Goddard Earth Observing System Model Research Articles

An assessment of CALIOP polar stratospheric cloud composition classification

Abstract. This study assesses the robustness of the CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) polar stratospheric cloud (PSC) composition classification algorithm – which is based solely on the spaceborne lidar data – through the use of nearly coincident gas-phase HNO3 and H2O data from the Microwave Limb Sounder (MLS) on Aura and Goddard Earth Observing System Model, Version 5 (GEOS-5) temperature analyses. Following the approach of Lambert et al. (2012), we compared the observed temperature-dependent HNO3 uptake by PSCs in the various CALIOP composition classes with modeled uptake for supercooled ternary solutions (STS) and equilibrium nitric acid trihydrate (NAT). We examined the CALIOP PSC data record from both polar regions over the period from 2006 through 2011 and over a range of potential temperature levels spanning the 15–30 km altitude range. We found that most PSCs identified as STS exhibit gas phase uptake of HNO3 consistent with theory, but with a small temperature bias, similar to Lambert et al. (2012). Ice PSC classification is also robust in the CALIOP optical data, with the mode in the ice observations occurring about 0.5 K below the frost point. We found that CALIOP PSCs identified as NAT mixtures exhibit two distinct preferred modes which reflect the fact that the growth of NAT particles is kinetically limited. One mode is significantly out of thermodynamic equilibrium with respect to NAT due to short exposure times to temperatures below the NAT existence temperature, TNAT, with HNO3 uptake dominated by the more numerous liquid droplets. The other NAT mixture mode is much closer to NAT thermodynamic equilibrium, indicating that the particles have been exposed to temperatures below TNAT for extended periods of time. With a few notable exceptions, PSCs in the various composition classes conform well to their expected temperature existence regimes. We have a good understanding of the cause of the minor misclassifications that do occur and will investigate means to correct these deficiencies in our next generation algorithm.

The Efficiency of Assimilating Satellite Soil Moisture Retrievals in a Land Data Assimilation System Using Different Rainfall Error Models

Abstract The efficiency of assimilating near-surface soil moisture retrievals from Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) observations in a Land Data Assimilation System (LDAS) is assessed using satellite rainfall forcing and two different satellite rainfall error models: a complex, multidimensional satellite rainfall error model (SREM2D) and the simpler (control) model (CTRL) used in the NASA Goddard Earth Observing System Model, version 5 LDAS. For the study domain of Oklahoma, LDAS soil moisture estimates improve over the satellite retrievals and the open-loop (no assimilation) land surface model estimates, exhibiting higher daily anomaly correlation coefficients (e.g., 0.36 in the open loop, 0.38 in the AMSR-E, and 0.50 in LDAS for surface soil moisture). The LDAS soil moisture estimates also match the performance of a benchmark model simulation forced with high-quality radar precipitation. Compared to using the CTRL rainfall error model in LDAS, using the more complex SREM2D exhibits only slight improvements in soil moisture estimates.

Optimal Initial Perturbations for Ensemble Prediction of the Madden–Julian Oscillation during Boreal Winter

AbstractAn initialization strategy, tailored to the prediction of the Madden–Julian oscillation (MJO), is evaluated using the Goddard Earth Observing System Model, version 5 (GEOS-5), coupled general circulation model (CGCM). The approach is based on the empirical singular vectors (ESVs) of a reduced-space statistically determined linear approximation of the full nonlinear CGCM. The initial ESV, extracted using 10 years (1990–99) of boreal winter hindcast data, has zonal wind anomalies over the western Indian Ocean, while the final ESV (at a forecast lead time of 10 days) reflects a propagation of the zonal wind anomalies to the east over the Maritime Continent—an evolution that is characteristic of the MJO.A new set of ensemble hindcasts are produced for the boreal winter season from 1990 to 1999 in which the leading ESV provides the initial perturbations. The results are compared with those from a set of control hindcasts generated using random perturbations. It is shown that the ESV-based predictions have a systematically higher bivariate correlation skill in predicting the MJO compared to those using the random perturbations. Furthermore, the improvement in the skill depends on the phase of the MJO. The ESV is particularly effective in increasing the forecast skill during those phases of the MJO in which the control has low skill (with correlations increasing by as much as 0.2 at 20–25-day lead times), as well as during those times in which the MJO is weak.

