCP over the contiguous United States (CONUS) during the period 1980–2013. Reanalyses capture the variability of the precipitation distribution over the CONUS as observed in CPCUGA and GPCP, but large regional and seasonal differences exist. Compared with CPCUGA, global reanalyses generally overestimate the precipitation over the western part of the country throughout the year and over the northeastern CONUS during the fall and winter seasons. These issues may be associated with the diffi...

Evaluation of NASA GISS Post-CMIP5 Single Column Model Simulated Clouds and Precipitation Using ARM Southern Great Plains Observations

The planetary boundary layer turbulence and moist convection parameterizations have been modified recently in the NASA Goddard Institute for Space Studies (GISS) Model E2 atmospheric general circulation model (GCM; post-CMIP5, hereafter P5). In this study, single column model (SCM P5) simulated cloud fractions (CFs), cloud liquid water paths (LWPs) and precipitation were compared with Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) groundbased observations made during the period 2002–08. CMIP5 SCM simulations and GCM outputs over the ARM SGP region were also used in the comparison to identify whether the causes of cloud and precipitation biases resulted from either the physical parameterization or the dynamic scheme. The comparison showed that the CMIP5 SCM has difficulties in simulating the vertical structure and seasonal variation of low-level clouds. The new scheme implemented in the turbulence parameterization led to significantly improved cloud simulations in P5. It was found that the SCM is sensitive to the relaxation time scale. When the relaxation time increased from 3 to 24 h, SCM P5-simulated CFs and LWPs showed a moderate increase (10%–20%) but precipitation increased significantly (56%), which agreed better with observations despite the less accurate atmospheric state. Annual averages among the GCM and SCM simulations were almost the same, but their respective seasonal variations were out of phase. This suggests that the same physical cloud parameterization can generate similar statistical results over a long time period, but different dynamics drive the differences in seasonal variations. This study can potentially provide guidance for the further development of the GISS model.

The Community Leveraged Unified Ensemble (CLUE) in the 2016 NOAA/Hazardous Weather Testbed Spring Forecasting Experiment

CapsuleThe CLUE system represents an unprecedented effort to leverage several academic and government research institutions to help guide NOAA’s operational environmental modeling efforts at the convection-allowing scale.