Michael A. Brunke

Evaluation of the Reanalysis Products from GSFC, NCEP, and ECMWF Using Flux Tower Observations

AbstractReanalysis products produced at the various centers around the globe are utilized for many different scientific endeavors, including forcing land surface models and creating surface flux estimates. Here, flux tower observations of temperature, wind speed, precipitation, downward shortwave radiation, net surface radiation, and latent and sensible heat fluxes are used to evaluate the performance of various reanalysis products [NCEP–NCAR reanalysis and Climate Forecast System Reanalysis (CFSR) from NCEP; 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA-40) and ECMWF Interim Re-Analysis (ERA-Interim) from ECMWF; and Modern-Era Retrospective Analysis for Research and Applications (MERRA) and Global Land Data Assimilation System (GLDAS) from the Goddard Space Flight Center (GSFC)]. To combine the biases and standard deviation of errors from the separate stations, a ranking system is utilized. It is found that ERA-Interim has the lowest overall bias in 6-hourly air temper...

Which Bulk Aerodynamic Algorithms are Least Problematic in Computing Ocean Surface Turbulent Fluxes

Bulk aerodynamic algorithms are needed to compute ocean surface turbulent fluxes in weather forecasting and climate models and in the development of global surface flux datasets. Twelve such algorithms are evaluated and ranked using direct turbulent flux measurements determined from covariance and inertial-dissipation methods from 12 ship cruises over the tropical and midlatitude oceans (from about 58 St o 608N). The four least problematic of these 12 algorithms based upon the overall ranking for this data include the Coupled Ocean‐Atmosphere Response Experiment (COARE) version 3.0 and The University of Arizona (UA) schemes as well as those used at the European Centre for Medium-Range Weather Forecasts (ECMWF) and the National Aeronautics and Space Administration (NASA) Data Assimilation Office for version 1 of the Goddard Earth Observing System reanalysis (GEOS-1). Furthermore, the four most problematic of these algorithms are also identified along with possible explanations. The overall ranking is not substantially affected by the use of the average of covariance and inertialdissipation flux measurements or by taking into consideration measurement uncertainties. The differences between computed and observed fluxes are further evaluated as a function of near-surface wind speed and sea surface temperature to understand the rankings. Finally, several unresolved issues in terms of measurement and algorithm uncertainties are raised.

An Assessment of the Uncertainties in Ocean Surface Turbulent Fluxes in 11 Reanalysis, Satellite-Derived, and Combined Global Datasets

AbstractOcean surface turbulent fluxes play an important role in the energy and water cycles of the atmosphere–ocean coupled system, and several flux products have become available in recent years. Here, turbulent fluxes from 6 widely used reanalyses, 4 satellite-derived flux products, and 2 combined product are evaluated by comparison with direct covariance latent heat (LH) and sensible heat (SH) fluxes and inertial-dissipation wind stresses measured from 12 cruises over the tropics and mid- and high latitudes. The biases range from −3.0 to 20.2 W m−2 for LH flux, from −1.4 to 6.0 W m−2 for SH flux, and from −7.6 to 7.9 × 10−3 N m−2 for wind stress. These biases are small for moderate wind speeds but diverge for strong wind speeds (>10 m s−1). The total flux biases are then further evaluated by dividing them into uncertainties due to errors in the bulk variables and the residual uncertainty. The bulk-variable-caused uncertainty dominates many products’ SH flux and wind stress biases. The biases in the bu...

Marine Atmospheric Boundary Layer Height over the Eastern Pacific: Data Analysis and Model Evaluation

The atmospheric boundary layer (ABL) height (h) is a crucial parameter for the treatment of the ABL in weather and climate models. About 1000 soundings from 11 cruises between 1995 and 2001 over the eastern Pacific have been analyzed to document the large meridional, zonal, seasonal, and interannual variations of h. In particular, its latitudinal distribution in August has three minima: near the equator, in the intertropical convergence zone (ITCZ), and over the subtropical stratus/stratocumulus region near the west coast of California and Mexico. The seasonal peak of h in the ITCZ zone (between 5.68 and 11.28N) occurs in the spring (February or April), while it occurs in August between the equator and 5.68N. Comparison of these data with the 10-yr monthly output of the Community Climate System Model (CCSM2) reveals that overall the model underestimates h, particularly north of 208N in August and September. Directly applying the radiosonde data to the CCSM2 formulation for computing h shows that, at the original vertical resolution (with the lowest five layers below 2.1 km), the CCSM2 formulation would significantly underestimate h. In particular, the correlation coefficient between the computed and observed h values is only 0.06 for cloudy cases. If the model resolution were doubled below 2.1 km, however, the performance of the model formulation would be significantly improved with a correlation coefficient of 0.78 for cloudy cases.

A gridded global data set of soil, intact regolith, and sedimentary deposit thicknesses for regional and global land surface modeling

Earths terrestrial near-subsurface environment can be divided into relatively porous layers of soil, intact regolith, and sedimentary deposits above unweathered bedrock. Variations in the thicknesses of these layers control the hydrologic and biogeochemical responses of landscapes. Currently, Earth System Models approximate the thickness of these relatively permeable layers above bedrock as uniform globally, despite the fact that their thicknesses vary systematically with topography, climate, and geology. To meet the need for more realistic input data for models, we developed a high-resolution gridded global data set of the average thicknesses of soil, intact regolith, and sedimentary deposits within each 30 arcsec (∼1 km) pixel using the best available data for topography, climate, and geology as input. Our data set partitions the global land surface into upland hillslope, upland valley bottom, and lowland landscape components and uses models optimized for each landform type to estimate the thicknesses of each subsurface layer. On hillslopes, the data set is calibrated and validated using independent data sets of measured soil thicknesses from the U.S. and Europe and on lowlands using depth to bedrock observations from groundwater wells in the U.S. We anticipate that the data set will prove useful as an input to regional and global hydrological and ecosystems models.