Relationship of cloud top to the tropopause and jet structure from CALIPSO data

[1] Cloud top and tropopause relationships are examined using cloud top observations from the Cloud-Aerosol Lidar Infrared Pathfinder Satellite Observations (CALIPSO) cloud data and National Centers for Environmental Prediction Global Forecast System (GFS) tropopause data. Statistical analyses of cloud top occurrence in tropopause and jet referenced relative altitude coordinates are performed on a global scale using 4 years (2006–2010) of CALIPSO 5 km resolution cloud layer data. The results show that the thermal tropopause appears to be a significant constraint for the cloud top. The zonal vertical distribution of cloud tops in tropopause-relative coordinates shows a maximum at the tropopause level for both the tropics (20°S–20°N) and midlatitudes (40°–60°S, 40°–60°N) for all four seasons. Occurrence of cloud tops above the tropopause is examined and quantified. The results show that with the consideration of tropopause height uncertainty, the data do not provide sufficient evidence of significant presence of cloud tops above the tropopause in the midlatitudes. In the tropics, the significant occurrences of cloud top above the thermal tropopause are found in regions known for seasonal deep convection. In most cases, the occurrence is up to 24% in 2° × 3° latitude-longitude bins with isolated higher frequencies in the western Pacific during the northern hemispheric winter season. The vertical distributions show that these events are mostly up to 2.5 km above the lapse rate tropopause, which is comparable to the differences between the lapse rate and the cold point tropopause in regions of active convection. We speculate that this separation may be responsible for a significant fraction of the cloud tops that do occur above the lapse rate tropopause in our analyses. It is also important to note that our results are limited by the CALIPSO twice-daily sampling with local equator crossing times of 0130 and 1330. The data therefore do not provide a good representation of convection over land, which is known to have maxima in afternoon local times. The tropopause determination is a significant component of this type of studies, and errors in the tropopause height may lead to significantly different conclusions. Our analyses show that the tropopause product from the GFS model is in better agreement with radiosonde measurements. The Goddard Earth Observing System Model Version 5 tropopause product, given as the ancillary data in the CALIPSO data file, shows a much larger uncertainty, primarily because the tropopause is identified at the model grid levels.

Assessment of the breakup of the Antarctic polar vortex in two new chemistry‐climate models

Successful simulation of the breakup of the Antarctic polar vortex depends on the representation of tropospheric stationary waves at Southern Hemisphere middle latitudes. This paper assesses the vortex breakup in two new chemistry‐climate models (CCMs). The stratospheric version of the UK Chemistry and Aerosols model is able to reproduce the observed timing of the vortex breakup. Version 2 of the Goddard Earth Observing System (GEOS V2) model is typical of CCMs in that the Antarctic polar vortex breaks up too late; at 10 hPa, the mean transition to easterlies at 60°S is delayed by 12–13 days as compared with the ERA‐40 and National Centers for Environmental Prediction reanalyses. The two models' skill in simulating planetary wave driving during the October–November period accounts for differences in their simulation of the vortex breakup, with GEOS V2 unable to simulate the magnitude and tilt of geopotential height anomalies in the troposphere and thus underestimating the wave driving. In the GEOS V2 CCM the delayed breakup of the Antarctic vortex biases polar temperatures and trace gas distributions in the upper stratosphere in November and December.

Observed vertical distribution of tropospheric ozone during the Asian summertime monsoon

We characterize the horizontal and vertical distribution of tropospheric ozone measured by the Tropospheric Emission Spectrometer (TES) over North Africa, the Middle East, and Asia. Studies have shown that the summertime circulation associated with the Asian monsoon significantly influences the spatial distribution of ozone and its precursors. However, there have been limited observations of the distribution of tropospheric ozone over this region. Over the Middle East, TES observations reveal abundances of ozone between 60 and 100 ppbv, with amounts over 80 ppbv typically occurring between 300 and 450 hPa, whereas over India, enhanced ozone abundances are near 300 hPa. Over central Asia, observed ozone amounts are 150–200 ppbv at altitudes near 300 hPa. These enhanced ozone abundances are observed in June and July, corresponding to the onset of the Asian monsoon, and begin to dissipate in August. Intercomparison of the TES data with ozone climatologies derived from the Measurements of Ozone and Water Vapor by in‐Service Airbus Aircraft program show that the TES ozone is biased high by about 15% between 300 and 750 hPa, consistent with prior validation studies. Comparison of the assimilation of TES data into the GEOS‐Chem model with assimilation of data from the Microwave Limb Sounder (MLS) and the Ozone Monitoring Instrument (OMI) into the Goddard Earth Observing System (GEOS‐4) model shows consistency in the distribution of ozone. For example, at 7–8 km across North Africa, the Middle East, and Asia the bias between GEOS‐Chem and the assimilated OMI and MLS fields was reduced from 6.8 to 1.4 ppbv following assimilation of the TES data.