Intercomparison of Seven NDVI Products over the United States and Mexico

Satellites have provided large-scale monitoring of vegetation for over three decades, and several satellite-based Normalized Difference Vegetation Index (NDVI) datasets have been produced. Here we intercompare four long-term NDVI datasets based largely on the AVHRR sensor (NDVIg, NDVI3g, STAR, VIP) and three datasets based on newer sensors (SPOT, Terra, Aqua) and evaluate the effectiveness of homogenizing the datasets using the green vegetation fraction (GVF) and the impact it has on phenology trends. Results show that all NDVI datasets are highly correlated with each other. However, there are significant differences in the regression slopes that vary spatially and temporally. There is a general trend towards higher maximum annual NDVI over much of the temperate forests of the US and a longer greening period due mostly to a delayed end of the season. These trends are less well-defined over rainfall dependent ecosystems in Mexico and the southwest US Compared with the NDVI datasets, the derived GVF datasets show more one-to-one relationships, have reduced interannual variation, preserve their relationships better over the entire time period and are characterized by weaker trends. Finally, weak agreement between the trends in the datasets stresses the importance of using multiple datasets to evaluate changes in vegetation and its phenology.

Simulating transient ice-ocean Ekman transport in the Regional Arctic System Model and Community Earth System Model

Abstract This work evaluates the fidelity of the polar marine Ekman layer in the Regional Arctic System Model (RASM) and Community Earth System Model (CESM) using sea-ice inertial oscillations as a proxy for ice-ocean Ekman transport. A case study is presented that demonstrates that RASM replicates inertial oscillations in close agreement with motion derived using the GPS. This result is obtained from a year-long case study pre-dating the recent decline in perennial Arctic sea ice, using RASM with sub-hourly coupling between the atmosphere, sea-ice and ocean components. To place this work in context, the RASM coupling method is applied to CESM, increasing the frequency of oceanic flux exchange from once per day in the standard CESM configuration, to every 30 min. For a single year simulation, this change causes a considerable increase in the median inertial ice speed across large areas of the Southern Ocean and parts of the Arctic sea-ice zone. The result suggests that processes associated with the passage of storms over sea ice (e.g. oceanic mixing, sea-ice deformation and surface energy exchange) are underestimated in Earth System Models that do not resolve inertial frequencies in their marine coupling cycle.

The Equatorial Pacific Cold Tongue Bias in a Coupled Climate Model

Abstract A set of multidecadal coupled ocean–atmosphere model integrations are conducted with different time steps for coupling between the atmosphere and the ocean. It is shown that the mean state of the equatorial Pacific does not change in a statistically significant manner when the coupling interval between the atmospheric general circulation model (AGCM) and the ocean general circulation model (OGCM) is changed from 1 day to 2 or even 3 days. It is argued that because the coarse resolution of the AGCM precludes resolving realistic “weather” events, changing the coupling interval from 1 day to 2 or 3 days has very little impact on the mean coupled climate. On the other hand, reducing the coupling interval to 3 h had a much stronger impact on the mean state of the equatorial Pacific and the concomitant general circulation. A novel experiment that incorporates a (pseudo) interaction of the atmosphere with SST at every time step of the AGCM was also conducted. In this unique coupled model experiment, the...

Stratocumulus Cloud Clearings and Notable Thermodynamic and Aerosol Contrasts across the Clear-Cloudy Interface

Data from three research flights, conducted over water near the California coast, are used to investigate the boundary between stratocumulus cloud decks and clearings of different sizes. Large clearings exhibit a diurnal cycle with growth during the day and contraction overnight and a multiday life cycle that can include oscillations between growth and decay, whereas a small coastal clearing was observed to be locally confined with a subdiurnal lifetime. Subcloud aerosol characteristics are similar on both sides of the clear–cloudy boundary in the three cases, while meteorological properties exhibit subtle, yet important, gradients, implying that dynamics, and not microphysics, is the primary driver for the clearing characteristics. Transects, made at multiple levels across the cloud boundary during one flight, highlight the importance of microscale (~1 km) structure in thermodynamic properties near the cloud edge, suggesting that dynamic forcing at length scales comparable to the convective eddy scale may be influential to the larger-scale characteristics of the clearing. These results have implications for modeling and observational studies of marine boundary layer clouds, especially in relation to aerosol–cloud interactions and scales of variability responsible for the evolution of stratocumulus clearings.

Temporal- and spatial-scale dependence of three CMIP3 climate models in simulating the surface temperature trend in the twentieth century

AbstractMotivated by increasing interests in regional- and decadal-scale climate predictions, this study systematically analyzed the spatial- and temporal-scale dependence of the prediction skill of global climate models in surface air temperature (SAT) change in the twentieth century. The linear trends of annual mean SAT over moving time windows (running linear trends) from two observational datasets and simulations by three global climate models [Community Climate System Model, version 3.0 (CCSM3.0), Climate Model, version 2.0 (CM2.0), and Model E-H] that participated in CMIP3 are compared over several temporal (10-, 20-, 30-, 40-, and 50-yr trends) and spatial (5° × 5°, 10° × 10°, 15° × 15°, 20° × 20°, 30° × 30°, 30° latitudinal bands, hemispheric, and global) scales. The distribution of root-mean-square error is improved with increasing spatial and temporal scales, approaching the observational uncertainty range at the largest scales. Linear correlation shows a similar tendency, but the limited observ...