Impact of Arabian Sea pollution on the Bay of Bengal winter monsoon rains

Accumulation of pollution over the southern Arabian Sea has been documented in numerous studies that followed the INDOEX field project of 1992. In this paper, we show several examples of this feature from the MODIS/CALIPSO data sets. We identify this feature as the Bombay Plume that makes its way into the Arabian Sea from the west coast of India. A second part of this work is on modeling the impacts of pollution. We use a NASA Goddard Earth Observing System (GEOS) model to carry out many comparative forecast simulation experiments that include the pollution based on MODIS and control runs that utilize climatological estimates of pollutions. The model invokes both the direct and indirect effects of aerosols. Our observations are as follows: (1) The Arabian Sea experienced above normal rain during these periods for the MODIS experiments as compared to the control. (2) The most interesting feature is the divergent outflow center, in the upper troposphere, over polluted regions of the atmosphere over the Arabian Sea as a consequence of tropospheric aerosol heating. (3) An important related feature is a compensating downward lobe with a divergent inflow in the upper troposphere center over the Bay of Bengal. (4) The presence of this downward lobe over the Bay of Bengal relates to a reduction of winter monsoon rains over the southeast coast of India. (5) We also show evidence of similarly reduced winter monsoon rains in raingauge data over the southeast coast of India during high‐pollution events ascertained from MODIS data.

Simulating the Midwestern U.S. Drought of 1988 with a GCM

Past studies have suggested that the drought of the summer of 1988 over the midwestern United States may have been caused by sea surface temperature (SST) anomalies, an evolving stationary circulation, a soil-moisture feedback on circulation and rainfall, or even by remote forcings. The relative importance of various contributing factors is investigated in this paper through the use of Goddard Earth Observing System (GEOS) GCM simulations. Seven different experiments, each containing an ensemble of four simulations, were conducted with the GCM. For each experiment, the GCM was integrated through the summers of 1987 and 1988 starting from an analyzed atmosphere in early January of each year. In the baseline case, only the SST anomalies and climatological vegetation parameters were prescribed, while everything else (such as soil moisture, snow cover, and clouds) was interactive. The precipitation differences (1988 minus 1987) show that the GCM was successful in simulating reduced precipitation in 1988, but the accompanying low-level circulation anomalies in the Midwest were not well simulated. To isolate the influence of the model’s climate drift, analyzed winds and analyzed soil moisture were prescribed globally as continuous updates (in isolation or jointly). The results show that remotely advected wind biases (emanating from potential errors in the model’s dynamics and physics) are the primary cause of circulation biases over North America. Inclusion of soil moisture helps to improve the simulation as well as to reaffirm the strong feedback between soil moisture and precipitation. In a case with both updated winds and soil moisture, the model produces more realistic evapotranspiration and precipitation differences. An additional case also used soil moisture and winds updates, but only outside North America. Its simulation is very similar to that of the case with globally updated winds and soil moisture, which suggests that North American simulation errors originate largely outside the region. Two additional cases examining the influence of vegetation were built on this case using correct and opposite-year vegetation. The model did not produce a discernible improvement in response to vegetation for the drought year. One may conclude that the soil moisture governs the outcome of the land–atmosphere feedback interaction far more than the vegetation parameters. A primary inference of this study is that even though SSTs have some influence on the drought, model biases strongly influence the prediction errors. It must be emphasized that the results from this study are dependent upon the GEOS model’s identified errors and biases, and that the conclusions do not necessarily apply to results from other models.

Storm Tracks and Barotropic Deformation in Climate Models

Abstract The relationship between the time-mean planetary-scale deformation field and the structure of midlatitude storm tracks is studied in wintertime simulations of the National Center for Atmospheric Research (NCAR) Community Climate Model and the National Aeronautics and Space Administration (NASA) Goddard Earth Observing System model. Model biases are determined by contrasting model simulations (forced by observed SSTs) with parallel analyses of NCEP–NCAR reanalyses. Barotropic diagnostics are employed to identify potential dynamical linkages between regional biases in the midlatitude storm tracks and the horizontal deformation field. Initial observational analyses confirm that synoptic eddies are optimally configured to transfer kinetic energy to the mean flow in the jet exit regions, where strong stretching deformation exists. In these regions, the major axes of the synoptic eddies are aligned along the dilatation axes of the mean flow. Consequently, mean flow advection stretches synoptic eddies a...

Geophysical validation of NSCAT winds using atmospheric data and analyses

A detailed geophysical evaluation of the initial NASA scatterometer (NSCAT) wind data sets was performed in order to determine the error characteristics of these data and their applicability to ocean surface analysis and numerical prediction. The first component of this evaluation consisted of collocations of NSCAT data to ship and buoy wind reports, special sensor microwave imager wind observations, and National Centers for Environmental Prediction and Goddard Earth Observing System (GEOS) model wind analyses. This was followed by data assimilation experiments to determine the impact of NSCAT data on analysis and forecasting. The collocation comparisons showed the NSCAT wind velocity data to be of higher accuracy than operational ERS 2 wind data. The impact experiments showed that NSCAT has the ability to correct major errors in analyses over the oceans and also to improve numerical weather prediction. NSCAT data typically show the precise locations of both synoptic‐scale and smaller‐scale cyclones and fronts over the oceans. This often results in significant improvements to analyses. Forecast experiments using the GEOS model show approximately a 1‐day extension of useful forecast skill in the southern hemisphere, in good agreement with the results of Observing System Simulation Experiments conducted prior to launch.